JuanCastillo29/space-mission-intelligence-data huggingface dataset:
B., Donati, J.-F., H´ebrard, ´E.

M., et al. 2021, MNRAS, 500, 1844, doi: 10.1093/mnras/staa3396 Knapp, M., Paritsky, L., Kononov, E., & Kao, M.

M. 2024, arXiv e-prints, arXiv:2404.08432, doi: 10.48550/arXiv.2404.08432 Kreidberg, L., Koll, D.

D.

B., Morley, C., et al. 2019, Nature, 573, 87, doi: 10.1038/s41586-019-1497-4 Lam, K.

W.

F., Csizmadia, S., Astudillo-Defru, N., et al. 2021, Science, 374, 1271, doi: 10.1126/science.aay3253 Lang, P., Jardine, M., Morin, J., et al. 2014, MNRAS, 439, 2122, doi: 10.1093/mnras/stu091 Lehmann, L.

T., Donati, J.

F., Fouqu´e, P., et al. 2024, MNRAS, 527, 4330, doi: 10.1093/mnras/stad3472 Lyu, X., Koll, D.

D.

B., Cowan, N.

B., et al. 2024, ApJ, 964, 152, doi: 10.3847/1538-4357/ad2077 McMullin, J.

P., Waters, B., Schiebel, D., Young, W., & Golap, K. 2007, in Astronomical Society of the Pacific Conference Series, Vol. 376, Astronomical Data Analysis Software and Systems XVI, ed.

R.

A.

Shaw, F.

Hill, & D.

J.

Bell, 127 Medina, A.

A., Winters, J.

G., Irwin, J.

M., & Charbonneau, D. 2020, ApJ, 905, 107, doi: 10.3847/1538-4357/abc686 Meier, T.

G., Bower, D.

J., Lichtenberg, T., Tackley, P.

J., & Demory, B.-O. 2021, ApJL, 908, L48, doi: 10.3847/2041-8213/abe400 Narang, M., Puravankara, M., Vedantham, H.

K., et al. 2024, AJ, 168, 265, doi: 10.3847/1538-3881/ad84e4 Nowak, G., Luque, R., Parviainen, H., et al. 2020, A&A, 642, A173, doi: 10.1051/0004-6361/202037867 ´O Fionnag´ain, D., & Vidotto, A.

A. 2018, MNRAS, 476, 2465, doi: 10.1093/mnras/sty394 Ortiz Ceballos, K.

N., Cendes, Y., & Berger, E. 2025, arXiv e-prints, arXiv:2512.16852, doi: 10.48550/arXiv.2512.16852 Ortiz Ceballos, K.

N., Cendes, Y., Berger, E., & Williams, P.

K.

G. 2024, AJ, 168, 127, doi: 10.3847/1538-3881/ad58be Osten, R.

A., & Wolk, S.

J. 2025, ApJ, 993, 5, doi: 10.3847/1538-4357/ae03b7

SPI Radio Search 25 Vidotto, A.

A., Gregory, S.

G., Jardine, M., et al. 2014b, MNRAS, 441, 2361, doi: 10.1093/mnras/stu728 Virtanen, P., Gommers, R., Oliphant, T.
8-3881/ad58be Osten, R.

A., & Wolk, S.

J. 2025, ApJ, 993, 5, doi: 10.3847/1538-4357/ae03b7

SPI Radio Search 25 Vidotto, A.

A., Gregory, S.

G., Jardine, M., et al. 2014b, MNRAS, 441, 2361, doi: 10.1093/mnras/stu728 Virtanen, P., Gommers, R., Oliphant, T.

E., et al. 2020, Nature Medicine, 17, 261, doi: 10.1038/s41592-019-0686-2
See, V., Amard, L., Bellotti, S., et al. 2025, MNRAS, 542, 1318, doi: 10.1093/mnras/staf1197 Sheeley, N.

R., Wang, Y.

M., Hawley, S.

H., et al. 1997, ApJ, 484, 472, doi: 10.1086/304338 Shporer, A., Collins, K.

A., Astudillo-Defru, N., et al. 2020, ApJL, 890, L7, doi: 10.3847/2041-8213/ab7020 Silverstein, M.

L., Schlieder, J.

E., Barclay, T., et al. 2022, AJ, 163, 151, doi: 10.3847/1538-3881/ac32e3 Silverstein, M.

L., Barclay, T., Schlieder, J.

E., et al. 2024, AJ, 167, 255, doi: 10.3847/1538-3881/ad3040 Stelzer, B., Marino, A., Micela, G., L´opez-Santiago, J., & Liefke, C. 2013, MNRAS, 431, 2063, doi: 10.1093/mnras/stt225 Stock, S., Kemmer, J., Reffert, S., et al. 2020, A&A, 636, A119, doi: 10.1051/0004-6361/201936732 Tasse, C., Zarka, P., Hardcastle, M.

J., et al. 2026, Nature Astronomy, doi: 10.1038/s41550-025-02757-7 Trigilio, C., Biswas, A., Leto, P., et al. 2023, arXiv e-prints, arXiv:2305.00809, doi: 10.48550/arXiv.2305.00809 Turner, J.

D., Grießmeier, J.-M., Zarka, P., Zhang, X., & Mauduit, E. 2024, A&A, 688, A66, doi: 10.1051/0004-6361/202450095 Turnpenney, S., Nichols, J.

D., Wynn, G.

A., & Burleigh, M.

R. 2018, ApJ, 854, 72, doi: 10.3847/1538-4357/aaa59c Vanderspek, R., Huang, C.

X., Vanderburg, A., et al. 2019, The Astrophysical Journal, 871, L24, doi: 10.3847/2041-8213/aafb7a Vedantham, H.

K., Callingham, J.

R., Shimwell, T.

W., et al. 2020, Nature Astronomy, 4, 577, doi: 10.1038/s41550-020-1011-9 Vidotto, A.

A. 2016, MNRAS, 459, 1533, doi: 10.1093/mnras/stw758 Vidotto, A.

A., Jardine, M., Morin, J., et al. 2014a, MNRAS, 438, 1162, doi: 10.1093/mnras/stt2265
Wandia, K., Tremblay, C., Garrett, M.

A., et al. 2026, MNRAS, 546, staf1998, doi: 10.1093/mnras/staf1998 Weber, E.
, 459, 1533, doi: 10.1093/mnras/stw758 Vidotto, A.

A., Jardine, M., Morin, J., et al. 2014a, MNRAS, 438, 1162, doi: 10.1093/mnras/stt2265
Wandia, K., Tremblay, C., Garrett, M.

A., et al. 2026, MNRAS, 546, staf1998, doi: 10.1093/mnras/staf1998 Weber, E.

J., & Davis, Leverett, J. 1967, ApJ, 148, 217, doi: 10.1086/149138 Whittaker, E.

A., Malik, M., Ih, J., et al. 2022, AJ, 164, 258, doi: 10.3847/1538-3881/ac9ab3 Wood, B.

E., M¨uller, H.-R., Redfield, S., et al. 2021, ApJ, 915, 37, doi: 10.3847/1538-4357/abfda5 Wright, N.

J., Drake, J.

J., Mamajek, E.

E., & Henry, G.

W. 2011, ApJ, 743, 48, doi: 10.1088/0004-637X/743/1/48 Wright, N.

J., Newton, E.

R., Williams, P.

K.

G., Drake, J.

J., & Yadav, R.

K. 2018, MNRAS, 479, 2351, doi: 10.1093/mnras/sty1670 Wulff, P.

N., Cao, H., & Aurnou, J.

M. 2026, arXiv e-prints, arXiv:2606.07484, doi: 10.48550/arXiv.2606.07484 Yu, S., Chen, B., Sharma, R., et al. 2024, Nature Astronomy, 8, 50, doi: 10.1038/s41550-023-02122-6 Zarka, P. 2007, Planet.

Space Sci., 55, 598, doi: 10.1016/j.pss.2006.05.045 Zarka, P., Louis, C.

K., Zhang, J., et al. 2025, A&A, 695, A95, doi: 10.1051/0004-6361/202450950 Zarka, P., Marques, M.

S., Louis, C., et al. 2018, A&A, 618, A84, doi: 10.1051/0004-6361/201833586 Zhang, M., Hu, R., Inglis, J., et al. 2024, The Astrophysical Journal Letters, 961, L44 Zhang, X., Zarka, P., Girard, J.

N., et al. 2025, arXiv e-prints, arXiv:2506.07912, doi: 10.48550/arXiv.2506.07912
S., Louis, C., et al. 2018, A&A, 618, A84, doi: 10.1051/0004-6361/201833586 Zhang, M., Hu, R., Inglis, J., et al. 2024, The Astrophysical Journal Letters, 961, L44 Zhang, X., Zarka, P., Girard, J.

N., et al. 2025, arXiv e-prints, arXiv:2506.07912, doi: 10.48550/arXiv.2506.07912

26 Villadsen et al.
APPENDIX
A. IMAGES Figure 4 shows Stokes I clean images of the field of view around each star, zoomed in to the area near the star. We cleaned a larger area of 1.5◦to 3◦(not shown). The purpose of imaging was to create a model for the visibilities of background sources, subtracted in order to create the time series. For most stars, we made a single image combining all epochs, since the epochs were separated by a few days, during which GHz-frequency background source variability is expected to be low. The exceptions are GJ 367, for which we created separate images for January and September 2022, and LHS 3844, for which we imaged June 21 and 26 separately.
B. TIME SERIES Figures 5-9 show the time series for the location of each star during the observing epochs, binned to 5-minute integrations. The 3σ thresholds were determined using the standard deviation σ of each time series. This works because the data reveal no clear stellar signal; the imaginary component of the visibilities (not shown), which should have no stellar signal, had comparable standard deviations. Some individual points exceed a 3σ threshold, which can occur randomly due to the large number of data points plus non-Gaussian noise such as RFI, but no events meet the requirement of two or more adjacent points exceeding 3σ.
C. SIMPLIFYING V sin θ FOR A WEBER-DAVIS WIND For a Weber-Davis wind model with an axisymmetric radial-azimuthal field, and a prograde circular orbit, then v sin θ = vorb(Br/B)(1−Porb/Prot) ≈vorb(1−Porb/Prot) for sub-Alfv´enic systems, especially slow rotators. We demonstrate this approximation as follows. The Weber-Davis wind model (Weber & Davis 1967) solves the combined flow problem for a magnetized equatorial wind around a rotating star. For star-planet interactions in this environment we needed to determine the Poynting flux in the exoplanet frame (see Saur et al. 2013). When assuming circular orbits of angular momentum aligned with the stellar rotational axis, we can make some useful approximations in this calculation. The key term is
|⃗v × ⃗B| = urBϕ −(uϕ −vorb)Br , (C1) vB sin θ = urBϕ −uϕBr + Brvorb , (C2) where v is the wind’s relative velocity in the planet frame, B is the wind magnetic field, θ is the angle between the two vectors in the planet frame, we use u for the velocities of the wind, and vorb is the planet Keplerian orbital velocity. For the perfectly conducting wind, in the stellar rotating frame the plasma outflow is parallel to the magnetic field direction which further imposes the condition r(urBϕ −uϕBr) = const. = −Ωr2Br , (C3) where Ωis the angular rotation rate of the surface. The value of the constant is defined at the surface boundary at the roots of the wind, where the magnetic field is modeled as radial and the 11.55
69.14
11.60
11.65
69.16
J2000 Declination
J2000 Declination
Jy / Beam
Jy / Beam
11.70
69.18
11.75
11.80
69.20
11.85
11.90
69.22
154.45 154.50 154.55 154.60 154.65 154.70 154.75 154.80
340.46 340.48 340.50 340.52 340.54
J2000 Right Ascension
J2000 Right Ascension
45.700
45.700
45.725
45.725
45.750
45.750
J2000 Declination
J2000 Declination
Jy / Beam
Jy / Beam
45.775
45.775
45.800
45.800
45.825
45.825
45.850
45.850
45.875
45.875
146.025 146.050 146.075 146.100 146.125 146.150 146.175 146.200
146.025 146.050 146.075 146.100 146.125 146.150 146.175 146.200
J2000 Right Ascension
J2000 Right Ascension
39.700
56.625
39.725
56.650
39.750
56.675
J2000 Declination
J2000 Declination
39.775
Jy / Beam
Jy / Beam
56.700
39.800
56.725
39.825
56.750
39.850
56.775
39.875
56.800
68.100 68.125 68.150 68.175 68.200 68.225 68.250 68.275
306.450 306.475 306.500 306.525 306.550 306.575 306.600 306.625
J2000 Right Ascension
J2000 Right Ascension

[Figure: Figure 4. Stokes I image cutouts from the field of view near each star. The red cross-hairs highlight the star’s location at the observing epoch (not detected). The synthesized beam shape is shown in red in the bottom left. The color scale is linear, with a low maximum set to highlight faint sources near the detection threshold. LTT 3780 (top left) is a VLA 2-4 GHz image, whereas the remaining 5 are ATCA 1.1-3.1 GHz images. GJ 367 has two separate images (center row) for the epochs in January and September. The only Stokes I source is LHS 3844 (top right), at 56 ± 17 µJyin its second epoch (first epoch in main text). LHS 1678 (bottom left), detected in Stokes V (image in main text), has possible Stokes I emission near the star’s location, but it is offset from the star and not point-like, likely due to a background source or sidelobe.]

28 Villadsen et al.

|  |  |  |
| --- | --- | --- |
|  |  |  |
|  |  |  |
| =27 Jy | =27 Jy | =24 Jy |
|  |  |  |
|  |  |  |
|  |  |  |
| =26 Jy | =24 Jy | =25 Jy |

Flux Density (mJy)
0.05
Stokes I
0.00 0.05
Flux Density (mJy)
0.05
Stokes V
0.00 0.05
Time (hr) Figure 5. VLA 2-4 GHz time series of LTT 3780. The black points show the flux density time series at the star’s location, binned to 5-minute integrations, obtained by averaging the visibilities across all baselines. Red lines mark 3 times the standard deviation σ of the time series. No data exceeded the detection requirement of two or more adjacent points above 3σ. Left to right: the epochs are the different observing dates in Table 2. Top row: Stokes I flux density, where the detection threshold is positive only. Bottom: Stokes V, where the detection threshold can be positive (right-hand polarized emission) or negative (left-hand).
wind velocity as radial in the rotating frame. The constancy of the expression is a requirement of having a divergence less magnetic field (⃗∇· ⃗B = 0). This last expression lets us rewrite Equation C2 as
vB sin θ = −ΩrBr + Brvorb . (C4)
Rearranging, we can express
� 1 −Porb
� , (C5)
v sin θ = vorb Br B
Prot
which is an exact expression within the Weber-Davis model when applied to planets in circular orbits. For a Weber-Davis wind, only the equatorial properties are included so the ratio of the radial field to the total field strength is
�−1/2
B2
Br
≈1 −1
ϕ
ϕ
. (C6)
B = � 1 + B2
B2
B2
r
r
In slowly rotating stars at close-in orbits Bϕ << Br, so Br/B ≈1 to first order. In the Weber-Davis model the azimuthal wind follows |  |  |
| --- | --- |
|  |  |
|  |  |
| =104 Jy | =177 Jy |
|  |  |
|  |  |
|  |  |
|  |  |
| =92 Jy |  |
|  | =136 Jy |

Flux Density (mJy)
0.50 0.25
Stokes I
0.00 0.25 0.50
Flux Density (mJy)
0.50 0.25
Stokes V
0.00 0.25 0.50
Time (hr) Figure 6. ATCA 1.1-3.1 GHz time series of LHS 3844, in the style of Figure 5.
Epoch 1
Flux Density (mJy)
Stokes I
0 1
=445 Jy
=250 Jy
Flux Density (mJy)
Stokes V
0 1
=113 Jy
=109 Jy
=135 Jy
=183 Jy
=122 Jy
0 5
0 5
0 5
0 5
0 5
Time (hr) Figure 7. ATCA 1.1-3.1 GHz time series of GJ 367, in the style of Figure 5.
1 −r2
Bϕ Br
Villadsen et al.

|  |  |  |
| --- | --- | --- |
|  |  |  |
|  |  |  |
| =404 Jy | =349 Jy | =393 Jy |
|  |  |  |
|  |  |  |
|  |  |  |
| =166 Jy | =223 Jy | =193 Jy |

Flux Density (mJy)
Stokes I
0 1
Flux Density (mJy)
Stokes V
0 1
Time (hr) Figure 8. ATCA 1.1-3.1 GHz time series of LHS 1678, in the style of Figure 5.

|  |  |
| --- | --- |
|  |  |
| =382 Jy | =393 Jy |
|  |  |
|  |  |
|  |  |
| =163 Jy | =145 Jy |

Flux Density (mJy)
Stokes I
Flux Density (mJy)
Stokes V
Time (hr) Figure 9. ATCA 1.1-3.1 GHz time series of GJ 1252, in the style of Figure 5.
SPI Radio Search 31 of kilometers per second. For the wind solution to exist, the fraction on the right is real and of order unity. Therefore, Bϕ/Br is small for the systems studied in this paper, and only becomes appreciable farther out when the stellar rotation period goes below 1 d: Ωr ∼15 km s−1 (10 d/Prot) (r/ 10R∗) for R∗= 0.3R⊙.
and characterized with TESS and MaHPS

Luis Thomas⋆ 1, 2, Louise D. Nielsen 1, Hanna Kellermann 1, 2, Bibiana Prinoth 3, 4 ⋆⋆, Yutong Liu1, Elif Zeynep Özden1, Arno Riffeser1, Claus Gössl 1, Frank Grupp1, 2, Jerome de Leon 5, Karen A. Collins 6, Allyson Bieryla 6, Lorena Acuña-Aguirre 7, Keith Baka 1, Malte Busmann 1, 8, David R. Ciardi 9, Catherine A. Clark 9,
1, 2, Mark E. Everett 10, Akihiko Fukui 5, Jan-Vincent Harre 1, Keisuke Isogai 11, 12, Felipe
13, 14, Norio Narita 5, 15, 13, Enric Palle 13, 14, Hannu Parviainen 13, 14, Jan-Niklas Pippert 1, 2, Christoph Ries1, Boris S. Safonov 16, Thomas Schäfer17, Michael Schmidt1, Richard P. Schwarz 6, Laura Schöller 2, Gregorg Srdoc18, Ivan A. Strakhov 16, Suzanne Taylor 19, and Raphael Zöller
The population of Jupiter-sized exoplanets with orbital periods between 10 and 200 days (WJs) exhibits a broad range of orbital eccentricities and system architectures, suggesting a diversity of formation and migration pathways. In this work, we report the detection and characterization of two new eccentric WJs, TOI-2147 b and TOI-6019 b, initially identified as planet candidates by the Transiting Exoplanet Survey Satellite (TESS). We combined TESS photometry with ground-based follow-up observations, including multiband photometry from LCOGT and MuSCAT2, highangular-resolution speckle imaging, and high-precision radial velocity measurements from the high-resolution Manfred Hirt Planet Finder Spectrograph (MaHPS). Using these data, we were able to confirm the planetary nature of both candidates. TOI-2147 b has a radius of 10.5±0.3 R⊕and a mass of 116 ± 22 M⊕. It orbits its slightly metal-poor ([Fe/H] = −0.29+0.07 −0.08) G-type host star on an eccentric orbit (e = 0.29 ± 0.07) with a period of 26.2 days. TOI-6019 b has a radius of 12.3 ± 0.3 R⊕and a mass of 149 ± 15 M⊕. It orbits a slightly evolved, solar-metallicity G-type sub-giant with a period of 14.5 days on a significantly eccentric orbit (e = 0.48+0.05
−0.04). Both planets have bulk densities below that of Jupiter, indicating mildly
inflated radii, with interior structure modeling using GASTLI. This suggests that tidal heating from the nonzero eccentricities likely contributes to this inflation and disfavors large atmospheric metal enrichment. No significant signals from additional companions were detected in the radial velocity time series or transit timing variations. Together with the elevated eccentricities, this is consistent with a high-eccentricity migration origin for both systems.
Key words. planets and satellites: detection – techniques: photometric – techniques: radial velocities – planets and satellites: gaseous planets –
stars: planetary systems
For high-eccentricity migration, the giant planets are placed on eccentric orbits through dynamical interactions such as planetplanet scattering (Rasio & Ford 1996; Chatterjee et al. 2008), Lidov–Kozai cycling (Wu & Murray 2003; Fabrycky & Tremaine 2007; Naoz 2016; Petrovich & Tremaine 2016; Vick et al. 2019), and secular chaos (Wu & Lithwick 2011; Petrovich 2015; Teyssandier et al. 2019). The orbit then circularizes and shrinks through tidal interaction with the star at periastron passage, delivering the planet to its present-day orbit.
The discovery of giant exoplanets orbiting close to their host stars has revolutionized our understanding of the formation and evolution of planetary systems. Hot Jupiters (HJs), with orbital periods of fewer than 10 days, and warm Jupiters (WJs), with periods between 10 and 200 days, challenge classical planet formation theories, which predict that gas giants should form beyond the ice line at orbital distances of several astronomical units (Pollack et al. 1996; Lecar et al. 2006; Kennedy & Kenyon 2008). The mechanisms responsible for their observed location remain a subject of debate, with leading hypotheses including high-eccentricity tidal migration, disk-driven migration, and in situ formation (a summary is provided in Dawson & Johnson 2018). While in situ formation might be feasible under special conditions (Batygin et al. 2016; Boley et al. 2016), the prevalent explanation is that giant planets form beyond the ice line and migrate inward through high-eccentricity or disk-driven migration. Disk-driven migration posits that giant planets migrate inward through interactions with the protoplanetary disk (Lin & Papaloizou 1986; Goldreich & Tremaine 1980; Lin et al. 1996).
The system architecture and properties of warm and HJs can give information on their dynamical history and possible migration mechanisms. Most HJs have no close-companion planets that would plausibly be destroyed during high-eccentricity migration (Mustill et al. 2015; Sha et al. 2026), but show signs of massive long-period companions, which could instigate the migration (Knutson et al. 2014; Zink & Howard 2023). Furthermore, HJs might be more abundant in dense stellar environments where increased dynamical interaction might lead to a higher migration rate (Brucalassi et al. 2017; Thomas et al. 2024). These results point toward high-eccentricity migration as the dominant formation mechanism for HJs. However, some HJs have been found to possess smaller close-in companions (e.g., Becker et al. 2015; Korth et al. 2023, 2024; Grieves et al. 2025). Additionally, analysis of transit timing variations found that 12 ± 6%
⋆Email:lthomas@mpe.mpg.de ⋆⋆ESO Fellow
Article number, page 1 of 14 of HJs might host nearby companions (Wu et al.
Mtra Mrot
Normalized Flux
0.995
0.990
0.985
Mtra residuals [ppm]
−200
−400 400
Mrot residuals [ppm]
−200
−400
377.95 378.00 378.05 Time [BJDT DB - 2459867]
0.60 0.65 0.70 Time [BJDT DB - 2459867]
0.60 0.65 0.70 Time [BJDT DB - 2459867]

[Figure: Fig. 1 WASP-121 b’s white transit light curves observed with JWST/NIRISS SOSS and JWST/NIRSpec G395H. Both observations have been reduced with Firefly. The first row shows the raw light curves integrated over NIRISS’s first grating order and NIRSpec’s NRS1 and NRS2 detectors together with the maximum-likelihood translational (Mtra) and rotational (Mrot) models inferred from a Markov-Chain Monte Carlo (MCMC) sampling of the posterior probability. Circles depict the fluxes per integration normalized by the median fluxes measured during the secondary eclipse observed before the transit and error bars depict the 1σ intervals measured from 150,000 posteriors samples of the light curve (see Methods). Transparent cyan and yellow lines depict models calculated from 100 samples randomly drawn from the MCMC chains of Mtra and Mrot, respectively. The second and third rows show the residuals between the maximum-likelihood models and the data. Vertical gray lines mark contact points 1, 2, 3, and 4 calculated from the planet’s orbital parameters and radius [27] with gray shaded regions indicating the times of ingress and egress.]
13, 2022, in the Exo filter using the remote 0.43 m iTelescope located during the time of observation at New Mexico Skies2.

Imaging was done with an SBIG STX-16803 CCD camera, which has an array of 4096 × 4096 pixels with a pixel size of 9 µm x 9 µm.

Weather conditions were good with clear skies.

During the imaging session, the wind speed reached peaks up to 16.1 km/h, and the seeing was measured between 1.3 and 2.5 FWHM arcseconds.

For the images, an exposure time of 60 s was used.

After visual inspection and blinking of all images, 23 images have been rejected due to poor guiding and defocus.

For the analysis of the observable transit egress, a collection of 118 images has been finally selected for light curve analysis and transit model calculation.
1 https://tess.mit.edu/followup 2 https://support.itelescope.net/support/solutions/articles/251589

[Figure: Fig. 1. PDCSAP from the TESS light curves for TOI-2147 (upper plot) and TOI-6019 (lower plot). The increased scatter for the TOI-2147 in later sectors is due to the shorter exposure times.]
2147 was observed between the 26th of January, 2023, and the 14th of December 2025, collecting a total of 136 spectra on 57 nights.

For TOI-6019, we collected 93 spectra (38 nights) between the 14th of July 2024 and the 18th of November 2025.

With V-band magnitudes of 11.1 and 10.8, both stars are close Article number, page 4 of 14
to the limit for precise RV work with MaHPS (Ehrhardt et al. 2024).

Therefore, we planned to collect three 1800 s exposures per night to reach the required RV precision, which was not always possible due to worsening weather conditions or observations with a higher priority.

The data were reduced and the RVs were extracted using our two in-house pipelines GAMSE (Wang et al. 2016) and MARMOT (Kellermann et al. 2020), following the procedure outlined in Thomas et al. (2025a).

We used all available observations to create the templates that were then used to calculate the RV shift using the template matching algorithm implemented in MARMOT.

The MaHPS RVs used in the following analysis are available in Tables 5 and 6 at the CDS.