11institutetext: Space sciences, Technologies and Astrophysics Research (STAR)
Institute, Université de Liège, Allée du 6 Août 19C, 4000 Liège, Belgium
22institutetext: Département d’Astronomie, Université de Genève, Chemin Pegasi
51b, CH-1290 Versoix, Suisse 33institutetext: Department of Physics,
University of Oxford, Oxford, UK 44institutetext: Centre for Exoplanet
Science, SUPA School of Physics and Astronomy, University of St Andrews, North
Haugh, St Andrews KY16 9SS, UK 55institutetext: Department of Physics,
University of Warwick, Gibbet Hill Road, Coventry, CV4 7AL, UK
66institutetext: INAF - Osservatorio Astrofisico di Torino, Via Osservatorio
20, I10025 Pino Torinese, Italy 77institutetext: DTU Space, National Space
Institute, Technical University of Denmark, Elektrovej 328, DK-2800 Kgs.
Lyngby, Denmark 88institutetext: Center for Astrophysics ${\rm\mid}$ Harvard &
Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA 99institutetext:
Astrophysics Group, University of Exeter, Exeter EX4 2QL, UK
1010institutetext: STFC Ernest Rutherford Fellow 1111institutetext: Fundación
Galileo Galilei – INAF, Rambla José Ana Fernandez Pérez 7, 38712 – Breña Baja,
Spain 1212institutetext: Instituto de Astrofísica de Canarias, C/Vía Láctea
sn, 38205 La Laguna, Spain 1313institutetext: Dipartimento di Fisica e
Astronomia ”Galileo Galilei”, Universitá di Padova, Vicolo del l’Osservatorio
3, I-35122 Padova, Italy 1414institutetext: INAF - Osservatorio Astronomico di
Padova, Vicolo dell’Osservatorio 5, Padova, 35122, Italy 1515institutetext:
INAF - Osservatorio Astronomico di Cagliari, Via della Scienza 5, I-09047,
Selargius, Italy 1616institutetext: School of Physics $\&$ Astronomy,
University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
1717institutetext: SUPA, Institute for Astronomy, University of Edinburgh,
Blackford Hill, Edinburgh EH9 3HJ, Scotland, UK

# A review of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).

M. Stalport A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). M. Cretignier A review of planetary systems around HD 99492,
HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars
is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). S. Udry A review of planetary systems
around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N
data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). A. Anna John A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). T. G.
Wilson A review of planetary systems around HD 99492, HD 147379 and HD 190007
with HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS
via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). J.-B. Delisle A review of planetary systems around HD 99492,
HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars
is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). A. S.
Bonomo A review of planetary systems around HD 99492, HD 147379 and HD 190007
with HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS
via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). L. A. Buchhave A review
of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). D. Charbonneau A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). S. Dalal A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). M. Damasso
A review of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). L. Di Fabrizio A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). X. Dumusque A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). A.
Fiorenzano A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). A. Harutyunyan A review
of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). R. D. Haywood A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). D. W. Latham A review
of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). M. López-Morales A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). V. Lorenzi A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). C. Lovis A review of planetary systems
around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N
data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). L. Malavolta A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of
planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). E. Molinari A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). A. Mortier A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). M. Pedani A
review of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). F. Pepe A review of planetary systems
around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N
data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). M. Pinamonti A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5). E. Poretti
A review of planetary systems around HD 99492, HD 147379 and HD 190007 with
HARPS-N††thanks: The HARPS-N data of these stars is available at the CDS via
anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary
systems around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The
HARPS-N data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5). K. Rice A review of planetary systems
around HD 99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N
data of these stars is available at the CDS via anonymous ftp to
cdsarc.cds.unistra.fr (130.79.128.5).A review of planetary systems around HD
99492, HD 147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these
stars is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5). A. Sozzetti A review of planetary systems around HD 99492, HD
147379 and HD 190007 with HARPS-N††thanks: The HARPS-N data of these stars is
available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr
(130.79.128.5).A review of planetary systems around HD 99492, HD 147379 and HD
190007 with HARPS-N††thanks: The HARPS-N data of these stars is available at
the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5).

(Received ?? / Accepted ??)

###### Abstract

Context. The Rocky Planet Search (RPS) program is dedicated to a blind radial
velocity (RV) search of planets around bright stars in the Northern
hemisphere, using the high-resolution echelle spectrograph HARPS-N installed
on the Telescopio Nazionale Galileo (TNG).

Aims. The goal of this work is to revise and update the properties of three
planetary systems by analysing the HARPS-N data with state-of-the-art stellar
activity mitigation tools. The stars considered are HD 99492 (83Leo B), HD
147379 (Gl617 A) and HD 190007.

Methods. We employ a systematic process of data modelling, that we selected
from the comparison of different approaches. We use YARARA to remove
instrumental systematics from the RV, and then use SPLEAF to further mitigate
the stellar noise with a multidimensional correlated noise model. We also
search for transit features in the Transiting Exoplanets Survey Satellite
(TESS) data of these stars.

Results. We report on the discovery of a new planet around HD 99492, namely HD
99492 c, with an orbital period of 95.2 days and a minimum mass of
$m\leavevmode\nobreak\ \sin i=$ 17.9 $M_{\oplus}$, and refine the parameters
of HD 99492 b. We also update and refine the Keplerian solutions for the
planets around HD 147379 and HD 190007, but do not detect additional planetary
signals. We discard the transiting geometry for the planets, but stress that
TESS did not exhaustively cover all the orbital phases.

Conclusions. The addition of the HARPS-N data, and the use of advanced data
analysis tools, has allowed us to present a more precise view of these three
planetary systems. It demonstrates once again the importance of long
observational efforts such as the RPS program. Added to the RV exoplanet
sample, these planets populate two apparently distinct populations revealed by
a bimodality in the planets’ minimum mass distribution. The separation is
located between 30 and 50 $M_{\oplus}$.

###### Key Words.:

Planets and satellites: detection – Techniques: radial velocities – Stars:
individual: HD 99492, HD 147379, HD 190007 – Stars: activity – Planetary
systems

##  1 Introduction

Since the early 2000s, the HARPS spectrograph (Pepe et al. 2000; Mayor et al.
2003), installed on the ESO-3.6m telescope at La Silla observatory, Chile, has
seen numerous breakthroughs in the detection and characterisation of new
worlds. Initially with a Guaranteed Time Observation (GTO) programme, and then
an ESO Large Programme, the instrument dedicated its time to observe a large
sample of stars. This blind planet search was performed on a well-chosen
sample of main sequence and quiet stars. Among the principal results of this
HARPS survey was the discovery of a new category of exoplanets, the sub-
Neptune and Super-Earth planets on close-in orbits (Mayor & Udry 2008; Lovis
et al. 2009). A significant number of detections later suggested that these
planets are among the most abundant in the exoplanet population (e.g. Mayor et
al. 2011; Lovis et al. 2011; Lo Curto et al. 2013; Bonfils et al. 2013;
Astudillo-Defru et al. 2017b; Delisle et al. 2018; Unger et al. 2021). Their
over-abundance was strengthened by the Kepler space telescope, which
scrutinised a small area of the North sky for 3.5 years in search for
transiting planets (Latham et al. 2011; Borucki et al. 2011; Fabrycky et al.
2014).

The successful HARPS story motivated the development of a ’HARPS twin’ in the
Northern hemisphere, HARPS-N (Cosentino et al. 2012, 2014). This high
resolution spectrograph is mounted on the 3.6m Telescopio Nazionale Galileo
(TNG), located at the Roque de Los Muchachos observatory on the La Palma
Island, Spain. The instrument is embedded in a vacuum-controlled tank,
ensuring a high level of stability in temperature and air pressure. It covers
the wavelength range 383 - 693 nm, and reaches a spectral resolution of R =
115 000. The instrument was built with two primary science goals. 1) To ensure
a synergy with the Kepler (Borucki et al. 2010), then K2 (Howell et al. 2014),
TESS (Ricker et al. 2015) and CHEOPS (Benz et al. 2021) missions. This is
achieved via a precise RV follow-up of promising transiting candidates.
Ultimately, such a strategy provides the community with bulk density
measurements of planets, which are essential to precisely characterise the
planet population and constrain formation and evolution processes (e.g.
Rajpaul et al. 2017; Malavolta et al. 2018; Bonomo et al. 2019; Cloutier et
al. 2020; Mortier et al. 2020; Lacedelli et al. 2021). 2) To undertake a blind
RV search for low-mass exoplanets, similar to the historical program of HARPS
but in the Northern sky. To achieve this, we started the Rocky Planet Search
(RPS) program with HARPS-N. It consists in a sample of 58 bright stars widely-
spread in right ascension, many of which presenting low levels of activity and
hence amenable for precise planet characterisation (see Motalebi et al. 2015,
for a presentation of the RPS program). Unlike the HARPS sample however, we
highlight that some targets with moderate activity are also part of this
sample, to serve as test cases for the development of tools aimed at
mitigating stellar activity (e.g. Cretignier et al. 2020a; Collier Cameron et
al. 2021; de Beurs et al. 2022) in parallel with the constant RV monitoring of
the Sun (Collier Cameron et al. 2019; Dumusque et al. 2021).

In order to fulfil these scientific objectives and discover low mass
exoplanets, stellar activity has to be treated carefully. The RV amplitude
induced by small planets on host main-sequence quiet stars is comparable to
the contaminating effect of stellar activity. In order to mitigate the latter,
we first adapt the observational strategy of the RPS sample. Following the
prescriptions of Dumusque et al. (2011), we systematically took two exposures
of fifteen minutes each per night, with at least two hours between each
exposure. This allows us to mitigate noise emanating from stellar oscillations
and granulation on different scales (Dumusque et al. 2011; Chaplin et al.
2019). Coupling this observational strategy with intense monitoring led to the
detection of four planets around HD 219134 (Motalebi et al. 2015). It is one
of the few systems where a planet was first discovered via the RV technique,
and subsequently found to transit its host star (HD 219134 b, with the use of
the Spitzer space telescope). Two years later, a second planet was also
observed to transit (Gillon et al. 2017).

In addition to the above, significant efforts have been dedicated to develop
tools for stellar activity mitigation and RV time-series analysis (e.g.
Delisle et al. 2020a, b; Collier Cameron et al. 2021; Cretignier et al. 2021;
Hara et al. 2022; de Beurs et al. 2022). Simultaneously, the RPS program
recently benefited from new Data Reduction Software (DRS) inspired from the
ESPRESSO data reduction pipeline, and further augmented by the removal of some
specific HARPS-N systematics via a study of the solar data (Dumusque et al.
2021). The convergence of all these efforts motivated us to revisit the RPS
sample, in search for new exoplanet candidates. A first outcome of this work
is the validation of HD 79211 b (DiTomasso et al. 2023), an exoplanet in a
24.4 days orbit and with a minimum mass of 10.6 $M_{\oplus}$. More recently,
the RV analysis of HD 166620 and HD 144579 demonstrated the potential for
HARPS-N to reach sub-metre per second detectability in blind searches (Anna
John et al. 2023).

In this paper, we present the results of the analysis of three systems, namely
HD 99492, HD 147379, and HD 190007, each of which was already known to host a
planet candidate. We aim to present an homogeneous procedure to analyse the
data, using the new techniques introduced above. The present paper is
organised as follows. Sect. 2 reports the observations available for each
star, and focuses on the estimation of the stellar parameters. Sect. 3
describes the various tools as part of our strategy to analyse the data. Then,
Sect. 4, 5, and 6 present our analyses of the data and their modelling with
planetary Keplerian orbits. Finally, we conclude and discuss these results in
Sect. 7.

##  2 Observations and stellar parameters

###  2.1 Observations

####  2.1.1 HD 99492

HD 99492, also denoted as 83 Leo B, was observed with HARPS-N between January
15, 2014 and June 17, 2022 using the observational strategy mentioned above
(per night, two 15 minutes exposures separated by at least two hours). A total
of 202 nightly binned spectra were recorded. For each binned spectrum, we
extracted the RV information from cross-correlation of the stellar spectra
with a K2 mask. We also derived different stellar activity indicators such as
the bisector span, the full width at half maximum (FWHM) of the cross-
correlation function (CCF), the S-index and Hα. 178 Keck/HIRES (Vogt et al.
1994) publicly available RV measurements were also taken over a time-span of
6365 days, between Jan 13, 1997 and June 19, 2014. In the top panel of Fig. 1
we present the RV time-series of the combined HIRES and HARPS-N datasets,
including an adjusted offset.

HD 99492 has 71 publicly available Hipparcos photometric measurements, and 368
observations from the Automatic Photoelectric Telescope (APT – Henry 1999;
Kane et al. 2009) at Fairborn observatory, Arizona (USA). This ensemble of
photometric data did not allow Kane et al. (2016) to constrain the stellar
rotation period, and will not be used in our analyses. Additionally, TESS has
observed the star in sectors 45 and 46 (i.e. in Nov and Dec, 2021) with a
2-min cadence.

Data from the third Gaia Early Data Release (EDR3, Gaia Collaboration 2020)
constrain the parallax of HD 99492 to 55.062$\pm$0.030 masec, leading to an
updated distance estimate of 18.16$\pm$0.01 pc from the Sun. The star forms a
gravitational binary with HD 99491, also named 83 Leo A. With a reported
angular separation between HD 99492 and HD 99491 of 28.3 asec, their mutual
distance projected on the sky was estimated to 513.9 AU. We note furthermore
the existence of 6 CORAVEL RV measurements of HD 99492 taken between the years
1983 and 1993, and 13 RV of HD 99491 gathered between 1980 and 1993, with a
mean RV error on the individual measurements of $\sim$300  m s-1. The
precision on those data is not significant enough to detect a slope in the RV
due to the gravitational influence between the two stars (Halbwachs et al.
2018).

Figure 1: RV time-series of the three stars analysed in this study. Top – HD
99492 (HARPS-N and HIRES data), Middle – HD 147379 (HARPS-N, SOPHIE, CARMENES
and HIRES data), Bottom – HD 190007 (HARPS-N, HIRES and APF data).

####  2.1.2 HD 147379

HD 147379, also named Gl 617 A, was observed with HARPS-N between February 18,
2013 and August 13, 2020. A total of 165 nightly binned spectra were recorded.
The same information as for HD 99492 was extracted from the spectra, this time
employing a M0 mask. The star benefits also from publicly available
observations performed with three other spectrographs. HIRES gathered 30 RV
measurements over about 13 years (from May 15, 2000 to May 21, 2013); the
CARMENES instrument (Quirrenbach et al. 2018) obtained 114 measurements over
$\sim$ 600 nights (from Jan 10, 2016 to Sep 2, 2017); the SOPHIE+
spectrograph111SOPHIE+ was started in 2011, and consists in an upgraded
version of SOPHIE (Perruchot et al. 2008). (Perruchot et al. 2011; Bouchy et
al. 2013), finally, brings an additional 163 high precision RV measurements
obtained over nearly six years (from Sep 22, 2011 to June 17, 2017). The RV
time-series of the combined instruments is presented in the middle panel of
Fig. 1. For the sake of clarity, we present a time-series centred on the
CARMENES, SOPHIE and HARPS-N data. The full RV time-series is presented in
Appendix – Fig. 14.

HD 147379 was also extensively observed in 28 TESS sectors with a 2-min
cadence (sectors 14-21, 23-26, 40-41, and 47-60). The total observing window
covers 1279 days, from Jul 18, 2019 to Jan 18, 2023, and contains 494 593 flux
measurements. Also, the star benefits from 103 Hipparcos photometric
measurements, obtained over a time-span of 2.5 years. Finally, it was observed
by KELT (Pepper et al. 2007) over slightly less than two years, for a total of
3304 measurements.

The Gaia EDR3 estimates the parallax of HD 147379 to 92.877$\pm$0.015 masec,
which converts to a distance of 10.767$\pm$0.002 pc from the Sun. The star has
a nearby companion with a similar proper motion, namely Gl 617 B. This
gravitationally-bound binary presents an angular separation of 64.4 asec,
which corresponds to an on-sky projected distance of 693.4 AU.

####  2.1.3 HD 190007

HD 190007 was observed with HARPS-N between July 21, 2015 and May 19, 2019,
for a total of 37 nightly binned spectra. We derived the RV from cross-
correlation of the stellar spectra with a K2 mask. These data complement the
set of publicly available RV measurements from the HIRES and APF/Levy (Vogt et
al. 2014) spectrographs. The former gathered 33 nightly binned RV over more
than 16 years (from Jun 19, 1998 to Sep 10, 2014), while the latter obtained
89 nightly binned high resolution spectra over more than six years (from Jul
9, 2013 to Oct 2, 2019). The RV time-series of the combined instruments is
presented in Fig. 1 – bottom panel.

HD 190007 was observed with the APT at Fairborn observatory for over twenty
years, gathering a total of 1092 flux measurements. Furthermore, the star was
followed up by TESS in sector 54 (in Jul, 2022), with a 2min cadence.

###  2.2 Stellar parameters and activity

Table 1 reports on the main stellar parameters gathered from the literature
for the three stars. We stress that the uncertainties on the effective
temperature $T_{\rm eff}$ and the stellar mass $M_{\star}$ are intriguingly
small. As Tayar et al. (2022) showed, important factors such as the systematic
uncertainties on the fundamental stellar properties, and the scatter in the
results from different stellar evolution models are often ignored. Due to
these factors, they estimate a minimum uncertainty of 2.0$\%\pm$ 0.5$\%$ on
$T_{\rm eff}$, to be added in quadrature to the reported uncertainties.
Regarding the stellar mass estimation, the authors provide maximal fractional
offsets between different model grids in the space of luminosity and effective
temperature (cf. their Fig. 5). For the three stars of this work, the models
variance adds uncertainties of between 5$\%$ and 10$\%$ on $M_{\star}$. This
additional error budget transposes directly to the mass estimates of
exoplanets (a similar uncertainty increase is also applicable on the radius,
but this is not relevant for this work). Finally, we also note that the
distances reported in Table 1 were obtained from the parallax measurements
reported in the Gaia EDR3 catalogue.

####  2.2.1 HD 99492

HD 99492 is a K-type main-sequence bright star (V = 7.6). Its stellar
companion 83 Leo A is a late G-type star (V = 6.5). HD 99492 shows a low
activity level, notably expressed by its $\log{(R^{{}^{\prime}}_{HK})}$= -4.93
(Marcy et al. 2005).

Kane et al. (2016) reported the detection of a magnetic cycle on HD 99492,
with a periodicity between 3000 and 5000 days222A planet was originally
proposed as the origin of this long-term periodicity, namely HD 99492 c
(Meschiari et al. 2011). The existence of this planetary companion was
rejected by Kane et al. (2016).. In the time-span of the HARPS-N observations,
which is 2270 days, we see a quadratic-like trend in the data. A similar trend
is observed in the time-series of our various spectroscopic activity
indicators, and we therefore attribute this trend to stellar activity (cf.
Appendix – Fig. 15).

From the estimation $\log{(R^{{}^{\prime}}_{HK})}$= -4.93, Marcy et al. (2005)
estimate the stellar rotation period to be $\sim$45 days. They used the
empirical relations from Wright et al. (2004) for this estimate, but stressed
that HD 99492 has a $B-V$ index that lies outside of the verified calibration
domain. Kane et al. (2016) analysed both the APT and Hipparcos photometry,
with no conclusive result. From our 202 nightly binned HARPS-N spectra, we
detect significant periodic signals at around 40 - 45 days in the periodograms
of different stellar activity indicators, such as the FWHM and S-index (cf.
Appendix – Fig. 15). They strengthen the previous analyses, and indicate a
stellar rotation period between 40 and 45 days.

Finally, we considered the TESS photometric measurements in search for
periodic signals. However, we found that the 2-min cadence Simple Aperture
Photometry (SAP) fluxes of the two available sectors (45 and 46), which are
derived by the TESS Science Processing Operations Center (SPOC, Jenkins et al.
2016), are strongly contaminated by the Moon. Therefore, to treat the
systematics we extracted our custom light-curve from the calibrated 2-min
cadence target pixel files using lightkurve333Lightkurve is an open-source
Python package for Kepler, K2 and TESS data analysis (Lightkurve Collaboration
et al. 2018).. For each sector, the extraction of the light-curve was
performed via aperture photometry employing the TESS SPOC pipeline mask. The
latter is shifted from the photometric centre of the source, so to limit the
contamination from the nearby companion HD 99491, which lies 28$\arcsec$ away
from HD 99492 and is hence blended with the latter on the TESS detector.
During the light-curve extraction, we corrected the fluxes from the background
systematics, and notably we partly accounted for the contamination of HD
99491. This was done by building a matrix of the out-of-aperture pixels (also
called a design matrix), and performing a principal component analysis to
retrieve the five main trends that we then removed from the pixels inside the
aperture. We also retrieved the cotrending basis vectors (CBV) computed by the
Pre-search Data Conditioning (PDC, Smith et al. 2012; Stumpe et al. 2014) unit
of the TESS SPOC pipeline. These are vectors that contain the most common
systematic trends found for each TESS CCD, and which are produced for every
sector. They are divided into three categories: the spike CBV contain the
short impulsive systematics, the single-scale CBV contain all systematics in a
single set of CBV, and multi-scale CBV are spread into three different band-
passes. We found that the combination of single-scale and spike CBV is best
suited to correct our light-curve from systematics while preserving stellar
signals with time-scales of a few tens of days. We detrended the light-curve
with these CBV, jointly with the background subtraction mentioned above. We
then removed outlier fluxes standing beyond five standard deviations
(5$\sigma$) of the smoothed light-curve, we normalised the flux data in each
sector, and merged the two sectors. Finally, we undertook a periodic signal
search in the resulting light-curve, via a generalised Lomb-Scargle (GLS)
periodogram (Zechmeister & Kürster 2009). We found a significant broad
periodic signal peaking at $\sim$21 days, which is consistent with half of the
expected stellar rotation period. We present those results in Fig. 2.

Figure 2: HD 99492: Periodic signal search in TESS sectors 45 and 46. Top:
TESS light-curve extracted using lightkurve, and corrected from systematics (2
sectors). Bottom: GLS periodogram computed between 2 and 40 days of the 1-day
binned light-curve.

####  2.2.2 HD 147379

HD 147379, or equivalently Gl 617 A, is a M-type main-sequence star with high
proper motion (V = 8.9 mag). It is also part of a gravitationally bound binary
with Gl 617 B, which is another M-type main-sequence star fainter than the
former (V = 10.6 mag). HD 147379 presents a reasonably low activity index too,
with $\log{(R^{{}^{\prime}}_{HK})}$= -4.75.

A correlation is visible in the spectroscopic data of HD 147379 between the RV
and FWHM or S-index. We observe a long-period variation in those time-series,
which is attributed to the stellar magnetic activity. The HARPS-N data spans
2734 days, and like HD 99492, does not cover a full magnetic cycle. Only a
quadratic trend is observed (cf. Appendix – Fig. 16).

Based on an empirical relation between X-ray activity and stellar rotation,
Reiners et al. (2018) estimate a stellar rotation period of $P_{rot}=31\pm 20$
days. Furthermore, with the use of the empirical relation of Astudillo-Defru
et al. (2017a) between $\log{(R^{{}^{\prime}}_{HK})}$and $P_{rot}$ for M
dwarfs, Hobson et al. (2018) evaluate the rotation period of HD 147379 to be
$28.8\pm 6.1$ days. These authors also analysed the Hipparcos photometry - 103
measurements over 2.5 years - but without conclusive results except a hint of
signal at $\sim$ 21 days. Pepper (2018) performed a photometric analysis of HD
147379 with KELT data, and found $P_{rot}=22$ days. All the previous studies
are therefore consistent with each other. We analysed the stellar activity
indicators time-series of HARPS-N to search for any hint of stellar rotation.
The most significant periodic signals were seen in the S-index, which reveal a
cycle of 21.5 days. This strongly supports the results of previous analyses on
this star.

We analysed the extensive TESS 2-min cadence photometric observations (28
sectors) in search for any photometric periodic variation. To proceed, we
extracted the light-curve of each of the 28 sectors following the same
procedure as described in Sect. 2.2.1. Notably, we note again that the SPOC
pipeline mask conveniently avoids a nearby source on the detector, and we opt
for this mask to perform aperture photometry. We performed a periodic signal
search in our custom light-curve corrected from systematics, by computing a
GLS periodogram. Both the TESS time-series and the periodogram are presented
in Fig. 3. We found two significant signals at 21 and 10.4 days, and we
associate them with the stellar rotation period and its half, respectively.
This analysis is consistent with the period found in the spectroscopic
observations and in Pepper (2018). We therefore conclude that the rotation
period is highly likely to be around 21 days.

Figure 3: HD 147379 TESS photometry. Top: TESS light-curve extracted using
lightkurve, and corrected from systematics (28 sectors). Bottom: GLS
periodogram computed between 2 and 40 days of the 1-day binned light curve.

####  2.2.3 HD 190007

HD 190007 is a bright K-type main-sequence star (V = 7.46). The star belongs
to the family of BY Draconis variables (Kazarovets et al. 2003). It is indeed
moderately active ($\log{(R^{{}^{\prime}}_{HK})}$= -4.65) and shows a clear
photometric quasi-periodic variation. It is slightly metal-rich, with an age
that remains uncertain. However, Burt et al. (2021) suggest that the star is
at least 1 Gyr old, based on data from the Kepler mission.

The radial velocities combined from the different instruments, which span more
than twenty years, present a linear trend of $\sim$1.4 m s-1 yr-1. This is in
line with the measurement of a statistically significant (S/N¿3) proper motion
anomaly between Hipparcos and Gaia DR3 mean epoch (Kervella et al. 2022). Both
the RV and the Hipparcos-Gaia absolute astrometry hint at the existence of a
long-period companion, and future observations will help shed light onto this
hypothesis.

Both from the spectroscopic stellar activity indicators and the analysis of
the available photometry, Burt et al. (2021) report a rotation period of
$P_{rot}\sim$29 days. This is in agreement with the previous estimation of
Olspert et al. (2018) using Gaussian Process (GP) modelling, which found
$P_{rot}=27.68$ days. We observe a similar periodicity in the spectroscopic
indicators when we add our HARPS-N measurements to the existing HIRES and APF
data (cf. Appendix – Fig. 17).

We also analysed the TESS photometric data of this star (sector 54) in search
for potential periodicity. We were limited by the small time-span of the
observations ($\sim$26 days). A simple inspection of the normalised SAP light
curve, consisting of 13 238 flux measurements, reveals a long-term variation
covering nearly a full cycle over the sector. We present the normalised SAP
light curve in Fig. 4. This is in agreement with previous analyses, suggesting
a stellar rotation period around 30 days. Yet, the time span of the TESS
observations is too short to firmly confirm it.

Figure 4: HD 190007 TESS SAP normalised time-series (sector 54).

Parameters [Units] HD 99492 HD 147379 HD 190007 Spectral Types K2V1 M0.0V6
K4V10 $V$ [mag] $7.58^{2}$ $8.9^{7}$ $7.46^{10}$ $B-V$ [mag] $1.02^{3}$
$1.11^{7}$ $1.128^{10}$ Distance [pc] $18.161\pm 0.010^{4}$ $10.767\pm
0.002^{4}$ $12.715\pm 0.003^{4}$ $T_{\rm eff}$[K] $4929\pm 44^{2}$ $4090\pm
50^{7}$ $4610\pm 20^{10}$ $\log{g}$[cgs] $4.57^{2}$ $4.609\pm 0.012^{8}$
$4.58\pm 0.02^{10}$ [Fe/H][dex] $0.3\pm 0.03^{2}$ $0.16\pm 0.16^{7}$ $0.16\pm
0.05^{10}$ $\log{(R^{{}^{\prime}}_{HK})}$ $-4.93^{5}$ $-4.75\pm 0.14^{9}$
$-4.65^{11}$ $v$ sin $i$[ km s-1] $0.41\pm 0.5^{2}$ $2.7\pm 1.5^{7}$
$2.55^{10}$ $M_{\star}$ [$\mathrm{M}_{\odot}$] $0.85\pm 0.02^{2}$ $0.58\pm
0.08^{7}$ $0.77\pm 0.02^{10}$

Table 1: Stellar parameters for HD 99492, HD 147379, and HD 190007.

(1) Meschiari et al. (2011) ; (2) Kane et al. (2016) ; (3) Koen et al. (2010)
; (4) Gaia Collaboration (2020) ; (5) Marcy et al. (2005) ; (6) Alonso-
Floriano et al. (2015) ; (7) Reiners et al. (2018) ; (8) Stassun et al. (2019)
; (9) Hobson et al. (2018) ; (10) Burt et al. (2021) ; (11) Olspert et al.
(2018)

##  3 Data analysis tools and general strategy

In this work, we employ a systematic approach to analyse the observations,
making use of a number of versatile tools. We aim to demonstrate the ability
of these new tools to correct for stellar activity effects and to provide
unbiased planetary parameters. Initially, we explore the spectroscopic data –
RV and stellar activity indicator time-series – with the Data $\&$ Analysis
Centre for Exoplanets (DACE). This web-platform, hosted at the University of
Geneva, is dedicated to extra-solar planet data visualisation, exchange and
analysis444DACE can be accessed via https://dace.unige.ch.. Among many other
functionalities, it shows the various spectroscopic time-series, but also the
correlation plots between the RV and indicators. Additionally, it offers the
possibility to perform interactive fits of the time-series, optionally with
Keplerians. Therefore, we systematically use DACE to get a first valuable view
of the data, and identify potential stellar activity signatures. As a second
step, we initiate in-depth data analysis. We first correct the HARPS-N data
from instrumental systematics and some stellar activity features thanks to the
YARARA software (Cretignier et al. 2021). Then, the datasets are investigated
in light of the correlated noise model SPLEAF (Delisle et al. 2020b). Below,
we briefly summarise these two tools. Finally, we explore the model parameters
via a Monte Carlo Markov Chain (MCMC) algorithm. For the latter, we employ
samsam, a scaled adaptive metropolis algorithm (Delisle 2022).

###  3.1 YARARA

YARARA (Cretignier et al. 2021) is a post-processing method that aims to
improve the spectra extracted by the classical DRS (Dumusque et al. 2021) by
removing the extra signatures introduced by the instrument and the Earth
atmosphere, leading ultimately to an improved RV precision. The method
involves correcting a residual spectral time-series with respect to a master
spectrum (built to be free from the systematics), where the corrections are
made of multi-linear regressions in the wavelength domain. The spectra are
corrected for: cosmics, tellurics, ghosts, fringing, instrumental defocus,
activity and residuals outliers. The cleaned RV are extracted with a CCF using
a tailored line selection based on the master spectrum itself (Cretignier et
al. 2020a) in order to increase the extraction of the Doppler information
content, whereas the merged-order 1d spectra are continuum normalised using
RASSINE (Cretignier et al. 2020b). A few adjustments were implemented in the
code in order to increase the orthogonality between the stellar activity and
instrumental signatures. The main reason for this update was to be able to
introduce back the stellar activity component at later stage (see Sect. 3.2
for a justification). In the old version of the code, both effects were
simultaneously fitted using the S-index, the CCF FWHM and the CCF contrast.
Those two moments contain redundant stellar activity information. The new
version of the pipeline uses an improved version of the S-index using CaIIH&K
lines better corrected for ghosts, whereas the fitted CCF moments are now
orthogonal to that component thanks to a Gram-Schmidt orthogonalisation
algorithm (see Appendix C).

YARARA itself is not able to simultaneously fit in the wavelength domain the
planetary signals and the systematics. However, since most systematics are
fixed in the terrestrial rest-frame, the code assumes that the planetary
signals are destroyed (or strongly mixed) in the wavelength domain once such a
change of rest-frame is performed. In Cretignier et al. (2021), the authors
showed that injected planetary signals were not absorbed more than 20% (and
only for a planet close to a 1-year harmonic). In order to further avoid such
absorption, large RV amplitude signals can be pre-fitted by shifting the
spectra according to a determined Keplerian solution. In this work, that
preliminary Keplerian solution will be obtained via a RV fit with DACE which
matches the orbital elements of the known planets. This Keplerian solution
will then be re-injected in the RV obtained on the residual spectra, before
that an improved Keplerian solution could be obtained. This process can be
called in an iterative way until convergence is reached, which usually occurs
after a single iteration.

Once spectra are corrected for systematics, new proxies orthogonal to a pure
Doppler shift can be extracted in the time-domain (Cretignier et al. 2022).
Under the assumption that the deformations of the line profiles are mainly
driven by the line profile itself, the residual spectra $\delta
f(\lambda)=f(\lambda)-f_{0}(\lambda)$ can be expressed rather as $\delta
f(\partial f_{0}/\partial\lambda,f_{0})$, with $f_{0}$ the master spectrum of
the star – an object that the authors called a ’shell’. An advantage of that
space is that a pure Doppler shift possesses an unique signature that can be
fitted out analytically with a first order approximation. Other distortions,
orthogonal to the pure Doppler shift can then be extracted with a principal
component analysis and their associated time-coefficients are used in a multi-
linear model to correct for the RV time-series. A cross-validation algorithm
is used to determine the number of components to select by randomly rejecting
10% of the observations. Such a strategy was shown successful to remove the
rotational period of stars moderately active and/or potential remaining
instrumental systematics uncorrected by YARARA.

This additional correction process (Cretignier et al. 2022) will be
subsequently designated as YARARA-Shell, as opposed to YARARA-V1 which
consists of YARARA (Cretignier et al. 2021) further augmented with the few
adjustments described above to increase the orthogonality between the stellar
activity and instrumental signatures.

###  3.2 SPLEAF

Correlated noise, or Gaussian Process (GP) models have been the object of
increasing research among the exoplanet community over the past ten years.
They account for physical processes that might be poorly understood or poorly
constrained, such as stellar activity (Haywood et al. 2014). Indeed, instead
of a deterministic model, the GP regression technique aims to parametrise the
covariance between the measurements. There exist different types of GP, which
differ from each other by their kernels, that is by the functional form of the
covariance matrices. SPLEAF (Delisle et al. 2020b) refers to a class of semi-
separable covariance matrices, which builds on the benefits of the celerite
kernel (Ambikasaran et al. 2015; Foreman-Mackey et al. 2017). SPLEAF can take
into account the calibration noise, and due to the semi-separable form of the
covariance matrix, it provides low computation costs. Once the GP regression
is properly performed, it should account for anything that is not due to the
deterministic model nor the measurements noise. Yet in practice, there might
be risks of over-fitting, and the planetary signals may be (partly) absorbed
by the GP. To limit the risk, Rajpaul et al. (2015) proposed to train the GP
simultaneously on the RV and on activity indicators time-series, by modelling
the activity-induced RV signals as linear combinations of the GP ($G(t)$) and
its derivative $\dot{G}(t)$ (Aigrain et al. 2012)

$\Delta RV\leavevmode\nobreak\ =\leavevmode\nobreak\
V_{c}G(t)\leavevmode\nobreak\ +\leavevmode\nobreak\ V_{r}\dot{G}(t)$ (1)
$\Delta\alpha\leavevmode\nobreak\ =\leavevmode\nobreak\ L_{c}G(t)$ (2)
$\Delta\beta\leavevmode\nobreak\ =\leavevmode\nobreak\
B_{c}G(t)\leavevmode\nobreak\ +\leavevmode\nobreak\ B_{r}\dot{G}(t)$ (3)

for $V_{c}$, $V_{r}$, $L_{c}$, $B_{c}$, $B_{r}$ free parameters, and $\alpha$
and $\beta$ referring to some activity indicators. Eq. 1 was first proposed by
Aigrain et al. (2012) to account for the effect of stellar spots on the RV
variations, where G(t) captures the suppression of the convective blueshift in
the spots, and $\dot{G}(t)$ provides the effect of stellar rotation. Rajpaul
et al. (2015) extended this framework to activity indicators (Eq. 2 and 3),
where the use of one equation or another depends on the nature of the
indicator. For instance, the S-index is a proxy for the proportion of the
visible stellar disk covered by active regions, and is therefore accounted for
by Eq. (2). On the other hand, the bisector span indicator, which informs
about the asymmetry of the spectral lines, also depends on the radial velocity
of the stellar surface at the location of the spots, and is hence described by
Eq. (3). The planetary signal being only in the RV time-series, it is less
likely to be absorbed by the GP if the latter is simultaneously trained on one
or several activity indicators. As a drawback though, the computation cost is
significantly larger, with a covariance matrix of size $2n\times 2n$ where $n$
is the number of measurements and in the case where only one activity
indicator time-series is used in parallel of the RV.

Delisle et al. (2022) generalised the SPLEAF model to account for different -
(potentially taken at different times) as modelled by Eq. (1, 2, 3), while
insuring a computation cost that scales linearly with the total number of
measurements. In this work we use this generalised SPLEAF correlated noise
model, which is publicly available555https://gitlab.unige.ch/Jean-
Baptiste.Delisle/spleaf. The kernel we employ for the quasi-periodic part is
an approximation of the squared-exponential periodic (SEP) kernel, where the
covariance has the following expression:

$k(\Delta t)\leavevmode\nobreak\ =\leavevmode\nobreak\
\sigma^{2}\leavevmode\nobreak\ \exp\left(-\dfrac{\Delta
t^{2}}{2\rho^{2}}-\dfrac{\sin^{2}\left(\frac{\pi\Delta
t}{P}\right)}{2\eta^{2}}\right).$ (4)

It consists of a sinusoid on top of a decreasing exponential, with $\Delta t$
being the time interval between two measurements. Therefore, this kernel
correlates one measurement with the others according to this functional form.
The hyperparameters $\sigma$, $\rho$, $P$ and $\eta$ describe respectively the
amplitude of the correlated noise, the rate of exponential decay of the
correlation, the period of variation of the sinusoid and the length-scale of
the periodic component, that is its ability to capture rapidly varying
features (smaller values pointing towards sharp variations). These
hyperparameters are constrained from the various time-series. SPLEAF develops
the periodic component of the SEP kernel in series, and keeps the two
strongest harmonics. In practice, we also add a white noise term to each time-
series, which consists in an additional term on the diagonal of the
correlation matrix.

In this work, we systematically apply the generalised SPLEAF model – denoted
as the SPLEAF model below – on the RV and S-index time-series. As was
described above, we find in the S-index time-series of the three stars traces
of the stellar magnetic cycles and stellar rotation. Therefore, the hyper-
parameters of the correlated noise model, which are estimated from the
analysis of these different datasets, are expected to converge to values
informing us about the stellar activity. We mostly set uninformative priors on
the model parameters, that is priors following a uniform law with wide
boundaries. In Table 2, we synthesise the priors we use in most of our
analyses. We explicitly note in the text when certain priors are further
constrained.

We express some caution about using the YARARA dataset with a correlated noise
model. Indeed, we noticed a convergence issue of the fit with any dataset that
would already be (partially) corrected for the stellar activity features. The
reason is that while the activity indicator time-series are still left intact,
the RV time-series are corrected for the trends observed in the former.
Therefore, the correlated noise model trains successfully on the activity
indicators, but struggles to transpose the results to the RV time-series. In
conclusion, the correlated noise model does not provide satisfactory results
with YARARA-V1 and YARARA-Shell. Nevertheless, YARARA also corrects the
various time-series for the instrumental systematics. The use of those
datasets is preferred, so to avoid observing spurious periodic signals.
Therefore, in the following analyses making use of SPLEAF, we use a modified
version of YARARA-V1 where the stellar activity has been re-injected into the
RV time-series, but not the instrumental systematics (see Appendix C for an
explanation of the process to separate the various components). In other
words, we use an alternative version of YARARA where only the instrumental
systematics have been corrected for. That allows for the convergence of the
fit with the correlated noise model.

Table 2: List of priors used for each parameter, unless stated otherwise in
the text. RVmin and RVmax are the minimum and maximum measured RV,
respectively, for each star.

Parameter | Units | Prior Distribution | Description
---|---|---|---
Offsets and noise |  |  |
Epoch | BJD | Fixed at 2 455 500 | Reference epoch
$\gamma_{inst}$ |  m s-1 | U [RVmin, RVmax] | Constant velocity offset
$\sigma_{RV}$ |  m s-1 | logU [0.001, 100] | Additional white noise (Jitter)
$P_{GP}$ | days | U [1, obs timespan] | Period of correlated noise
$\rho_{GP}$ | days | U [1, obs timespan] | Decay timescale
$\eta_{GP}$ |  | U [0, 100] | Smoothing parameter
$\sigma_{GP}$ |  m s-1 | U [0, 100] | Amplitude of correlated noise
Keplerians |  |  |
$P$ | days | U [1.5, 5000] | Orbital period
$K$ |  m s-1 | logU [0.1, 105] | RV semi-amplitude
$e$ |  | U [0, 0.8] | Orbital eccentricity
$\omega$ | radians | U [0, 2$\pi$] | Argument of periastron
$\lambda_{0}$ | radians | U [0, 2$\pi$] | Mean longitude at epoch

  * •

U denotes a Uniform prior and logU denotes a logarithmic Uniform prior.

##  4 HD 99492 data analysis

HD 99492 is known to be orbited by a planet. Marcy et al. (2005) first
announced the detection with 35 HIRES RV measurements, and reported an orbital
period of 17 days and a minimum mass of $\sim$25 $M_{\oplus}$. The solution
was refined by Meschiari et al. (2011) with an additional 58 HIRES velocities,
and the authors proposed another planet candidate at an orbital period of
$\sim$5000 days. A few years later and with 130 HIRES RV, the latter signal
was shown to be related to stellar magnetic activity (Kane et al. 2016).

We added our 202 nightly binned HARPS-N spectra processed with YARARA-V1, and
performed an exploratory analysis on DACE. First, we focused on stellar
activity signatures. In this dataset, the S-index time-series displays a
significant long-term trend that peaks at a periodicity of $\sim$3000 days in
a GLS periodogram. The latter signal is associated with the magnetic cycle
described in Kane et al. (2016). Fig. 5 presents this time-series (top plot)
and the corresponding periodogram (middle plot). At short periods, we observe
a strong signal at 42.9 days, which appears once we fit the long-period
variation with a Keplerian. This is illustrated in the bottom plot of Fig. 5.
Furthermore, we also detect its 1 year aliases at 47.3 and 38.4 days. The
S-index indicator reveals a notable correlation with the RV, with a
correlation coefficient of $r=0.50$. We detected a similar 42.9 days
periodicity in other activity indicator time-series such as the CCF contrast
and CCF FWHM. We also systematically identified the 1 year aliases of this
signal. Therefore, all these observations constitute strong evidence for the
42.9 days signal to be associated with the stellar rotation period. This
estimate is consistent with previous works (cf. Sect. 2.2).

Figure 5: HD 99492: YARARA-V1 S-index dataset. Top – S-index time-series.
Middle – GLS periodogram of that time-series ($k_{0}$ stands for no Keplerian
in the model). Bottom – GLS periodogram of the residual S-index -, after
subtracting a Keplerian model with $P\sim 3000\leavevmode\nobreak\ $days
($k_{1}$). The red bands locate the periodicities seen in this activity
indicator.

The HIRES publicly available data also contain the S-index activity indicator.
In this dataset, we observe a clear quasi-periodic variation covering several
magnetic cycles of the star, whose correlation with the RV is weaker than in
the HARPS-N dataset. After fitting the most significant periodic signal in the
S-index with a Keplerian (which converges to $\sim$3000 days), we do not find
any significant residual periodicity at $\sim$43 days. In fact, there is no
remaining significant signal below 800 days. We searched for the presence of
the stellar rotation in the other activity indicator available (i.e. the Hα
index). Again, we did not find any significant signal. As a result, we note
that the rotation of the star does not present a measurable signature in the
HIRES data. A potential cause of this non detection is the larger scatter
observed in the S-index time-series of HIRES combined with a more sparse
sampling. Finally, combining HARPS-N and HIRES datasets, we set tighter
constraints on the period of the stellar magnetic cycle. With now an extended
baseline of 9286 days, we constrain the main period of the S-index time-series
to around 3300 days.

Taking the above information into account, we then undertook a search for
planets. We performed the latter using different models and datasets, so as to
compare several approaches. In the first, we used the HARPS-N data as derived
from the DRS together with the HIRES dataset. In a second approach, we
analysed the YARARA-V1 dataset of HARPS-N together with HIRES, and included a
correlated noise model. As a third approach, we repeated this procedure on the
YARARA-V1 data only. Finally, in a fourth approach we analysed the YARARA-
Shell data without a correlated noise model. We describe our planet search
analyses below.

###  4.1 Approach 1: DACE – HARPS-N DRS + HIRES

As a first preliminary analysis, we looked for periodic signals in the nightly
binned RV time-series of the combined HARPS-N + HIRES datasets, using the DRS
version of the HARPS-N data. While we noticed inconsistencies in the Hα time-
series of the HIRES data, the S-index is consistent throughout the entire
time-span. We selected this activity indicator to detrend the RV via the
inclusion of a scaling parameter. Additionally, we included a quadratic drift
to remove what remains of long-term variations. After adding these components
in the model, we searched for periodic signals in the periodogram. The signal
of the planet at 17d is very strong, with a FAP of 7.1 10-77. We included a
Keplerian at that period into our model, and computed the periodogram of the
residuals from the fit. This periodogram shows a very significant second
signal. It has a period of 95.5 days and FAP of 2.1 10-21, and is not
associated with any of the activity indicators. This favours the planet
hypothesis, and we fitted that signal with another Keplerian. A third signal
is revealed in the new periodogram of the residuals, with a period of 13.9
days and FAP of 0.23$\%$. Not only its FAP is above our defined detection
threshold of 0.1$\%$, but also, this period is about a third of the expected
stellar rotation period. Hence, it has to be interpreted carefully.

We explored the two Keplerians model via a MCMC algorithm, which allows us to
constrain the planet parameters. The parameters of HD 99492 b are in
accordance with previous publications, with results converging to
$P_{b}$=17.0492$\pm$0.0007 days and $K_{b}$=7.30$\pm$0.23  m s-1. Concerning
the new planet candidate, we found a moderate eccentricity
$e_{c}$=0.237$\pm$0.080, while the orbital period and the RV semi-amplitude
are estimated to $P_{c}$=95.373$\pm$0.050 days and $K_{c}$=3.08$\pm$0.27  m
s-1.

Figure 6: HD 99492: Periodograms of the combined YARARA-V1 and HIRES RV time-
series. The periodograms are computed from a fit of the time-series with a
detrend + drift model. Top – No Keplerian. Middle – Periodogram of the
residual time-series, after removing a Keplerian at $\sim$17 days. Bottom –
Periodogram of the residuals after removing Keplerians at $\sim$17 and 95
days.

###  4.2 Approach 2: SPLEAF – HARPS-N YARARA-V1 + HIRES

We repeated the process highlighted in Sect. 4.1 with HIRES and the YARARA-V1
data reduction of HARPS-N. Again, the signals at 17 and 95.5 days are
unambiguous. Fig. 6 illustrates our successive fitting process. The top plot
presents the periodogram of the RV time-series (the highest peak has a FAP of
1.1 10-80), while the middle plot shows the periodogram of the residuals after
fitting the RV with a Keplerian at 17 days. The highest peak in this middle
plot, located at P=95.4 days, has a FAP of 3.2 10-22. The bottom plot displays
the periodogram of the residuals after performing a two Keplerian fit,
including one at 17 days and one at 95.4 days. Now, the remaining signal at
13.9 days is no longer detected in the latter plot, but we observe another
signal at 14.5 days with a FAP of 0.13$\%$. Its significance is still below
our threshold of 0.1$\%$ in FAP. Both the low significance and the different
period detected for this third signal, in addition to its periodicity of about
a third of the expected stellar rotation period, cast doubt on its planetary
origin.

In order to shed light on the origin of this third signal, we scrutinised the
HIRES and HARPS-N datasets in a correlated noise model via SPLEAF (cf. Sect.
3.2), using both the RV and S-index time-series. At this stage, we used the
alternative YARARA-V1 dataset where the stellar activity was injected back
into the RV. We did not set any constraining prior on the period of the
correlated noise, nor on any other parameter (cf. Table 2). However, we
initialised the correlation period to 43 days, and the decay time-scale to 500
days. The large value for the latter is aimed at mitigating the magnetic
cycle, which takes place on a long time-scale. In order to facilitate the fit
convergence, we fitted the correlated noise model parameters on a step-by-step
strategy, successively adding an additional parameter. Then, we progressively
incorporated Keplerians until no more significant signal was observed. In
addition to these parameters, we also included an offset for each instrument
and a white noise term, both included for each time-series – namely the RV and
S-index time-series. Finally, we added a RV linear drift in the model, which
provided the best results in terms of signal significance and fit convergence
compared to a quadratic drift or no drift. As a result of our fit, we found a
first significant periodic signal at 17.05 days, with a negligible FAP of
4.5$\times$10-52. After adding a Keplerian in the model and proceeding with a
new fit, we detected another significant signal with a period of 95.3 days and
FAP=2.5$\times$10-18. Therefore, we incorporated a second Keplerian in our
model, and performed a new fit. In the periodogram of the residuals, there
remains a significant power around 3500 days which we attribute to a remnant
of the stellar magnetic cycle, while the decay time-scale of the correlated
noise converged to 194 days. Concerning the correlation period, it peaked at
44.8 days, which is compatible with the stellar rotation period. Then, we
explored the parameter space of the two-Keplerian model with a MCMC algorithm.
We performed 1M iterations, and obtained an effective sample of 4288
independent solutions. The period of the correlated noise is estimated to be
44.9$\pm$0.5 days. The outermost planet, at an orbital period of 95.4 days,
has an estimated RV semi-amplitude of 2.7$\pm$0.2 m/s, which corresponds to a
planet minimum mass of 17.4 $M_{\oplus}$. Its eccentricity is moderate, with
$e_{c}$=0.112$\pm$0.086.

###  4.3 Approach 3: SPLEAF – HARPS-N YARARA-V1

In a third approach, we employed again SPLEAF for a correlated noise model but
analysed only the HARPS-N data – YARARA-V1 with activity injected back into
the time-series. We undertook the same process as described above for the
second approach. Once again, we found two significant signals at 17 and 95.5
days. Their FAP are 3.0$\times$10-35 and 2.5$\times$10-20 respectively. A
third residual signal with a period of 14.7 days just reaches our detection
threshold, and has a FAP of 0.05$\%$. It has a small semi-amplitude of 1.0
m/s. This period is different from the previously found signals at 13.9 and
14.5 days, but is also compatible with a third of the stellar rotation period.
We note that the period of the correlated noise is estimated to 43.1 days. We
remind the reader that SPLEAF approximates the periodic component of the SEP
kernel by a development to the second order. To investigate further the
stellar rotation origin for the 14.7d signal, we developed the periodic
component to a higher order, so as to account for the third harmonic of the
stellar rotation period. We applied this refined kernel to the same dataset.
After the removal of two Keplerians at 17 and 95.5 days, the residual signal
at 14.7d is still significant with a FAP of 0.07$\%$. Developing the kernel up
to one additional order so as to entail the fourth harmonic yielded similar
results. The residual 14.7d signal has a FAP of 0.08$\%$ with this refined
development. However, in all cases, the period of the correlated noise
unambiguously converges towards the stellar rotation period. Therefore,
developing the periodic component of the kernel to a higher order should
absorb the harmonics of the stellar rotation. Consequently, the survival of
the 14.7d signal irrespective of the kernel development suggests this signal
is not a direct outcome of the third harmonic of stellar rotation. Instead,
its origin is likely different.

We undertook an MCMC exploration of the model with three Keplerians. As the RV
semi-amplitude of the third signal is small and in order to facilitate the
MCMC convergence, we fixed the eccentricity and argument of periastron of the
third Keplerian to 0. We performed 1M iterations, and obtained a total of 4856
independent solutions. Out of this exploration, we found RV semi-amplitudes of
$K_{b}$=6.99$\pm$0.17, $K_{c}$=2.83$\pm$0.20 and $K_{d}$=0.94$\pm$0.17  m s-1.
The orbital eccentricity of planet c is now smaller: $e_{c}$=0.052 with a
68.27$\%$ confidence interval of [0.019, 0.102].

We also explored the parameter space of a model with only two Keplerians,
given the doubt that we cast on the origin of the 14.7d signal. We performed a
new MCMC exploration of the model with two Keplerians, again with 1M
iterations. This time, we obtained a sample of 5440 independent solutions. The
correlated noise parameters display similar values at the end of the MCMC
exploration, compared to the model with three Keplerians. The same is observed
for planets b and c RV semi-amplitudes, and the orbital eccentricity of planet
c is once again constrained to be small. For this two Keplerian model, we
estimate a Bayesian information criterion (BIC) of -327.1, while the BIC of
the three Keplerian model amounts to -349.5. Therefore, the BIC indicates a
slight preference for the model with three Keplerians. As such, we further
tested the planetary nature of the 14.7 days signal, by investigating its
resistance to the removal of RV measurements. If the signal was due to a
planet, its power would monotonously decrease with the number of removed
observations. Instead, a signal of stellar origin would react irregularly to
the suppression of RV measurements. We performed different tests, following
various patterns of data removal (random, lowest S/N, highest S/N, data in
quadrature of the 14.7 days signal) and removing up to 10$\%$ of the time-
series. We found that while the signals at 17 and 95 days successfully passed
our tests, the significance of the 14.7 days signal did not decrease
monotonously with the number of removed observations. Instead, its power in
the periodogram evolved irregularly with the number of removed observations.
From this analysis, we conclude that the current observations do not support a
third planetary signal. On the other hand, the resilience of the 14.7 days
signal to the degree of development of SPLEAF indicates that it does not
emanate from the third harmonic of stellar rotation. Instead, it could be the
result of a combination between stellar rotation (or its second harmonic) and
the spectral window of the observations.

Figure 7: HD 99492 c posterior distributions for our different models and
datasets. The grey, blue, orange and green distributions refer to our first,
second, third, and fourth approaches to derive the posteriors, respectively.
In the case of the third approach, we further show the distributions resulting
from two different models. The plain line distribution was obtained from a
model with two Keplerians, while the dashed line corresponds to a model with
three Keplerians. Figure 8: HD 99492 orbital solutions for planets b and c
derived from the HARPS-N YARARA-V1 dataset. Left – Cartesian representation of
the planetary system for a sample of 205 MCMC solutions. The star is in red,
the orbit of HD 99492 b in blue and the orbit of HD 99492 c in orange.
Additionally, the green area marks the beginning of the conservative habitable
zone, which continues outwards. This was calculated from the prescription of
Kopparapu et al. (2013). Right – RV measurements phase-folded on the best fit
Keplerian solutions, together with the model curves.

###  4.4 Approach 4: HARPS-N YARARA-Shell

Finally, we investigated the YARARA-Shell dataset which, as compared to
YARARA-V1, further corrects from stellar activity features. We designed a
model that includes a white noise term, but does not include correlated noise.
After an iterative search, we found two significant signals at the periods
already mentioned above. The first signal, at 17.05 days, has a FAP of 5.1
10-62, while the second signal at 95.3 days has a FAP of 3.5 10-28. In the
residuals of this two planet model, we did not find any significant period.
The 14.7 days signal has now a FAP of 9.7$\%$. This observation further
comforts us in the non detection of a third Keplerian signal with the current
dataset. The analysis of YARARA-Shell, following the analysis of YARARA-V1
with SPLEAF, hereby demonstrates the power of using complementary analysis
techniques to shed light onto the nature of periodic signals.

We explored the two-planet model via the MCMC algorithm introduced above. We
performed 1M iterations, and obtained a set of 4095 independent solutions that
constitute our posterior distribution. While the RV semi-amplitude of the
outer planet $K_{c}$ is very similar to its estimate obtained using approach
3, the orbital eccentricity of that planet converges towards a larger value of
about 0.1.

In Fig. 7, we synthesise the results from the four approaches described above.
It shows the posterior distributions obtained with the different approaches,
and projected on the orbital parameters of planet c. Additionally, we also
distinguish between the two and three planets fits performed in the third
approach. We conclude that the inclusion of the HIRES RV measurements
increases the estimation of the eccentricity of planet c. This is probably due
to a less efficient mitigation of stellar activity effects on the HIRES
measurements. Indeed, as was already mentioned,we did not find a clear
periodicity of $\sim$43 days in the S-index of HIRES. We note that the
analysis without the HIRES data provides the best estimations on the planet
parameters. Furthermore, using the YARARA-V1 data alone, the estimates we
obtain for the parameters of planet c are very similar in the models with two
or three Keplerians. The third periodic signal at 14.7 days is absent from the
YARARA-Shell data. This latter dataset, however, leads to a larger estimate of
the eccentricity $e_{c}$. As pointed out in Hara et al. (2019), complex noise
patterns – if not modelled – can boost the eccentricity estimations. This
additional eccentricity induced by stellar activity likely also drives the
shift observed in the distribution of $\omega_{c}$ from YARARA-Shell. Indeed,
small orbital eccentricities do not constrain well the argument of periastron,
as illustrated with the orange distributions. Any additional eccentricity
would hence carry a significant influence on the distribution of $\omega$. In
conclusion, we favour the approach leading to the smallest eccentricities. We
opt for the approach using the YARARA-V1 dataset only together with a
correlated noise analysis, namely approach 3 with a two-planet model. These
results are synthesised in Table 3. They suggest that planet c has a minimal
mass of 17.9$\pm$1.3 $M_{\oplus}$, which is equivalent to the mass of Neptune.
So far, few planets in that mass range have been found with large (¿50 days)
orbital periods. We further discuss this result in Sect. 7. We present in Fig.
8 the plot of the orbits in the cartesian space, and the RV phase-folded on
the period of the two planets.

###  4.5 Independent confirmation using tweaks

The HARPS-N CCF were independently analysed for planetary signals using
tweaks. This pipeline was particularly designed for attaining a sub-m/s
detection threshold at long orbital periods, by combining the wavelength-
domain and time-domain stellar activity mitigation (Anna John et al. 2022,
2023). We first conducted a blind search of the radial velocities, using a
model with up to five unidentified Keplerian signals. For this, we used the
kima nested-sampling package (Faria et al. 2018). Using scalpels (Collier
Cameron et al. 2021), which involves doing a principal-component analysis on
the autocorrelation function of the CCF, time-domain activity-decorrelation
vectors were produced. These basis vectors were then used for the spectral
line-shape decorrelation (Collier Cameron et al. 2021) in kima, as Anna John
et al. (2022) reported that de-trending the RV for line shape variations using
the SCALPELS basis vectors yields a model that is significantly better than a
model that does not account for these stellar activity signatures.

The joint posteriors showed clear detection of two Keplerian signals at
orbital periods 17.05 days and 95.2 days. We conducted a False Inclusion
Probability (FIP) analysis (Hara et al. 2022) in frequency space, with the bin
size set to the Nyquist frequency resolution over the entire data duration to
search for multiple planet signals simultaneously. While a strong FIP of 0.13
was found for the 17.05 day signal, the 95.2 day signal was detected even more
strongly with a FIP of 0.04; in other words, 96% of the mutually independent
kima posterior solutions favoured a planet detection at an orbital period of
95.2 days. We present these results in the Appendix – Fig. 18. The RV semi-
amplitudes obtained from this analysis were combined with the stellar mass of
0.85 $M_{\odot}$, leading to a minimum mass determination of 27.13 ± 1.18
$M_{\oplus}$ and 19.85 ± 2.19 $M_{\oplus}$ respectively. We also validated
these detections by confirming the coherency of the signals across different
data subsets. Unlike the signals occurring from sampling patterns, stellar
activity or aliases, both the 17.05 and 95 d signals were strongly detected in
all the subsets with sigma $\geq$9$\sigma$. Finally, as opposed to these two
planetary signals, the signal at 14d is not consistent in time. It is only
detected in the second half of the data. This further motivates us to discard
this signal as a potential additional planet.

###  4.6 Transit search

We analysed the TESS photometry in search for transit signals. To treat the
instrumental systematics, we extracted our custom light-curve from the 2-min
cadence pixel files with lightkurve, following the process explained in Sect.
2.2.1. To aim at the transit search, we detrended our light curve from a
combination of multi-scale and spike CBV. Indeed, we found that this model
performs better at minimising the Combined Differential Photometric Precision
(CDPP) metric, which is a measure of the remaining scatter in the light curve
expressed in parts-per-million (ppm). Our corrected light curve presents a
CDPP of 123 ppm.

As a second step, we undertook the removal of the remaining stellar
systematics on our corrected light-curve. We applied a detrending via splines
fitting using keplersplinev2666https://github.com/avanderburg/keplersplinev2,
and letting free the parameter describing the time-scale of variation of the
spline, only imposing a lower boundary of 0.5 day. The fit converged to a
time-scale of 0.74 day, and the modelled trend was removed from our light-
curve. The resulting detrended light-curve is presented in Appendix, Fig. 20
(top panel).

We undertook a multi-transits search in this detrended light-curve. It was
carried out with the transitleastsquares
software777https://transitleastsquares.readthedocs.io/en/latest. This search
was done via the computation of a box least square (BLS) periodogram, with an
orbital period search comprised between 2 and 20 days. We did not find any
significant transit signal in this period range. From the estimated minimum
mass of planet b, the mass-radius relationship for rocky planets888While the
minimum mass of planet b points towards a gas-rich composition, here we
explored the unfavourable case of rocky composition so to estimate the transit
detectability in an unfavourable scenario. This comment also applies for the
transit searches presented in Sect. 5.2 and 6.2. from Otegi et al. (2020) and
the stellar radius reported on exofop999https://exofop.ipac.caltech.edu/tess/,
we estimated a transit depth of $\sim$1000ppm. We do not observe any hint of a
transit signal at the period and phase of planet b estimated from our RV
analysis. Concerning planet c, the expected transit time occurred at the
beginning of sector 45. Under the hypothesis of a rocky composition, the
planet would induce a transit depth of 850ppm on its parent star, which we do
not see in the data. For both planets, the hypothetical transit depths are
large enough compared to the light-curve noise, and they would be detected.
Therefore, we rule out the transiting configuration of HD 99492 b. Concerning
the outer planet, the TESS observations do not cover all the orbital phases,
and given the uncertainty on the transit time it is possible that a potential
transit was missed. However, it is unlikely given the low transit probability
of such a long-period planet ($\sim$1$\%$). Details of the transit searches
can be found in Appendix B and Fig. 20.

We also analysed the TESS sectors 45 and 46 in search for potential single
transit features. To proceed, we fitted our detrended light curve based on two
distinct models: no planet and one planet models. We compared the posterior
probabilities of the models using the true inclusion probability (TIP)
detection criterion (Hara et al. 2022), which provides us with a rigorous
transit detection threshold. A TIP of 1 would favour the one planet model with
a probability of 100$\%$ (TIP=1-FIP). This framework was first designed for RV
data, and was later on applied to transit analyses (Hoyer et al. 2022;
Ehrenreich et al. 2023, Wilson et al. in prep.). To aid convergence we
performed the TIP analyses on one-day slices of the TESS sectors. We ran two
sets of analyses employing different priors to first search for any transit
signal and subsequently to probe the transiting nature of HD 99492 b: wide
planetary priors in one case, priors constrained on the HD 99492 b planet
parameters as reported in this study in the other case. We did not find any
preference for the one-planet model as the TIP never exceeds 0.5 across the
entire light curve (cf. Appendix – Fig. 21). Therefore, we conclude on the
absence of transit signals in this data set.

##  5 HD 147379 data analysis

HD 147379 was first found to harbour a planet by the CARMENES team (Reiners et
al. 2018). With the help of 114 CARMENES RV measurements and an additional 30
HIRES RV, they detected a planet with a minimum mass of $\sim$25 $M_{\oplus}$
in a 86.5 day orbit. This detection was independently confirmed by the SOPHIE
team, with a dataset of 163 SOPHIE RV measurements (Hobson et al. 2018). A
noticeable fact about HD 147379 b is that it lies in the conservative
habitable zone of its host star, as defined by Kopparapu et al. (2013).

###  5.1 RV analysis

We analysed this system using exclusively the 165 nightly binned HARPS-N RV
measurements. As with HD 99492, we first looked in the modified YARARA-V1
dataset for activity signatures – that is YARARA-V1 where the stellar activity
was injected back in the RV. Besides the long-term trend due to the stellar
magnetic cycle, the most significant signal is detected in the S-index
indicator and peaks at 21.6 days. Furthermore, we observe a weak correlation
between the RV and the S-index measurements, with a correlation coefficient of
R=0.39 (cf. Appendix – Fig. 16).

Figure 9: HD 147379 planet search. Top and Middle panels – GLS periodograms of
the HARPS-N YARARA-V1 RV time-series, in a model with correlated noise and
with no Keplerian in the model ($k_{0}$) and one Keplerian ($k_{1}$) at a
period of 86.5 days. Bottom panel – RV measurements phase-folded on the 86.5
days signal.

In a second step, we undertook an analysis of the RV in search for planetary
signals. We employed a correlated noise model with SPLEAF, using both the RV
and S-index time-series. We also included in the model an offset, a white
noise term and a linear drift term101010The inclusion of a linear drift in our
model yielded the largest likelihood.. Wide uniform priors were injected, and
we initialised the correlated noise with a period of 22 days and a large
correlation decay time-scale of 500 days. After performing a first fit – again
through a successive addition in the model of the different correlated noise
parameters – we find a significant signal at 86.5 days in the periodogram of
the residuals (Fig. 9). We include the latter in our model as a Keplerian, and
fit again the RV time-series with the new model. In the periodogram of the
residuals, we do not find additional significant signals and the correlated
noise period is fitted to 21.8 days, which is the expected stellar rotation
period. The most prominent signal that we find in the residuals has a period
of 7.1 days, which is about a third of the estimated stellar rotation period,
and FAP=3.8$\%$. This signal is pushed down to a FAP of 23$\%$ when we use the
augmented version of SPLEAF, which develops further the periodic component of
the kernel to account for the third harmonic. This result further suggests the
stellar rotation origin of the 7.1d signal. Furthermore, we do not find any
signal around 500 days, which was reported by Hobson et al. (2018) using the
SOPHIE data alone. Therefore, we stop our planet search and consider a model
composed of one Keplerian only. The exploration of this model was performed
with a MCMC, using 500k iterations leading to a final sample of 3298
independent solutions. The results are presented in Table 3. The stellar
rotation period that we estimate ($P_{GP}$=21.9$\pm$0.4 days) is consistent
with previous investigations, and our correlated noise model converges to a
correlation decay time-scale of 28.3$\pm$4.4 days. The minimum mass of HD
147379 b is found to be smaller than both the estimates of Reiners et al.
(2018) with 24.7$\begin{subarray}{c}+1.8\\\ -2.4\end{subarray}$ $M_{\oplus}$
and Hobson et al. (2018) with 28.6$\pm$1.5 $M_{\oplus}$ – our result suggests
21.6$\pm$1.1 $M_{\oplus}$, or about 1.26 times the mass of Neptune, and was
derived from a careful mitigation of stellar rotation features. The bottom
plot of Fig. 9 presents the RV measurements folded on the orbital period and
phase of HD 147379 b.

As a comparison, we searched for planetary signals with HARPS-N using the
YARARA-Shell post-process. After deriving the cleaned RV, we computed a
periodogram which unambiguously revealed the 86.5d planet (FAP=3.3 10-33).
After fitting the latter with a Keplerian model and computing the periodogram
of the residual RV, we did not find any signal that reaches our detection
threshold of FAP=0.1$\%$. The strongest peak stands at a period of 12.3d, and
has FAP=0.5$\%$. Because of this too large FAP and the weakness of the signal
in V1-SPLEAF (FAP¿10$\%$), we did not retain this signal as a planetary
candidate. Further observations are needed to shed light on this signal.

Finally, we also analysed the entire dataset composed of the HARPS-N (DRS),
CARMENES, SOPHIE and HIRES RV. This ensemble consists of 458 RV
measurements111111Nine measurements from the SOPHIE spectrograph were
neglected following Hobson et al. (2018), because of an uncertainty larger
than 35 m/s on the RV measurement.. However, we note that the CARMENES and
SOPHIE public data do not contain spectroscopic activity indicators, but only
the RV measurements. Therefore, we could not carry a reliable modelling of
stellar activity. We only applied a linear drift fit, in order to account for
an observable trend. We computed the GLS periodogram of the residuals on this
combined dataset, and found the 86.5d planet as the most significant peak.
After its subtraction from the time-series and the computation of the updated
periodogram, we found several periodic signals with a FAP below 0.1$\%$ at
10.6, 12.3 and 21.4 days. While the signals at 10.6 and 21.4 days are
attributed to stellar rotation (they correspond to 0.5 and 1 time the stellar
rotation period, respectively), the signal at 12.3 days is more unclear.
Nevertheless, we note that its fit with a Keplerian yields a large
eccentricity of 0.25. With the HARPS-N data alone, this remaining signal not
only is less significant, but also leads to a large orbital eccentricity of
0.62 if we fit it with a Keplerian. As a result, we put strong caution about
the planetary nature of this 12.3d signal, and presently interpret it as an
artefact of stellar activity. The Keplerian orbital parameters of HD 147379 b
that we derived from the combined dataset suggest a minimum mass of
msini=25.2M⊕ (K=5.25 m s-1). In Fig. 19, we present the RV folded on this
Keplerian solution. Again, we stress that these results do not include a
careful modelling of stellar activity. Therefore, our analysis of the HARPS-N
YARARA-V1 data alone together with SPLEAF is favoured, and its results defines
our final solution for the orbital parameters of HD 147379 b.

###  5.2 Transit search

We scrutinised the full TESS light curve in search of any transiting signal.
To proceed, we extracted the light curve of each of the 28 sectors following
the same procedure as described in Sect. 2.2.1. After downloading the CBV of
those sectors, we found that the combination of multi-scale and spike CBV
provides the best corrections in terms of minimising the CDPP metric, with an
average CDPP of $\sim$90 ppm over the sectors. We further detrended the
resulting light curve from any remaining stellar systematics with
keplersplinev2. Our detrending fit converged to a spline variation time-scale
of 0.9 d.

We then undertook several successive transit searches, for orbital periods
between 2 and 20 days, between 20 and 70 days, and between 70 and 100 days. In
none of the BLS periodograms did we find significant peaks. Concerning HD
147379 b, using the mass-radius relationship of the rocky population from
Otegi et al. (2020) – considering the unfavourable case of a high bulk density
– and the stellar radius provided on exofop, we estimated the transit depth to
$\sim$1200ppm. The planet would hence be detected given the large time-span of
the TESS observations, and we conclude that it does not transit its parent
star. We refer to the Appendix – Fig. 22 for more details.

##  6 HD 190007 data analysis

A planet candidate was recently suggested to orbit HD 190007 (Burt et al.
2021). The authors used the combined RV dataset of APF and HIRES in order to
determine the planetary characteristics. They found a body that orbits its
star with a period of 11.7 days and a minimum mass of 16.46 $M_{\oplus}$. The
stellar rotation is visible in the data, and they modelled the latter using a
Keplerian with a period consistent with the photometric variability ($\sim$ 29
days).

Figure 10: HD 190007: Periodograms of the full RV time-series. Top left – No
Keplerian ($k_{0}$), and no correlated noise (CN) in the model. Bottom left –
One Keplerian ($k_{1}$) in the model, at a period of 11.7 days. Top right –
Inclusion of a CN model, no Keplerian. Bottom right – Inclusion of both CN and
one Keplerian models. Figure 11: HD 190007: RV measurements phase-folded on
the Keplerian solution of HD 190007 b.

###  6.1 RV analysis

We reviewed this solution by adding our set of 37 nightly binned HARPS-N
measurements, and analysing the combined dataset. In total, we used 159 RV.
Given the small number of HARPS-N RV measurements, we could not reliably
process them with YARARA. Indeed, the algorithms behind the post-processing
require several dozens of observations with different barycentric Earth RV
(BERV) in order to not over-fit the data. Also, to work properly, having
several observations per BERV bin element is mandatory, a condition not
satisfied in this case. Instead, we used the data derived from the new DRS
(Dumusque et al. 2021). After correcting for the different instrument offsets
and accounting for drifts, the periodogram of the RV time-series clearly shows
the presence of the 11.7 days planet. Additionally, a significant signal is
visible with a period of $\sim$28 days, consistent with the stellar rotation
period. This periodogram is presented in the top left plot of Fig. 10. At the
bottom left, we show the periodogram of the residual RV, after subtraction
from a Keplerian model with a period of 11.7 days. Significant power is still
observed at the rotation period and half of it. Burt et al. (2021) fitted the
28 days signal with another Keplerian.

Our three datasets – HARPS-N, HIRES and APF – contain the S-index indicator.
We used this information to train a correlated noise model, and apply it
simultaneously on the RV time-series. Again, we employed SPLEAF to model the
correlated noise. Given the tight constraints on the stellar rotation period,
we set a uniform prior on the correlated noise period between 25 and 30 days.
We set priors on the other parameters of the correlated noise model according
to Table 2. We initialised the model with a correlated noise period of 28 days
and a decay time-scale of 200 days. Beside the correlated noise parameters, we
also included in the model the instrumental offsets and a white noise term. We
fitted the data with all the parameters of the model, and present the
resulting periodogram of the RV residuals at the top right plot of Fig. 10.
The planetary signal at 11.7 days is more significant. Its has a FAP of 3
10-10. Naturally, we further note that the signal at $\sim$28 days
disappeared. As a second step, we included a Keplerian with a period of 11.7
days in the model, and performed a new fit. The bottom right plot of Fig. 10
shows the periodogram of the new residuals. Without ambiguity, no significant
signal remains. Therefore, the correlated noise modelling provides a solution
cleaned from the stellar rotation effects. It is able to model the main
stellar rotation period and its harmonic better than a single Keplerian as
previously done by Burt et al. (2021). The minimum mass of the planet and the
orbital eccentricity are estimated to 15.5$\pm$1.3 $M_{\oplus}$ and
0.14$\pm$0.08, respectively. This is in agreement with Burt et al. (2021),
which estimated a minimum mass of 16.5$\pm$1.7 $M_{\oplus}$ and an
eccentricity of 0.14$\pm$0.07. We present the updated planetary parameters in
Table 3, and the phase-folded RV time-series in Fig. 11.

###  6.2 Transit search

We analysed the photometry of TESS sector 54 in search for transit signals.
Again, we retrieved the 2-min cadence target pixel files and downloaded the
CBV of sector 54. We applied aperture photometry and corrected the light-curve
for instrumental systematics via a joint fit of multi-scale and spike CBV and
background subtraction at the pixels level (as explained in Sect. 2.2.1). A
special care with the detrending was needed due to the rapidly-varying
variability of the star. When let free, the parameter describing the time-
scale of variation of the spline converged to the lower limit that we imposed
(i.e. 0.5d). We undertook several BLS transit searches between orbital periods
of 0.5 and 13 days, exploring various detrend time-scales in the interval
[0.5, 1.5] days with the parameter bkspace of the function keplersplinev2.
Irrespective of the detrend time-scale, we did not find any significant signal
in the BLS periodogram.

We computed the expected transit times, depth and duration of planet b. To
proceed, we used the results of our RV analysis, the stellar radius reported
on exofop, and the mass-radius relationship for rocky planets taken from Otegi
et al. (2020) – again, we tested the transit detectability in the unfavourable
case of a high bulk density, noting however that HD 190007 b is more likely
gas-rich. We estimated the transit depth to 920ppm, which is significant
compared to the scatter observed in our detrended light curve. However, we did
not find hints of transits that match with the expected ephemerides of planet
b. We refer to the Appendix – Fig. 23 for more details.

In a second approach, we scrutinised the TESS sector 54 considering potential
single transit features. To proceed, we applied the same single-transit search
process as the one employed for HD 99492 (cf. Sect. 4.6) and based on the TIP
framework. Again, we ran two distinct analyses with wide priors on one side,
and priors constrained on the ephemerides of HD 190007 b as derived from our
RV modelling on the other side. In both cases, the absence of planetary
transits was unambiguously favoured. Therefore, we rule out the presence of
transits in the data.

Table 3: Final results of the fits on HD 99492, HD 147379, and HD 190007. We report the median values from the posterior distribution of the MCMC exploration. The uncertainties in the parameters are 68.27$\%$ confidence intervals. Parameter | Units | HD 99492 |  | HD 147379 | HD 190007
---|---|---|---|---|---
Offsets ($\gamma$) and jitter ($\sigma$) |  |  |  |  |
$\gamma_{HARPS-N}$ | m s-1 | -2.18$\pm$0.69 |  | -113.2$\pm$22.8 | 0.94$\pm$0.97
$\gamma_{APF}$ | m s-1 | / |  | / | -1.44$\pm$0.44
$\gamma_{HIRES}$ | m s-1 | / |  | / | -1.37$\begin{subarray}{c}+1.37\\\ -1.40\end{subarray}$
$\sigma_{RV}$ | m s-1 | 1.56$\pm$0.10 |  | 0.98$\begin{subarray}{c}+0.13\\\ -0.12\end{subarray}$ | 2.57$\begin{subarray}{c}+0.30\\\ -0.27\end{subarray}$
Correlated noise |  |  |  |  |
$P_{GP}$ | days | 43.65$\begin{subarray}{c}+0.47\\\ -0.56\end{subarray}$ |  | 21.94$\begin{subarray}{c}+0.42\\\ -0.44\end{subarray}$ | 30.71$\begin{subarray}{c}+0.89\\\ -0.72\end{subarray}$
$\rho_{GP}$ | days | 152.7$\begin{subarray}{c}+22.5\\\ -20.7\end{subarray}$ |  | 28.31$\begin{subarray}{c}+4.43\\\ -4.12\end{subarray}$ | 39.0$\begin{subarray}{c}+7.1\\\ -5.7\end{subarray}$
$\eta_{GP}$ |  | 0.94$\begin{subarray}{c}+0.16\\\ -0.13\end{subarray}$ |  | 0.61$\begin{subarray}{c}+0.10\\\ -0.09\end{subarray}$ | 0.97$\begin{subarray}{c}+0.17\\\ -0.15\end{subarray}$
Planets |  |  |  |  |
Parameter | Units | HD 99492 b | HD 99492 c | HD147379 b | HD 190007 b
$P$ | days | 17.0503$\pm$0.0016 | 95.233$\begin{subarray}{c}+0.098\\\ -0.096\end{subarray}$ | 86.58$\pm$0.14 | 11.724128(99)
$K$ | m s-1 | 7.05$\pm$0.18 | 2.79$\begin{subarray}{c}+0.22\\\ -0.21\end{subarray}$ | 4.49$\pm$0.22 | 4.91$\pm$0.45
$e$ |  | 0.034$\begin{subarray}{c}+0.025\\\ -0.021\end{subarray}$ | 0.063$\begin{subarray}{c}+0.060\\\ -0.040\end{subarray}$ | 0.063$\begin{subarray}{c}+0.047\\\ -0.038\end{subarray}$ | 0.136$\begin{subarray}{c}+0.085\\\ -0.080\end{subarray}$
$\omega$ | deg | 154.3$\begin{subarray}{c}+48.6\\\ -48.0\end{subarray}$ | 137.5$\begin{subarray}{c}+107.7\\\ -62.9\end{subarray}$ | 130.1$\begin{subarray}{c}+58.3\\\ -48.1\end{subarray}$ | 2.3$\begin{subarray}{c}+50.5\\\ -46.3\end{subarray}$
$\lambda_{0}$ | deg | 276.4$\pm$5.2 | 351.2$\pm$10.3 | 204.6$\begin{subarray}{c}+20.1\\\ -19.7\end{subarray}$ | 78.1$\begin{subarray}{c}+8.2\\\ -7.9\end{subarray}$
$m\hbox{sin\,$i$}$ | $M_{\oplus}$ | 25.5$\pm$0.6 | 17.9$\pm$1.3 | 21.6$\pm$1.1 | 15.5$\begin{subarray}{c}+1.2\\\ -1.3\end{subarray}$

##  7 Discussion and conclusions

In this work, we presented the HARPS-N spectroscopic data acquired on three
stars: HD 99492, HD 147379 and HD 190007, all of them already known to harbour
planets. We reviewed those planetary systems with the help of advanced data
analysis tools. YARARA-V1 provided us with HARPS-N datasets cleaned from any
instrumental effects. Additionally, we used the generalised SPLEAF model to
carefully and efficiently mitigate stellar activity. The combination of these
two tools was shown to provide the best results with respect to other
strategies, as discussed for HD 99492 in Sect. 4. We updated the orbit of the
known planet HD 99492 b ($P$=17.05 days), and unambiguously detected a second
planetary companion, namely HD 99492 c, that we confirmed independently using
tweaks. This second planet orbits its parent star in 95.2 days, and has an
estimated minimum mass of 17.9$\pm$1.3 $M_{\oplus}$. The analysis of the 165
nightly binned HARPS-N measurements of HD 147379 did not lead to a new planet
detection. We also did not find any transit signal in the extensive 28 TESS
sectors. However, we updated the parameters of HD 147379 b, and notably found
a minimum mass smaller than previous studies (Reiners et al. 2018; Hobson et
al. 2018) – our new estimate, peaking at 21.6$\pm$1.1 $M_{\oplus}$, is
2.6$\sigma$ away from the nearest value provided by Reiners et al. (2018).
Finally, we reviewed the system HD 190007 with the addition of our 37 nightly
binned HARPS-N measurements to the publicly available HIRES and APF data. We
performed a correlated noise analysis to account for the strong stellar
rotation signal. We updated the solution of the known planet at $P=11.7$ days,
and obtained a minimum mass of 15.5$\pm$1.3 $M_{\oplus}$. The results from our
review of the three planetary systems are presented in Table 3. We also
carried out a systematic transit search in the available TESS sectors, and did
not find transit signals.

Figure 12: Exoplanet population with a minimum mass measurement msini. Panel
a: Sub-population with large orbital periods (P¿50 days). This sample contains
428 exoplanets. Top – Histogram of that population, with respect to the planet
minimum mass. The vertical grey and green lines identify the position of HD
99492 c and HD 147379 b, respectively. Bottom – Proportion of planets that are
part of multi-planet systems, among the considered sub-population. Panel b:
Sub-population with small orbital periods (P¡50 days). Top – Distribution of
that sub-population according to msini (in orange). The red histogram
indicates companions to the low-mass long-period planets (red zone in Panel
a). The grey histogram focuses on companions to the large-mass long-period
planets (grey zone in Panel a). Bottom – Proportion of planets part of multi-
planet systems. Figure 13: Exoplanet population from the Kepler and TESS
surveys, distributed in planet radius between 3.5 and 15 $R_{\oplus}$. This
population is composed of 632 planets as of March 22, 2023. Top – Histogram of
the considered populations. Bottom – Proportion of planets part of multi-
planet systems.

HD 99492 c and HD 147379 b have orbital periods and minimum masses that stand
in an underpopulated region of the parameter space. Fig. 12a presents the
distribution of known exoplanets with measured minimum masses
$m\hbox{sin\,$i$}$, and with large orbital periods $P>50$ days. This
population is composed of 962 planets, according to the Exoplanet
Archive121212https://exoplanetarchive.ipac.caltech.edu/ as of March 22, 2023.
We note that this distribution also includes long-period transiting planets
whose masses are constrained with RV measurements. The positions of HD 99492 c
and HD 147379 b in this plot are represented by vertical grey and green lines,
respectively. For comparison, we indicate the position of Neptune, Saturn and
Jupiter in this histogram. This distribution unambiguously reveals a larger
number of long-period giant exoplanets. Naturally, observational biases play
an important role in this picture, since Neptune-mass exoplanets on long
orbital periods are technically more challenging to detect. However, a closer
inspection of this histogram may reveal a potential lack of planets between 30
and 50 Earth masses, giving rise to two distinct populations that the
observational biases hardly explain.

To estimate the statistical significance of this bimodality, and hence the
existence of two planet populations, we tested the similarity between this
distribution and a single-mode Gaussian distribution. To proceed, we defined
the large-mass sub-sample by setting a mass threshold at 50 $M_{\oplus}$, and
fitted a Gaussian law on this sub-sample. Then, we generated a random sample
following this law, and with the same size as the full distribution. Finally,
we computed the p-value between this Gaussian and the blue histogram. We
repeated this procedure 10 000 times, and derived a distribution of p-values.
In those results, the maximum p-value obtained is 3 10-4, which indicates that
all of our 10 000 tests support the hypothesis of two distinct distributions
between the planet distribution and the fitted Gaussian. As a second
statistical test, we performed a Z-test between the sample of planets with
msin $i$¡ 50 $M_{\oplus}$ (red shaded area), and the sample with msin $i$¿ 50
$M_{\oplus}$ (grey shaded area) to quantify their mutual difference. This test
compares the means and standard deviations of two samples, and indicates if
these samples significantly differ from each other. We fitted both large-mass
and small-mass sub-samples with a Gaussian, and applied the Z-test on these
adjusted laws. The test returned the value of 2.94, which points towards a
significant difference between the two populations. We repeated the Z-test
with a new separation threshold of 30 $M_{\oplus}$ between the two
populations, and obtained the value of 3.06, again indicating a significant
difference between these two populations. Therefore, our analyses support the
bimodality of the planet distribution.

We bring an additional support to the bimodality in the bottom panel of Fig.
12a. It presents, among the considered population, the percentage of planets
found in multi-planet systems. The planets seem to be globally found in
distinct system architectures. Despite the large uncertainties in the small-
mass population caused by the small number of detections, we observe that
these planets are most often found in multi-planet systems. For higher-mass
planets, this ratio is significantly smaller. Those results support previous
RV-detected planet statistics. Notably, Winn & Fabrycky (2015) pinpoint a
bimodality in the distribution of minimum masses, without distinction of
orbital period – see their Fig. 4. In that same figure, the authors
illustrate, at the population level, the increase in eccentricity scatter for
larger minimum masses. Besides, among the exoplanet population, lower
multiplicity systems present also a larger eccentricity scatter (Wright et al.
2009; Limbach & Turner 2015). Through the link of orbital eccentricity, we
hence deduce that large-mass planets tend to be found in systems with smaller
multiplicity, according to the RV surveys. The results that we present in the
lower panel of Fig. 12a corroborate these observations, since larger-mass
planets seem to be more often found in single-planet systems. Again, while we
raise a hint of a trend, we stress that a treatment of detection biases is
needed to confirm this statement.

We compared these results with the short-period planet population. Fig. 12b
shows the population of exoplanets with measured minimum masses, but this time
with a focus on short-period planets ($P<50$ days). The double peak
distribution is more prominent than for the long-period population, and a
similar trend with the system multiplicity is observed. We undertook a new
Z-test for a threshold mass of 50 $M_{\oplus}$, and obtained a value of 2.78
which confirms the likely bimodality of the distribution. We note that at
short orbital periods, low-mass planets appear more common than giant planets.
The opposite is observed for long-period planets. This observation is in line
with classical theories of planet formation, for which gas giants are formed
in cooler regions of the protoplanetary disk, as opposed to smaller-mass
planets. However, we stress that detection biases likely alter this picture.
Furthermore, we highlighted with the red histogram the short-period planet
companions to the low-mass long-period planets located in the red zone of Fig
12a. Most of these planets have smaller masses too. Conversely, we highlighted
with the grey histogram the short-period planet companions to the large-mass
long-period planets inside the grey zone of Fig. 12a, which does not indicate
a strong preference for large or small mass companions. Additionally, the red
histogram constitutes most of the planet companions to low-mass long-period
planets with a measured minimum mass, with 80 planets out of 94 companions in
total, that is 85$\%$. The remaining 15$\%$ are long-period planets. As a
result, most of the companions to the small-mass long-period planets have
small masses and short periods.

Based on all those observations, we would therefore expect HD 147379 to be
orbited by at least a second planetary companion inner to HD 147379 b, with
the hypothesis that this system follows the observed trend. We stress,
however, that the statistics have low numbers and that the observational
biases could alter this picture. Continuing observational efforts using high-
resolution spectrographs will help to augment those statistics and refine the
architectures of planetary systems. Finally, we note that a similar bimodality
is observed in the true mass distribution of exoplanets.

We put these results in light of the Kepler and TESS transit surveys in Fig.
13. The histogram presents the population of confirmed Kepler and TESS planets
spread over radius, in the range [3.5, 15] $R_{\oplus}$ so to entail the
Neptune-size regime and above. In these data, there might also be a tentative
hint of two distinct populations separated around 7 $R_{\oplus}$, which
corresponds to a mass of 38$M_{\oplus}$ using the mass-radius relationship for
volatile-rich planets (Otegi et al. 2020). The location of this boundary hence
overlaps with the ones observed in Fig. 12a and b. Nevertheless, this
separation is here too shallow for any further prospects. Moreover, there is
no clear trend in the proportion of planets in multi-planet systems as a
function of planet radius in this considered radius range, as is illustrated
in the bottom panel. Different factors could explain this discrepancy with the
RV surveys, such as a non homogeneous scaling law for the planets bulk
density, or probing different types of systems from the transit and RV
surveys. This is briefly discussed in Leleu et al. (2023), in the context of
the mass dichotomy between RV and transit-timing variations (TTV) techniques.

This work has once again proven the importance of long-term RV surveys with
stable high-precision spectrographs for the detection and characterisation of
warm planets, which constitute a yet under-explored family of exoplanets.
Additionally, the use of advanced tools for the removal of instrumental
systematics and for modelling correlated noise sheds light on the noise
pattern, and pushes further the barriers of small-mass planet detections.

###### Acknowledgements.

This work is based on observations made with the Italian Telescopio Nazionale
Galileo (TNG) operated by the Fundación Galileo Galilei (FGG) of the Istituto
Nazionale di Astrofisica (INAF) at the Observatorio del Roque de los Muchachos
(La Palma, Canary Islands, Spain). The HARPS-N project was funded by the
Prodex Program of the Swiss Space Office (SSO), the Harvard University Origin
of Life Initiative (HUOLI), the Scottish Universities Physics Alliance (SUPA),
the University of Geneva, the Smithsonian Astrophysical Observatory (SAO), the
Italian National Astrophysical Institute (INAF), University of St. Andrews,
Queen’s University Belfast, and University of Edinburgh. This work has been
carried out within the framework of the National Centre of Competence in
Research PlanetS supported by the Swiss National Science Foundation under
grants 51NF40_182901 and 51NF40_205606. The authors acknowledge the financial
support of the SNSF. This work has made use of data from the European Space
Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the
Gaia Data Processing and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement. M.C. acknowledges the SNSF
support under grant P500PT_211024. R.D.H. is funded by the UK Science and
Technology Facilities Council (STFC)’s Ernest Rutherford Fellowship (grant
number ST/V004735/1). FPE and CLO would like to acknowledge the Swiss National
Science Foundation (SNSF) for supporting research with HARPS-N through the
SNSF grants nr. 140649, 152721, 166227 and 184618. The HARPS-N Instrument
Project was partially funded through the Swiss ESA-PRODEX Programme. TGW
acknowledges support from STFC consolidated grant number ST/V000861/1 and UKSA
grant number ST/R003203/1. This project has received funding from the European
Research Council (ERC) under the European Union’s Horizon 2020 research and
innovation programme (grant agreement SCORE No 851555). A.S. acknowledges
financial support from the agreement ASI-INAF n.2018-16-HH.0. Finally, the
authors thank the referee for their insightful comments and suggestions on the
paper.

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##  Appendix A Complementary spectroscopic data

We present in this section complementary spectroscopic data, in the order with
which they are mentioned in the main text. Fig. 14 illustrates the entire
high-precision RV time-series of HD 147379, built up from the combination of
HIRES, CARMENES, SOPHIE and HARPS-N data. Fig. 15, 16, and 17 display the
various spectroscopic activity indicator data on HD 99492, HD 147379 and HD
190007, respectively. Trends and correlations with the RV are hinted. Fig. 18
presents the TWEAKS results on HD 99492, which confirm the detection of two
planet signals and help to rule out the planetary nature of the 14d signal.
Finally, Fig. 19 depicts the HD 147379 RV folded on our Keplerian solution for
planet b obtained with all the available RV data. This solution results from
an analysis of the RV only, and hence it is not favoured. We refer to Table 3
for the preferred updated Keplerian parameters of HD 147379 b, based on the
analysis of the HARPS-N YARARA-V1 data together with SPLEAF.

Figure 14: Entire RV time-series of HD 147374. It combines our HARPS-N RV
measurements with the public data from HIRES, CARMENES, and SOPHIE high-
resolution spectrographs. Figure 15: HARPS-N RV and spectroscopic activity
indicators of HD 99492. This dataset is cleaned from instrumental systematics
but still contains the stellar activity features, as obtained with the
YARARA-V1 post-process described in Sect. 3.1 and Appendix C. The left column
presents the RV and indicator time-series, while the middle column contains
the periodograms of these time-series. No drift nor white noise was included
prior to their computation. However concerning the activity indicators, we
included a Keplerian in the model so to absorb most of the long-period power,
which impacts the short-period signals. In those cases, we present the
periodograms of the residuals. The red bands depict the estimated range for
the stellar rotation period, obtained from both literature and a preliminary
analysis of our data. The right column illustrates the correlation between the
various indicators and the RV. Figure 16: HARPS-N YARARA-V1 RV and
spectroscopic activity indicators of HD 147379. Similar description to Fig.
15, except with the periodogram computation. The long-period trends observed
in the time-series of the spectroscopic indicators are better fitted by
quadratic drifts instead of Keplerians. The corresponding periodograms were
computed from the residuals of these fits. Figure 17: HARPS-N YARARA-V1, HIRES
and APF RV and spectroscopic activity indicators of HD 190007. Similar
description to Fig. 15. We did not include any Keplerian nor drift prior to
the computation of the periodograms. We note that only two and one
chromospheric activity indicators are publicly available for the APF and HIRES
data, respectively (namely the Hα and S-index indicators). Hα being absent
from the HIRES data (Butler et al. 2017), the correlation coefficient between
the RV and Hα only takes the HARPS-N and APF data into account. Furthermore,
this correlation is stronger in HARPS-N, for which R=0.47. Figure 18: HD99492:
Results from the TWEAKS pipeline. Left column: posterior distribution. Right
column: FIP periodogram. From top to bottom rows: Analyses on the entire RV
time-series, on the first half and on the second half of the time-series,
respectively. The vertical plain lines (light green) depict the two planet
detections, at 17.05 and 95.2 days, respectively. The red dashed lines help to
guide the eye on the 14d signal, which is inconsistently present in the data.
Figure 19: Entire RV time-series of HD 147374 folded on the best-fit Keplerian