dataesr/scientific-paragraphs-categorization huggingface dataset:
g. , van der Marel & Franx 1993), provided a better fit than an "optically thick Gaussian" to the CO emission. However, the Gauss-Hermite expansion failed to describe the data as well as the "optically thick Gaussian," in addition to requiring an additional free parameter. A straightforward minimization of χ 2 was achieved with the curve_fit routine in scipy  (Virtanen et al. 2020)  to yield an initial fit to the data. Although fast, this approach often found local minima in the χ 2 surface resulting in moment maps with a large variance over small spatial ranges. Instead, an MCMC sampling approach, implemented with the emcee package (Foreman-Mackey et al. 2013), was found to be more forgiving in such cases. Taking the median of the posterior distributions as the "best-fit" parameter produced far more spatially coherent maps.
For each map, we consider two models: pure Keplerian rotation, v kep , requiring five free parameters, Θ kep ; and pressure support rotation, v prs , requiring eight free parameters, Θ prs. We model the posterior distributions through eddy, which wraps the emcee MCMC sampling package  (Foreman-Mackey et al. 2013). Only regions between 0 4 (roughly twice the beam FWHM) and out to 3 75 for CO and 3 5 for CS, were fit, where the inner boundary was to chosen to avoid effects from beam smearing, while the outer boundary removed regions with low-S/N measurements of v 0. The cubes were spatially downsampled such that only spatially independent pixels were considered. One hundred and twenty-eight walkers were initialized in a cluster around previous literature values; they were then given 5000 steps to burn in and an additional 5000 steps to sample the posterior distribution.
In particular, these more conservative constraints remain consistent with high dust fractions in early QGs. We find that these measurements are very sensitive to the adopted extraction method and conversion factors: the use of an extended light model to fit the FIR emission increases the flux of detections by up to 50% and the upper limit by up to a factor 6. Adding the FIR-to-dust conversion, this amounts to an order of magnitude difference in dust fraction, casting doubts on the power of these data to discriminate between star formation quenching scenarios. Unless these are identified by other means, mapping the dust and gas in high-redshift QGs will continue to require somewhat costly observations.
Sample and data The REQUIEM-ALMA sample (W21) consists of six QGs at z = 1. 5-3. 2 observed under programs 2018. 1. 00276 (PI: K. E. Whitaker) and 2019. 1. 00227 (PI: J. Tan) with the Atacama Large Millimeter/Submillimeter Array (ALMA) at 1. 3 mm, corresponding to the ALMA Band 6 and 300-500 µm rest frame. We obtained the raw data from the ALMA Science Archive and processed them to produce calibrated visibility sets, which were then split and binned in both time and channels, and finally exported as a single continuum UVFITS table per QG with Gildas 1. All six QGs are strongly lensed by intermediateredshift (z = 0. 3-0. 8) massive galaxy clusters, with two creating giant arc images. Due to the nature of the lenses, they benefit from optical-near-infrared (NIR) imaging by the Hubble (HST) and Spitzer space telescopes, accumulated over the years under a variety of observing programs and publicly available in their respective archives.
Analysis Based on two point-like detections, W21 concluded that the 1. 3 mm emission from dust was confined to compact, unresolved regions of the QGs. These correspond, spatially, to their cores (the central kiloparsec, in the case of the most extended, MRG-0138), which are also the brightest regions of the galaxies in stellar light. More recently, the QG MRG-2129 was followed up on with ALMA at very high resolution by  Morishita et al. (2022) , who similarly concluded that the emission is compact and localized. However, this new observation consists of a single pointing with a maximum recoverable scale of ∼0. 6 , or half the beam width of the data used in W21. Therefore, if conversely the distribution of dust includes an overall continuous component following the stellar one, the emission from lower-surface brightness regions could very well be either below the noise level of the data or missed entirely by the instrument.
As a test, we examined resolved, integral field spectroscopy of two of the most extended galaxies in the sample, MRG-0138 and MRG-1341 (see Appendix B). Within the wavelength range of the spectra, we found no appreciable difference between the bright central regions of these galaxies and their extended outer regions, which would for example suggest that one contains a larger fraction of younger stars than the former. For each galaxy, we first constructed a model of their stellar distribution from the longest-wavelength high-resolution data available, namely the HST Wide Field Camera 3 (WFC3) F160W imaging, corresponding to the rest-frame optical range. Cutouts centered on the QGs were extracted from the F160W images and the light of nearby objects was modeled and subtracted using Galfit  (Peng et al.
Acknowledgements. G. B. C. acknowledges the  Max Planck Society  for financial support through the  Max Planck Research Group  for  S. H. Suyu  and the academic support from the  German Centre for Cosmological Lensing. This paper makes use of the following ALMA data:  ADS/JAO ALMA2018. 1. 00276. S and  2019. 1. 00227. 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.
Therefore, in this paper we present a frequentist inspired likelihood analysis for the GTHDM, simultaneously including the FCCC observables, both b → sµ + µ -transitions and the muon anomalous magnetic moment, along with other flavour observables. We perform a global fit of all constraints using the inference package GAMBIT, the Global And Modular Beyond-the-Standard-Model Inference Tool  [94, 95]. GAMBIT is a powerful software framework capable of performing statistical inference studies using constraints from collider  [96] , dark matter  [97] , flavour  [98]  and neutrino  [99]  physics, as well as cosmology  [100]. It has already been used for detailed statistical analyses of a variety of beyond the Standard Model (BSM) models, including supersymmetry  [101] [102] [103] , scalar singlet DM  [104] [105] [106] [107] [108] , axion and axion-like particles  [109, 110] , and neutrinos  [99, 111] , as well as an initial analysis of the 2HDM  [112].
Our work enhances the FlavBit  [98]  and PrecisionBit  [113]  modules of GAMBIT to support the GTHDM. We also make use of various external codes: SuperIso 4. 1  [114] [115] [116] [117]  for computing flavour observables, the 2HDMC 1. 8 package  [118]  for precision electroweak constraints, the HEPLike package  [119]  which provides likelihoods for the neutral anomaly related observables, and the differential evolution sampler Diver 1. 0. 4 [120]. The paper is organised as follows. In section 2 we present the Higgs and Yukawa sectors along the theoretical bounds for their parameters. In section 3 we define the effective Hamiltonian and the Wilson coefficients (WCs) for b → sµ + µ -transitions. Then, in section 4 we list the observables to be used in our scans. Following this, our results from the global fit and predictions for future experiments in colliders are discussed in section 5.
7) where a ± = 3 2 (λ 1 + λ 2 ) ± 9 4 (λ 1 -λ 2 ) 2 + (2λ 3 + λ 4 ) 2 , (2. 8) b ± = 1 2 (λ 1 + λ 2 ) ± 1 2 , (λ 1 -λ 2 ) 2 + 4λ 2 4 , (2. 9 ) c ± = 1 2 (λ 1 + λ 2 ) ± 1 2 (λ 1 -λ 2 ) 2 + 4λ 2 5 , (2. 10 ) d ± = λ 3 + 2λ 4 ± 3λ 5 , (2. 11 ) e ± = λ 3 ± λ 5 , (2. 12 ) f ± = λ 3 ± λ 4. (2. 13) Following  [71, 125]  we also include the oblique parameters S, T and U , which parametrise radiative corrections to electroweak gauge boson propagators. In this study we computed these oblique parameters with the 2HDMC package and these are contrasted with the most probable values inferred from experimental data, as found by the Gfitter group  [129]  S = 0. 05 ± 0. 11, T = 0. 09 ± 0. 13, U = 0. 01 ± 0. 11, with correlations given by Σ =    1. 0 0. 9 -0. 59 0. 9 1. 0 -0. 83 -0. 59 -0. 83 1. 0   .
We also note that neither the SM or the GTHDM can explain the central values (with larger uncertainties) from the ATLAS 2018 data. As for the measured branching ratios of B 0 → K 0 * µ + µ -and B + → K + µ + µ -, in figure  12  we show the SM and GTHDM predictions using the LHCb results  [190] [191] [192] , where we can see again how the GTHDM fits better the data compared to the SM, specially in the region above the open charm threshold, sensitive to both C ( ) 9 and C ( )  10. In contrast, the performance of the model is worse than the SM (figure  13  left) in the low recoil region of the differential branching ratio dBR dq 2 (Λ b → Λµ + µ -) when comparing to the LHCb 2015  [193]  data. As pointed out in  [65] , the decays of the Λ b baryon, such as Λ b → Λµ + µ - have much larger uncertainties than those of the corresponding meson decays.
The next interesting results are related with the charged anomalies, in particular we find that the R(D ( * ) ) ratio can (can not) be explained at the 1σ level with the GTHDM, a result in agreement with the phenomenological analysis of  [132]. We furthermore corroborate that ) theoretical ratios compared to both the LHCb  [151, 153]  and Belle data  [198, 199]. the constraint coming from the B c lifetime makes it very difficult to fit R(D * ) and R(D) simultaneously. In figure  15  we show the preferred values by the profile likelihood. We see a slightly better performance of the GTHDM compared to the SM with respect to the HFLAV average. Regarding the dΓ(B → D ( ) τ ν)/(Γdq 2 ) distributions measured by BaBar  [169] , we find that the GTHDM prediction is indistinguishable from the SM, in agreement with  [16].
C. S. thanks Ulrik Egede for useful comments on the future sensitivity of the HL-LHC, and  Peter Stangl  for discussions about correlations in FCNC observables. F. M. thanks  Grégoire Uhlrich  for his help in cross-checking the Wilson coefficients with MARTY. The work of C. S. was supported by the  Monash Graduate Scholarship (MGS)  and the  Monash International Tuition Scholarship  (MITS). T. E. G. is supported by  DFG Emmy Noether  Grant No. KA 4662/1-1. The research placement of D. J. for this work was supported by the  Australian Government Research Training Program (RTP) Scholarship  and the  Deutscher Akademischer Austauschdienst (DAAD)   One-Year Research Grant. The work of P. A. was supported by the  Australian Research Council   Future Fellowship grant   FT160100274. The work of P.
A. , C. B. and T. E. G. was also supported with the  Australian Research Council Discovery Project  grant  DP180102209. The work of C. B. was supported by the  Australian Research Council  through the  ARC Centre of Excellence for Particle Physics at the Terascale   CE110001104. This project was also undertaken with the assistance of resources and services from the  National Computational Infrastructure , which is supported by the  Australian Government. We thank  Astronomy Australia Limited  for financial support of computing resources, and the  Astronomy Supercomputer Time Allocation Committee  for its generous grant of computing time.
g. , HD 189733 b  (Grillmair et al. 2007; Todorov et al. 2014 ), HD 209458 b (Zellem et al. 2014) , HD 219134 b and c  (Gillon et al. 2017b ), TRAPPIST-1 b through h  (Ducrot et al. 2018; Morris et al. 2018; Zhang et al. 2018; Ducrot et al. 2020), and WASP-26 b (Mahtani et al. 2013). To collect more data on the planetary object detected by TESS, Spitzer Directors Discretionary Time observations were proposed and awarded (PID 14214 and 14241) in the final year of operations for observations of AU Mic with the Infrared Array Camera (IRAC;  Fazio et al. 2004)   03:40:07-12:33:36 UT). The first two observations were originally considered to be eclipses from the initially assumed orbital period for AU Mic b from the TESS mission Cycle 1 observations. However, these observations detected additional transits of AU Mic b, establishing a true period to be half as long as originally thought  (Plavchan et al.
5 μm, as this channel has a lower systematics due to the intrapixel sensitivity. The coordinates were adjusted for the high parallax and proper motion of AU Mic for the proposed observation dates. Each observation set consisted of a 30 minute prestare dither pattern, an 8 hr stare, and a 10 minute poststare dither pattern. All data were calibrated by the Spitzer pipeline S19. 2 and can be accessed using the Spitzer Heritage Archive. 47  For each of the three transit observations discussed here, the following data reduction steps were performed on each AU Mic stellar image measured on 0. 1 s intervals. We used the IDL routine box_centroider 48  supplied by the Spitzer Science Center to measure the location of AU Mic on the pixel. We  then performed aperture photometry on each image using the IDL Astronomy Users Library routine aper 49  with a fixed aperture of 2.
3 from the target. Martioli et al. (2020)  implemented the reduction pipeline APERO (N. J. Cook et al. 2022, in preparation)  to reduce and process the SPIRou data and calculate the cross-correlation functions (CCFs). Next, the "M2_weighted_RV_-5. mas" line mask was applied to the spectra, and the lines were masked if their telluric absorption was deeper than 40%. The line mask then underwent further refinement by removing lines not present in AU Mic's Stokes I spectrum using the technique from  Moutou et al. (2020). The CCFs were calculated from each spectral order and summed to achieve greater precision; then, the RVs were measured from the CCF by using the velocity shift's least-squares fit. The iSHELL RVs were extracted using the pychell pipeline and yielded consistent RVs and precision with the SPIRou RVs  (Cale et al.
P. P. P. acknowledges support from  NASA   (Exoplanet Research Program  award No. 80NSSC20K0251 ,  TESS Cycle 3 Guest Investigator Program  award No. 80NSSC21K0349 ,  JPL Research and Technology Development, and Keck Observatory Data Analysis) , the  NSF  (Astronomy and Astrophysics grant Nos. 1716202  and  2006517 ), and the  Mt. Cuba Astronomical Foundation. D. D. acknowledges support from the  TESS Guest Investigator Program  grant No. 80NSSC21K0108  and  NASA   Exoplanet Research Program  grant No. 18-2XRP18_2-0136. E. G. acknowledges support from  NASA   Exoplanet Research Program  award No. 80NSSC20K0251. The material is based upon work supported by  NASA  under award No. 80GSFC21M0002. L. D. V. acknowledges funding support from the  Heising-Simons Astrophysics Postdoctoral Launch Program  through a grant to  Vanderbilt University.
This work makes use of observations from the  Las Cumbres Observatory  global telescope network. Part of the LCOGT telescope time was granted by  NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by  NSF. This research has made use of the PEST photometry pipeline 63 by  Thiam-Guan Tan. This research has made use of the  NASA Exoplanet Archive  and the Exoplanet Follow-up Observation Program website, both of which are operated by the  California Institute of Technology , under contract with the  National Aeronautics and Space Administration  under the  Exoplanet Exploration Program. This research has made use of the SIMBAD database, operated at  CDS, Strasbourg, France. This research has made use of  NASA's Astrophysics Data System Bibliographic Services. This research has made use of an online calculator that converts a list of  Barycentric Julian Dates in Barycentric Dynamical Time (BJD_TDB)  to JD in UT (Eastman et al.
A public Feynman and post-Newtonian code The entire framework presented here was also put into a fully open automated computation tool, "EFTofPNG", that is approachable and encouraging engagement within the community  14. The comprehensive and self-contained "EFTofPNG" code can be found in the public repository in https://github. com/miche-levi/ pncbc-eftofpng, where the current version handles the point mass sector, and all the spin sectors up to the state of the art. The design of the code is modular, see Fig. 1 , so that various units of the code could be efficiently used and developed independently for different purposes in various generic contexts in physics. In particular, since the Mathematica code builds on the "xTensor" package for efficient computer tensor algebra, the treatment of Wick contractions is made significantly more efficient, compared to other common Feynman codes, by considering n-point functions as tensors of rank n.
Acknowledgments I am grateful to  John Joseph Carrasco  for his pleasant and significant support. I would like to thank  Luc Blanchet , who chaired the session, and invited me to present the EFTs of PN theory with spins. I would like to especially acknowledge my collaborator on this line of research,  Jan Steinhoff , who also created with me the "EFTofPNG" code. It is with great pleasure that I extend my gratitude to  Donato Bini  for the warm hospitality throughout the MG15 meeting. My work is supported by the  European Research Council  under the European Union's  Horizon 2020 Framework Programme   FP8/2014-2020 , "preQFT" grant no. 639729 , " Strategic Predictions for Quantum Field Theories " project.
STM measurement The STM and STS measurements were performed under ultrahigh vacuum (pressure ≤10 -11 mbar) and liquid helium temperature with an Omicron low-temperature STM. The etched tungsten wires were used as the STM tip. The constant-height dI=dV spectroscopy was acquired by turning off the feedback loop and using the standard lock-in techniques (f ¼ 991. 7 Hz, V ampl ¼ 4 mV). The constant-current dI=dV spectroscopy was acquired by leaving on the feedback loop. The tip-sample distance Z changed to keep the constant tunneling current. The tip was calibrated on Ag (111) before measurements on the samples. STM or STS data were analyzed using SPIP 6. 7. 3 and MATLAB.
ACKNOWLEDGMENTS B. W. and J. X. acknowledge financial support from the  Ministry of Science and Technology of China  ( 2017YFA0305400 ) and the  Strategic Priority Research Program of Chinese Academy of Sciences  ( XDA18010000 ), and experimental support from the  Soft Nano Fabrication Center at ShanghaiTech. D. P. and S. H. thank the  China Scholarship Council  for support. Y. L. acknowledges the support from the  National Natural Science Foundation of China  (No. 12104304 ) and  China Postdoctoral Science Foundation  (No. 2021M692131 ). H. W. acknowledges the support from the  National Natural Science Foundation of China  (No. 2018YFA-0305700 , No. XDB33000000 , No. 11925408 , and No. 12188101 ). Z. Z. , L. A. , and N. W. thank the  National Key R&D Program of China  ( 2020YFA0309600 ) and the  Hong Kong Research Grants Council  (Project No.
16303720 ) for support. D. P. is thankful for the useful discussion with  Niels B. M. Schröter. The micro-ARPES research in SOLEIL is under Proposal No. 20210047. The research leading to micro-ARPES results in Elettra under Proposal No. 20195301 has been supported by the project  CALIPSOþ  under Grant Agreement No. 730872  from the  EU Framework Program for Research and Innovation HORIZON 2020. Preliminary ARPES experiments were performed at nano-ARPES branch of BL07U end station, SSRF. The computational resource is provided by the  Platform for Data-Driven Computational Materials Discovery in Songshan Lake material Laboratory.
Acknowledgments The work performed at LPC2E is supported by CNES APR. The Scientific colour map "lajolla"  (Crameri, 2021)  is used in this study to prevent visual distortion of the data and exclusion of readers with colour-vision deficiencies  (Crameri et al. , 2020). We acknowledge the use of the WHAMP software  Roennmark (1982)  for the validation of the model. We benefited from the computing resources provided by CaSciModOT. This work was granted access to the HPC/AI resources of TGCC under the allocation 2021-A0100412428 made by GENCI. L. B. was supported by funds from Région Centre Val de Loire (France).
Experimental discharges Neon seeding was studied during the recent C38 experimental campaign at JET. A scan was performed, from discharge #96132 to #96139, with decreasing neon puffing. The analysis in this paper will consider the two extremes, unseeded discharge #96139 and high seeding #96133, both in deuterium. Average Z eff was ∼ 1. 4 and ∼ 1. 8 respectively. The details are presented in table  1. The experiments were performed at high triangularity and ITER-relevant, vertical target divertor configuration. The electron density n e , T e , T i and the toroidal rotation ω were extracted and fitted using the Gaussian process regression tools available at JET  [32]. The experimental data were fitted on the 12. 5-13 s and 14-14. 5 s time intervals for the unseeded and the seeded cases respectively.
Modelling settings The integrated modelling is performed using the JETTO transport solver, within the JINTRAC  [38, 39]  suite of codes. While JINTRAC has the capability of modelling both edge and core, only the latter was evolved. Within JINTRAC this is handled by JETTO, which is a 1. 5 dimensions transport solver. The Faraday's equation for the time evolution of the plasma current, the electron and total-ion energy equations and the individual ion mass-continuity and total ion toroidal momentum equations are solved. A number of modules calculating sources, sinks and transport are called with various frequencies, maximizing the speed and maintaining the accuracy. The relevant modules are mentioned below. In this work, the current profile j, T e , T i , and n e , are predicted self consistently.
GENE From the analysis presented above, the importance of Qua-LiKiz being able to correctly predict the impurity transport is evident. This section will focus on the effect of the rotation on the impurity profiles, since as shown in figure  6 , section 3, it was found to be a strong actuator. Other phenomena not captured in QuaLiKiz can impact the impurity transport, as for example finite β effects  [57]  and fast ions  [58] , but since they are not expected to be relevant in this case such effects will not be included in this work. The QuaLiKiz predictions are compared with the output from the higher fidelity gyrokinetic code GENE. Only the linear physics is validated and direct comparison to nonlinear simulations, is left for future work. For simplicity, only Neon impurities are considered.
Unfortunately, such methodology proved not to be suitable at nominal rotation. Within the scope of code comparison between GENE and QuaLiKiz, the predicted transport coefficients were compared at lower E × B shear. The E × B shear was therefore reduced by a factor 4 with respect to the experimental value. The differences in the prediction of growthrates and transport coefficient ratios between GENE and QuaLiKiz at reduced shear can be observed comparing the green and blue lines in figure  10. A 4% reduction of the input R/L T i passed to QuaLiKiz was sufficient to obtain similar growthrates. Since this had little to no effect on the neon transport coefficients ratios, the simulations with the same drive are shown for brevity. Some differences between the two models are evident. At larger k θ ρ s , QuaLiKiz is stabilised faster than GENE.
Acknowledgments This work has been carried out within the framework of the  EUROfusion Consortium  and has received funding from the  Euratom research  and training programme  2014-2018  and  2019-2020  under Grant Agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. A previous version of this paper appeared in the thesis of the first author  M Marin , published in September 2021 with the title Integrated modelling of multiple-ion tokamak discharges. ORCID iDs J. Citrin  https://orcid. org/0000-0001-8007-5501 C. Bourdelle  https://orcid. org/0000-0002-4096-8978 L. Garzotti  https://orcid. org/ 0000-0002-3796-9814  A. Ho  https://orcid. org/ 0000-0001-5107-3531.