dataesr/scientific-paragraphs-categorization huggingface dataset:
Results and discussion Before the discussion and analysis of the newly proposed algorithms, we validated the implementation of the standard model which will then represents our target reference. This was done by selecting, from the S66 57 dataset, 9 structures for which dispersion plays a major role in inter-molecular interaction energies. For these selected dimers the implemented model generates MBD energies being in agreement (average deviation of 0. 4 kcal/mol, Supporting Information) with the ones computed with the MBD correction implementation included in the Q-Chem package. 58  We note however, that the Hirshfeld partitioning can give as output slightly different parameters according to the software implementation employed thus leading to potentially small discrepancies.
Acknowledgements This work has received funding from the  European Research Council (ERC)  under the  European Union 's  Horizon 2020 research and innovation program  (grant agreement No  810367 ), project  EMC2  (JPP). Computations have been performed at  GENCI (IDRIS, Orsay, France  and  TGCC ,  Bruyères le Chatel ) on grant no  A0070707671.
Context. HD 95086 is a young nearby Solar System analog hosting a giant exoplanet orbiting at 57 au from the star between an inner and outer debris belt. The existence of additional planets has been suggested as the mechanism that maintains the broad cavity between the two belts. Aims. We present a dedicated monitoring of HD 95086 with the VLT/SPHERE instrument to refine the orbital and atmospheric properties of HD 95086 b, and to search for additional planets in this system. Methods. SPHERE observations, spread over ten epochs from 2015 to 2019 and including five new datasets, were used. Combined with archival observations, from VLT/NaCo (2012-2013) and Gemini/GPI (2013-2016), the extended set of astrometric measurements allowed us to refine the orbital properties of HD 95086 b. We also investigated the spectral properties and the presence of a circumplanetary disk around HD 95086 b by using the special fitting tool exploring the diversity of several atmospheric models.
In addition, we improved our detection limits in order to search for a putative planet c via the K-Stacker algorithm. Results. We extracted for the first time the JH low-resolution spectrum of HD 95086 b by stacking the six best epochs, and confirm its very red spectral energy distribution. Combined with additional datasets from GPI and NaCo, our analysis indicates that this very red color can be explained by the presence of a circumplanetary disk around planet b, with a range of high-temperature solutions (1400-1600 K) and significant extinction (A V ≳ 10 mag), or by a super-solar metallicity atmosphere with lower temperatures (800-1300 K), and small to medium amount of extinction (A V ≲ 10 mag). We do not find any robust candidates for planet c, but give updated constraints on its potential mass and location.
2003; Lenzen et al. 2003)  at the Very Large Telescope (VLT), the HD 95086 planetary system has become a reference to investigate the processes of planetary formation and evolution, and to characterize young planetary architectures. The star is an A-type star with an approximate effective temperature of 7750 K and a mass of 1. 6 M ⊙. Until very recently, the star was identified as a young star located at the border of the Lower Centaurus Crux (LCC) association and thus with an age of 17 ± 2 Myr  (Pecaut et al. 2012). However, based on the Gaia Data Release 2,  Booth et al. (2021)  showed that the star could instead belong to the Carina association, which   Su et al. 2017; Chauvin et al. 2018). The exoplanet b is detected at the K1 band (red dot). The white dashed ring at 180 au represents the peak location of the outer cold belt located from 106 ± 6 au to 320 ± 20 au.
2019)  between February 2015 and May 2019. These datasets include five new unpublished epochs covering January 2018 to May 2019. In Sect. 2 we present the data acquired, together with the archival data used for this analysis. In Sect. 3 we describe the image processing methods used, along with our data selection and the decision to combine the different datasets considering the individual epoch contrast performance and adaptive optics (AO) correction quality. In Sect. 4 we present the updated astrometry for the exoplanet HD 95086 b based on VLT/NaCo and VLT/SPHERE data, covering a total of seven years of monitoring between 2012 and 2019, and determine the best orbital solution. In Sect. 5 we present for the first time the SPHERE-JH (1. 2-1. 6 µm) spectroscopic observations of HD 95086 b. Using the MCMC special code  (Christiaens et al.
2021 ) applied to the combined spectrum, we re-analyze the physical parameters of the planet and investigate the presence of a circumplanetary disk around it. In Sect. 6 we finally look for the hypothetical exoplanets c and d in the system by updating the HARPS and SPHERE combined observations, and also by applying the K-Stacker algorithm (Le  Coroller et al. 2015)  to the SPHERE multi-epoch datasets.
Pre-processing All SPHERE observations of HD 95086 were reduced by the SPHERE Data Center  (Delorme et al. 2017a ), using the SPHERE Data Reduction and Handling pipeline  (Pavlov et al. 2008) , following the same approach as described by  Chauvin et al. (2018). To summarize, the pre-processing corrects the noncoronagraphic point spread function (PSF) and the coronagraphic image cube for bad pixels, dark current, flat nonuniformity; the sky background for both IRDIS and IFS; and the wavelength and cross-talk between spectral channel calibration for IFS. A normalization is applied to calibrate the coronagraphic images in intensity relative to the star (i. e. , in terms of contrast). The coronagraphic images are centered by using the four satellite spots to accurately determine the position of the star behind the coronagraphic mask, as also described in  Chauvin et al.
The 1. 2-3. 8 µm spectrum of HD 95086 b For the first time, we have extracted the spectrum of the planet HD 95086 b in the J and H bands. This was achieved on the SpeCal-PCA ADI reduced images by measuring the contrast of the planet in an aperture of 1 FWHM of the six-epoch averaged image in which we corrected for the exoplanet's orbital motion by using its precise astrometry through time before stacking. The exoplanet is still not detectable in the Y band, hardly in the J band, and with a signal-to-noise ratio of about 5 per spectral channel in the H band. By using the BT-NEXTGEN synthetic spectrum of the star HD 95086 A, we converted the contrast values to flux values. We completed the SPHERE-IFS YJH (0. 96-1. 64 µm, resolution 30) and SPHERE-IRDIS K12 photometric points (2. 10 and 2. 26 µm) with archival data from GPI, which provides the spectrum of the exoplanet HD 95086 b in the K1 band at low resolution (1.
Comparison to models To constrain the physical properties of the exoplanet HD 95086 b with atmospheric and circumplanetary disk models, we used the special package  (Christiaens et al. 2021) , first known as specfit, a module of the open-source python package VIP 2  (Gomez Gonzalez et al. 2017) and now available as a distinct package  3. The special package is compatible with any atmospheric grid if a snippet function which reads the input grid files is provided. It can also fit for blackbody components (either alone or as additional component(s) to the atmosphere), the optical extinction A V , the optical-to-selective extinction ratio R V , or the intensity of emission lines that are provided in a dictionary. special utilizes the MCMC sampler emcee (Foreman-Mackey The orbital parameters are: the orbital period (P (yr)), the eccentricity (e), the inclination (i ( • )), the longitude of ascending node (Ω ( • )), the argument of periastron (ω ( • )), the time of periastron passage (T p (yr AD)).
K-Stacker exploration The existence of HD 95086 c has been investigated by  Le Coroller et al. (2020)  using the K-Stacker algorithm  (Nowak et al. 2018). The code was applied to a combination of six IFS observations (median over Y-H wavelengths) obtained at different epochs (from February 2015 to May 2017). Following a similar strategy, the complete set of observations reported in Table  2  is now considered for both IFS and IRDIS. They represent a total of ten epochs between February 2015 and May 2019. Based on the detection limits achieved with SpeCal-PCAPad and SpeCal-TLOCI in the H and K1 bands with IFS and IRDIS, respectively (see Fig. 3 ), we selected the eight best ones, rejecting February 2015 and January 2016. For IFS, the choice of  H band (median over the channels between 1. 47 and 1.
Detection probabilities Without any clear detection of additional planets orbiting HD 95086 on individual epochs or using K-Stacker and all the best epochs available, we now explore the completeness of previous HARPS and new SPHERE observations using the pyMESS2 code (A. -M. Lagrange, priv. comm. ) , a Pythonized version of the MESS2 code  (Lannier et al. 2017)  Fig. 12. Probability of companion detection as a function of the distance to the star from pyMESS2. On the left, overview of the detection limit results based on radial velocity (≤ 5 au) and direct imaging (all SPHERE+NaCo observations, ≥5 au) data for the whole HD 95086 system. In the middle and right, direct imaging results are zoomed between 5 and 35 au. In the left and middle, coplanarity is assumed between the researched exoplanets and the outer belt (i.
In this specific case, we chose to restrict the inclination and the longitude of the node of each orbital set to make sure that all companions in the population would lie in the same orbital plane as the disk (i. e. , with i = -30 ± 3 • and Ω = 97 ± 3 • ) for one run, and consider no a priori information on the system's orientation for a second run. We also assumed a uniform distribution for the eccentricity, with a maximum value of 0. 6. While MESS was limited in its use to direct imaging, both DMC and pyMESS2 can also be used to draw similar constraints using other kinds of datasets, including radial velocity (RV) data. Given the provided RV time series, both codes use the local power analysis (LPA) approach described by  Meunier et al. (2012)  to estimate, for each mass and separation in the grid, for what fraction of the generated orbital sets the signal generated by the companion would be compatible with the data.
Conclusion In this work we presented and analyzed five new observations from SPHERE (2018-2019) on the young Solar System analog HD 95086, as well as a re-analysis of the five previous SPHERE observations  (2015) (2016) (2017) , and the results from archival data from the GPI and NaCo instruments. We reported an in-depth characterization of the system HD 95086: 1. Regarding the exoplanet HD 95086 b, we extracted for the first time its spectrum in the J and H bands by combining six epochs imaged with SPHERE-IFS to maximize the signalto-noise ratio of the planet as it is hardly detectable in these bands. 2. We constrained the physical properties of HD 95086 b providing spectroscopic and photometric measurements in J, H, K1, K2, and L ′ bands from the SPHERE-IFS, GPI, SPHERE-IRDIS, and NaCo instruments.
Acknowledgements. We would like to thank  Kate Su  for sharing the ALMA continuum image used in Fig. 1 together with the SPHERE-IRDIS high-contrast image at K1-band. We acknowledge financial support from the  Programme National de Planétologie (PNP)  and the  Programme National de Physique Stellaire (PNPS)  of  CNRS-INSU. The project is supported by  CNRS , by the  Agence Nationale de la Recherche  ( ANR-14-CE33-0018 ). This work is partly based on data products produced at the SPHERE Data Center hosted at  OSUG/IPAG, Grenoble. SPHERE is an instrument designed and built by a consortium consisting of  IPAG (Grenoble, France ),  MPIA (Heidelberg, Germany) ,  LAM (Marseille, France), LESIA (Paris, France), Laboratoire Lagrange (Nice, France) ,  INAF -Osservatorio di Padova (Italy) ,  Observatoire de Genève (Switzerland) ,  ETH Zurich (Switzerland) ,  NOVA (Netherlands) ,  ONERA (France)  and  ASTRON (Netherlands)  in collaboration with  ESO.
SPHERE was funded by  ESO , with additional contributions from  CNRS (France) ,  MPIA (Germany) ,  INAF (Italy) ,  FINES (Switzerland)  and  NOVA (Netherlands). SPHERE also received funding from the  European Commission Sixth and Seventh Framework Programmes as part of the Optical Infrared Coordination Network for Astronomy (OPTICON)  under grant number  RII3-Ct-2004-001566  for  FP6  ( 2004-2008 ), grant number  226604  for FP7 (2009)(2010)(2011)(2012) and grant number  312430  for FP7 (2013)(2014)(2015)(2016). This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme (COBREX ; grant agreement n • 885593). V. C. acknowledges funding from the  Australian Research Council  via  DP180104235. A. V. and G.
, together with the Exoplanet Detection Map Calculator (Exo-DMC Bonavita 2020) 4. Both codes are the latest versions of the Multi-purpose Exoplanet C. Desgrange et al. : HD 95086 10 2 100% 20 100% 20 100% 99% 99% 99% Mass (MJup) 10 1 b 50% 68% 90% Mass (MJup) 5 10 15 50% 68% 90% Mass (MJup) 5 15 10 50% 68% 90% 10 0 10% 10% 10% 10 -1 10 0 10 1 10 2 0% 0 5 10 15 20 25 30 35 0% 0 5 10 15 20 25 30 35 0% Semi-major axis (au) Semi-major axis (au) Semi-major axis (au) A139, page 16 of 28 4 https://github. com/mbonav/Exo_DMC.
The data reduction was performed using the VAC-CINE software package  (Adams et al. 2011) , and these data were further flux calibrated using a bootstrapping method which compares each fiber response to a calibrated SDSS b-image of the galaxy (e. g. Joshi et al. 2019). Wavelength calibration was performed using lamp spectra obtained at the beginning of the observing run. (2010). This emission from warm molecular hydrogen highlights the North-South shocked ridge of the intra-group medium, as well as an extension towards NGC 7319, called "the bridge". The blue circles are the COS apertures (2. 5" in diameter) corresponding to 1. 1 kpc at a distance D = 94 Mpc. The positions, observing parameters and integration times are listed in Table  1.
g. Shull & McKee 1979; Dopita & Sutherland 1996; Lehmann et al. 2020). Due to collisional ionization of hydrogen, Lyα and Hβ photons are mostly produced in gas at temperatures smaller than T= 10 5 K, with collisional excitation dominating recombination for T> 10 4 K  (Raga et al. 2015). In the intra-group medium of SQ, it is likely that a wide distribution of shock velocities is present  (Guillard et al. 2009). In this paper we do not attempt at a detailed modelling of the line emission from shocks. We rather aim at qualita-tively determining which shocks contribute the most to the Lyα and Civ line emission. To do so, we use the results from the MAPPINGS V shock code library. The physics of the models is fully described in  Sutherland & Dopita (2017)  and the data in  Alarie & Morisset (2019).
ACKNOWLEDGMENTS PG thank the  Centre National d'Etudes Spatiales (CNES) , the  University Pierre and Marie Curie , and the  "Programme National de Cosmologie and Galaxies" (PNCG)  and the  "Physique Chimie du Milieu Interstellaire" (PCMI)  programs of  CNRS/INSU  for there financial supports. We thank  Daniel Kunth  and  Brigitte Rocca  for very useful physical and technical discussions about Lyα scattering. Support for Program number  HST-GO-13321. 001-Awas  provided by  NASA  through a grant from the  Space Telescope Science Institute , which is operated by the  Association of Universities for Research in Astronomy, Incorporated , under  NASA  contract  NAS5-26555. PA thanks  Guillermo Blanc  ( Carnegie Observatories ) and  Emily Freeland  (formerly  Texas A&M University)  for providing assistance with observations, and software/data reduction associated with the Mitchell Spectrograph.
As this U -R colour is related to stellar population age, this suggests there may also be an age-based effect in addition to dust. In this work, we build upon the model of BS21 to qualitatively investigate the relationships between host g alaxy mass, R V , g alaxy colour, and age, with the aim of explaining the residual U -R step observed by K22 by expanding upon the multiple SN Ia age populations modelled by  Nicolas et al. ( 2021 ). Most modern simulations of SN Ia data sets use the SuperNova Analysis ( SN AN A ;  Kessler et al. 2009  ) software which constructs an accurate representation of how a large sample of SNe would appear in a surv e y, at the image lev el, by passing synthesized light curves through telescope responses and surv e y cadences. In this analysis we build a simplified toy model of the DES-SN surv e y by approximating many of the complex steps involved in SN AN A , such as the light curve generation and fitting.
VA L I DAT I O N Before presenting the results, we describe the metrics used to validate the simulations introduced in Sections 2 and 3. We validate our model by comparing it to the DES5YR SN Ia data presented in K22. A set of qualitative and quantitative validations are outlined as follows. In the following sections, we define the chi-squared statistic on a histogram with both the data and simulation in equi v alent bins, χ 2 = i N data i -N sim i 2 e 2 i , (20) where N data i is the count of the observed data in the i th bin, N sim i is the equi v alent for the simulation, and e 2 i the error on the data approximated by N data i. While this estimate of the error does not take into account uncertainty on the measurements themselves, doing so would require a further level of resampling that would render the procedure computationally prohibitiv e.
Each model is compared to the Hubble residuals measured in the DES5YR data of K22 split by M * and U -R. A summary of the results of our simulations and comparison to the data is presented in Tables  3  and 4. Since SNe are simulated stochastically by sampling from a number of interlinked distributions and a numerical host galaxy library, an analytical e v aluation of the relationship between Hubble residual and c in the model is not possible. We thus compare the simulated and observed trends in a similar way to the one-dimensional parameter distributions (Section 4. 2 ). For each bin i in a host galaxy property X , we group simulated SNe in the same bins c j as used for the data. The reduced chi-squared is then χ 2 ν, μres = 1 N bins X i N bins j μ res , data ,i,j -μ res , sim ,i,j 2 e 2 i,j , ( 22 ) where μ res , data ,i,j and μ res , sim ,i,j are the weighted mean Hubble residuals in each host bin i and colour bin j for data and simulations, respectively, and e i , j is the standard error on the means of the data.
10  upper panels, Table  3  ), the fa v oured models ( χ 2 ν = 1. 94) include a similar difference in R V between old (1. 5) and young (2. 75) hosts and no intrinsic luminosity step is required. When splitting the data on U -R this model provides a significantly better match than the mass-R V -step model of BS21 (when implemented with no further luminosity step, i. e. Table  3. Dust population parameters for the models presented in this work when compared to DES5YR data split at host stellar mass log ( M * /M ) = 10 (left-hand panels of Figs 9 and 10. ) Y represents the host galaxy or SN property used to determine R V , while X is the property on which an intrinsic luminosity step (of magnitude γ X ; equation 6 ) is placed. Model Name BiasCor R V , 1 σ R V , 1 R V , 2 σ R V , 2 Y Y split Y 1 Y 2 X X split γ X χ 2 ν,μres ( M * ) BS21 1D 1.
C O N C L U S I O N S A N D F U T U R E W O R K This work presents a host-galaxy oriented framework for simulating populations of SNe Ia in a cosmological context. We trace stellar population ages throughout the build up of stellar mass of galaxies, and use this information combined with the SN Ia DTD from W21 in order to associate SNe to hosts at realistic rates. The resulting host galaxy library is made available to the community for use in future cosmological SN Ia simulations. 2 SNe are then simulated according to their host galaxy properties as highlighted below: (i) light-curve width x 1 is drawn from a two-population age-based model based on N21, which accurate reproduces the x 1 distribution. The x 1 versus stellar mass and x 1 versus U -R relations are also relatively well modelled, although the strength of the relation is stronger in the data than we reco v er in the model.
Additionally we find that: 2 https:// github. com/wisemanp/ des sn hosts/tree/main/simulations/data (i) if galaxy age is the driver of R V change, then the evolution is different to if it is driven by stellar mass. However the change (with mass) is opposite to that observed in the galaxy population, while the change with age is consistent with the difference between star forming and passive galaxies; (ii) when Hubble residuals are split based on host stellar mass, the R V models can fully explain the trends between Hubble residual and c ; (iii) when the data are split by host U -R , the addition of an intrinsic luminosity step to the model slightly impro v es the fit to the data. (iv) there is no preference for the intrinsic luminosity step to be based on stellar mass or SN age, but neither are able to simultaneously reproduce the data when split by host stellar mass and by host U -R.
AC K N OW L E D G E M E N T S We thank the referee  Mickael Rigault  for comments which significantly impro v ed this paper. P. W. acknowledges support from the  Science and Technology Facilities Council (STFC)  grant  ST/R000506/1. MS acknowledges support from  EU/FP7-ERC  grant  615929. LK thanks the  UKRI Future Leaders Fellowship  for support through the grant  MR/T01881X/1. LG acknowledges financial support from the  Spanish Ministerio de Ciencia e Innovaci ón (MCIN) , the  Agencia Estatal de Investigaci ón (AEI)   10. 13039/501100011033 , and the  European Social Fund (ESF)  ' Investing in your future ' under the  2019 Ram ón y Cajal program   RYC2019-027683-I  and the  PID2020-115253GA-I00   HOSTFLOWS  project, from  Centro Superior de Investigaciones Cient íficas (CSIC)  under the  PIE  project  20215AT016 , and the  program Unidad de Excelencia Mar ía de Maeztu   CEX2020-001058-M.
Based in part on observations at  Cerro Tololo Inter-American Observatory at NSF's NOIRLab (NOIRLab Prop. ID  2012B-0001 ; PI:  J. Frieman ), which is managed by the  Association of Universities for Research in Astronomy (AURA)  under a cooperative agreement with the  National Science Foundation. The DES data management system is supported by the  National Science Foundation  under Grant Numbers  AST-1138766  and  AST-1536171. The DES participants from Spanish institutions are partially supported by  MICINN  under grants  ESP2017-89838 ,  PGC2018-094773 ,  PGC2018-102021 ,  SEV-2016-0588 ,  SEV-2016-0597 , and  MDM-2015-0509 , some of which include ERDF funds from the  European Union. IFAE is partially funded by the  CERCA program  of the  Generalitat de Catalunya. Research leading to these results has received funding from the  European Research Council  under the European Union's  Se venth Frame work Program  (FP7/2007-2013) including  ERC  grant agreements  240672 ,  291329 , and  306478.
test()' in "psych" package in RStudio. All statistical analyses were performed using R v4. 0. 3 (R-core Team 2020) and a significance level of p < 0. 05 was used throughout, significances denoted as; (. = p < 0. 1, * = p < 0. 05, ** = p < 0. 01, and *** = p < 0. 001). All gene copy numbers are presented on a per gram of dry soil basis (Figs. 1, 2,  and 3 ).