The TESS Grand Unified Hot Jupiter Survey. I. Ten TESS Planets

We report the discovery of ten short-period giant planets (TOI-2193A b, TOI-2207 b, TOI-2236 b, TOI-2421 b, TOI-2567 b, TOI-2570 b, TOI-3331 b, TOI-3540A b, TOI-3693 b, TOI-4137 b). All of the planets were identified as planet candidates based on periodic flux dips observed by NASA's Transiting Exoplanet Survey Satellite (TESS). The signals were confirmed to be from transiting planets using ground-based time-series photometry, high angular resolution imaging, and high-resolution spectroscopy coordinated with the TESS Follow-up Observing Program. The ten newly discovered planets orbit relatively bright F and G stars ($G<12.5$,~$T_\mathrm{eff}$ between 4800 and 6200 K). The planets' orbital periods range from 2 to 10~days, and their masses range from 0.2 to 2.2 Jupiter masses. TOI-2421 b is notable for being a Saturn-mass planet and TOI-2567 b for being a ``sub-Saturn'', with masses of $0.322\pm 0.073$ and $0.195\pm 0.030$ Jupiter masses, respectively. In most cases, we have little information about the orbital eccentricities. Two exceptions are TOI-2207 b, which has an 8-day period and a detectably eccentric orbit ($e = 0.17\pm0.05$), and TOI-3693 b, a 9-day planet for which we can set an upper limit of $e<0.052$. The ten planets described here are the first new planets resulting from an effort to use TESS data to unify and expand on the work of previous ground-based transit surveys in order to create a large and statistically useful sample of hot Jupiters.


INTRODUCTION
The origin of hot Jupiters is one of the longeststanding unresolved problems in exoplanet science. Prior to the discovery of the first hot Jupiter 51 Pegasi b (Mayor & Queloz 1995), our understanding of planet formation was entirely based on our knowledge of our solar system. It was thought that giant planets could only form beyond a few astronomical units from their host stars, where the surface density of solids within the protoplanetary disk would be high enough to allow for the formation of a solid body massive enough to undergo runaway gas accretion. The existence of hot Jupiters implies that either this expectation was incorrect and giant planets can form close in to their host stars, or that the initially wide orbits of giant planets can sometimes shrink by a factor of 100 (see the reviews by Dawson & Johnson 2018;Fortney et al. 2021, and references therein). In the latter scenario, the orbital shrinkage might be due to gravitational interactions with the gaseous protoplanetary disk, and would therefore need to occur within the first few million years after the formation of the star (Lin & Papaloizou 1986), or the orbital alterations might be caused by eccentricity excitation followed by tidal orbital circularization, which need not occur early in the system's history (Rasio & Ford 1996;Fabrycky & Tremaine 2007). Each of these possible formation pathways would shape the population of hot Jupiters in different ways, and hence studying the demographics of hot Jupiters and the distributions of their orbital properties may help us understand their relative importance.
NASA's ongoing TESS mission (Ricker et al. 2015) was designed to detect smaller planets -super-Earths and sub-Neptunes -but TESS is also capable of revolutionizing our knowledge of hot Jupiter demographics. As a nearly all-sky space-based photometric survey that dwells on a given star field for 27 days at a time, the TESS survey should be able to identify nearly all of the hot Jupiters that transit stars which are bright and nearby enough for detailed follow-up observations and characterization (Zhou et al. 2019). Simulations have predicted that the TESS planet catalog will eventually contain ≈400 hot Jupiters around FGK stars brighter than G = 12.5 (Yee et al. 2021). Such a sample would be an order of magnitude larger than the sample of 40 hot Jupiters found during the original Kepler mission, which is the largest statistically useful sample of such planets currently available. The process of constructing a very large sample of hot Jupiters around bright stars is greatly facilitated and accelerated by the fact that hundreds of these planets have already been discovered by the ground-based transit surveys such as TrES (Alonso et al. 2004), XO (McCullough et al. 2005), WASP (Pollacco et al. 2006), HATNet and HATSouth (Bakos et al. 2004(Bakos et al. , 2013, KELT (Pepper et al. 2007(Pepper et al. , 2012, and NGTS (Wheatley et al. 2018), accounting for roughly 40% of the expected 400 planets in a G < 12.5 magnitude-limited sample. The hard work of these previous surveyors over many years led to the discovery of many important and well-studied systems, but the selection functions of these surveys are complex, different from each other, and not well documented. TESS will provide a homogeneous dataset that encompasses essentially all of the previously known planets and has a selection function that should be easier to model. Hence, TESS offers the possibility of unifying all of the previous surveys and leveraging over two decades of observational effort.
Still, even with TESS , expanding and completing a statistical sample suitable for demographic study will require a significant follow-up effort to rule out astrophysical false positives (generally eclipsing binaries that masquerade as transiting planets), measure planet masses, and model the selection function. Ground-based imaging and time-series photometric follow-up with higher angular resolution than TESS can be used to check for nearby eclipsing binaries and confirm that the transit signal belongs to the identified star and not a foreground or background star. Additional transit observations help to improve our knowledge of the planet parameters and transit ephemerides, while observations in multiple bandpasses can also be used to check for chromatic effects that are indicative of eclipsing binaries. High-resolution Doppler spectroscopy provides final confirmation of the planet's existence and measures its mass, as well as providing a high signal-to-noise spectrum that is useful for characterizing the host star.
Given all the different types of observations and resources that are needed, confirming hundreds of new hot Jupiters from TESS within a reasonable amount of time is only feasible with a large community effort.
The lead authors of this paper have begun to organize such an effort, the Grand Unified Hot Jupiter Survey, by playing a linking role between the new planet discoveries from various TESS follow-up groups, and the planets (and false positives) that have already been investigated in previous planet searches. This work is being conducted as part of the TESS Follow-Up Observing Program (TFOP; ; ExoFOP 2019) 1,2 , which provides a platform for coordinating observations and sharing data, and is open to any interested astronomer.
The 10 planets described in this paper are the first newly discovered planets from this survey, and are based on data contributed by many TFOP members. The planets are known by their TESS Object of Interest (TOI) numbers: TOI-2193A b, TOI-2207 b, TOI-2236 b, TOI-2421 b, TOI-2567 b, TOI-2570 b, TOI-3331 b, TOI-3540A b, TOI-3693 b, and TOI-4137 b. Section 2.1 presents time-series photometry from TESS , and Sections 2.2 through 2.4 describe ground-based follow-up photometry, imaging, and spectroscopic follow-up observations. Section 3 presents a characterization of each host star, and Section 4 describes the application of EXOFASTv2  to jointly model all of the data and determine the parameters of each system. Section 5 examines the properties of the new planets within the context of the entire known sample of hot Jupiters, and Section 6 draws some conclusions.

TESS Photometry
All of the new planets described here were first detected in TESS photometry. TESS observes a 24 • × 96 • region of the sky for 27 days at a time, before rotating its field of view to a new sector. During its initial two-year Prime Mission (Sectors 1 -26, running from July 2018 to July 2020), TESS obtained high-precision photometry of 200,000 preselected stars with a twominute cadence, with the remainder of the field-of-view being observed in the full-frame images (FFIs) at 30minute cadence. With the Extended Mission beginning in 2020 (Sectors 27 onward), two-minute cadence data continues to be obtained for ≈ 20,000 targets per sector, while the FFI cadence has been reduced to 10 minutes.
The 2-minute TESS photometry was extracted and reduced by the TESS Science Processing Operations Center (SPOC) pipeline, as described by Jenkins et al. (2016). Only one of the 10 planet-hosting stars presented in this paper had been preselected for 2-minute cadence observations (TOI-2207, Sector 27). However, several others were added to the short-cadence target list in the Extended Mission following their identification as planet candidates in the FFIs from the Prime Mission. The longer-cadence FFI data were calibrated with the tica software (Fausnaugh et al. 2020), and the light-curves were extracted with the MIT Quick-Look Pipeline (QLP; Huang et al. 2020a,b;Kunimoto et al. 2021).
Both the SPOC pipeline and QLP search the extracted light-curves for transit-like signals ("Threshold Crossing Events" or TCEs) which are then vetted by the TESS Science Office (TSO). Objects with signals surviving the vetting process are designated TESS Objects of Interest (TOIs; Guerrero et al. 2021) and public notifications are distributed. All of the planets in this paper were alerted as TOIs, including some from the recent search of QLP light-curves for stars fainter than T > 10.5 by Kunimoto et al. (2022). Table 1 summarizes the ten targets and the TESS sectors they were observed in.
In addition, four of the targets had previously been identified as "community TOIs" (cTOIs) by separate investigators. TOI-2421 b was first flagged as a planet candidate by Montalto et al. (2020), who used the DIAmante pipeline to extract difference imaging light-curves from the first year of TESS FFIs. They then identified transit events in the light-curves with the Box-Least Squares algorithm (Kovács et al. 2002), and vetted the candidate events with a Random Forest classifier. TOI-2567 b, TOI-2570 b, and TOI-4137 b were identified as planet candidates by Olmschenk et al. (2021), who classified light-curves from the SPOC-calibrated FFIs extracted by the eleanor pipeline (Feinstein et al. 2019) with a convolutional neural network. These light-curves were then subjected to the Quasi-Automated Transit Search (QATS; Kruse et al. 2019) pipeline and vetted with the Discovery and Vetting of Exoplanets pipeline (DAVE; Kostov et al. 2019). All four cTOIs were later promoted to TOIs following vetting by the TESS Science Office (Mireles et al. 2021).
We identified these targets as candidate hot Jupiters (R p > 8 R ⊕ , P < 10 days) from the TOI catalog, with selection based on catalog photometry and astrometry indicating that they orbit FGK stars. We then began performing follow-up observations to determine whether the transit-like signals are truly from transiting planets or are instead from eclipsing binaries or other "false positives." When analyzing each planetary system (Section 4), we used all of the available photometry from TESS. We used the lightkurve package (Lightkurve Collaboration et al. 2018) to download the TESS lightcurves from the Mikulski Archive for Space Telescopes (MAST). When available, we used light-curves produced from the SPOC pipeline -this applies to all the shortcadence data, as well as some of the long-cadence FFI data, for which the SPOC pipeline has recently begun processing 160,000 targets per sector (Caldwell et al. 2020). We used the Presearch Data Conditioning (PDC; Stumpe et al. 2012;Smith et al. 2012;Stumpe et al. 2014) light-curves, which have been corrected for instrumental effects. We additionally "flattened" the SPOC PDC light-curves with the Keplerspline 3 routine ( Vanderburg & Johnson 2014;Shallue & Vanderburg 2018), which fits a spline to the light-curve (with transit events masked) to correct for stellar or instrumentally induced variability ( Figure 1). When SPOC light-curves were unavailable for the long-cadence data, we used the lightcurves extracted by the QLP, which were also flattened with Keplerspline. We provide the flattened and normalized TESS photometry in Table 2.

Ground-Based Photometry
Additional ground-based photometry of each of our targets was obtained as part of TFOP's Seeing-limited Photometry Sub-Group 1 (SG1). These multi-band photometric observations of individual transits helped to rule out false-positive scenarios such as nearby eclipsing binaries. We also used the ground-based light-curves to refine the transit parameters and ephemerides. Observations were obtained from the Brierfield Observatory; KeplerCam on the Fred Lawrence Whipple Observatory (FLWO) 1.2m telescope; the Hazelwood Observatory; the Acton Sky Portal; the Villa '39 observatory; the Observatori Astronòmic de la Universitat de València (OAUV) TURIA2 0.3m telescope; the Grand-Pra Ob- MEarth-South data were reduced according to the procedures described in Berta et al. (2012) and Irwin et al. (2007). We summarize the observations and facilities used for each target in Table 3, and present the complete set of photometric observations in Table 4.

High-Resolution Imaging
We also obtained high angular-resolution imaging of all of our target systems, in order to detect and characterize stellar companions that might have been blended with the primary target in the TESS images. This allows us to assess the spectroscopic follow-up potential of a target star, eliminate false-positive scenarios, and evaluate the impact of any contamination on the fitted planetary properties. Table 5 summarizes the observations made for each system, which were coordinated by the TFOP High-Resolution Imaging Sub-Group 3 (SG3). Nearby companions were detected in three cases: TOI-2193, TOI-3331, and TOI-3540, with imaging shown in Figures 2, 3 and 4 respectively. No companions were found for the other targets down to detection limits, and plots illustrating these observations can be found at the end of this paper, in Figure 21. TOI-2193, TOI-2207, TOI-2421, TOI-3331, and TOI-3540 were observed in the I band with the High-Resolution Camera (HRCam; Tokovinin & Cantarutti 2008), a speckle imaging instrument on the Southern Astrophysical Research (SOAR) 4.1m telescope. The general observing strategy for TESS targets and data reduction procedure are described in Ziegler et al. (2019Ziegler et al. ( , 2021 and Tokovinin (2018) respectively, while an example SOAR observation for TOI-2193 is shown in Figure 2. Nearby stellar companions were detected in the SOAR a Flux has been normalized such that the mean out-of-transit flux has a baseline of 1.0, but is not yet detrended.
b The detrend variables are as listed in Table 3.
Note-This table is available in its entirety in machine-readable form.  (Kupke et al. 2012;Gavel et al. 2014;McGurk et al. 2014). Two sequences of observations were taken with the Shane adaptive optics system in natural guide star mode, one with a Ks filter (λ 0 = 2.150 µm, ∆λ = 0.320 µm) and one with a J filter (λ 0 = 1.238 µm, ∆λ = 0.271 µm). The data were reduced using the publicly available SImMER pipeline (Savel et al. 2020). 4 We found no evidence for stellar companions within our detection limits.
TOI-2570 and TOI-3540 were also observed in the near-infrared with the Palomar High Angular Resolution Observer (PHARO; Hayward et al. 2001) on the 200-in Hale telescope at Palomar Observatory. Both targets were observed in the Brγ filters, while TOI-3540 was also observed in the H-cont filter. These observations improved the bound for the lack of stellar companions to TOI-2570, while also identifying the 0. companion to TOI-3540, as seen in the SOAR speckle images. We observed TOI-2236 and TOI-2567 with the Zorro and 'Alopeke imaging instruments on the Gemini-South and Gemini-North telescopes respectively (Scott & Howell 2018;Scott et al. 2021). No companions were detected in either set of observations, down to the instrumental detection limits.
Finally, the targets TOI-3693 and TOI-4137 were observed with the speckle polarimeter on the 2.5m tele- scope at the Caucasian Observatory of Sternberg Astronomical Institute (SAI) of Lomonosov Moscow State University (Safonov et al. 2017). The observations were made in the I-band, and no stellar companions were detected for either target.

High-Resolution Spectroscopy
We obtained high-resolution spectroscopy for each of the ten target systems to measure precise relative radialvelocities (RVs) for each system, allowing us to confirm the planetary nature of the transiting companion and measure its mass. We sought to obtain 6-8 observation epochs per target, primarily at orbital quadratures. We describe the instruments used and data analysis procedures in the rest of this section, and summarize the observations for each target in Table 6.
In addition to extracting RV measurements from each spectroscopic observation, we measured the bisector inverse slope (BIS) of the spectral line profiles, using the procedures described by Hartman et al. (2019), for the observations from PFS, CHIRON, FEROS, HIRES and NEID. For spectra that were observed through an iodine cell, we only used the iodine-free orders to perform this measurement. The complete RV and BIS data for each target are presented in Table 7, and plotted in Figures  6 and 12-20.

PFS Spectroscopy
We observed TOI-2193, TOI-2207 and TOI-3331 with the Planet Finder Spectrograph (PFS) on the 6.5-meter Magellan II Clay Telescope at the Las Campanas Observatory in Chile (Crane et al. 2006(Crane et al. , 2008(Crane et al. , 2010. PFS is a high-resolution echelle spectrograph that uses an iodine absorption cell to produce precise radial-velocities. We observed each target in the 3x3 binning mode with the iodine cell in the optical path, choosing short exposure times of ten minutes or less, which allowed us to attain a typical RV precision of about 5 m s −1 , well above the instrument's demonstrated long-term precision of 1 m s −1 . The spectra were reduced and velocities extracted with the custom pipeline described by Butler et al. (1996). A high S/N, iodine-free, template spectrum was also obtained for each target, as required for the RV extraction procedure.

CHIRON Spectroscopy
TOI-2207, TOI-2236, and TOI-2421 were observed with the CTIO High Resolution Spectrometer (CHI-RON; Tokovinin et al. 2013;Paredes et al. 2021) on the CTIO 1.5m telescope on Cerro Tololo in Chile. CHI-RON is an optical, fiber-fed echelle spectrometer with a spectral resolution of R ≈80,000 when used with an image slicer. We observed with typical exposure times of 1200 to 1800s, bracketed by calibration observations of a ThAr lamp. The spectra were flat-fielded, bias subtracted, and wavelength calibrated using the standard CHIRON pipeline. Radial-velocities were extracted via least-squares deconvolution of the spectra against synthetic templates (Donati et al. 1997;Zhou et al. 2020), achieving a typical RV precision of 30-70 m s −1 . We also used the Stellar Parameter Classification (SPC; Buchhave et al. 2012) code to derive atmospheric properties from the spectra, with the results shown in Table 10.

FEROS Spectroscopy
TOI-2207 was also observed on six epochs with the FEROS spectrograph (Kaufer et al. 1999) mounted on the MPG 2.2m telescope at the ESO La Silla Observatory, in Chile, in the context of the Warm gIaNts with tEss collaboration (WINE, Brahm et al. 2019;Trifonov et al. 2021). FEROS is a stabilized fiber-fed high resolution spectrograph configured with a comparison fiber to trace instrumental radial-velocity drift during the scientific exposures. The six observations of TOI-2207 were performed between 2021-07-22 and 2021-10-24 with a typical exposure time of 1200 seconds, achieving an S/N per resolution element ranging from 70 to 100. All FEROS data were processed with the CERES pipeline (Brahm et al. 2017), which executed all steps involved in obtaining high precision radial-velocities with the cross-correlation technique, starting from the raw images. The typical radial-velocity error of these observations was ≈ 10 m/s. CERES also estimates the stellar atmospheric parameters from the spectra, which are tabulated in Table 10.

MINERVA-Australis Spectroscopy
We also obtained 11 observations of TOI-2421 between 2021-06-26 and 2021-08-16 using the Minerva-Australis telescope array (Wittenmyer et al. 2018;Addison et al. 2019), located at Mt. Kent Observatory, Australia. Minerva-Australis is an array of four identical 0.7 m telescopes linked via fiber feeds to a single KiwiSpec echelle spectrograph at a spectral resolving power of R ∼80,000 over the wavelength region of 5000-6300Å. The array is wholly dedicated to radial-velocity followup of TESS planet candidates (e.g., Nielsen et al. 2019;Addison et al. 2021;Wittenmyer et al. 2018). Simultaneous wavelength calibration is provided via two calibration fibers illuminated by a quartz lamp through an iodine cell. The spectra were extracted for each telescope individually and the radial-velocities were extracted via  the same techniques as those described above for the CHIRON observations.

TRES Spectroscopy
We observed all five targets in the Northern hemisphere (TOI-2567, TOI-2570, TOI-3540, TOI-3693, and TOI-4137) with the Tillinghast Reflector Echelle Spectrograph (TRES; Fűrész 2008). TRES has a spectral resolution of R ∼ 44, 000 and is located on the FLWO 1.5m Tillinghast Reflector telescope on Mount Hopkins, Arizona. The observations for each target were scheduled near the two opposite quadratures, ensuring maximum sensitivity to the planet's orbital motion. Two TRES spectra were taken of each target except for TOI-3693, for which we collected three observations. The data were reduced and radial-velocities extracted using the pipeline described in Buchhave et al. (2010) and Quinn et al. (2012).
The spectra were also analyzed with SPC to derive the stellar atmospheric parameters T eff , log g, [Fe/H], and v sin i. The results from each observation were weighted according to the cross-correlation function and averaged together, with the final stellar properties presented in Table 10.

HIRES Spectroscopy
We observed TOI-2567, TOI-3540 and TOI-3693 with the High Resolution Echelle Spectrometer (HIRES; Vogt et al. 1994) on the Keck-I 10m telescope on Maunakea, Hawaii. We obtained 6-9 observations for each target with an iodine cell that provides a precise wavelength calibration and allows for radial-velocity extraction. These observations were made through the queue system operated by the California Planet Search (CPS), and reduced with the standard CPS procedures (Howard et al. 2010;Howard & Fulton 2016).
To reduce the observation time necessary to obtain a high-S/N, iodine-free template spectrum, we used the matched template technique developed by Dalba et al. (2020). Briefly, we first obtained an iodine-free but low S/N (∼ 40/pixel) reconnaissance spectrum, which was then matched against a library of archival HIRES template spectra described in Yee et al. (2017). A Deconvolved Stellar Spectral Template (DSST) was then derived for the target using the high S/N spectrum of the best-matching library star, which could then be used in the radial-velocity extraction procedure. For the slowly rotating F and G dwarfs observed here, Dalba et al. (2020) found that the technique introduced a median error of 4.7 m s −1 to the RV measurements, compared with obtaining a high-S/N template of the target star. We included this introduced error by adding it in quadrature to the internal RV precision of the observations. For the massive planets targeted by our work, this additional error should not significantly affect the characterization of the planetary systems, especially given that we chose observation exposure times of 10 minutes to yield an RV precision of a similar magnitude, 5-10 m s −1 .

NEID Spectroscopy
TOI-2570 and TOI-4137 were observed with the NEID spectrograph on the WIYN 3.5m telescope at Kitt Peak National Observatory (KPNO). NEID is a newly commissioned stabilized, fiber-fed optical spectrograph with a resolving power of R ≈110,000 spanning the wavelength range from 3800 to 9300Å. (Schwab et al. 2016;Halverson et al. 2016). The data were reduced and RVs extracted using v1.1.2 of the standard NEID Data Reduction Pipeline (NEID-DRP) 5 , which derives velocities through cross-correlation with a weighted numerical stellar mask based on spectral type (Baranne et al. 1996;Pepe et al. 2002). We used relatively short exposure times for our observations, obtaining RV precisions of about 5 m s −1 for TOI-2570 and 15 m s −1 for the relatively fainter TOI-4137.

Spectroscopic Parameters
For each system, we further characterized the host star properties using the high resolution stellar spectra obtained as part of our spectroscopic follow-up program. In the case of systems observed with the stabilized spectrographs CHIRON and NEID, we used a spectrum from a single epoch with the highest signal-to-noise ratio (S/N). For systems observed with PFS, we used the high S/N iodine-free template spectrum. For those observed with HIRES, we used the low S/N iodine-free reconnaissance spectrum.
We used the publicly available code SpecMatch-Emp (Yee et al. 2017) 6 to obtain a homogeneous set of stellar properties for our targets. This code works by comparing a target spectrum to a library of observed highresolution (R ≈60,000), high S/N (S/N ≈ 150/pixel) spectra from Keck/HIRES. The library stars have welldetermined empirical stellar properties from a variety of sources, including asteroseismology, interferometry, and spectrophotometry. The code finds the five library spectra that best match the target, accounting for rotational broadening, and interpolates between those stars' properties to derive (T eff , R , [Fe/H]) for the target, with uncertainties of σ(T eff ) = 100 K, σ(∆R /R ) = 15%, σ([Fe/H]) = 0.09 dex, which are robust even when the S/N is as low as 20/pixel. While SpecMatch-Emp was developed for use with Keck/HIRES spectra, it has been successfully used with spectra from other instruments (e.g., Teske et al. 2018).
To account for the narrow line spread functions of the other spectrographs used compared with that of HIRES, we modified the code to allow the target star's spectrum to be broadened relative to the library spectra. We found that this produced sharper χ 2 minima, and a better match to the target spectrum. Previous testing of this approach using a cross-validation technique with the library Keck/HIRES spectra showed no degradation in the accuracy of the derived parameters. We compared the SpecMatch-Emp-derived parameters to those derived from the TRES reconnaissance spectra when available ( §2.4.5), and found them to be within 1-σ agreement.
We measured v sin i for each of the targets using the SpecMatch-Synth 7  code. This code works similarly to SpecMatch-Emp, but matches the target spectrum to a synthetic spectral library from Coelho et al. (2005) instead. A set of eight best-matching spectra are selected from the synthetic library, which spans a range of T eff , log g, and [Fe/H]. These are then combined using trilinear interpolation and convolved with a rotational-macroturbulent profile and Gaussian instrumental profile to create a better match to the target spectrum. During this process, the macroturbulent broadening is assumed to follow the relationship from Valenti & Fischer (2005): The code optimizes over the interpolation weights and v sin i to derive the target stellar atmospheric proper-ties. We report only the v sin i from this code, but we found that the other parameters were typically within 1-σ agreement with those derived by SpecMatch-Emp, which is more robust for low S/N spectra. We report T eff , log g, and [Fe/H] from SpecMatch-Emp, and v sin i and v mac from SpecMatch-Synth in Table 10. For those targets with observations from TRES, we also used SPC (Buchhave et al. 2012) to derive stellar atmospheric properties. SPC cross-correlates an observed spectrum against a grid of synthetic spectra from Kurucz (1993), allowing T eff , log g, [Fe/H], and v sin i to be determined. The SPC stellar parameters are also tabulated in Table 10, and we found that in all cases, the derived properties did not differ from those from SpecMatch by more than 1.5-σ. For targets with CHI-RON spectra, we derived stellar properties by matching the spectra against a library of ∼10,000 observed spectra previously classified by SPC. This procedure is described in more detail in Rodriguez et al. (2021), with results shown in Table 10. Finally, for TOI-2207, we used the CERES code (Brahm et al. 2017) to estimate stellar properties from the FEROS spectra. In all cases, the stellar properties derived by these different codes do not differ significantly, giving us greater confidence in these results. For consistency, we used the SpecMatch results for T eff , R and [Fe/H] for all targets as prior constraints in our EXOFASTv2 fits, as described in Section 4.  0.18 ± 0.09 0.22 ± 0.08 0.12 ± 0.09 0.18 ± 0.09 0.30 ± 0.08 0.12 ± 0.09 -0.09 ± 0.08 0.08 ± 0.09 0.14 ± 0.08 v sin i (km/s) 2.3 ± 1.0 4.0 ± 0.5 3.5 ± 1.0 3.9 ± 1.0 6.3 ± 0.5 4.4 ± 1.0 5.1 ± 0.5 8.8 ± 1.0 9.2 ± 0.5 vmac (km/s) The v sin i in the SpecMatch column was computed from SpecMath-Synth. b vmac is assumed based on effective temperature and the relation from Valenti & Fischer (2005).

SED Fitting for Stars with Nearby Companions
Three of the target systems (TOI-2193, TOI-3331, TOI-3540) had nearby companions detected in highresolution imaging ( §2.3, Figures 2-4). The magnitude difference and angular separation of the primary and secondary derived from this imaging are presented in Table 11. In the case of TOI-2193 and TOI-3331, these companions were also detected by Gaia as they are relatively bright and at separations 1. 0, which Gaia can reliably resolve.
To correct the catalog photometry and photometric timeseries data for contamination by these companions, we used the isochrones package (Morton 2015) to perform a multi-component Spectral Energy Distribution (SED) fit. For each system, we fitted the blended catalog photometry, together with the ∆mag between the primary and secondary stars obtained from high-resolution imaging, to synthetic photometry derived from the MIST isochrones (Dotter 2016;Choi et al. 2016). We placed an error floor of 0.02 mag for the Gaia and 2MASS photometry, and 0.03 mag for the WISE photometry, to account for possible systematic errors in the isochrones in reproducing the broad-band photometry measurements. The fit was additionally constrained by the parallax measurements from Gaia, the spectroscopic parameters derived for the primary in Section 3.1, and an upper limit on the line-of-sight extinction from Schlegel et al. (1998) and Schlafly & Finkbeiner (2011).
We provide the best-fit stellar properties and MIST isochrone synthetic photometry for the secondary, along with corresponding uncertainties from a Markov Chain Monte Carlo analysis, in Table 12. We then subtracted the synthetic photometry from the blended catalog photometry (as listed in Tables 8 and 9), and use these corrected fluxes for our global modelling ( §4). We also computed flux dilution factors (defined in §4) for each band in which time-series photometry was obtained, to correct for the contribution from the nearby stars to the light-curve. These dilution factors were used in the global ExoFAST fits.
In addition, as a further check that the spectroscopic parameters derived in Section 2.4 were not biased by possible contamination of the observed spectrum by the companion, we performed a series of tests on the SpecMatch-Emp code. We injected a diluted spectrum matching the companion's spectral type into the target spectrum and performed the stellar characterization procedure. We found that even if the companion was responsible for contaminating the target spectrum by up to 10%, the derived stellar properties did not vary by   11.32 ± 0.05 a We did not correct the catalog photometry for the secondary fluxes in these bands, as the primary and secondary were resolved in the Gaia catalog.
more than the uncertainties. Furthermore, contamination down to ∼1% would be detected in the residuals as a poor χ 2 match, which was not the case for these three targets.
We discuss each of these three targets in more detail in the rest of this section.

TOI-2193 Companion
The TOI-2193 system contains two stars (TOI-2193A and TOI-2193B) separated by 1. 885 and a magnitude difference of ∆I = 3.8 mag. The Gaia EDR3 catalog (Brown et al. 2021;Riello et al. 2021) contains astrometry for both components, as well as 3-band photometry (G, G BP , G RP ) for the primary and G-band photometry for the secondary. The parallaxes and proper motions for the two components are identical within the uncertainties, suggesting that they are a bound system with a projected separation of ≈ 640 AU (Table 11). We therefore performed the isochrone fit assuming that the two stars have the same age and had the same initial metallicity.
The best-fit SED model found the secondary to have a mass of M = 0.54±0.01M , and the estimated fluxes are shown in the top panel of Figure 5. We used this best-fit model to correct the 2MASS and WISE catalog photometry, but not the Gaia and TIC photometry, since the two components were resolved in Gaia as well as the TESS Input Catalog (TIC; Stassun et al. 2018Stassun et al. , 2019. For the same reason, we do not impose an additional dilution factor for the TESS light-curve, since it was already accounted for in the crowding corrections performed by the TESS SPOC.

TOI-3331 Companions
In the case of the TOI-3331 system, SOAR imaging detected a nearby star with an angular separation of 2. 663 and ∆I = 2.6 mag. This system was also resolved by Gaia. The Gaia EDR3 catalog gives a parallax of Π 2 = 5.39±0.17 for the secondary, compared with Π 1 = 4.577±0.057 for the primary. The proper motions for the two stars differ significantly (Table 11). Thus, the two stars are most likely a chance alignment along the line of sight. Gaia photometry also resolved a third star at an angular separation of 4. 89, but we ignored this object in our fit due to its faintness (G = 20.1). In our isochrone fit, we model the two stars with independent ages and metallicities, with individual parallaxes as constrained by Gaia, and show the results in the middle panel of Figure 5. As with the previous case, we did not correct the Gaia and TESS photometry, as the secondary was resolved in those catalogs.

TOI-3540 Companion
For TOI-3540, SOAR speckle imaging as well as PHARO AO imaging both detected a companion at 0. 917, with ∆I = 1.8 mag. This companion was not resolved by Gaia, so we do not have parallax or proper motion measurements for this object. However, studies (e.g., Horch et al. 2014;Matson et al. 2018) have shown that most nearby companions within 1" are likely to be bound, leading us to assume that this is the case for TOI-3540. This would give the pair of stars a projected separation of ≈ 250 AU. We then performed the isochrone fit under this assumption, finding that the catalog photometry is well-described by a twocomponent system in which the secondary has a mass of M = 0.79 ± 0.02M . We corrected the fluxes in all photometric bands, and computed the appropriate dilution factors for the TESS and ground-based time-series photometry.

PLANETARY SYSTEM CHARACTERIZATION
We characterized each planetary system with the exoplanet fitting code EXOFASTv2 Eastman et al. 2019). This software models the star and planet in a self-consistent manner, fitting transit and radial-velocity observations as well as the broadband photometry, with constraints on the stellar properties from the MIST stellar evolutionary models (Dotter 2016; Choi et al. 2016). EXOFASTv2 uses a differential evolution Markov Chain Monte Carlo (DE-MCMC) algorithm to explore the posterior distribution and determine uncertainties of each fitted parameter.
In this section, we first describe our general fitting strategy, before describing some deviations from the general strategy for specific targets. We imposed Gaussian priors on the stellar spectroscopic properties T eff , R , and [Fe/H] based on the SpecMatch-Emp characterization described in §3.1. For the SED fit, we used broadband photometry from the Gaia EDR3 (Brown et al. 2021;Riello et al. 2021), Tycho-2 (Høg et al. 2000), 2MASS , and WISE (Cutri 2012) catalogs. We imposed a minimum uncertainty of 0.02 mag for the Gaia and 2MASS photometry, and 0.03 mag for the WISE photometry. We also imposed a Gaussian prior on the parallax from Gaia EDR3, corrected for the parallax zero-point as described in Lindegren et al. (2021) 8 , as well as an upper limit on line-of-sight extinction from Schlegel et al. (1998) and Schlafly & Finkbeiner (2011).
We fitted the available radial-velocities with an independent RV offset γ and jitter σ jit terms for each instrument and target. For those targets with only two observations from TRES (TOI-2567, -2570, -3540, -4137), we did not include the TRES RVs in the fit, as the introduction of two additional per-instrument free parameters did not justify their inclusion. In all cases however, we find that the TRES measurements are consistent with the modelled RV semiamplitude from the global fit (Figures 15,16,18 & 20), giving us additional confidence in our results. We did not allow for any long-term radialvelocity trends, because our initial testing showed that trends were not required to achieve a good fit to the data for any of our systems, especially given the relatively short baseline of our RV observations. We used both the TESS and ground-based time-series photometry to constrain the transit model. EXOFASTv2 fits an analytic transit model from Mandel & Agol (2002) and Agol et al. (2020) to the transit light-curve, with quadratic limb-darkening coefficients in each band constrained by the stellar properties and the tables from Claret & Bloemen (2011) and Claret (2017). EXOFASTv2 ensures that the constraint on the stellar mean density implicit in the transit model is consistent with the mean density implied by the MIST stellar evolution model. We also fit for a separate flux baseline F 0 and added variance σ 2 for each transit light-curve.
While the fluxes from TESS are already corrected for dilution from neighboring stars in the TESS Input Catalog (TIC; Stassun et al. 2018Stassun et al. , 2019, we still fitted for a dilution factor A D , to account for any inaccuracies and to propagate uncertainties, as recommended by Eastman et al. (2019). Here, A D = F 2 /(F 1 + F 2 ) is the fractional contribution to the total flux (F 1 + F 2 ) from all neighboring stars (F 2 ). We imposed a Gaussian prior on this dilution factor centered at zero and with a width equal to 10% the contamination ratio found in the TIC. For the ground-based photometry, we simultaneously detrended against the detrending vectors listed in Table 3. We normalized the detrend parameters to be between [−1, +1], and used an additive detrending model for the light-curve. The final light-curve model at time i is then where T i is the transit model with an out-of-transit baseline of 1, d i,j is the j-th detrending parameter at time i, and C j the additive coefficient for the j-th parameter. For the TESS long-cadence data, this model is integrated over the 30-minute or 10-minute exposure time to account for smearing of the light-curve over each exposure. We performed our initial fits requiring circular orbits for each planet. We also performed a second fit in which the eccentricity was allowed to be a free parameter. In EXOFASTv2 , the eccentricity is parameterized in terms of √ e cos ω and √ e sin ω. In all but one case (TOI-2207 b), the data are consistent with a circular orbit. As such, we adopt the results from the circular fit for these objects, but also report 1-σ upper limits on the eccentricity from the fit where we allowed eccentricity to float. For TOI-2207 b, our eccentric fit found that the median of the posterior distribution was more than 3-σ above zero, suggesting that this planet, with an orbital period of P ≈ 8.00 days, has a detectably eccentric orbit. We adopt the results from the eccentric fit for this target.
We ran the EXOFASTv2 DE-MCMC algorithm using the convergence criteria suggested by Eastman et al. (2019), requiring the Gelman-Rubin statistic (Gelman & Rubin 1992) to be < 1.01, as well as > 1,000 independent draws in each parameter. Tables 13 and 14 contain the median and 68% confidence intervals of the marginalized one-dimensional posterior probability distributions for the fitted stellar and planetary parameters, from the adopted fit. Additional fitted parameters specific to the observations (e.g. RV offset, jitter, and flux dilution factors) are provided in Table 15 at the end of the paper. We also provide the full results from both circular and eccentric fits for all targets as a machinereadable companion to those tables. The best-fit model for the transit, radial-velocities, and SED for each system are shown in Figures 6 and 12 through 20.

Target-Specific Notes
In the case of TOI-2207 b, our eccentric fit found that the median of the posterior distribution was more than 3-σ above zero, suggesting that this planet, with an orbital period of P ≈ 8.00 days, has a detectably eccentric orbit. As such, in Table 13, we report the median and 68% confidence intervals for the eccentric fit for all parameters listed.
The objects TOI-2193A b and TOI-3540A b appear to be on orbits wherein the planetary transits graze the stellar limb. In this regime, there is a strong degeneracy between the planet-to-star radius ratio R p /R and the transit impact parameter b. The resulting posterior distributions for these parameters have long tails allowing for extremely large and unphysical planet radii. In these cases, we placed an upper limit of R p /R < 0.5 during the fit to ensure convergence of the MCMC fits within these limits. As the medians of the posterior distributions would be heavily skewed by the long tails, we report the mode of the posterior distributions and the 95% lower limit on the planet radius and 95% upper limit on the orbital inclination (note that these limits also depend on the cutoff chosen during the fit).
In general, we did not fit for any dilution factors in the transit light-curves, except for the TESS data, where we allowed A D to vary within a small range around zero. However, for the targets described in Section 3.2 that have stellar companions, we also allowed for dilution of the ground-based light-curves, since the apertures used also contained the stellar companions. In these cases, we used the best-fit multi-component SED model to derive dilution factors for each photometric filter to correct the light-curves, imposing a Gaussian prior with width equal to 10% of the dilution factor around the mean value.
For targets observed in multiple TESS sectors, we generally fit each sector of data separately, with a separate baseline flux F 0 and variance σ 2 per sector. TOI-2567 was observed by TESS in a total of 15 sectors (14-26, 40, 41), which would greatly increase the dimensionality of the fit were we to include these two additional free parameters for each. In this case, we fit the Sectors 14-26 data, which were all at 30-min cadence, as a single light-curve. The sectors 40 and 41 data were taken at 2-min cadence, and we fit these as a single light-curve too. In general, our fitted values for F 0 and σ 2 for the TESS data are close to 1.0 and 0.0 respectively, indicating minimal baseline offsets between sectors, so combining these consecutive sectors of data should not have had a significant impact on the fit.

Potential False-Positive Scenarios
Various astrophysical phenomena can lead to lightcurves that appear similar to planetary transits, leading to false-positive planet detections (e.g. . The goal of our ground-based follow-up observations was to help rule out or reduce the likelihood of such scenarios. For each of our ten hot Jupiter systems, the seeing-limited ground-based photometry confirm that the transits occur on the target stars, as opposed to being nearby eclipsing binaries that contaminate the TESS photometric aperture. The measured RV semi-amplitudes for all companions are also consistent with planetary mass objects, rather than brown dwarfs, which can have similar radii despite their significantly larger masses. Furthermore, the spectra of each target showed no indications of secondary spectral lines. To check for the possibility of unresolved blended eclipsing binaries causing line-profile variations that may appear as RV variations, we computed the Pearson-r coefficient to check for correlations between the measured RV and the spectral line BIS. For each of the ten target systems, we found no statistically significant correlations (p > 0.1).
Given the extensive ground-based follow-up observations and lack of BIS variations, we are confident that all of our targets are confirmed as true planets. However, we chose to pay closer attention to the two systems TOI-2193 and TOI-3540, which exhibit grazing transits and have close resolved stellar companions. Although the measured RV reflex motions measured on the primary stars are indicative of planetary mass objects orbiting them, there may be concern that these may actually be blended eclipsing binary (EB) false positives, where the diluted light of the companion is the source of both the transit and apparent radial-velocity variations. In the case of TOI-2193, the nearby companion TOI-2193B is 1. 885 away. A small aperture measurement (1. 2) of the LCO-CTIO light-curve taken on UT 2021-07-26 confirmed that the source of the transit signal is indeed TOI-2193A. For TOI-3540, the companion star is just 0. 917 away and could not be resolved by seeing-limited photometry.
In order to definitively rule out such scenarios for these two objects, we carried out a detailed blend modeling of each system following the procedures described in Hartman et al. (2019), which is based on the work of Torres et al. (2004). In each case we jointly model the available TESS and ground-based light curves, catalog broadband photometry, Gaia parallaxes, and spectroscopically determined atmospheric parameters. We include the resolved stellar companions in the modelling, jointly fitting for the masses, metallicities, distances, and ages of all stars that we assume contribute to the blended (or resolved) measurements, and we include the measured magnitude differences from high-resolution-imaging as observations to be fit in the modelling. We use the MIST stellar models to constrain the properties of the stars. For TOI-2193 we force the resolved stellar companion to have the same age, distance and metallicity as the primary star, while for TOI-3540 we allow the components to have independent values.
For each system we consider four scenarios: (1) the primary object in the resolved pair is a single star with a transiting planet, while the secondary object is also a single star; (2) the primary object in the resolved pair is a single star, while the secondary object is a twocomponent stellar eclipsing binary system; (3) the primary object in the resolved pair is itself an unresolved hierarchical triple consisting of a bright non-eclipsing star and a fainter stellar eclipsing binary, and the secondary object in the resolved pair is a single star; and (4) the primary object in the resolved pair is an unresolved blend between a bright non-eclipsing star and a line-ofsight background eclipsing binary, while the secondary object in the resolved pair is a single star. For both TOI-2193 and TOI-3540 we find that scenario (1) provides the best (lowest χ 2 ) fit to the observations, despite using the fewest model parameters. In both cases the combination of the photometry and Gaia parallax measurements favors scenarios where each of the resolved point sources is itself a single star, while the transit duration and depth, and the lack of secondary eclipses or ellipsoidal variations in the light curves favors a transiting planet around the primary star over scenarios involving eclipsing stellar binaries. For both TOI-2193 and TOI-3540 we find that scenario (4) is the next-bestfitting scenario, and that this scenario has ∆χ 2 ≈ 70, and ∆χ 2 ≈ 9 compared to scenario (1) for TOI-2193 and TOI-3540, respectively. The relative inability of the blend-models to fit the photometric data, together with the significant RV variations consistent with transiting giant planet companions, and the lack of any significant BIS variation in phase with the transit ephemerides, leads us to conclude that both TOI-2193A b and TOI-3540A b have been confirmed as transiting planets.  Figure 6. Results of EXOFASTv2 fits for TOI-2193. Left: TESS and ground-based photometric observations, phased to the best-fit orbital period and time of conjunction. The black points are the photometric time-series data binned to 15-min cadence, while the faint colored points are the unbinned data. The red line shows the best-fit transit model, corrected for flux dilution and additive detrending. Top right: Radial-velocity observations of TOI-2193, phased to the best-fit orbital period. The error bars reflect the internal measurement error added in quadrature to the fitted jitter σjit parameter for each instrument. The two lower subpanels show the phased radial-velocity residuals and bisector span measurements. Middle right: The best-fit MIST stellar evolution track (black line), which is fit simultaneously and self-consistently with the transit and RV model. The blue point shows the best-fit stellar T eff and log g, while the red asterisk corresponds to the star's position along the track given its best-fit age. The small discrepancies between the two are well within the fitted uncertainties in each parameter. Lower right: Result of the SED fit, performed using the MIST bolometric correction grid. The red points are the catalog broadband photometric measurements, corrected for the presence of any stellar companions (i.e. subtracting the yellow points in Figure 5), with vertical error bars showing the catalog uncertainty and horizontal error bars showing the bandpass width. The model fluxes in each bandpass, derived from the MIST grid, are the blue points. An atmospheric model from Kurucz (1993) corresponding to the best-fit stellar parameters is plotted in gray for illustrative purposes only, and is not used directly in the fit. The lower subpanel shows the residuals to the model fit, in units of the uncertainty on each measurement. Note-This table contains the fit results from the preferred fit for each target: circular fits (e fixed at 0.0) for all targets apart from TOI-2207 b, and an eccentric fit for TOI-2207 b. The results from both fits for each target are available as a machine-readable table.
For TOI-2193A b and TOI-3540A b, we provide the posterior mode and 95% lower limits for the (Rp/R ) 2 , Rp, and b, and the posterior mode and 95% upper limits for i, ρ P ,log g P , and τ circ . a−d Additional notes are provided following Table 14. Note- Table 3 in Eastman et al. (2019) provides a detailed description of all derived and fitted parameters. a For those targets where we adopt a circular fit, we also provide the 68% upper limit on eccentricity derived from the eccentric fits. b The tidal circularization timescale is computed with Equation (3) of Adams & Laughlin (2006), assuming a tidal quality factor Q S = 10 6 . c The stellar metallicity when the star was formed, that define the grid points for the MIST stellar evolutionary tracks. d The equal evolutionary phase (EEP) corresponds to specific points in the stellar evolutionary tracks, as described in Dotter (2016  TESS HJs New HJs Known Exoplanets Figure 8. Mass-radius distribution for the systems presented in this paper (colored circles). For TOI-2193A b and TOI-3540 b, we plot the mode and lower limits on the planet radii. The navy blue squares show hot Jupiter systems discovered by TESS , while the gray circles show the masses and radii of all planets from the NASA Exoplanet Archive (not just hot Jupiters) with masses determined to better than 50% and radii to better than 20%.

DISCUSSION
The ten planets presented in this paper have orbital periods between 2 and 10 days, and masses between 0.2 and 2.2 M J . To put these newly-discovered planets into context, we downloaded data from the NASA Exoplanet Archive (NASA Exoplanet Archive 2022) 9 .
In Figure 7, we show the distribution of the stellar hosts of our ten planets in color-magnitude space, in the context of other hot Jupiter hosts (orbital period P < 10 days, planet radius 8 R ⊕ < R p < 24 R ⊕ ). Our ten planets orbit F and G stars, and all of the stars have metallicities similar to that of the Sun or higher, with a median [Fe/H] of +0.18. This is in line with the wellknown preference for hot Jupiters to exist around stars with super-solar metallicities (Santos et al. 2004;Valenti & Fischer 2005).
The planets in our sample have masses and radii generally consistent with the previously known population of hot Jupiters (Figure 8). The new planets are also consistent with the previously noted trend that hot Jupiters with higher incident fluxes tend to have larger radii (Figure 9; see also Demory & Seager 2011).

Two Inflated Saturns
Two of the host stars (TOI-2421, TOI-2567) appear to have recently evolved off the terminal age main sequence, with stellar radii R = 1.75 ± 0.05 R and 1.69±0.04 R respectively. Their masses are both about 1.13 M . These two stars also host the lowest-mass planets in our sample -TOI-2421 b is a Saturn-mass planet, with a mass of M p = 0.33 ± 0.08M J , and TOI-2567 b is a sub-Saturn (M p = 0.20 ± 0.03M J ). The two planets lie on the upper boundary of the hot Neptune desert (Mazeh et al. 2016), as shown in the lower panel of Figure 9.
Both planets are inflated, with radii of R p = 0.925 +0.035 −0.034 R J and 0.975 +0.031 −0.029 R J respectively. Indeed, TOI-2567 b has a bulk density of just 0.27 ± 0.05g cm −3 , making it one of the least dense planets known for its mass ( Figure 10). The two planets join a small but growing collection of hot Saturns orbiting slightly evolved stars, including TOI-954 b (Sha et al. 2021), TOI-1296 b (Moutou et al. 2021) and TOI-1842 b (Wittenmyer et al. 2022). Such planets can help test models of radius reinflation around evolved stars (e.g. Lopez & Fortney 2016;Thorngren et al. 2021) by helping to place constraints on the timescale of reinflation, and via comparison with such trends for their more massive counterparts (e.g. Hartman et al. 2016).

Planet Eccentricities
While the shortest period hot Jupiters are expected to be on circular orbits due to tides raised by the star  Figure 9. Distribution of planet radius (top panel) and mass (lower panel) as a function of planet insolation, expressed as the equilibrium temperature at the planet's orbital distance, assuming no albedo and perfect heat redistribution. The two least massive planets in our sample, TOI-2421 b and TOI-2567 b, lie on the lower edge of the distribution of known hot Jupiters, just above the hot Neptune desert (Mazeh et al. 2016). The navy blue squares and gray circles represent the same previously known systems as described in Figure 8. on the planet, the tidal circularization timescale increases rapidly with orbital distance. Tidal circularization might be too slow to have affected planets with periods approaching 10 days or longer, with an extreme example being the recently discovered TOI-3362 b, a potential proto-hot Jupiter on a P = 18.1 day, e = 0.82 orbit (Dong et al. 2021). Indeed, the two longest period planets in our sample, TOI-2207 b (P = 8.00 days) and TOI-3693 b (P = 9.09 days) have theoretical tidal circularization timescales of 12 ± 5 and 22 ± 6 Gyr, based on Equation 3 of Adams & Laughlin (2006) which extended the work from Goldreich & Soter (1966), and assuming a tidal quality factor of Q P = 10 6 . The measured orbital eccentricity of TOI-2207 b is e = 0.174 +0.048 −0.052 , which is greater than zero by more than 3-σ, although the significance of this result may be affected by the Lucy-Sweeney bias (Lucy & Sweeney 1971). Given that the estimated stellar age is 4 Gyr, which is of the same order of magnitude as the theoretical circularization timescale, the current eccentricity might be a remnant of a high-eccentricity migration formation pathway for this planet.
In contrast, TOI-3693 b, which has a longer orbital period, appears to have a more circular orbit. The 68% and 95% upper limits for the eccentricity of this planet are e < 0.054 and e < 0.13 respectively. More data, including the possible timing and detection of a secondary eclipse, would be required to obtain a more secure measurement of the planet eccentricity, but TOI-3693 b is not likely to have an orbital eccentricity similar to that of TOI-2207 b or some other warm Jupiters (e.g. TOI-640 b ), TOI-559 b (Ikwut-Ukwa et al. 2021).
These two longer period hot Jupiter systems are also potential targets for stellar obliquity measurements with the Rossiter-McLaughlin (RM) effect (Rossiter 1924;McLaughlin 1924). The expected RM amplitudes for the two systems are ≈ 30 m s −1 for TOI-2207 b and ≈ 90 m s −1 for TOI-3693 b (Gaudi & Winn 2007), which should be measurable on a large telescope given the relatively bright host stars (V = 11.4, 12.0 respectively). The large planet-star separations of the two planets (a/R ≈ 12 and 22 respectively) result in long tidal realignment timescales. Thus, misaligned orbits in these systems, particularly when correlated with orbital eccentricity, could be indicative of a high-eccentricity formation pathway, although they could also result from perturbations by an outer planets in the system.

CONCLUSIONS
We presented the discovery and characterization of ten new hot Jupiters around F and G stars from NASA's TESS mission. These planets orbit relatively bright stars (G < 12.5) and are potential targets for atmospheric characterization, measurements of stellar obliquity, and other follow-up observations. While we have drawn attention to some of the notable features of the new planets, including the low density of the sub-Saturn TOI-2567 b and the detectable eccentricity of TOI-2207 b, the larger and longer-term purpose of the survey is to allow for more general conclusions to be drawn about the hot Jupiter population. This will require more observations to detect and confirm new planets (the "numerator" of demographic calculations) as well as a detailed examination of the TESS selection function and survey characteristics (the "denominator"). Based on the forecast of Yee et al. (2021), to assemble a sample of 400 hot Jupiters (an orderof-magnitude more planets than the Kepler sample), a magnitude-limited survey would need to be complete down to G = 12.5. The ten planets described here, along with the other new TESS hot Jupiters that have been described in the literature (e.g., Rodriguez et al. 2019;Zhou et al. 2019;Brahm et al. 2020;Davis et al. 2020;Nielsen et al. 2020;Ikwut-Ukwa et al. 2021;Rodriguez et al. 2021;Sha et al. 2021;Wong et al. 2021;Knudstrup et al. 2022;Rodriguez et al. 2022) are steps toward realizing the promise of TESS for hot Jupiter demographics.
We thank the anonymous reviewer whose comments helped improve the manuscript. S.W.Y. thanks Gummi Stefansson for helpful conversations regarding the NEID observations. This paper includes data collected by the TESS mission that are publicly available from the Mikulski Archive for Space Telescopes (MAST). Funding for the TESS mission is provided by NASA's Science Mission Directorate. We acknowledge the use of public TESS data from pipelines at the TESS Science Office and at the TESS Science Processing Operations Center. Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center for the production of the SPOC data products. We also acknowledge the use of data from the Exoplanet Follow-up Observation Program website, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This research made use of Lightkurve, a Python package for Kepler and TESS data analysis (Lightkurve Collaboration et al. 2018).
Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. Keck telescope time was granted by NOIRLab (Prop. ID 2021B-0162, PI: Yee) through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. This paper contains data taken with the NEID instrument, which was funded by the NASA-NSF Exoplanet Observational Research (NN-EXPLORE) partnership and built by Pennsylvania State University. NEID is installed on the WIYN telescope, which is operated by the National Optical Astronomy Observatory, and the NEID archive is operated by the NASA Exoplanet Science Institute at the California Institute of Technology. NN-EXPLORE is managed by the Jet Propulsion Laboratory, California Institute of Technology under contract with the National Aeronautics and Space Administration. Data presented herein were obtained at the WIYN Observatory from telescope time allocated to NN-EXPLORE through the scientific partnership of the National Aeronautics and Space Administration, the National Science Foundation, and NOIRLab. This work was supported by a NASA WIYN PI Data Award, administered by the NASA Exoplanet Science Institute. The authors thank Sarah Logsdon and Heidi Schweiker for help with the NEID observations. The authors are honored to be permitted to conduct astronomical research on Iolkam Du'ag (Kitt Peak), a mountain with particular significance to the Tohono O'odham.
This paper includes data gathered with the 6.5 meter Magellan Telescopes located at Las Campanas Observatory, Chile.
This research has used data from the CTIO/SMARTS 1.5m telescope, which is operated as part of the SMARTS Consortium by RECONS (www.recons.org) members Todd Henry, Hodari James, Wei-Chun Jao, and Leonardo Paredes. At the telescope, observations were carried out by Roberto Aviles and Rodrigo Hinojosa. The CHIRON data were obtained from telescope time allocated under the NN-EXPLORE program with support from the National Aeronautics and Space Administration.
Some of the data presented herein were obtained at the Minerva-Australis facility from telescope time allocated under the NN-EXPLORE program with support from the National Aeronautics and Space Administration. Minerva-Australis is supported by Australian Research Council LIEF Grant LE160100001, Discovery Grants DP180100972 and DP220100365, Mount Cuba Astronomical Foundation, and institutional partners University of Southern Queensland, UNSW Sydney, MIT, Nanjing University, George Mason University, University of Louisville, University of California Riverside, University of Florida, and The University of Texas at Austin. We respectfully acknowledge the traditional custodians of all lands throughout Australia, and recognise their continued cultural and spiritual connection to the land, waterways, cosmos, and community. We pay our deepest respects to all Elders, ancestors and descendants of the Giabal, Jarowair, and Kambuwal nations, upon whose lands the Minerva-Australis facility at Mt Kent is situated.
This work makes use of observations from the LCOGT network. Part of the LCOGT telescope time was granted by NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF.
This paper makes use of data from the MEarth Project, which is a collaboration between Harvard University and the Smithsonian Astrophysical Observatory.       Table 15 the median and 68% confidence intervals for additional fit parameters not listed in Tables  13 and 14 for the adopted fits. These are the linear and quadratic limb-darkening parameters (u 1 , u 2 ) in each band; additional flux dilution from neighboring stars in each band (D); the relative RV offset for each instrument γ rel (m s −1 ); and the RV jitter for each instrument σ J (m s −1 ).