dataesr/scientific-paragraphs-categorization huggingface dataset:
(2019) , except for the two GPI epochs measured by  Crepp et al. (2018) , which we replaced with our new measurements from Section 3. 2. We choose not to use the companion RV as measured by KPIC for this fit, because it does not appreciably improve our already well-constrained orbital solution. To fit the relative astrometry, radial velocity, and absolute astrometry from Gaia and Hipparcos together, we use the orvara package  (Brandt et al. 2021b) , which is designed to jointly fit these types of data and takes into account the Gaia and Hipparcos astrometry at the epoch astrometry level using htof  (Brandt et al. 2021a ). We use the priors listed in Table  4  of  Brandt et al. (2021b)  for the fitted parameters. The posterior is sampled using the parallel-tempering Markov Chain Monte Carlo sampler  (Vousden et al.
Gemini Planet Imager IFS The Gemini Planet Imager (GPI) observed HD 4747 B on UT 2015 December 24 and 25, in the K 1 (1. 90-2. 19 μm, R = 66) and H (1. 50-1. 80 μm, R = 46. 5) bands, respectively, and the data were published in  Crepp et al. (2018). After doing some fits to the published spectrum, we found that the average flux levels of the K 1 and H bands are inconsistent, and the error bars appear to be significantly overestimated. We therefore re-extracted the GPI spectrum using the pyKLIP package  (Wang et al. 2015) , which models a stellar PSF with Karhunen-Loève Image Processing (KLIP; also known as principal component analysis) following the framework in  Soummer et al. (2012)  and  Pueyo (2016). We tested various model choices to minimize the residuals after stellar PSF subtraction while preserving the companion signal.
In this section, we explore reasons why the data prefer disequilibrium chemistry in the atmosphere of HD 4747 B. The physical implications of our retrieved quench pressure, including an estimate of the vertical diffusion coefficient (K zz ), are discussed in Section 8. 2. To understand why the data prefer a deep quench pressure, we plot lines of constant log(CO/CH 4 ) volume-mixing ratios (VMRs) along with the best-fit P-T profile from our baseline HRS retrieval in Figure  7. We calculate CO/CH 4 from this quenched chemistry retrieval by finding the abundances of each molecule in the chemical grid, iterating over our posterior distribution of C/O, [C/H], and P-T profile. We find that CO/CH 4 = -+ 13. 6 4. 6 5. 8. If the atmosphere was in chemical equilibrium, we repeat our calculation and find that we would expect CO/CH 4 = -+ 1.
This confirms our initial intuition that the noise in the SPHERE and GPI images is likely dominated by correlated speckle noise based on visual inspection of the images. For the SPHERE data set, we estimate that the retrieved length scale is roughly equal to the number of steps that a speckle would move across the PSF for our brown dwarf's separation; indeed, we see speckles moving across the companion PSF in the reduced images. Overall, the SPHERE spectrum is less reliable than that from GPI because only four exposures are available, compared to the ∼40 exposures from GPI. Finally, the P-T profile retrieved from our baseline LRS retrieval shows a bimodal distribution (see Figure  6 ). The degeneracy seen here may be related to issues with the LRS (see Section 6. 3).
From the LRS retrievals, we consistently find a factor of ∼2-3 more CH 4 and H 2 O than observed in the HRS, implying that the LRS retrievals could be compensating for our imperfect cloud models by increasing the gas opacities. Using a more flexible cloud model might alleviate some of these issues. For example,  Burningham et al. (2021)  retrieved the 1-15 μm LRS of a field L dwarf and found the data preferred silicate clouds much higher up than the predicted cloud base locations from condensation curves. In addition, their retrieved cloud particles also have smaller sizes (submicron) than predicted by the EddySed model (a few microns). Similarly,  Luna & Morley (2021)  found that submicron cloud particles at lower pressures than predicted by EddySed are required to fit the mid-IR silicate feature (≈8-10 μm) of many L dwarfs.
9-2. 5 μm) helps distinguish between clouds and metallicity and provides better constraints on both. Thus, if we wish to obtain constraints on clouds and abundances at the same time, it would be important to extend our current HRS to a broader range of wavelengths. KPIC Phase II will allow us to obtain Lband data (≈3. 4-4. 1 μm) to complement existing K-band data  (Delorme et al. 2021) , and future upgrades could benefit from including the H and J bands as well. In this study, we have assumed that the atmosphere of HD 4747 B is globally uniform. However, it would be important to examine the impact of 3D effects, including nonuniform cloud coverage. Past studies with photometry or LRS show that many brown dwarfs exhibit clear rotational variability signals (e. g. ,  Apai et al. 2013; Biller et al.
AST-1611623. A. V. acknowledges funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program , grant agreement Nos. 757561 (HiRISE). H. A. K. acknowledges support from the  President 's and Director's  Research & Development Fund Program , which is jointly funded by the  Jet Propulsion Laboratory  and the  California Institute of Technology  under a contract with the  National Aeronautics and Space Administration. The computations presented here were conducted in the  Resnick High Performance Center , a facility supported by  Resnick Sustainability Institute at the California Institute of Technology. Facilities: Keck (KPIC). Software: petitRADTRANS (Mollière et al. 2019), dynesty (Speagle 2020), PyAstronomy (https://github. com/sczesla/PyAstronomy).
On the other hand, in very embedded, non-irradiated regions, the 14 N/ 15 N ratio should not change significantly, something that has been recently confirmed by observations with a linear resolution of ∼ 600 au (i. e. at core scales) obtained with the Atacama Large Millimeter Array (ALMA) of the protocluster OMC-2 FIR4, which have revealed negligible variations in the 14 N/ 15 N ratio in the embedded protocluster cores  (Fontani et al. (2020) ). However, N 2 H + is the only species investigated so far in 14 N/ 15 N at core scales, therefore more observational results are needed to shed light onto the 15 N fractionation process in cluster-forming environments. In order to better investigate this, we obtained observations of isotopologues of HCN towards OMC-2 FIR4 in order to provide the first high angular resolution comparison of the 14 N/ 15 N ratio between HCN and N 2 H + using interferometric data in one of the best analogues of the environment in which our SS was born.
Observations Our observations were obtained using the IRAM NOrthern Extended Millimeter Array (NOEMA) Interferometer as part of the Seeds Of Life In Space (SOLIS) Large Program  (Ceccarelli et al. (2017) ) with eight antennas on three days: April 29 and October 26, 2016 (both in C configuration) and January 16, 2017 (in A configuration). The phase centre was R. A. (J2000)=05 h 35 m 26 s 97, Dec. (J2000)=-05 • 09 56 8 and the local standard of rest velocity was set to 11. 4 km s -1. Baselines range from 20 to 760 m, providing an angular resolution of ∼ 4. 1 × 2. 2 (A+C configuration), corresponding to a linear scale of ∼ 860 au. The primary beam is ∼ 59. 3 at the representative frequency of 85 GHz. The system temperature, T sys , was typically in between ∼ 60 and ∼ 100 K in all tracks and the amount of precipitable water vapour was generally ≤ 5 mm.
The calibration of the bandpass and absolute flux scale was performed on 3C454. 3 and MWC349 (∼ 1. 05 Jy at 85. 0 GHz), while 0524+034 and 0539-057 were used for calibration of the gains in phase and amplitude. The lines were all observed with the Widex band correlator, providing a velocity resolution of 6. 9 km s -1. The continuum was imaged by averaging the line-free channels of the Widex and Narrow correlator units and subtracted from the spectrum in the (u,v)-domain. Calibration and imaging were performed using the CLIC and MAPPING softwares of the GILDAS 1 package using standard procedures. The continuum image was self-calibrated and the solutions were applied to the lines. In order to estimate the amount of flux that is filtered out by the interferometer, we compare our spectra of HCN isotopologues to the single-dish spectra of the same lines; we used publicly available IRAM 30m observations of OMC-2 FIR4 to achieve this  (Kahane et al.
The line at 86. 1GHz is SO (2 2 -1 1 ). For the purpose of comparison, we also utilised archival data consisting of N 2 H + (1 -0) emission along with emission of both of its 15 N isotopologues ( 15 NNH + (1 -0) and N 15 NH + (1 -0)) towards OMC-2 FIR4 (ALMA project 2016. 0. 00681. S PI: F. Fontani). These lines were observed using ALMA in Band 3 (3 mm) with a velocity resolution of 0. 2 km s -1 and a spatial resolution of about 600 au. Technical details of these observations (e. g. calibration, configurations used, weather conditions, sensitivity achieved) are given in  Fontani et al. (2020). In the same way as for the HCN observations, the effect of flux filtering is the same for all isotopologues of N 2 H + , meaning that the effect on the 14 N/ 15 N ratios is minimal. Table  1  shows the spectral parameters of the observed lines, including the parameters for the hyperfine (HF) components of N 2 H + and its isotopologues.
0 → 0 1 1 N 15 NH + 91. 2042615 1 1 → 0 1 3 4. 38 3. 44×10 -5 91. 2059911 1 2 → 0 1 5 91. 2085167 1 0 → 0 1 1 N 2 H + 93. 1716157 1 1 0 → 0 1 1 1 4. 47 3. 63×10 -5 93. 1719106 1 1 2 → 0 1 2 10 3. 60×10 -5 93. 1720477 1 1 1 → 0 1 0 9 3. 63×10 -5 93. 1734734 1 2 2 → 0 1 1 10 3. 63×10 -5 93. 1737699 1 2 3 → 0 1 2 7 3. 63×10 -5 93. 1739640 1 2 1 → 0 1 1 9 3. 63×10 -5 93. 1762595 1 0 1 → 0 1 2 9 3. 63×10 -5 ( As stated above, we extracted spectra of N 2 H + , 15 NNH + and N 15 NH + (1 -0), observed with ALMA, from the dataset published in  Fontani et al. (2020). The analysis of these spectra will allow us to compare, for the first time at high angular resolution, the 14 N/ 15 N ratio simultaneously in HCN and N 2 H + (i. e. the two molecules in which nitrogen fractionation should behave in an opposite way) if both are regulated by selective photodissociation.
Extraction of the spectra and analysis Using the MAPPING package of GILDAS (see Sect. 3), the spectra were extracted in flux density units (Jy) from the five regions illustrated in Fig. 4 , which have been labelled depending on the position of the peak with respect to the phase centre, as: north-west (NW), north-east (NE), south (S), east (E) and FIR3. Due to the complexity of the emission and the partial overlap of some sub-structures, we decomposed the average emission map of H 13 CN by eye into the polygons shown in Fig. 4 , which do not overlap and pick up the intensity peak of each sub-region. The CLASS package of GILDAS was employed to convert our spectra into temperature units (K) before they were imported into CASSIS 2. As can be seen in Fig. A. 1, the lines of H 13 CN and HC 15 N show generally a Gaussian shape; hence, each line was fitted with a single Gaussian in CASSIS using Levenberg-Marquardt (L-M) fitting.
The fit provides several line parameters, among which is the full width at half maximum (FWHM), which was then used as one of the input parameters for local thermal equilibrium (LTE) analysis using CASSIS. In order to check our LTE assumption, which is satisfied if the H 2 density is larger than the critical density of the analysed transition, we computed the critical density of each of our lines from the equation: n CRIT = A ul C ul. (1) In Eq 1, n CRIT represents the critical density (cm -3 ) while A ul (s -1 ) represents the Einstein coefficient and C ul (cm -3 s -1 ) represents the collisional coefficient. We use collisional coefficients taken from the CASSIS collision database and calculated by  Hernandez-Vera et al. (2014)  for HCN and by  Daniel et al. (2005)  and  Lique (2015)  for N 2 H +.
Eqs. 3 (and 2), which can be found in the Formalism for the CASSIS software 3 (author: C. Vastel), describe how to compute the total column density (and opacity) from our spectroscopic and observational parameters under the conditions of LTE and optically thin lines. We justify our use of the optically thin assumption in Sects. 4. 2 and 4. 3 for HCN and N 2 H + , respectively.
CLASS Due to the aforementioned presence of HFS, we first used the specific HFS fitting routine that is provided within CLASS to model our spectra. This routine requires the following inputs for each isotopologue: relative intensity, r i (with sum normalised to 1) and velocity separation from the reference component (computed from the Doppler law based on the frequency differences obtained in the lab), v i (km s -1 ) for each HF component. Both inputs were in this case obtained from the Cologne Molecular Database for Spectroscopy (CDMS) for each isotopologue. If we define the central velocity of the ith component as v 0,i =v i +p 2 , then we can calculate the opacity of our lines, τ, using Eq. 4: τ(ν) = p 4 Σ N i=1 r i e -4ln2( v-v i -p 2 p 3 ) 2. ( 4 ) In this equation, τ represents the opacity as a function of frequency (ν), N represents the number of HF components, r i is the relative intensity of the ith HF component and v i is the velocity separation of the ith HF component from the reference component, (km s -1 ).
2 km s -1 ) and rms is 10. 1 mK for 15 NNH + , 10. 3 mK for N 15 NH + and 31 mK for N 2 H +. From fitting our spectra using L-M fitting in CASSIS, FWHM is obtained as 0. 8 km s -1. It should be noted that the values for W obtained using the method described previously are given in K km s -1 ; therefore, for Eq. 5, these are converted to K cm s -1 as everything else is in cgs units. All spectroscopic parameters used in Eq. 5 are taken from the CDMS database. The CMB temperature (T bg ) is assumed to be 2. 73 K. For the excitation temperature (T ex ), we cannot constrain this using our analysis alone because, despite resolving the HFS in our spectra, the opacity of the N 2 H + spectra is not well constrained and the 15 N-isotopologue lines are optically thin (see Table  2 ). Therefore, we must take our values from previous measurements.
CASSIS Within CASSIS, there is a Python library (LineAnalysisScripting. py) that allows users to create Jython scripts to model sources in LTE using the Markov chain Monte Carlo (MCMC) method. As part of the script, we define a number of parameters that will be varied and give upper and lower limits for the variation range. In most cases, we have sufficient S/Ns to vary four parameters: N T OT , T ex , FWHM and V LS R. From L-M fitting, we know the order of magnitude for N T OT in each case as well as the FWHM for all of the components (∼0. 8 km s -1 ). Therefore, N T OT is varied between 10 10 cm -2 and 10 15 cm -2 for the 15 N isotopologues and between 10 12 cm -2 and 10 15 cm -2 for the main isotopologue. From this we also vary FWHM between 0. 3 km s -1 and 1. 2 km s -1 in each case. For T ex , once again we use previous research of this source to determine our upper and lower limits: 50 K and 30 K, respectively (5 K above and below the upper and lower limits used to model the spectra and calculate N T OT from the CLASS method).
For these cases, we also constrain the V LS R , fixing this parameter to the value obtained in the corresponding position in the main isotopologue. In all cases, the script is run and the model is compared to the observations. The values obtained with the two methods are the same within error bars except for the cases with higher opacity (i. e. NW Region) or with low S/N (i. e. E Region in both 15 N isotopologues and S Region in N 15 NH + ). For the latter, the fit obtained using MCMC with the aforementioned limits was not optimal and underestimated N T OT with respect to the observations, causing overestimations of the 14 N/ 15 N ratio. Therefore, we concluded that these three spectra had insufficient S/N to be analysed using MCMC; therefore, to analyse these data, first we fitted a single Gaussian to the strongest HF component using L-M fitting in the relevant spectrum (see Table  2 ) to obtain a value of V LS R for spectrum.
Results Fig. 5 : Visual comparison of the 14 N/ 15 N ratios obtained for HCN and N 2 H + in the regions of OMC-2 FIR4, from both CASSIS and CLASS (in the latter case) and as calculated from the different 15 N isotopologues (also in the latter case). Figure  5  shows a visual comparison between all of the 14 N/ 15 N ratios obtained during the course of our analysis, while Fig. 6  shows how the 14 N/ 15 N ratios from our dataset and that described in  Fontani et al. (2020)  vary across the regions defined in each paper across OMC-2 FIR4. We now explore the results of our analysis of both the HCN and N 2 H + datasets in detail.
Conclusions In this work, within the framework of the Large Program SO-LIS, we have mapped the H 13 CN (1 -0) and HC 15 N (1 -0) lines towards the protocluster OMC-2 FIR4 with the NOEMA interferometer. We have also analysed archival data obtained with the ALMA interferometer of the 1-0 lines of N 2 H + and both its 15 N isotopologues. For the first time, we compare at high angular resolution the 14 N/ 15 N isotopic ratios in HCN and N 2 H + , two important N-bearing species that are expected to possibly behave differently in the enrichment or depletion of 15 N. The results can be summarised as follows: 1. H 13 CN (1 -0) and HC 15 N (1 -0) show spatial similarities in their emission, with H 13 CN showing systematically stronger emission across all regions of the source. There are obvious peaks to both the H 13 CN (1-0) and HC 15 N (1-0) emission in the north-west, north-east and (to a lesser extent in HC 15 N) south of the central area of emission, plus a peak farther to the east in an outer region that appears in H 13 CN only.
Acknowledgements This project has received funding from (i) the  European Union   Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No  811312  for the Project " Astro-Chemical Origins , (ACO) and (ii) the  European Research Council (ERC)  under the  European Union   Horizon 2020 research and innovation programme , for the Project "The  Dawn of Organic Chemistry" (DOC) , grant agreement No  741002. This paper makes use of the following ALMA data: ADS/JAO. ALMA# 2016. 0. 00681. S. ALMA is a partnership of  ESO  (representing its member states),  NSF (USA)  and  NINS (Japan) , together with  NRC (Canada) ,  MOST  and  ASIAA (Taiwan)  and  KASI (Republic of Korea) , in cooperation with the  Republic of Chile. The Joint ALMA Observatory is operated by  ESO ,  AUI/NRAO  and  NAOJ.
Code We use RAMSES-RT  (Rosdahl et al. 2013; Rosdahl & Teyssier 2015) , which is an RHD version of the adaptive mesh refinement code RAMSES  (Teyssier 2002). RAMSES-RT adopts the HLLC  (Toro et al. 1994 ) and the particle-mesh method  (Guillet & Teyssier 2011)  to solve the Euler equations and the Poisson equations, respectively. The RAMSES-RT version used herein includes a modified photochemistry model for tracing the formation and destruction of molecular hydrogen  (Katz et al. 2017; Kimm et al. 2017) , as well as the nonequilibrium chemistry and cooling of six chemical species: H I, H II, He I, He II, He III, and e -  (Rosdahl et al. 2013; Rosdahl & Teyssier 2015). Atomic metal cooling at T  10 4 K is computed using the CLOUDY cooling model  (Ferland et al. 1998) , whereas fine-structure line cooling at T  10 4 K is computed using the cooling model of  Rosen & Bregman (1995).
1997). To compute ϒ i,j (T) for the Hα photon emission from electron collisional excitation of H I, we use the CHIANTI database  (Del Zanna et al. 2021, version 10) , which provides the scaled effective electron collision strength based on the rules formulated by  Burgess & Tully (1992). We compute the collisional emission under a case B approximation for collisions up to energy level 5  (Dere et al. 2019). In practice, the collisional emissivity of Hα can be approximated as a function of temperature (H. Katz et al. 2022 , in preparation): T T 6. 01 10 exp 8. 13 10 erg cm s.  ⎜ ⎟ ⎛ ⎝ ⎞ ⎠ ( ) = ´- á - - Note that we neglect the collisional Hα emission from a cell if its net cooling timescale is less than three times the local simulation time step to avoid spurious emission from cells where the cooling time is underresolved.
The authors would like to thank the anonymous referee for their constructive review of this manuscript. The authors also thank  Ming Sun  for helpful comments on the comparison of X-ray luminosities. J. L. is supported by the  National Research Foundation of Korea  (grant No. NRF-2021R1C1C2011626 ). T. K. is supported by the  National Research Foundation of Korea  (grant No. NRF-2020R1C1C1007079 ) and acted as the corresponding author. Y. -K. S. acknowledges support from the  National Research Foundation of Korea (NRF)  grant funded by the  Ministry of Science and ICT  (grant No. NRF-2019R1C1C1010279 ). The supercomputing time for numerical simulations was kindly provided by  KISTI  (grant No. KSC-2020-CRE-0278 ), and large data transfer was supported by  KREONET , which is managed and operated by  KISTI.
This work is supported by the  Center for Advanced Computation  at  Korea Institute for Advanced Study. This work was also performed using the DiRAC Data Intensive service at Leicester, operated by the  University of Leicester IT Services , which forms part of the  STFC DiRAC HPC Facility  (www. dirac. ac. uk). The equipment was funded by  BEIS  capital funding via STFC capital grants  ST/K000373/1  and  ST/ R002363/1  and  STFC DiRAC Operations  grant  ST/R001014/ 1. DiRAC is part of the  National e-Infrastructure.
The sample was heated up to facilitate the removal of the solvent; indeed, the presence of residual solvent molecules in the crystal may quench the thermal SCO transition. The absence of dichloromethane molecules was further confirmed investigating the Cl2p XPS region where any signals was not detected (Figure  S1d ). XPS measurements were performed using a micro-focused, monochromatic Al K α radiation source (1486. 6 eV, model SPECS XR-MS Focus 600) and a multichannel-detector electron analyzer (model SPECS Phoibos 150 1DLD) with a pass energy of 40 eV to ensure appropriate resolution. The spectra were measured in normal emission, with the X-ray source mounted at 54. 44 • from the analyser. The binding energy was calibrated using the C1s peak at 284. 5 eV. Spectra were deconvoluted using CasaXPS software, introducing mixed Gaussian and Lorentzian contributions for each component.
Its calculation requires the wavelength λ ≈ 847 nm of the transitions X 2 Σ(v = 1, J , N ) → A 2 Π 3/2 (v = 0, J ), the natural width of the excited state Γ ≈ 2π × 3. 32 MHz  [24]  and α, a coefficient accounting for the Q-branch transitions. More precisely, α = q 01 × HL where q 01 ≈ 0. 036 is the Franck-Condon factor between v = 0 and v = 1 calculated from the Morse potentials of the A and X states thanks to the parameters found in  [25]  and HL ≈ 0. 27 is an averaged value of the Hönl-London coefficients for the Q-branch A-X transitions that we calculated with the PGOPHER software  [26]. This allows us to estimate B ν e ≈ 1. 1 × 10 19 m 3 Hz (J -1 s -1 ). The mean spectral intensity Īν is obtained by dividing the mean light intensity Ī by the TA typical spectral width (4. 3 cm -1 ). The averaged intensity seen by the molecules is given by Ī = 4P {1exp[-D 2 /(2w 2 )]}/(πD 2 ) where w ≈ 3 mm is the beam waist and D = 2.