dataesr/scientific-paragraphs-categorization huggingface dataset:
5% of the available slices), and 201 hardwired 25 × 18-bit DSP48E blocks (27% of the available blocks). When it comes to the RT validation, the suggested figures highlight the waveforms of the main variables, collected with a 1 µs time resolution and using a Xilinx ChipScope platform  [29]. Figure  6  presents the waveforms of the per-unit three-phase voltages v La , v Lb , and v Lc. The evolution of transistor voltage and current at the commutation scale can be seen back with a better resolution in Figure  3. Regarding the currents, Figure  7  highlights the per-unit waveforms of the three-phase load currents and those of T 1 and T 2 transistor currents. Here again, the evolution at the commutation scale can be seen with a better resolution in Figure  3. In addition to their visual coherency, all the obtained FPGA results are the same as their Matlab/Simulink counterparts.
The average fitting error, because of the limited fixed-point data format, is evaluated to be less than 1. 5% with regard to the equivalent floating-point Matlab/Simulink simulation. Regarding the currents, Figure  7  highlights the per-unit waveforms of the threephase load currents and those of T1 and T2 transistor currents. Here again, the evolution at the commutation scale can be seen with a better resolution in Figure  3. In addition to their visual coherency, all the obtained FPGA results are the same as their Matlab/Simulink counterparts. The average fitting error, because of the limited fixed-point data format, is evaluated to be less than 1. 5% with regard to the equivalent floating-point Matlab/Simulink simulation. Regarding the currents, Figure  7  highlights the per-unit waveforms of the threephase load currents and those of T1 and T2 transistor currents.
As a general comment, knowing that the same transfer functions are used for all the tested topologies, the approximation quality remains at the same level of satisfaction, with a very low average error compared to the Matlab/Simulink results. In Figure  11 , the waveform of the load current is shown in the same graph as the reference voltage (on the left side) and the inverter output voltage (on the right side). The above-described four quadrants are also highlighted, which may help in analyzing the remaining waveforms provided in Figure  12. Indeed, the figure shows the evolution of the current in each power switch and successfully confirms the switching configurations given for each quadrant. Like the previous case study, the overall design is developed and RT-tested with the Xilinx Artix-7 XC7A200T-2 FPGA device.
The parallel structure of the designed NPC eRTS allows the preservation of the same timing performances as before, namely, a 45 ns execution time with the 200 MHz clock (thus, a 50 ns simulation time step). In terms of hardware resources and with the adopted fixed-point format (25Q18 for the leg eRTS and 32Q28 for the RL load), the overall design uses 4320 flip-flops, 2617 lookup tables (1. 6% of the available slices), and 124 hardwired 25 × 18-bit DSP48E blocks (16. 7% of the available blocks). Figures  11  and 12  provide the obtained RT results. They are collected with a 1 µs time resolution and using a Xilinx ChipScope platform  [29]. As a general comment, knowing that the same transfer functions are used for all the tested topologies, the approximation quality remains at the same level of satisfaction, with a very low average error compared to the Matlab/Simulink results.
The amplitudes of these references are equally set to 0. 9 pu (over VDC/2 = 300 V) and their frequency to 200 Hz. The 10 kHz PWM process can be seen in Figure  9. The RT results obtained with this operating condition are highlighted in Figure  14 , which shows the load voltages (vLa, vLb, vLc) and the load currents (iLa, iLb, iLc). They are compared with Matlab/Simulink equivalent simulations, and the limited fixed-point precision (25Q18 format) introduces an average fitting error of less than 2%. The controller generates three-phase sinusoidal voltage references assuming that the back-EMF terms are compensated. The amplitudes of these references are equally set to 0. 9 pu (over V DC /2 = 300 V) and their frequency to 200 Hz. The 10 kHz PWM process can be seen in Figure  9. The RT results obtained with this operating condition are highlighted in Figure  14 , which shows the load voltages (v La , v Lb , v Lc ) and the load currents (i La , i Lb , i Lc ).
They are compared with Matlab/Simulink equivalent simulations, and the limited fixed-point precision (25Q18 format) introduces an average fitting error of less than 2%. The controller generates three-phase sinusoidal voltage references assuming that the back-EMF terms are compensated. The amplitudes of these references are equally set to 0. 9 pu (over VDC/2 = 300 V) and their frequency to 200 Hz. The 10 kHz PWM process can be seen in Figure  9. The RT results obtained with this operating condition are highlighted in Figure  14  which shows the load voltages (vLa, vLb, vLc) and the load currents (iLa, iLb, iLc). They are compared with Matlab/Simulink equivalent simulations, and the limited fixed-point precision (25Q18 format) introduces an average fitting error of less than 2%.
2018). In this work, we search for SiO in absorption against eight background radio continuum sources at 3 mm wavelength in the direction of diffuse and translucent gas in the Milky Way with the Northern Extended Millimeter Array (NOEMA). We also observe HCO + in absorption in these directions to trace the total quantity of molecular gas. The observations are described in Section 2. In Section 3 we present the methods for decomposing absorption spectra into Gaussian components and calculating the column densities of different molecular species. We then characterize the observed environments using new and existing data in the direction of our background radio continuum sources. In Section 5, we report the SiO column densities and abundances in these diffuse and translucent environments. We discuss these results in Section 6, both in the context of diffuse interstellar chemistry and in the context of existing literature.
We carried out standard calibration using the CLIC and MAPPING software, part of the GILDAS software collection 4  (Pety 2005; Gildas Team 2013). Because our background sources were bright (1 Jy; Table  1 ), we further performed self-calibration using the 2020 selfcalibration tool in MAPPING on all sources. The final spectra presented in Figure  2  were smoothed to a 0. 4 km s -1 velocity resolution. Table  1  lists the noise in the line divided by the continuum (e -τ( v) ) for reference (the noise levels in the HCO + and SiO spectra are very similar). In the direction of 3C 111, where the HCO + absorption is saturated, we also utilized observations of H 13 CO + (J = 1-0, 86. 7543 GHz) from NOEMA obtained in the same observing run of the HCO + observations (project W19AQ), achieving comparable sensitivity.
Gaussian Decomposition We decompose all absorption spectra in this work into Gaussian components. For each spectrum, we supply initial guesses for the number of components as well as for the amplitude, FWHM, and central velocity of each component. We then use Python's scipy. optimize. curve_fit to fit the Gaussian components to the spectrum. To obtain the final estimates and uncertainties, we refit the spectra with Gaussian components over 1000 trials, adding random noise to the spectrum in each trial. We take the mean and standard deviation over all trials to be the estimate and uncertainty for each fitted quantity (the amplitude, FWHM, and central velocity of each Gaussian component). We use the same initial guesses for the number of components and the central velocities of the components in the HCO + and SiO absorption spectra.
Deriving Molecular Column Densities For a transition from an upper state u to a lower state l observed in absorption, the column density, N, is given by N Q T c g A h kT v dv 8 1 1 exp , 1 u ul ex 3 3 ex 1 ( ) [ ( )] ( ) ( ) ò pn n t = - - - where T ex is the excitation temperature (see Section 3. 3), Q(T ex ) is the partition function, ν is the rest frequency of the transition, g u is the degeneracy of the upper state, A ul is the Einstein A coefficient for the transition, and τ(v) is the optical depth of the line at velocity v. We evaluate Equation (1) using the values given in the Cologne Database for Molecular Spectroscopy  (Müller et al. 2001; Endres et al. 2016 ) and the Leiden Atomic and Molecular Database  (Schöier et al. 2010). Results are listed in Table  3  for different excitation temperatures (in this work, we use T ex = 2.
We are grateful to  Benjamin Godard ,  Bruce Draine ,  Guillaume Pineau des Forêts ,  Ana López-Sepulcre ,  Bob Benjamin ,  Jérôme Pety , and  Maryvonne Gerin  for helpful conversations about the interpretation of results presented here. We thank the anonymous referee for constructive comments. D. R. R. thanks  Jan Martin Winters  for support in the data reduction process. This work was supported by the  University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education  with funding from the  Wisconsin Alumni Research Foundation , the  NSF  Award  AST-2108370 , and the  National Aeronautics and Space Administration  under grant No. 4200766703. Support for this work was provided by the  NSF  through award  SOSPA6-030  from the  NRAO.
20 dex. The age distributions of the full GALAH sample and matched stars are shown in Figure  3. The latter shows a broad peak with a maximum probability at 7 Gyr; the median age of the distribution and 25% and 75% quantiles yields an age estimate of 6. 6 +3. 2 -2. 2 Gyr. TOI-715 is likely to be as old or older than the Sun, consistent with its low degree of magnetic activity. Analyses of ground-based and Kepler photometry by  Newton et al. (2016)  and  McQuillan et al. (2014) , respectively, show that typical rotational periods of old M4 dwarfs (0. 4 -0. 5 M ) are roughly 15-50 days, most likely at the longer end of this range (and possibly beyond; longer periods in  Newton et al. (2016)  are "grade B" detections due to low amplitude variations). This range falls within the detectable period range for the full TESS dataset; however, the absence of detectable Hα emission suggests a lack of significant spotting, so even if the period were within this range TESS measurements may not be sufficient to detect variability.
IDENTIFICATION OF PLANETARY CANDIDATES TOI-715 is in TESS's southern continuous viewing zone (CVZ), meaning that in principle, it would be observed in all southern sectors. In practice, it was not optimally placed on the CCD during sectors 28 and 38, so at the time of writing, there are 24 sectors of short-cadence (2 minute) data for this target 3. In the following sections we describe first the initial candidate identification in the TESS data, followed by our own search for further candidates.
1 are reported as threshold crossing events (TCEs). TOI-715. 01 was first reported as a candidate on 2019 May 24  (Guerrero et al. 2021 ) following a multi-sector transit search  (Jenkins 2002; Jenkins et al. 2010 Jenkins et al. , 2020) )  conducted on 2019 May 5 for sectors 1-9. The candidate was already identified in the multi-sector search of Sectors 1-6 conducted on 2019 April 18, but did not at this time pass the necessary tests to be reported as a TOI. The transit signal was fitted with an initial limb-darkened transit model  (Li et al. 2019 ) and subjected to a suite of diagnostic tests  (Twicken et al. 2018)  to help determine whether the signature is from an exoplanet. The transit signature passed all of the tests reported in the Data Validation report for Sectors 1-9 4  , and the difference image centroiding test located the source of the transit signal to within 3.
7 ± 3. 5 in the subsequent data validation reports for the multi-sector searches of Sectors 1-13 and 27-39. At the time of the first reported TCE 5  , the TESS Input Catalog (TIC) in use was version 7, which had not yet incorporated the Gaia-DR2 data; as such, TOI-715 did not have a stellar radius and the planet candidate was reported as a 7. 1 R ⊕ object with a period of ∼ 19. 2 days. Following the update to the TICv8  (Stassun et al. 2019)  the planet candidate's radius estimate was revised, demonstrating that TOI-715. 01 was likely a super-Earth and thus a high priority target. SPOC TCEs are subject to the TESS-EXOCLASS 6  automated classifier that reduces the number of TCEs that undergo the manual TOI vetting procedure. TESS-EXOCLASS applies a series of tests that are similar to the Kepler ROBOVETTER  (Coughlin et al.
2016; Thompson et al. 2018 ). TOI 715. 01 passes all the tests of TESS-EXOCLASS and has been placed in the Tier 1 (highest quality candidate) category, and has been classified as a Tier 1 candidate in the subsequent SPOC multi-sector 1-13, 1-36, and 1-39 searches. Further details for the TOI assignment process are available in  Guerrero et al. (2021). We present the PDCSAP TESS lightcurves for all 24 sectors of 2-minute cadence data in Figure  4 ; the timings of the 29 transits are indicated with dark pink arrows.
2004) 10. Nonetheless, high resolution imaging provides crucial information toward our understanding of exoplanetary formation, dynamics and evolution  (Howell et al. 2021 ). TOI-715 was observed on 2020 December 26 UT using the Zorro speckle instrument on the Gemini South 8-m telescope  (Scott et al. 2021). Zorro provides simultaneous speckle imaging in two bands (562 nm and 832 nm) with output data products including a reconstructed image with robust contrast limits on companion detection (see  Howell & Furlan 2022). TOI-715 was found to be a single star to within the angular and brightness contrast levels achieved. Eight sets of 1000 × 0. 06 s images were obtained and processed by our standard reduction pipeline  (Howell et al. 2011). Figure  6  shows our final contrast curves and the 832 nm reconstructed speckle image.
ExTrA ExTrA  (Bonfils et al. 2015 ) is a near-infrared (0. 85-1. 55 µm) multi-object spectrograph fed by three 0. 6 m telescopes located at La Silla observatory. We observed four full transits of TOI 715. 01 on 2021 February 26, 2021 April 25, 2022 February 08, and 2022 April 07. We observed the first three transits using two telescopes, and the fourth using three; all observations were carried out with 8 aperture fibers. For both nights, we used the spectrograph's low resolution mode (R ∼ 20) and 60s exposures. Five fibre positioners are used at the focal plane of each telescope to collect light 13 https://github. com/lgrcia/prose from the target and four comparison stars. As comparison stars, we also observed 2MASS J07381369-7347351, 2MASS J07410628-7341297, 2MASS J07393394-7330535, and 2MASS J07372328-7321411 with J-magnitude  (Skrutskie et al.
GLOBAL PHOTOMETRIC ANALYSIS We carried out a global photometric analysis of the TESS photometry and the datasets described in Section 4. 3 using ALLESFITTER  (Günther & Daylan 2021 , 2019) , a flexible and publicly available PYTHON-based inference package. We exclude all partial transits, as well as the transit obtained from OACC (due to large scatter in the data) from our analysis, leaving 15 full transits from our ground-based facilities. ALLESFITTER generates lightcurve models using ELLC  (Maxted 2016) , and Gaussian Process (GP) models using CELERITE  (Foreman-Mackey et al. 2017 ). The best fitting models are then chosen using either a nested sampling algorithm via DYNESTY (Speagle 2020), or MCMC sampling with EM-CEE  (Foreman-Mackey et al. 2013). For all modeling in this paper, we make use of the nested sampling algorithm as it calculates the Bayesian evidence at each step in the sampling; this allows us to compare the Bayesian evidence for different models by calculating the Bayes Factor  (Kass & Raftery 1995).
Given its location in radius-instellation space, TOI-715 b could also help us understand the characteristics of the M-dwarf radius valley. Confirmation of the existence of the TIC 271971130. 02 in the coming months will also be crucial in planning further characterisation of planet b, as disentangling the two planets in a putative radial velocity campaign could prove challenging if the orbit of a second planet is not well known. (Lightkurve Collaboration, 2018). This work made use of Astropy: 19 a community-developed core Python package and an ecosystem of tools and resources for astronomy  (Astropy Collaboration et al. 2013a , 2018b , 2022). This research has made use of the NASA Exoplanet Archive, 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 exoplanet (Foreman-Mackey et al. 2021a) and its dependencies  (Agol et al. 2020; Kumar et al. 2019; Astropy Collaboration et al. 2013b , 2018a; Luger et al. 2019; Salvatier et al. 2016; Theano Development Team 2016). 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.
ACKNOWLEDGEMENTS We thank the reviewer for their comments and feedback as these helped clarify and streamline the maniscript significantly. 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. This research has made use of 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 paper includes data collected by the TESS mission that are publicly available from the  Mikulski Archive for Space Telescopes (MAST). Based on data collected by the  SPECULOOS-South Observatory  at the  ESO Paranal Observatory in Chile.
The ULiege's contribution to SPECULOOS has received funding from the  European Research Council  under the  European Union 's  Seventh Framework Programme  ( FP/2007-2013 ) (grant Agreement n •  336480/SPECULOOS ), from the  Balzan Prize and Francqui Foundations , from the  Belgian Scientific Research Foundation (F. R. S. -FNRS ; grant n •  T. 0109. 20 ), from the  University of Liege , and from the  ARC  grant for Concerted Research Actions financed by the  Wallonia-Brussels Federation. This work is supported by a grant from the  Simons Foundation (PI Queloz , grant number  327127 ). This research is in part funded by the  European Union 's  Horizon 2020 research and innovation programme  (grants agreements n •  803193/BEBOP ), and from the  Science and Technology Facilities Council (STFC ; grant n •  ST/S00193X/1 , and  ST/W000385/1 ).
The material is based upon work supported by  NASA  under award number  80GSFC21M0002  Based on data collected by the  TRAPPIST-South  telescope at the  ESO La Silla Observatory. TRAPPIST is funded by the  Belgian Fund for Scientific Research (Fond National de la Recherche Scientifique, FNRS)  under the grant  FRFC 2. 5. 594. 09. F, with the participation of the  Swiss National Science Fundation (SNF). Based on data collected under the ExTrA project at the  ESO La Silla Paranal Observatory. ExTrA is a project of  Institut de Planétologie et d'Astrophysique de Grenoble (IPAG/CNRS/UGA) , funded by the  European Research Council  under the  ERC  Grant Agreement n. 337591-ExTrA. This work has been supported by a grant from  Labex OSUG@2020  ( Investissements d'avenir   -ANR10 LABX56 ). This work has been carried out within the framework of the NCCR PlanetS supported by the  Swiss National Science Foundation.
BVR thanks the  Heising-Simons Foundation  for support. MG is F. R. S. -FBRS Research Director. YGMC acknowledges support from  UNAM-PAPIIT-IG101321  FJP acknowledges financial support from the grant  CEX2021-001131-S  funded by  MCIN/AEI/10. 13039/501100011033. This research made use of Lightkurve, a Python package for Kepler and TESS data analysis.
These observables are computed from synthetic spectra produced with the PHOENIX code and rely on a 2D stellar structure from the ESTER code. These quantities are computed for a grid of models in the range 2-7 M , and rotation rates from 30% to 80% of the critical rate. Then, for any triplet (T IRFM , c 1 , c 2 ), we try to retrieve the mass, rotation rate, and inclination using a Levenberg-Marquardt scheme, after a selection step to find the most suitable starting models. Results. Hare-and-hound tests showed that our algorithm can recover the mass, rotation rate, and inclination with a good accuracy. The difference between input and retrieved parameters is negligible for models lying on the grid and is less than a few percent otherwise. An application to the real case of Vega showed that the u filter is located in a spectral region where the modelled and observed spectra are discrepant, and led us to define a new filter.
Two-dimensional internal structure code ESTER The 2D internal structure is computed with Evolution STEllaire en Rotation (ESTER), a stellar evolution code dedicated to the modelling of rapidly rotating stars  (Rieutord & Espinosa Lara 2009 , 2013a,b; Espinosa Lara & Rieutord 2013; Rieutord et al. 2016). ESTER relies on the following assumptions: a steady state structure that includes the baroclinic flows in radiative regions (differential rotation and meridional circulation), and hydrogen burning in the convective core. Evolution is presently only possible along the main sequence. The equations are solved in a non-spherical geometry that follows the centrifugal distortion of the star. Solutions are obtained using spectral elements and a discretisation of the star in 'onion' shells, where the radial and the horizontal directions are respectively discretised using a Gauss-Lobatto and a Gauss-Legendre collocation grid.
Spectrum synthesis Synthesising a spectrum requires a model atmosphere. Unlike the 1D case where effective temperature and gravity are constant over the stellar surface, we have to compute several atmosphere models following the local surface flux and gravity provided by the internal structure at each point of the visible surface of the star. Each atmosphere model is used to calculate a contribution to the observed spectrum. This approach is used in  Bouchaud et al. (2020)  with the PHOENIX spectra from the Göttingen database  (Husser et al. 2013 ). However, using precomputed spectra requires applying a weighting to account for the limb darkening effect  (Claret 2000). In the present study we use the PHOENIX code  (Hauschildt et al. 1999)  to compute all the model atmospheres and corresponding spectra from scratch, which provides us with the intensity spectra for different directions, the limb darkening effect being included inevitably.
We first tested the method with a hare-and-hound exercise using our grid of the ZAMS model. As the results were satisfactory (Figs. 13  and 14 ), we moved to a test with real data, considering the observed spectra of Vega from the CALSPEC database 3. After designing a 2D model of Vega that meets the data from interferometric and spectroscopic observations, we computed the synthetic spectrum of this star and derived the three observables (T IRFM , c 1 , c 2 ). We also computed these three values using the calibrated spectrum from CALSPEC and found that c 1 differed from the synthetic value by 6%, while T IRFM and c 2 agreed within a percent. The discrepancy between the observed c 1 and the synthetic index has been traced back to the known discrepancy between the synthetic spectrum and the observed one at wavelengths just below the Balmer jump (e.
Acknowledgements. We would like to thank the referee  Y. Frémat  for his careful reading of the manuscript, and whose questions and comments helped to improve it. Most of the calculations have been performed on CALMIP supercomputing center (Grant  2023-P20025 ). We also acknowledge the support of the  French Agence Nationale de la Recherche (ANR) , under grant  ESRR  ( ANR-16-CE31-0007-01 ).