dataesr/scientific-paragraphs-categorization huggingface dataset:
It is evident that at lower energies, where a plethora of other data exist  [2] , the PWAs predict well the precise measurement of E from CLAS. At higher energies, significant deviations between the solutions and data are evident. Overall, the SAID and Bonn-Gatchina PWA solutions agree well, especially at larger π 0 angles in the c. m. frame, whereas deviations in all angles are observed between the MAID PWA solutions and our data. The full kinematic coverage of the CLAS dataset is illustrated in Fig. 3  (CBELSA results are omitted in these plots). The new results were included in the world database and PWA fits were performed in all three frameworks. Specifically, the new PWA solutions for SAID (blue solid line), MAID (magenta dashed-dotted line), and Bonn-Gatchina (green dashed line) that account for the CLAS E results (in addition to the other world data), are shown in Fig.
The model describes experimental data up to photon energies of 18 GeV and is well adapted for predictions at higher energies. The Bonn-Gatchina model was developed for the partial wave analysis of reactions with multi-particle final states. The particle interaction vertices are described in the framework of the covariant tensor formalism and the energy-dependent part of the partial wave amplitudes satisfies unitarity and analyticity conditions. The description of the method can be found in Ref. [57]. The present solution describes 201 datasets, which includes the pion-and photon-induced reactions with one or two pseudoscalar mesons in the final state, as well as photon-induced reactions with production of the ω meson. In Table  2 , χ 2 values are compared for fits in which the present data were included and those in which they were   2  (blue for SAID, magenta for MAID, and green for Bonn-Gatchina) not.
The different panels show the real and imaginary parts of the electric and magnetic multipoles. The current solutions from SAID KI22 (blue solid curves), MAID (magenta dashed-dotted curves), and Bonn-Gatchina (green dashed curves) are shown with fits including the new CLAS E data from this analysis While the inclusion of new and precise polarization measurements, in general, has led to better agreement between groups extracting multipoles, the prediction of new quantities, or existing quantities outside their ranges of measurement, is generally only qualitative. The most extensive single-and double-polarization data above photon energies of 2 GeV, come from pre-1980 Daresbury experiments with limited angular coverage. More recent measurements at Jefferson Lab, MAMI, Bonn, and SPring-8 have provided data with higher precision and broader angular range, but do not provide a database approaching a "complete experiment.
" Each new measurement is particularly valuable at these higher energies. More detailed analyses from SAID  [46] , MAID, and Bonn-Gatchina are expected and will include these and other recent data. The Bonn-Gatchina solution currently includes more than 200 data sets. The new data confirm the E observable measured by the CBELSA Collaboration and improve the precision in some regions. Thus the total weight of the Eobservable data was increased in the combined analysis, which led to an improved description of the E data (both from CLAS and CBELSA). This also resulted in a small deterioration in the description of the differential cross section data.
Summary and outlook The CLAS E-03-105 experiment (FROST), which utilized longitudinally polarized protons and circularly polarized photons, allowed the precise determination of the beamhelicity asymmetry E for the γ p → pπ 0 reaction. The new results provide an important independent check on the extraction of the double-polarization observable E with a statistical precision improved over the past data from CBELSA, while extending the kinematical coverage at lower energies. Specifically, the newly obtained data cover c. m. energies between W = 1. 25 GeV and W = 2. 23 GeV, whereas results from CBELSA provided an energy coverage between W = 1. 42 GeV and W = 2. 58 GeV. PWA fits within the SAID, MAID, and Bonn-Gatchina frameworks were performed with the inclusion of this newly obtained dataset.
The Bonn-Gatchina group found changes in the helicity 1/2 and 3/2 photon decay amplitudes associated with the N (2120)3/2 -and changes of the helicity 1/2 amplitude associated with the (1940)3/2 -, while the MAID solution did not show any significant changes. A detailed analysis from the SAID group is underway to establish the impact of this new dataset and their findings will be reported in a dedicated paper.
DE-SC0016583  and  DE-SC0016582 ; by the  U. K. Science and Technology Facilities Council  grants,  ST/P004385/2 ,  ST/T002077/1 ,  ST/V001035/1 ,  ST/V002570/1 , and  ST/L00478X/2 ; by the  EU Horizon 2020 research by innovation program ,  STRONG-2020  project (under grant agreement No. 824093 ), as well as by the  Russian Science Foundation   RSF22-22-00722  grant. We also acknowledge the outstanding efforts of the staff of the  Accelerator and Physics Divisions at Jefferson Lab  that made this experiment possible. The  Southeastern Universities Research Association (SURA)  operated the  Thomas Jefferson National Accelerator Facility  for the  United States Department of Energy  under contract  DE-AC05-06OR23177. Further support was provided by the  National Science Foundation , the  Italian Istituto Nazionale di Fisica Nucleare , the  Chilean Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) , the  Chilean Agency of Research and Development (ANID) , the  French Centre National de la Recherche Scientifique , the  French Commissariat à l'Energie Atomique , and the  National Research Foundation of Korea.
We present an analysis of Titan data acquired by the Cassini Visual and Infrared Mapping Spectrometer (VIMS) at the landing site of the Dragonfly mission, using a new version of our radiative transfer model for Titan, with significant updates for the spectroscopic parameters of atmospheric gases and photochemical aerosols. Our updated radiative transfer model is validated against the in situ spectroscopic measurements of the Huygens probe during its descent and once landed. We confirm that aerosols with a fractal dimension of 2. 3-2. 4 provide the best fit to the observations. We apply our radiative transfer model to four VIMS data cubes over the Selk crater region including the Dragonfly landing and exploration areas, further validating our model by producing consistent aerosol population and surface albedo maps.
2010 ) at the latitude of Huygens. We include atmospheric opacity sources from gases -Rayleigh scattering from nitrogen (N 2 ) and methane (CH 4 ); collision-induced absorption by nitrogen and hydrogen (H 2 ); and absorption by methane, its isotopologues 13 CH 4 and CH 3 D, acetylene (C 2 H 2 ), and carbon monoxide (CO)-and photochemical aerosols. Molecular line lists for gaseous methane and its isotopologues have been compiled over the whole spectral range of the VIMS infrared channel (0. 88-5. 11 μm) from laboratory measurements, theoretical calculations, and empirical models (all the corresponding references can be found in  Hirtzig et al. 2013). Line lists for acetylene and carbon monoxide are taken from the GEISA2009 database  (Jacquinet-Husson et al. 2011). Correlated-k absorption coefficients have been computed for all the gaseous species at the VIMS spectral sampling, on a "pressure-temperature" grid defined by the Huygens and Cassini measurements, with line profiles and cutoffs recommended by De  Bergh et al.
(2007)  and constant above their highest altitude value-480 km. As it condenses at ≈70 km, the profile is adapted following the acetylene saturation curve. From the surface up to 80 km, we use the  Niemann et al. (2010)  methane VMR, linearly interpolated to 1% at 350 km following  Yelle et al. (2021) , and constant up to the highest grid level. Hydrogen cyanide (HCN), the simplest and most abundant nitrile, has been added to our gases database, and its VMR is set using the most recent profile of  Thelen et al. (2019)  and linearly extrapolated above their highest altitude value. D/H and 12 C/ 13 C isotopic ratios were set to the most recent observations with ALMA (Atacama Large Millimeter/submillimeter Array), which are 1. 033 10 -4 (Thelen et al. 2019) and 89. 9 10 -5  (Serigano et al. 2016) , respectively.
Methane and its isotopes opacities are simulated as described in  Rey et al. (2018)  using recent developments from laboratory measurements (T = 50-350 K). This is the first accurate unified theoretical methane line lists of 12 CH 4 and 13 CH 4 up to 13,400 cm -1 (> 0. 75 μm). CO, C 2 H 2 , and HCN correlated-k coefficients are calculated from the HITRAN database  (Rothman et al. 2013 ). For the line broadening, the line profiles are represented by a Voigt function with collision broadening coefficients from  Menard-Bourcin et al. (2007) , and a cutoff for the Lorentzian far wings is set at 26 cm -1 from the line center for all lines and modified with a sub-Lorentzian exponential decay with a wavenumber characteristic length of 120 cm -1 for all species except CO  (Campargue et al. 2012). For the latter, we used the recommended cutoff by  Lellouch et al.
(2003). Despite recent improvements in the spectroscopic databases, the line lists of numerous species, including ethane, which may have important contributions in the 2. 0-2. 7 and 3. 0-3. 7 μm ranges  (Maltagliati et al. 2015a) , are still not available. Tomasko et al. (2008)  and  Doose et al. (2016)  recommended the use of phase functions, single-scattering albedos, and extinction profiles that best fit the DISR measurements, based on an idealized aerosol structure, i. e. , fractal aggregates of 3000 spherical monomers 50 nm in radius and fractal dimension 2. The mean radius of the monomers was constrained by the high degree of linear polarization measured by DISR. Monomer radii must be less than about 0. 05 μm to give sufficient polarization in a single scattering to produce the degree of linear polarization measured in Titanʼs atmosphere at 140 km altitude  (Tomasko et al.
All the differences between the 2016 and 2022 models have consequences for the aerosol opacity and surface albedo retrievals. This will be explored in depth and validated with the help of the available in situ Huygens measurements in the following section. VIMS was an imaging spectrometer part of the payload of the Cassini spacecraft. VIMS performed observations within 96 channels in the visible from 0. 3 to 1 μm, with a mean spectral sampling capability of 7. 3 nm, and within 256 channels in the infrared (IR) from 0. 884 to 5. 110 μm, with a mean spectral sampling capability of 16. 6 nm. In this work, we only deal with the infrared part of the spectrum. We perform the radiometric calibration of the raw data into I/F as a function of wavelength for each of the 256 VIMS-IR channels using the standard RC19 VIMS pipeline  (Clark et al.
2018 ). This calibration includes a time-dependent radiometric calibration aimed at correcting a wavelength shift that has been identified during the last years of the mission  (Clark et al. 2018). Up to ≈15 nm of progressive shift is observed when comparing data taken in 2004 and data taken in 2017. This shift can dramatically alter the surface information in the sharp atmospheric windows (especially the narrow ones at short wavelengths) because of the wide-band correlated-k coefficients calculation used in our RT model. For every pixel, we determined the viewing geometry and location information using the SPICE (Spacecraft, Planet, Instrument C-matrix-"Camera matrix"-Events) toolkit from NAIF (Navigation and Ancillary Information Facility)  (Acton et al. 2018). Radiometric error is computed for every VIMS spectel using the scheme described in Appendix A.
The incidence, emergence, and phase angles of the VIMS observation vary between 31°. 9 and 38°. 0, 30°. 4 and 36°. 5, and 18°. 4 and 18°. 8, respectively. These observation angles allow us to use the plane-parallel approximation in our radiative transfer calculation. We use the VIMS CM_1481624349_1 observation over the HLS to validate our RT-IPGP-2022 model by comparing it with the in situ Huygens/DISR spectral measurements. First, we extract the most representative spectrum of the HLS from the VIMS data cube. To do so we superimpose the CM_1481624349_1 data cube over the highest-resolution mosaic. We use the photometrically calibrated mosaic of  Karkoschka & Schröder (2016)  constituted of about 300 images taken by the Huygens/DISR instrument starting from 70 km altitude at 770 nm wavelength  (Karkoschka et al.
2007 , and refined by  Karkoschka et al. 2012). Since the spatial resolution of the VIMS data cube does not allow us to distinguish as many small-scale surface features at the landing site, many attempts have been done to reconstruct the HLS spectrum with linear combinations of VIMS pixels around the HLS (e. g. ,  Griffith et al. 2012; Hirtzig et al. 2013; Corlies et al. 2021). But the method, the choice of VIMS pixels, and the calculation of the linear combination coefficients were not explicitly described and our tests with these different combinations showed that they were not accurate enough for a valid comparison. The DISR mosaic reveals the presence of different brightness units in the surroundings of the HLS, with a spatial resolution of about 1% of the distance to the HLS (i. e. , 1 km at 100 km from the HLS and 50 cm at 50 m from the HLS).
The data collection was managed by the DISR solar sensor system and, due to the unexpected rotation direction of the probe, data were acquired by integrating over random azimuth angles relative to the Sun rather than at well-defined azimuths as planned. A total of 214 spectra were acquired by ULIS: 4 spectra per 48 observation sequences from 141 to 5. 3 km, plus 22 observations made in snapshot mode (short exposure time) from 3 km down to the surface. ULIS spectra, calibrated in radiance (W m -2 μm -1 sr -1 ), are archived in the ESA Planetary Science Archive and in the NASA Planetary Data System (PDS), along with information relevant to each of the observation sequences (altitude, solar zenith angle, and Huygens rotation speed and tilt). At the nodes of our RT model altitude grid, we can only extract, over the ULIS wavelength range, up-or down-welling hemispheric integrated fluxes radioed to the incoming solar flux.
It is worth noting that fitting the data with a more physical function, like a + b * e -z/H , with z the altitude and H a free parameter representative of the atmospheric scale height, does not significantly improve the fit. We averaged the spectra belonging to the same observation sequence, reducing the final number of spectra to 21. We convert the radiances of each selected ULIS spectrum into I/F as follows: I F I D S , 7 T S 2 l l p l = - ( ) ( ) ( ) ( )  with D T-S the Titan-Sun distance in astronomical units and S(λ) the solar flux spectrum at 1 au  (Kurucz 2005). The resulting ULIS spectra, expressed as I/F and interpolated at our RT model (and VIMS) spectral sampling, are shown in Figure  10. The same figure also shows the spectra simulated by the RT-IPGP-2022 and the RT-IPGP-2016 models, interpolated at the altitudes of the ULIS spectra.
2021). Selk is an impact crater that measures approximately 90 km in diameter with water-rich material potentially exposed in and around the crater and its ejecta, and a complex impact-induced and post-impact geology  (Soderblom et al. 2010; Lorenz et al. 2021). It was best observed by VIMS during Titan's flybys T35, T38, and T40  (Soderblom et al. 2010 ). Among all the VIMS observations of the Selk crater area, we selected four cubes that allow us to map the region with the best compromise between spatial coverage and spatial sampling. The main characteristics of the four selected VIMS data cubes are presented in Table  3. Due to uncertainties in the navigation, the four cubes have been co-registered as was done in  Soderblom et al. (2010). Taking the map with the largest spatial sampling as a reference, we performed the coregistration by defining manually ground control points and applying a classic rotationscaling-translation warping and bilinear resampling to the three other maps.
Hence, the seams are mainly originating from the varying viewing geometries (Figures  12(g), (h),  and (i) ) that our RT model should be able to account for or at least mitigate. We inverted haze and mist scaling factors and surface albedos for all the pixels of the four VIMS data cubes with the RT-IPGP-2022 model. This represents a total of 16,384 pixels to be processed and two continuous weeks of parallel computations on a 40 core workstation. We present the first part of the results in Figure  13 , which are the haze and mist scaling factor maps over the Selk crater area. The I/F mosaic at 0. 88 μm (Figure  13(a) ), in the first atmospheric band available in the VIMS-IR channel, is strongly heterogeneous, presenting marked I/F slopes within each individual data cube and notable I/F value discrepancies between the data cubes, all correlated with the viewing geometries (see Figure  12 ).
This work was supported by  CNES  ( Centre National d'Études Spatiales ),  Programme National de Planétologie of the Institut National des Sciences de l'Univers/Centre National de la Recherche Scientifique  and  ANR (Agence Nationale de la Recherche)  project  RaD 3 -net  ( ANR-21-CE49-0020 ). We thank  B. Seignovert  for Cassini VIMS cube coregistration,  Sandrine Vinatier  for discussions, and two anonymous reviewers for their helpful suggestions and very constructive criticism that greatly improved the quality of the final manuscript.
In addition the RHESSI spacecraft is put into safety mode when it passes through the South Atlantic Anomaly(SAA) region and there are no RHESSI observations during that time. The FERMI orbit does not pass through SAA region and is devoid of this data gap in its observation. Even though both RHESSI and FERMI have low-earth orbits which dictates their orbital period, their orbits are not in phase. Hence events missed by one instrument can be picked by the other instrument if occurring during the day time for that instrument. Thus the data availability from the two missions from 2008 till the end of the study enabled us to detect many more events than would have been possible just with RHESSI. Once HXR events were selected, the HXR counts measured by each instruments were then processed in OSPEX to derive from HXR spectroscopy the HXR producing electron spectrum (see details below).
Selection criteria and event list In order to select events, software was developed in Python to produce daily (08:00-16:00 UT) quick-look plots showing HXR count-rates observed by RHESSI and FERMI/GBM (depending on the period) with a combination of 1D projections of the radio Article number, page 2 of 15 emissions recorded by the NRH at 150 MHz in two perpendicular directions (EW and NS terrestrial directions) corresponding to the two arms of the NRH and radio spectra in the 1GHz-20 kHZ range from PHOENIX-2, PHOENIX-3, ORFEES (depending on the period), NDA and WIND/WAVES. The quick-look plots were then used to select manually associated HXR bursts and radio type III emissions. As solar radio emissions can be complex in the case of large ares producing not only type III burst but also other kinds of emissions like type II, type IV,.
Data analysis For each of the shortlisted events, systematic analysis of their radio and HXR emission was carried out. For both analysis we used the standard SolarSoftware(SSW) packages developed for these instruments. Article number, page 5 of 15 A&A proofs: manuscript no. output Fig. 4. Same as gure 3 for the event selected on 20 October 2013. The HXR data is from RHESSI. Two events are selected and considered in the study during the period plotted. The positions of the type III sources at 150 MHz for the two events are plotted on the right. Figure  1  shows the event that occurred at 10:03 UT on 10 March 2003. A well dened peak is seen in the HXR energy range (up to energies above 25 keV). We also show the lightcurves corresponding to the radio ux (see next section) at three frequencies 150, 228, 327 MHz.
Peak Type III radio uxes as a function of frequency Observations from the Nançay Radioheliograph were used to estimate the peak uxes of type III bursts at 4 frequencies: 150 MHz, 228 MHz, 327 MHz and 432 MHz. To achieve that, we used the 10s integrated raw data les containing measured visibilities and produced images of the radio type III sources using the standard CLEAN routine implemented in the standard NRH software. These images provide information on the location of the radio type III sources on the solar disk (see e. g. gures 1 -4). The radio ux of the type III burst was then computed using the standard NRH software on a region enclosing the burst position as shown in gures1 -4. The peak ux was then obtained after subtracting the background dened as the mean of the ux before the burst.
Fermi/GBM data consists of 12 NaI detectors which provide full-sky observations. For the present study, we select data from the most sunward NaI detector (here detector 5). As in the case of RHESSI observations, the spectral tting was achieved only up to 100 keV. Unlike RHESSI the energy bins are pre-binned quasilogarithimcally for FERMI. Figure  8  shows the results of the t for the 22 April 2013 event. The electron spectral index below the break δ low is -4. 20 while the spectral index above the break δ high equals -4. 57. In that case, the break energy is at 85. 3 keV. Once the spectral tting is achieved, the number of nonthermal electrons above variable energy thresholds (low energy cut-o: 10 keV or 20 keV) at the time of the HXR peak can be directly computed from the t and is used in the next section.
Acknowledgements. Tomin James  acknowledges the support of the  European Commission Horizon   2020 INFRADEV-1-2017 LOFAR4SW  project number  777442. Nicole Vilmer  acknowledges support from the  Centre National d'Études Spatiales (CNES) , and from the  French programme on Solar-Terrestrial Physics (PNST)  of  INSU/CNRS  for the participation to the  RHESSI  project. The NRH is funded by the  French Ministry of Education  and the  Région Centre. The  Institute of Astronomy, ETH Zürich and FHNW Windisch, Switzerland  is acknowledged for funding Phoenix spectrometers. The RHESSI team, the  FERMI/GBM team , the  WIND/WAVES team  and the NRH and ORFEES teams are acknowledged for providing data access and analysis software. The authors acknowledge the  Nançay Radio Observatory/Observatoire Radioastronomique de Nançay of the Paris Observatory (USR 704-CNRS , supported by  Université d'Orléans, OSUC, and Région Centre in France)  for providing access to NDA observations accessible online at http://www.
Diameters d s , d p , and the system semi-major a are in kilometers (km). than that of the general asteroid population. In Sect. 2, we present the data used in this study and the sources from which they were acquired. In Sect. 3, we discuss how we build a taxonomic reference by selecting asteroids from the general population. In Sect. 4, we show the resulting discrepancies in composition between the binary systems and general population. Section 5 provides a discussion of these results.
Datasets In this study, three main populations were considered. First, the 402 known binary asteroids. Second, asteroid pairs, which are expected to have originated as binary systems that are no longer gravitationally bound  (Vokrouhlický & Nesvorný 2008). There are 239 pairs of asteroids suspected to share a common origin, and we mainly consider the primary object of these systems. Finally, the general population, encompassing all known asteroids for which reliable data on their dynamics and composition are available. In order to construct the largest possible dataset, we included information from a plethora of sources. Using the rocks 1  interface for SsODNet 2   (Berthier et al. 2022) , we gathered values for physical and dynamical parameters of all asteroids considered in this study with full traceability to their original sources, which are outlined in Appendix A.