dataesr/scientific-paragraphs-categorization huggingface dataset:
For the D + /D 0 ratios, which show a flat trend as a function of p T , the fit to a constant was used in the determination of the central value of the D + yield, while for the D * + /D 0 ratio the fit with a constant plus a logarithmic function was used. The systematic uncertainty due to the extrapolation was estimated by evaluating the yields using the other fit function and the shape of the SHMc predictions with normalisation parameter left free. The   [37]. The right panels show the ratios in central Pb-Pb collisions compared to the predictions from the statistical hadronisation model (SHMc)  [67, 68]  with a core-corona approach and the FastReso package  [69]  for resonance decays. Statistical (bars) and systematic (boxes) uncertainties are shown. difference between the central value and the yields obtained with other functions for the extrapolation was assigned as systematic uncertainty and summed in quadrature to the uncertainty on the D 0 yield in the aforementioned p T interval.
Conclusions We have reported the measurement of the p T -differential production yields of prompt D 0 , D + , and D * + mesons and charge conjugates at midrapidity (|y| < 0. 5) in central and semicentral Pb-Pb collisions at a centre-of-mass energy per nucleon pair √ s NN = 5. 02 TeV. The results were obtained with the data sample collected at the end of 2018 with the ALICE detector. The p T -spectra were measured in finer p T intervals with respect to the previous measurements at the same centre-of-mass energy  [30] , providing a more precise description of the p T distribution. The large data sample allowed for the first measurement of the D 0 -meson yield down to p T = 0 in Pb-Pb collisions at the LHC. This enabled the determination of the p T -integrated production yields of prompt D 0 , which is obtained in a model independent way, of prompt D + and D * + , and the comparison with predictions from the statistical hadronisation model  [67, 68].
Acknowledgements The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the  Worldwide LHC Computing Grid  (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the  ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL) ,  State Committee of Science and World Federation of Scientists  (WFS), Armenia;  Austrian Academy of Sciences, Austrian Science Fund (FWF) : [M  2467-N36 ] and National-.
Lens Modeling In this section, we introduce the GIGA-Lens 14  modeling framework. In the initial stages of the development of our pipeline, lenstronomy served as a helpful guide, specifically, in its approach of using optimization to find a region of high posterior density from which the MC sampler can be initialized. We believe that our framework represents a significant improvement on the lenstronomy modeling pipeline in terms of speed, optimization, and sampling. Our entire framework is implementated in both TensorFlow  (Abadi et al. 2015)  and JAX  (Bradbury et al. 2018). Complete integration with either of these libraries confers significant advantages. It enables seamless execution of our code on graphics processing units (GPUs), which can achieve much faster gravitational lens simulation and modeling.
, under  NASA  contract  NAS 5-26555. S. H. S. thanks the  Max Planck Society  for support through the  Max Planck Research Group. E. J. acknowledges funding from  Excellence Initiative of Aix-Marseille University  -A * MIDEX, a  French "Investissements d'Avenir" program  ( AMX-19-IET-008-IPhU ). Y. S. acknowledges support from the  Max Planck Society  and the  Alexander von Humboldt Foundation  in the framework of the  Max Planck-Humboldt Research Award  endowed by the  Federal Ministry of Education and Research. This research used resources of the  National Energy Research Scientific Computing Center , a  DOE Office of Science User Facility  supported by the  Office of Science of the U. S. Department of Energy  under contract No. DE-AC02-05CH11231  using  NERSC  award  HEP-ERCAP0021270. Software: TensorFlow (Abadi et al.
Our flux density measurements of (324) Bamberga and (13) Egeria roughly agree with predictions, while our measurements of (22) Kalliope suggest lower flux, corresponding to effective emissivities of 0. 64 ± 0. 11 at 2. 0 and < 0. 47 at 3. 2 mm. We predict the asteroids detectable in other SPT data sets and find good agreement with detections of (772) Tanete and (1093) Freda in recent data from the SPT-3G camera, which has ∼10× the mapping speed of SPTpol. This work is the first focused analysis of asteroids in data from CMB surveys, and it demonstrates we can repurpose historic and future data sets for asteroid studies. Future SPT measurements can help constrain the distribution of surface properties over a larger asteroid population.
Instruments like ALMA can track celestial targets for a short time with high sensitivity, but these instruments are generally facilities that require proposals for use. These facilities receive many observation requests, so studying asteroids comes at a high opportunity cost. However, astronomers can incur no opportunity cost if they repurpose data from other types of observations that happen to include asteroids. Sky surveys at millimeter wavelengths fill this niche and are made frequently using telescopes designed to study the cosmic microwave background (CMB). In this paper, we show that we can use data from the South Pole Telescope (SPT) to detect asteroids at high signal-to-noise ratios (S/N) at millimeter wavelengths when we average maps of the sky centered on known asteroid locations.
By showing this, we demonstrate that historic and future data from CMB experiments can be repurposed for observing asteroids. In Section 2, we describe the SPT and the cameras from which the data in this paper are taken, the specific observations used in this work, and the data processing used in making the single-observation maps used in the asteroid search. In Section 3, we explain the asteroid selection criteria in historic data. In Section 4, we describe how we search for the selected asteroids in our observations. In Section 5, we show the detection of three large asteroids-(324) Bamberga, (13) Egeria, and (22) Kalliope-with the SPTpol camera at 2 mm (150 GHz), as well as (324) Bamberga at 3. 2 mm (95 GHz). In Section 6, we discuss these results. In Section 7, we suggest prospects for continuing this analysis on other data sets.
We conclude in Section 8. Although the Planck Collaboration has previously published detections of asteroids in their analysis connecting dust observations to asteroid families  (Cremonese et al. 2002; Planck Collaboration et al. 2014 ) and the Atacama Cosmology Telescope (ACT) collaboration masked asteroids in their search for Planet 9  (Naess et al. 2021) , this work represents the first focused analysis of asteroid flux in data from an experiment designed to measure the CMB. With continued analysis, historic and future data measuring the CMB can provide more observations of asteroids at submillimeter and millimeter wavelengths. In particular, scientists can make these measurements using a wealth of data provided by current experiments, such as those on SPT and ACT, as well as upcoming experiments like the Simons Observatory and CMB-S4  (Kosowsky 2003; Abazajian et al.
Instruments, Observations, Data Processing The primary results in this work use observations from the SPTpol camera on the SPT, with some proof-of-concept results from the currently installed SPT-3G camera. We provide a brief description of the telescope and both cameras, the method of data collection-particularly as it pertains to the sensitivity to moving objects-and the standard data analysis through the mapmaking step. We describe the post-map processing specific to asteroid detection and characterization in Section 4.
0 mm and 50-60 μK-arcmin at 3. 2 mm, corresponding to 1σ point-source sensitivities of roughly 2 and 3 mJy at 2. 0 and 3. 2 mm, respectively. In Section 7, we perform a rough validation of predictions for asteroid yield in other surveys using 2020 data from the main SPT-3G science field, a 1500 deg 2 field centered at R. A. 0 h , decl. -56°(a superset of the SPTpol main science field). In 2020 this field was observed from March through November, with an effective cadence of 1-2 days (the full field is split into four subfields, two of which are observed during a given refrigerator cycle-see  Guns et al. (2021)  for details).
Calibration Relative gains across the detector array and between observations are measured using regular observations of the Galactic H II region RCW38 and regular observations of an internal thermal calibration source. As in  Bleem et al. (2020) , the absolute calibration of the map was derived by comparing the full-season co-added maps with the Planck map of the same field. The SPT-ECS fields were taken at significantly higher levels of atmospheric loading compared to other SPTpol survey data, and the resulting larger change in detector loading with elevation necessitated a further calibration step beyond a constant normalization factor for 3. 2 mm data. Although noise in SPTpol data does not in general depend strongly on airmass, the 3. 2 mm data required this additional calibration step as the calibration was empirically found to vary significantly with elevation within a field (which is equivalent to decl.
for observations from the South Pole). This trend is fit well as a linear function of decl. , and  Bleem et al. (2020)  used the Planck data to fit for and correct this variation across the fields. Because in this work we aim to measure asteroid flux density on an observation-to-observation basis, we also compare individual observations with Planck data. We find that the single-observation calibration varies significantly less than the noise on the measurement of any asteroid in a single observation, and we ignore this as a source of uncertainty in subsequent analysis. We also repeat the B20 comparison of the full-depth SPTpol maps with Planck data and make small (∼5% level) corrections to the B20 absolute calibration. The comparison to Planck yields a calibration at angular scales where the CMB temperature anisotropy is strongest (roughly degree scales), and transferring this to a flux density scale requires accurate knowledge of the beam and filtering.
The NEATM has become the standard model for thermal asteroid analysis following its wide use by the NEOWISE Collaboration  (Mainzer et al. 2011). To identify asteroids present in those fields, we compiled a list of potentially visible objects. First, we queried the JPL Small-body Database (SBD) Search Engine (Giorgini 2020) to generate a list of all small bodies with reported values of effective spherical diameter D, perihelion distance q, and minimum orbit intersection distance (MOID). Next, we estimated the maximum possible flux density of each of those objects with the STM. We considered maximum possible flux by assuming values of 1 for emissivity and 0 for albedo, and using q as solar distance and MOID as Earth distance for optimal viewing geometry. We adopted the standard empirical assumption of 0.
756 for the model's beaming parameter. Finally, we eliminated all asteroids for which the maximum possible flux fell below 0. 5 mJy, which would correspond to roughly a 2σ fluctuation at the projected depth of the main SPT-3G field after 5 yr of observing. However, we maintained all comets and near-Earth objects as potentially interesting objects regardless of the maximum possible flux. This resulted in a list of 5885 objects of interest. After compiling a list of viable observation candidates, we identified those that were within our observation fields during our observation periods. We did so using astroquery, a set of Python tools developed by  Ginsburg et al. (2019)  to request data from online astronomical databases and web services. First, we queried JPL HORIZONS Web-Interface  (Giorgini et al.
5% to the co-added map. This bias would be much larger for asteroids moving at angular speeds much slower than the size of one SPTpol beam between observations, or roughly 29″ hr -1. In this work we analyze asteroids moving quickly enough that this bias is not concerning, with (324) Bamberga moving the slowest at an average angular speed of ∼20″ hr -1. Because our goal is to detect asteroids, the differenced maps are the primary form of data that we analyze in this work. To enhance the sensitivity of the asteroid search, we choose to look at the locations of known asteroids, which requires precisely knowing those locations. Some asteroids can move across the sky at angular speeds such that the change in their position over an hour is comparable to the SPT beam size. Since each observation lasts roughly 2 hr, we must more precisely define what time we scan over any asteroid.
We then adopt external constraints on the rotational period of the asteroids and attempt to detect the modulation effect in folded light curves. We assume rotational periods based on published observations at other wavelengths reported by the Minor Planet Center's Asteroid Lightcurve Database (LCDB)  (Warner et al. 2009). We assume that (324) Bamberga rotates with a rotational period of 29. 43 hr, (13) Egeria with a rotational period of 7. 045 hr, and (22) Kalliope with a rotational period of 4. 1483 hr. We fold the light curve on the rotational periods and show the resulting phased light curves in Figure  6. None of these light curves modulate enough at 2. 0 mm to detect within our sensitivity, and we use that fact to set limits on maximum possible modulation amplitude, which we list in Table  1.
Furthermore, it is even clearer that rotational effects cannot solely explain (22) Kalliope's lower effective emissivity when its spin axis orientation is considered. The Database of Asteroid Models from Inversion Techniques (DAMIT) 54  is a database of three-dimensional models for many asteroids, including (22) Kalliope (Sidorin & Kaasalainen, M 2010). (22) Kalliope's proposed shape models suggest a spin axis with an ecliptic latitude of 3°and ecliptic longitude of 196°  (Kaasalainen et al. 2002; Ďurech et al. 2011; Hanuš et al. 2017; Vernazza et al. 2021). This low ecliptic latitude means (22) Kalliope has a large axial tilt relative to its orbital axis. Given our viewing geometry, (22) Kalliope's subsolar point and rotational north pole are both near each other and visible to the observer.
Predicted Asteroid Detections for Other SPT Surveys As described in Section 2. 1, the SPT has been equipped with three separate cameras over its lifetime: SPT-SZ, SPTpol, and SPT-3G. With SPT-SZ, observations were made of a patchwork of many fields to comprise its survey. With SPTpol and SPT-3G, observations were made of main, deep fields during austral winters and various other fields for shorter durations during austral summers. We refer to all observations made to date collectively as the SPT's historic data, while we refer to future observations planned with the SPT-3G camera as the SPT's future data. Using the methods described in Section 3, we compile lists of all asteroids present in historic and future data and predict their S/N. We show all objects we expect to observe in Figure  7  and summarize these predictions in Table  2.
Validation of Prediction Model with SPT-3G 1500d Data As shown in Appendix B, we should see two asteroids at high S/N in the SPT-3G main survey field during the 2020 austral winter. Since maps were generated following each observation of the SPT-3G survey field as part of an online data-quality monitoring pipeline, it was straightforward to extract thumbnail maps around the locations of the asteroids using methods similar to those in Section 4. We constructed a proof-of-concept pipeline for SPT-3G, and although the pipeline was separate, it was similar in construction and methodology to the pipeline used for the detections in SPTpol data. We report the mean fluxes and S/Ns for the two asteroids with predicted S/N > 5 at 2. 0 mm in the 1500 deg 2 survey region during the austral winter 2020.
Conclusion In this work, we have demonstrated that we are able to detect asteroids in millimeter observations of the sky made with the SPT, and we show that we will detect even more asteroids in other historic and future data from the SPT. Using maps from repeated observations of the same area of the sky over the course of months, we measure three asteroids, (324) Bamberga, (13) Egeria, and (  22 ) Kalliope, at wavelengths of 3. 2 and 2. 0 mm with the SPTpol camera, and we report measurements of the asteroids' mean fluxes at 2. 0 mm with an S/N of 11. 2, 10. 5, and 6. 1, respectively. We also report measurements of (324) Bamberga at 3. 2 mm with an S/N of 4. 1. Although others have studied asteroid thermal emission at mm wavelengths, this work is the first focused analysis of asteroid flux using data taken with the primary science goal of characterizing the CMB.
Observing asteroids with CMB survey data expands the breadth of two separate fields of astronomy. CMB survey scientists can now include asteroid science as part of their data analysis, and they have more scientific use for their historic data. They may perform more focused studies of asteroids in the future, potentially including near-Earth asteroids that pass through survey fields. Meanwhile, asteroid scientists now have access to more data on the thermal emission of asteroids. They can make use of measurements in mm wavelengths made using CMB experiments, especially as the instantaneous sensitivity of CMB cameras improves and allows more precise time-domain astronomy. Our measurements in millimeter wavelengths come at an important time for asteroid scientists, when studies like  Keihm et al.
With historic and future data, we expect to observe 34 total asteroids, including very precise measurements of (2) Pallas and (344) Desiderata; multiple measurements of (31) Euphrosyne, (154) Bertha, (326) Tamara, (705) Erminia, and (772) Tanete; and measurements of (617) Patroclus, a target of NASA's Lucy mission  (Levison et al. 2021). Using data from SPTpol, we made significant measurements of (13) Egeria and (22) Kalliope at only one wavelength, and we did not have high enough sensitivity in individual observations to describe light curves to high accuracy. However, SPT-3G will improve on both of these limitations with its higher sensitivity and third wavelength band, as shown by the detections of (772) Tanete and (1093) Freda. SPT-3G's higher sensitivity will also allow us to observe fainter objects than with SPTpol.
In fact, SPT-3G and other future CMB surveys may have to mask asteroids during transient source analysis, since as of the writing of this paper, objects like (344) Desiderata are bright enough to trigger the SPT-3G transient alert system. Furthermore, many of the asteroids detectable with SPT-3G will be observed for longer periods of time than those with SPT-SZ or SPTpol. The longer observation times and higher instantaneous sensitivity of SPT-3G will allow us to place tighter constraints on modulation amplitude for those asteroids, and potentially to detect modulations of more than a few percent. With SPT-3G sensitivity, we will be able to observe more asteroids at more wavelengths, and, for many of them, over longer times. By repurposing historic and future data from the SPT, we will observe asteroids without needing to dedicate telescope observation time to do so.
ple of six common objects with the Cluster Lensing And Supernova survey with Hubble (CLASH) lensing data. For the LPSZ clusters we have at our disposal both high-angular resolution observations of the thermal SZ with NIKA and NIKA2 and X-ray observations with XMM-Newton from which hydrostatic mass estimates can be derived. In addition, the CLASH dataset includes lensing convergence maps that can be converted into lensing estimates of the total mass of the cluster. One-dimensional mass profiles are used to derive integrated mass estimates accounting for systematic effects (data processing, modeling, etc. ). Two-dimensional analysis of the maps can reveal substructures in the cluster and, therefore, inform us about the dynamical state of each system. Moreover, we are able to study the hydrostatic mass to lensing mass bias, across different morphology and a range of redshift clusters to give more insight on the hydrostatic mass bias.
2001) , and magnetic field measurements sampled at 22 Hz from the fluxgate magnetometer  (Balogh et al. 2001 ) are used to check the stationarity of the solar wind. The Cluster data repository also provides the power density spectra measured by STAFF with the Search Coil sensors (SC) from 0. 5 to 9 Hz and with the Spectrum Analyzer (SA) from 8 to 4 kHz. Cluster search-coil measurements are severely affected by instrumental noise above 400 Hz  (Alexandrova et al. 2012). Finally, electron plasma measurements obtained from the Plasma Electron And Current Experiment instrument  (Johnstone et al. 1997 ) are used.
The tests are run with computer control of thermal actuator signals and deflections are measured using a high-speed camera operating at up to 200,000 frames per second. Further details are given in Reference 61. Figure  2b   (small 1/F N ). As F N decreases, the behavior transitions to steady sliding. If instead F N is held constant but v T increases, the behavior again transitions from stick-slip to steady sliding. Values of measured rate-and-state parameters from five different types of tests are combined as input to perturbation theory  62  to derive the solid and dashed lines seen in Figure  2b. They predict the transition from stick-slip to steady sliding behavior for k T = 10 and 100 N/m. The modeled lines are independently verified by direct testing. That is, the data markers in Figure  2b  indicate observed experimental values of v T and F N at which these transitions occur, either through decreasing F N or increasing v T.
Acknowledgements This work has partly been carried out at the  Advanced Research Center for Nanolithography , a public-private partnership of the  University of Amsterdam , the  Vrije Universiteit Amsterdam , the  Dutch Research Council (NWO)  and the semiconductor equipment manufacturer ASML. This work was supported by  LABEX MANUTECH-SISE  ( ANR-10-LABX-0075 ) of  Université de Lyon , within the  program Investissements d'Avenir  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR). JS is indebted to  Institut Carnot Ingénierie@Lyon  for support and funding. MdB acknowledges funding from the  U. S. National Science Foundation Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP HI) Program  under Grant  CMMI-1854702. AD research was supported by  NSF  ( DMR-2208464 ).
XPCT image analysis Ring artifacts were removed using an in-house tool implemented by the company NOVITOM (France; https://www. novitom. com/en/) [19]. Samples were isolated from the background (air, glass tube and ethanol) and rotated within the AMIRA 3D software (release 2021. 1, Thermo Fisher Scientific, USA). Aβ plaques were segmented semi-automatically using a random forest algorithm from the IPSDK software (Reactiv'IP, France; https: //www. reactivip. com/). The generated masks were screened for false positive segmentations and ∼ 20 plaques were selected, along with ROIs of the background. Signal intensity measurements -as a ratio of the mean intensities of the plaques and the mean intensities of the background ROIs -were retrieved with MorphoLibJ  [37] , an ImageJ plugin.