dataesr/scientific-paragraphs-categorization huggingface dataset:
2015). Objects without a known diameter were not rejected from the set, but the diameter of these objects was instead estimated as described in Sect. 3. No selection was performed based on the spin period of the primary. While theoretical models  (Walsh et al. 2008; Jacobson & Scheeres 2011)  suggest that these systems are formed through rapid rotation, the spin of the primary may have been reduced because of loss of angular momentum during the formation of the secondary, or through decelerating YORP effects  (Pravec et al. 2010). Furthermore, easily accessible datasets of spin periods are typically incomplete, and while early reviews of binary systems and binary candidates  (Pravec et al. 2006 ) listed typical spin periods of NEA binary systems ranging from 2. 2 to 2. 8 h, with outliers trailing to 4h, current observations show a much broader range  (Warner et al.
Acknowledgement. We thank  CNES  for supporting  K. Minker  in her internship during her Masters of astrophysics (MAUCA: http://mauca. oca. eu). This research used the VO TOPCAT software (Taylor 2005). The properties of Solar System Object are from the service SsODNet. ssoCard of the  Service des éphémérides de l'IMCCE  through its Solar System Portal (https://ssp. imcce. fr). We thank all the developers and maintainers of resources for the community.
Cosmic ray flux An analytic expression for the cosmic neutron spectrum at sea level is presented by Gordon et al. in Ref. [55] , deduced by fitting data from a set of measurements for energies above 0. 4 MeV; with this parameterization, the integral flux from 10 MeV to 10 GeV is 3. 6×10 - 3  cm - 2  s - 1  (for New York City). In Ref. [56] , a similar parameterization is provided as well as correction factors,  , to the flux when considering exposure at different locations, as flux depends on the altitude and geomagnetic rigidity. For example, outside LNGS at an altitude of ∼1000 m, a correction factor  = 2. 1  [18]  is used. Alternatively, the EXPACS (''EXcel-based Program for calculating Atmospheric Cosmic-ray Spectrum'') program 1 could be used to calculate fluxes of nucleons, muons, and other particles for different positions and times in the Earth's atmosphere; in this way, possible temporal variations of the cosmic rays fluxes are taken into account.
Production cross sections Measurements at fixed energies and calculations using different computational codes must be both be taken into account in evaluating (). The following have been used in this work: • The Experimental Nuclear Reaction Data database (EXFOR, CSISRS in US)  [57] , which provides nuclear reaction data and then measured production cross sections. 2 • The Silberberg and Tsao equations presented in Refs. [58] [59] [60] , which are semiempirical formulae derived from proton-induced reactions for energies >100 MeV and integrated in different codes: COSMO  [61] , YIELDX  [60]  and ACTIVIA  [62]. • The MC simulation of the interaction between projectiles and nuclei, which allows also computation of production cross sections. Many different models and codes have been developed and validated considering the relevant processes.
Acknowledgments This report is based upon work supported by  FSC   2014-2020 -Patto per lo Sviluppo ,  Regione Sardegna , Italy, the  U. S. National Science Foundation (NSF)  (Grants No. PHY-0919363 , No. PHY-1004054 , No. PHY-1004072 , No. PHY-1242585 , No. PHY-1314483 , No. PHY-1314507 , associated collaborative grants, No. PHY-1211308 , No. PHY-1314501 , and No. PHY-1455351 , as well as  Major Research Instrumentation Grant  No. MRI-1429544 ), the  Italian Istituto Nazionale di Fisica Nucleare  (Grants from  Italian Ministero dell'Istruzione, Università , e Ricerca Progetto Premiale 2013 and  Commissione Scientific Nazionale II) , the  Natural Sciences and Engineering Research Council of Canada , SNOLAB, and the  Arthur B. McDonald Canadian Astroparticle Physics Research Institute. We acknowledge the financial support by  LabEx UnivEarthS  ( ANR-10-LABX-0023  and  ANR18-IDEX-0001 ), the  São Paulo Research Foundation  (Grant  FAPESP-2017/26238-4 ),  Chinese Academy of Sciences  ( 113111KYSB20210030 ) and  National Natural Science Foundation of China  ( 12020101004 ).
The authors were also supported by the  Spanish Ministry of Science and Innovation (MICINN)  through the grant  PID2019-109374GBI00 , the  ''Atraccion de Talento '' Grant  2018-T2/ TIC-10494 , the  Polish NCN , Grant No. UMO-2019/ 33/ B/ ST2/ 02884 , the  Polish Ministry of Science and Higher Education ,  MNi-SW , grant number  6811/IA/SP/2018 , the  International Research Agenda Programme AstroCeNT , Grant No. MAB-/2018/7 , funded by the  Foundation for Polish Science  from the  European Regional Development Fund , the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No  952480  (DarkWave), the  Science and Technology Facilities Council , part of the  United Kingdom Research and Innovation , and  The Royal Society  ( United Kingdom ), and  IN2P3-COPIN consortium  (Grant No.
II. METHODS In this paper we examine extended cosmological models that include interactions between DM and neutrinos to determine the constraints that can be obtained from the latest Cosmic Microwave Background (CMB) and large-scale structure probes. To this end, we make use of the publicly available code COBAYA  [44]. The code explores the posterior distributions of a given parameter space using the Monte Carlo Markov Chain (MCMC) sampler developed for CosmoMC  [45]  and tailored for parameter spaces with speed hierarchy implementing the "fast dragging" procedure detailed in Ref. [46]. To compute the theoretical model and introduce the possibility of interactions between neutrinos and DM, we exploit a modified versions of the Cosmic Linear Anisotropy Solving System code, CLASS  [47]. 1 We treat neutrinos as massless and ultra-relativistic in the early universe.
In both cases, we begin by setting the effective number of ultra-relativistic particles at recombination (N eff ) to its reference value of 1 A publicly available version of this modified CLASS can be found at https://github. com/MarkMos/CLASS_nu-DM , see also Refs. [48, 49]. N eff = 3. 044  [50] [51] [52]. We then allow N eff to be an additional free parameter of the sample, enabling us to relax this requirement and explore a wider range of possibilities. The prior distributions for all the sampled parameters involved in our analysis are chosen to be uniform along the range of variation provided in Table  I , with the only exception of the optical depth at reionization (τ ) for which the prior distribution is chosen accordingly to the CMB datasets. The convergence of the chains obtained with this procedure is tested using the Gelman-Rubin criterion  [53]  and we choose a threshold for chain convergence of R -1 ≲ 0.
02. Concerning CMB and large-scale structure probes, our baseline data sets consist of: • The full Planck 2018 temperature and polarization likelihood  [54] [55] [56] , in combination with the Planck 2018 lensing likelihood  [57] , constructed from measurements of the power spectrum of the lensing potential. We refer to this dataset as "Planck". • The full Atacama Cosmology Telescope temperature and polarization DR4 likelihood  [58] , assuming a conservative Gaussian prior on τ = 0. 065 ± 0. 015. We refer to this dataset as "ACT". • The full Atacama Cosmology Telescope temperature and polarization DR4 likelihood  [58] , in combination with the Planck 2018 TT TE EE likelihood  [54] [55] [56]  in the multipole range 2 ≤ ℓ ≤ 650. We refer to this dataset as "ACT+Planck". • The Baryon Acoustic Oscillations (BAO) and Redshift Space Distortions (RSD) measurements from BOSS DR12  [59].
We refer to this dataset as "BAO". Finally, to conduct a model comparison, we calculate the Bayesian evidence of each model and then estimate the corresponding Bayes factors ln Bij using the publicly available package MCEvidence  [60, 61] , 2 that has been suitably modified to be compatible with COBAYA. In particular, for the case with N eff fixed to N eff = 3. 044, we calculate ln Bij as the difference between the evidence for ΛCDM and the interacting νDM cosmology (ln Bij = ln Z LCDM -ln Z νDM ). When instead N eff is allowed to vary, we compute ln Bij as the difference between the evidence for ΛCDM+N eff and the respective interacting scenario (ln Bij = ln Z LCDM+Neff -ln Z νDM+Neff ). Within this convention, negative ln Bij values indicate a preference for an interacting dark sector, while positive values indicate a preference for ΛCDM or ΛCDM+N eff.
In particular, we find log 10 u νDM = -5. 20 +1. 2 -0. 74 at 68% CL, with a definite distribution of the minimum of the χ2 around this peak, as we can see in Figure  3 , that is not disfavored by a Bayesian model comparison. It is important to notice here that this value of the coupling favored by the full combination is not in disagreement with the Planck data, as we can see in the top panel of Figure  2 , as in the Planck multipole range this model is indistinguishable from the ΛCDM scenario (see also the discussion in Ref. [43] ). However, unfortunately, also this ACT+Planck+BAO dataset combination is not powerful enough to bound the interaction with a stronger statistical evidence, and this could certainly be a goal for future experiments. We will describe the phenomenological implications of having a νDM coupling different from zero in section IV.
In a second step, we consider N eff free to vary and report the constraints on the cosmological parameters at 68% (and 95% CL) in Table  III  for the temperature independent νDM cross-section case. The reason behind the variation of the effective number of relativistic degrees of freedom at recombination, different from the expected N eff = 3. 044, is that we can expect a contribution to this parameter for the interaction between DM and neutrinos. However, as we can easily see in Table  III  and Figure  4 , this is not the case for all the combinations of datasets explored in this work. Indeed, the constraints on N eff obtained in this scenario are the same obtained assuming a model without coupling between DM and neutrinos, i. e. a ΛCDM+N eff model. This happens because N eff is very strongly constrained by the CMB data, and the preferred mean value is slightly below the expected 3.
044. However, interestingly, all the features regarding the re- sults on the coupling in Table  II  are still valid in this one parameter extension. In particular, we find only an upper limit for log 10 u νDM from Planck and Planck+BAO, while we have the same 1σ indication for a non-vanishing νDM coupling by ACT as well as by its combination with BAO and the low-multipoles Planck data. We therefore obtain for the full dataset combination ACT+Planck+BAO data log 10 u νDM = -5. 29 +1. 3  -0. 81 at 68% CL (log 10 u νDM < -4. 21 at 95% CL). In the latter case the Bayes Factor weakly favors the interacting model against the model without interaction. In conclusion, a non-zero coupling between DM and neutrinos has a very robust 1σ indication coming from the ACT CMB data (alone and in combination with Planck and BAO) and it is also favored by a Bayesian model comparison.
V. CONCLUSIONS In a recent study  [43] , we have pointed out that precise measurements of CMB anisotropies on small angular scales (i. e. , large multipoles l ≳ 3000) can provide crucial insights into neutrino DM interactions. Specifically, we have demonstrated that accurate measurements with a few per cent uncertainty on those scales can yield a significant amount of information, whereas detecting these interactions on larger angular scales (such as those probed by the Planck experiment) would require substantially greater sensitivity. Interestingly, although the most recent observations of the cosmic microwave background released by the Planck satellite do not provide any concrete evidence in support of the aforementioned models, the analysis of smallscale CMB data from the Atacama Cosmology Telescope shows a preference for a non-zero interaction strength, underscoring the significance of current, forthcoming and future high-multipole measurements to constrain better such scenarios.
In order to validate further the robustness of these findings, in this work we have presented an extended and comprehensive analysis of νDM interactions in the cosmic microwave background, conducting a significant number of additional tests. First and foremost, we have shown that our results remain robust when combining observations from the two most accurate CMB experiments to date (Planck and ACT), both including and excluding astrophysical measurements of Baryon Acoustic Oscillations and Redshift Space Distortions. In presence of the small-scale CMB measurements provided by ACT, all of these combinations of independent datasets confirm the same preference for a non-zero interaction strength, see also Table  II. Secondly, we have proved that the same preference is found by both fixing the effective number of relativistic particles to the Standard Model value of N eff = 3.
2 +1. 8 -1. 1 at 1σ. However, also in this case, we find only an upper limit at 95% CL. The results are stable under the inclusion of the BAO measurements. Interestingly, once we include in the analysis the Planck data up to multipoles ℓ = 650, and we study the combination ACT+Planck+BAO (last column of Table IV) the 1σ indication for a νDM coupling is slightly strengthened, but this dataset combination is not powerful enough to bound the νDM coupling with a stronger statistical evidence. In particular we find log 10 u νDM = -14. 9 +1. 5 -0. 63 at 68% CL. Also in this case, as a further step, we consider N eff free to vary, and we report in Table V the constraints on the cosmological parameters at 68% (and 95% CL) for the T 2 νDM cross-section case. However, as already happened for the temperature independent cross section case, the constraints on N eff obtained in this scenario are the same as those obtained assuming a non-interacting model, and all the features regarding the coupling in Table IV remain valid also in this extended scenario.
Therefore, we find only an upper limit for log 10 u νDM from Planck and Planck+BAO, and 1σ indication for a DM-ν coupling different from zero for ACT, ACT + BAO, and ACT + BAO + the low-multipoles Planck data. In particular, we find for the full dataset combination ACT+Planck+BAO data log 10 u νDM = -15. 1 +1. 7 -0. 90 at 68% CL. To conclude, when the full ACT+Planck+BAO dataset combination is considered, this interacting model fits the cosmological data as well as the standard ΛCDM scenario, and the two models are indistinguishable from a model comparison point of view, as we can deduce with the Bayes Factor in the last row of Table  IV  and Table V. However, in general, the effects on the CMB anisotropies predicted by a the temperature dependent case are smaller, so that such the preference for a nonzero νDM interaction is somewhat mitigated with respect to the temperature-independent case (see also Appendix B where the correlation between cosmological parameters is shown for all the cases under study in this work).
Observations and methods We used spectroscopic observations obtained at the solar telescope THEMIS dating from July 18 to July 22, 2022, in the FeI 630. 15 nm line. We performed a data reduction following  Wöhl et al. (2002). We also used HINODE Solar Optical Telescope (SOT) spectropolarimetric (SP) data from the irradiance program, HOP79, performed on July 21, 2022. With THEMIS, we scanned 40 × 108 quiet solar regions at different positions along the west-east central axis with the spectrograph slit oriented along the west-east direction, and along the south-north polar axis with the slit oriented along the south-north direction. The slit width was 0. 5 and the scan step one arcsecond. The HOP79 irradiance program performs monthly systematic scans of 30 × 130 regions at 20 positions along the polar axis, covering the solar diameter from the north to the south limb with the spectrograph slit oriented along the south-north direction.
Acknowledgements. This work was supported by the  Programme National PNST of CNRS/INSU  co-funded by  CNES  and  CEA. Hinode is a Japanese mission developed and launched by  ISAS/JAXA , collaborating with  NAOJ  as a domestic partner,  NASA  and  STFC (UK)  as international partners. Scientific operation of the Hinode mission is conducted by the  Hinode science  team organized at  ISAS/JAXA. This team mainly consists of scientists from institutes in the partner countries. Support for the post-launch operation is provided by  JAXA  and  NAOJ (Japan) ,  STFC (UK) ,  NASA ,  ESA , and  NSC (Norway).
Novel photon detectors (PDs) called X-ARAPUCAs  [20]  will be placed behind the Anode Plane Assembly (APA) collection wire planes. The PDs are used to provide a timestamp of the interaction, thus giving an estimate of the drift distances traveled by the ionization electrons to reconstruct the third event coordinate. The DUNE Collaboration has constructed and operated a large horizontal drift prototype detector, known as ProtoDUNE-SP. The detector has been assembled and tested at the CERN Neutrino Platform  [21]. ProtoDUNE-SP was operated from 2018 to 2020, and its large samples of high-quality beam data have been used to demonstrate the effectiveness of the single-phase far detector design. Results on the performance of the ProtoDUNE-SP liquid argon TPC in the test beam can be found in Ref.
III. ELECTRONS IN LARTPCS For the DUNE physics program it is critical to understand the far detector response to electromagnetic showers since DUNE will measure electrons produced in ν e interactions, where the ν e are from ν μ oscillations, the Sun, and possibly supernova explosions. In addition, DUNE will search for proton decay signatures, as event identification may proceed via the detection of a lowenergy electron. ProtoDUNE-SP has collected data samples of test-beam electrons and data samples of electrons from cosmic ray muon decays  [22]. Data from ProtoDUNE-SP beam runs with 1 GeV=c beam momentum, including a sample of beam positrons, were used for the initial classification of track-and showerlike energy deposits using a convolutional neural network technique  [23]. Studies of electron selection and identification in ProtoDUNE-SP TPC lead to a more accurate understanding of the calorimetric response to electrons and offer an opportunity for a precise understanding of the electron energy resolution parameters for electron neutrino reconstruction in future DUNE far detectors.
A collection of hits is merged together to form a particle track or a shower that belongs to an event. The hit finding algorithm searches for candidate hits based on charge deposits in the waveform on a single wire as a function of time, and fits them to a Gaussian shape. Pattern recognition and event reconstruction are performed by the PANDORA software package  [29] , which is a collection of reconstruction algorithms that focus on specific hit topology patterns. The first step in the reconstruction procedure is the two-dimensional clustering of observed charge pulses in each of the three detector readout planes separately. In the second step, sets of twodimensional clusters are matched between the three views to produce 3D hits and to create particle interaction hierarchies. As described in  [22] , one important feature of the cosmic ray reconstruction step is the "stitching" of tracks across the boundaries between neighboring drift volumes bounded by a CPA or an APA.
A. Muon track selection (i) Only the T 0 -tagged candidate muon tracks are selected from muon tracks reconstructed by PAN- DORA. These are the tracks that cross the cathode or anode plane boundaries, and the two pieces of the track from the two volumes help determine the correct end position of the track in the drift direction. The fraction of tracks having a T 0 assigned to them is 2% from the data sample. Since this requirement selects most of the events and the corresponding charge coming from locations farther away from the anode in ProtoDUNE-SP, it is expected that the DUNE far detector will perform equally or better in terms of charge reconstruction. This is because there will be less ionization charge attenuation as events, on average, will be closer to the anode plane wires and that may slightly affect the energy reconstruction.
These uncertainties quantify how well the absolute energy scale of Michel electrons is understood. Systematic uncertainty contributions from C calib , εðY i ; Z i Þ) and C norm are negligible. Table  II  presents the systematic uncertainties on the reconstructed Michel electron energy spectrum. The uncertainties are expressed with respect to the mean energy of the reconstructed Michel electron energy spectrum. Individual contributions are added in quadrature. The hit association systematic uncertainty was evaluated by considering the number of candidate Michel electron hits within 10 cm of the muon stopping point in both data and simulation. The difference in the average number of hits in data and simulation was used to vary the MC Michel electron hit distribution. A shift in the mean value of the reconstructed Michel electron energy scale was determined based on the hit distribution variations.
The data error bars represent the statistical uncertainties. MC simulation error bands include MC statistical and systematic uncertainty contributions added in quadrature. The mean value of the reconstructed Michel electron energy spectra is 29. 4 AE 0. 2ðstatÞ MeV and 28. 7 AE 0. 2ðstatÞ AE 1. 4ðsystÞ MeV for data and MC simulation, respectively. Relative energy scales of data and MC simulation events agree to within 1. 8%. The ratio of data to MC reconstructed energy spectra is flat within statistical and systematic uncertainties. Figure 7 (bottom)  shows the reconstructed Michel electron energy versus the true Michel electron energy distribution. These results demonstrate that the Michel electron energy spectrum from data is closely reproduced by the theoretically well-understood Michel electron energy distribution when propagated through the detector simulation and reconstruction.
(ii) The energy resolution constant term (∼26%) describes the resolution losses due to the lost energy. In the MC simulation, it is possible to add the lost energy to the reconstructed energy balance. In this case, the energy resolution drops from about 40% to 25% at 50 MeV. The lost energy recovery is not possible in the collected data set with the existing charge readout threshold and applied selection (cone cut) optimized to reduce backgrounds. (iii) If the lost energy is accounted for, as performed in the simulation, the stochastic term decreases from 1. 91 to about 1. 24. The stochastic term described here may suggest that the energy resolution at a few percent level might be achievable for the DUNE far detector in the few GeV electron neutrino energy range, assuming negligible lost energy and noise contributions to the resolution.
VIII. SUMMARY This article describes the event selection and energy reconstruction of low-energy electrons in the DUNE prototype ProtoDUNE-SP LArTPC. A high-purity (95%) Michel electron event sample is selected and used to calibrate the electron energy scale, and to quantify the effects of the detector response to low-energy electrons including readout electronics threshold effects. The event selection techniques for cosmic ray muons and Michel electrons have been developed. The selected Michel electron sample was used to verify the recombination correction factor and the data and MC simulation agreement was presented based on the Modified Box recombination model. Two complementary energy reconstruction techniques to calibrate the Michel electron energy spectrum are described. The "cosmic-muon" based calibration is based on a model-dependent recombination correction and relies on the calibration constant derived from cosmic ray muon measurements.