dataesr/scientific-paragraphs-categorization huggingface dataset:
, Y. T. and N. L. acknowledge support from " programme national de physique stellaire" (PNPS) and from the "programme national cosmologie et galaxies" (PNCG)  of  CNRS/INSU. We acknowledge the support of the scientific cooperation program ECOS-ANID Number  180049. L. C. acknowledges the support of the postdoc fellowship from  French Centre National d'Etudes Spatiales (CNES). P. J. acknowledges financial support of  FONDECYT  Iniciación grant Number  11170174  and  FONDECYT Regular  grant Number  1200703. This work was partially supported by the  Spanish Ministry of Science, Innovation and University (MICIU/FEDER, UE)  through grant  RTI2018-095076-B-C21 , and the  Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia 'María de Maeztu ') through grant  CEX2019-000918-M.
In this paper, we use the LArSoft package  [14]  to realistically model the detector response, including the asymmetric response due to the orientation of the detector with respect to the incoming neutrino, and we use the Pandora package  [16]  to perform track reconstruction. We also find that, although the charged lepton is produced roughly isotropically, its direction is correlated with that of the proton, providing a new method for rejecting background that can significantly improve the signal-to-background ratio. At DUNE, the charged current interaction ν + 40 Ar → -+ p + + 39 Ar produces an ejected proton and charged lepton which can be well-measured  [12]. But the recoil of the remnant 39 Ar will not be well-measured, and although the kinetic energy of the remnant nucleus will be small, its momentum may be substantial.
We assume that the number of signal and background events seen by DUNE will be drawn from Poisson-distributions whose means are given by the expected number of signal and background events, denoted by N µ S and N µ B , respectively. To estimate the sensitivity of DUNE, we assume a representative ("Asimov"  [32] ) data set in which the number of observed neutrinos is taken to be the number of expected background neutrinos, rounded to the nearest integer (that is, N µ O = round(N µ B )). We denote by N µ,90 S the number of expected signal events such that the likelihood of an experimental run observing a number of total events larger than round(N µ B ) is 90%. A model for which the expected number of signal events satisfies N µ S > N µ,90 S lies in the region to which we estimate DUNE would be sensitive.
Application: Search for Inelastically Scattered Dark Matter To place this result in context, we consider a dark matter scenario which can be constrained by data from DUNE, but which would be difficult to constrain with direct detection experiments. In particular, we consider the case of low-mass dark matter (m X 10 GeV) Figure  12. DUNE sensitivity to φ 236 MeV , the flux of 236 MeV ν µ 's from the Sun, independent of the new physics model that produces them. The blue lines correspond to the reconstructed quantities in the first and second rows of Table  1  and the green lines correspond to the generator level quantities in the third and fourth rows. The dashed lines are for maximum S/B and the filled lines are for maximum DM sensitivity. The discontinuities are due to the limit of small numbers of events; noticeable when the number of observed events jumps by one.
S. Department of Energy, Office of Science, HEP User Facility. Fermilab  is managed by  Fermi Research Alliance, LLC (FRA) , acting under Contract No. DE-AC02-07CH11359. This work was supported by  CNPq ,  FAPERJ ,  FAPEG  and  FAPESP, Brazil ;  CFI ,  IPP  and  NSERC ,  Canada ; CERN; M ŠMT, Czech Republic; ERDF,  H2020-EU  and  MSCA ,  European Union ;  CNRS/IN2P3  and  CEA, France ;  INFN, Italy ; FCT, Portugal; NRF, South Korea;  CAM, Fundación "La Caixa ",  Junta de Andalucía-FEDER , and  MICINN, Spain ;  SERI  and  SNSF, Switzerland ;  T ÜB İTAK ,  Turkey ;  The Royal Society  and  UKRI/STFC ,  United Kingdom ;  DOE  and  NSF ,  United States of America. We are grateful to  Xerxes Tata  for useful discussions. C. Rott  acknowledges support from the  National Research Foundation of Korea.
8 < η < 5. 1 and -3. 7 < η < -1. 7 ([82], section 5. 1). The Zero Degree Calorimeter (ZDC), used for offline event rejection in p-Pb collisions, consists of two sets of neutron and proton calorimeters positioned along the beam axis on both sides of the ALICE apparatus, about 110 m from the interaction point ([82], section 5. 4). The results presented in this paper were obtained from the analysis of the LHC Run 2 data samples collected from pp collisions at √ s = 5. 02 TeV in 2017 and p-Pb collisions at √ s NN = 5. 02 TeV in 2016. The proton-nucleon centre-of-mass system in p-Pb collisions is shifted in rapidity by ∆y = 0. 465 The selection of candidates was performed using a combination of kinematical, geometrical, and PID selections. The selection criteria were tuned on Monte Carlo simulations in order to maximise the statistical significance in each p T interval.
For each of the above trials, the fit was repeated with different hypotheses on the signal peak width and mean, with variations including a) treating both the Gaussian width and mean as free parameters, b) fixing the peak width to the MC expectation and leaving the mean free, c) fixing the mean to the MC expectation and leaving the peak width free, and d) fixing both the peak width and mean to the MC expectation. The systematic uncertainty was defined as the RMS of the distribution of the raw yield values extracted from these trials. The systematic uncertainty on the tracking efficiency was estimated by i) comparing the probability of prolonging a track from the TPC to the ITS ("matching efficiency") in data and simulation, and ii) by varying track selection criteria in the analyses. The matching efficiency in simulation was determined after re-weighting the relative abundance of primary and secondary particles to match that in data.
52 GeV  [100]. The measured p T -differential cross section is significantly underestimated by the POWHEG prediction, by a factor of up to 15 in the lowest p T interval of the measurements, and around a factor 2. 5 in the highest. While the discrepancy between the data and calculation decreases as the p T increases, the measured cross section at 8 < p T < 12 GeV/c is still ∼50% larger than the upper edge of the POWHEG uncertainty band. The discrepancy between the data and POWHEG is similar to what was observed in pp collisions at √ s = 7 TeV  [14]. The GM-VFNS predictions also significantly underestimate the data, by about a factor of 3-4 at low p T and by about a factor of 1. 5 at high p T. In Fig. 6 , the Λ + c -production cross section in pp collisions at √ s = 5. 02 TeV is compared with the measurement at √ s = 7 TeV  [14].
the POWHEG prediction by a factor of up to 15 in the lowest p T intervals, similar to what is observed for pp collisions. The difference between the POWHEG predictions and the measured cross section decreases with increasing p T and in the highest p T interval of the measurement (12 < p T < 24 GeV/c) the data point lies on the upper edge of the POWHEG uncertainty band. The Run 2 p-Pb results are compatible with our previous results from the sample of p-Pb collisions at √ s NN = 5. 02 TeV collected in LHC Run 1  [14]. The statistical uncertainties have been reduced by approximately a factor of two for all p T intervals, and the systematic uncertainties improved by approximately 30% at low p T and 10% at high p T.
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  Nationalstiftung für Forschung ,  Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan ;  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ,  Financiadora de Estudos e Projetos (Finep) ,  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)  and  Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Ministry of Education of China (MOEC)  ,  Ministry of Science & Technology of China (MSTC)  and  National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation , Croatia;  Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear  ( CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic ; The  Danish Council for Independent Research | Natural Sciences , the  VILLUM FONDEN  and  Danish National Research Foundation (DNRF) ,  Denmark ;  Helsinki Institute of Physics (HIP) , Finland;.
We report the direct imaging discovery of a low-mass companion to the nearby accelerating A star, HIP 109427, with the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument coupled with the MKID Exoplanet Camera (MEC) and CHARIS integral field spectrograph. CHARIS data reduced with reference star PSF subtraction yield 1. 1-2. 4 µm spectra. MEC reveals the companion in Y and J band at a comparable signal-to-noise ratio using stochastic speckle discrimination, with no PSF subtraction techniques. Combined with complementary follow-up L p photometry from Keck/NIRC2, the SCExAO data favors a spectral type, effective temperature, and luminosity of M4-M5. 5, 3000-3200 K, and log 10 (L/L ) = -2. 28 +0. 04 -0. 04 , respectively. Relative astrometry of HIP 109427 B from SCExAO/CHARIS and Keck/NIRC2, and complementary Gaia-Hipparcos absolute astrometry of the primary favor a semimajor axis of 6.
2006). The CHARIS data also enables spectral differential imaging (SDI;  Marois et al. 2000). CHARIS and MEC data utilized the Lyot coronagraph (0. 23 diameter) to suppress the stellar halo, as well as satellite spots for precise astrometric and spectrophotometric calibration (e. g. Jovanovic et al. 2015a; Currie et al. 2018a; Sahoo et al. 2020). NIRC2 exposures left the HIP 109427 primary unocculted and unsaturated. Parallactic angle rotation for all data sets was small to negligible; however, we obtained reference star observations for the CHARIS broadband and NIRC2 data  (HIP 105819 and HIP 112029, respectively). To complement these new data, we analyzed Keck/NIRC2 L p data for HIP 109427 taken on 28 October 2015 from the Keck Observatory Archive (Program ID C197NI). These data were obtained with Keck II's facility (Shack-Hartmann) adaptive optics system and the vector vortex coronagraph  (Serabyn et al.
2017). We used HD 212061, observed immediately after HIP 109427, for reference star subtraction. MEC data was reduced using the MKID Data Reduction and Analysis Pipeline  (Walter et al. 2020)   1. This pipeline notably includes a wavelength calibration, a flat-field correction, and a spectrophotometric calibration amongst other steps. The MKID Pipeline can output calibrated images in a fits file format to be able to interface with traditional post processing techniques and astronomical image viewing software, but can also output microsecond precision, time-tagged photon lists due to the unique nature of MKID detectors. Each pixel in an MKID array is a superconducting LC resonant circuit with a photosensitive inductor and tunable interdigitated capacitor. When a photon strikes the inductor of the MKID pixel, cooled below its transition temperature, quasiparticles are generated by the breaking of Cooper pairs.
We adopted the scaling between modulation amplitude and contrast from  Currie et al. (2018b)  to generate the expected satellite spot flux values per passband. A stellar spectrum from the PHOENIX stellar library appropriate for an A1V star was used and the data normalized to match HIP 109427's reported J band flux  (Ducati 2002). Given MEC's low energy resolution, we focused on broadband MEC photometry (not spectra). Additionally, due to the wavelength scaling of the spots, the satellite spots are extended out into elongated streaks instead of appearing as copies of an unocculted stellar PSF. This is similar to the case for GPI's polarimetry mode. To derive photometry for the satellite spots, we therefore follow similar methods to those outlined for GPI's polarimetry mode from  Millar-Blanchaer et al.
Detector dithers mitigated the large number of dead pixels in the current (engineering grade) MEC array. The SSD code is run on a single dither position at a time, and the resulting I C and I S images are drizzled together into a combined image using an adaptation of the STScI DrizzlePac software package  (Gonzaga et al. 2012). We used this SSD code to process our 15 minute observation of HIP 109427 taken on 7 October 2020 to generate the image in Figure  1. The companion is clearly visible. Dark circular regions close to the edge of the coronagraph represent pinned speckles that have been suppressed by SSD due to their large I S component. For this analysis, a conservative bin size of 10 ms was chosen. Macintosh et al. (2005)  found that speckles evolve on timescales similar to the aperture clearing time of the telescope which is given by τ 0 = (0.
The noise was calculated by taking the standard deviation of the sums of the sky subtracted flux for each non-companion containing aperture (see also  Currie et al. 2011; Mawet et al. 2014). This procedure was performed for both the total intensity and SSD I C /I S image of HIP 109427 B. The SNR of the I C /I S image is 21. 2, about a factor of 3 higher than the SNR of 6. 9 found for the total intensity image. For the CHARIS broadband data (NIRC2 Lp data), we retained 5 (3) KL modes for PSF subtraction but obtain similar results for other settings.
The vectors f phot,i , F phot,ik , and σ phot,i are measured photometry, model predicted photometry, and photometric uncertainty; α k is the scaling factor for the model that minimizes χ 2 (see also  De Rosa et al. 2016). Figure  5  shows the best-fit solar and non-solar metallicity models (top panels) and the associated χ 2 contours (bottom panels). An atmosphere with a temperature of T eff = 3200 K and a high gravity (log(g) = 5. 5) fits the data the best in both cases. The 1-σ contour for temperature and gravity is narrowly defined about this peak for both metallicities: T eff = 3100-3300 K and log(g) = 5. 25-5. 5. At the 2-σ level, the best-fit temperature and gravity ranges widen to 3000-3400 K and log(g) = 5-5. 5. The radii that minimize χ 2 are ∼2. 1-2. 6 Jupiter radii. The best-fit solar metallicity model accurately reproduces the H and K portions of CHARIS spectrum and the NIRC2 L p photometry; however, it underpredicts the brightness of HIP 109427 B in Y and J band by 85% and 25%, respectively.
Orbit and Dynamical Mass We used the open source code orvara,  Brandt & et al. (2021 -submitted) , to fit the mass and orbit of HIP 109427 B. orvara is an MCMC orbit fitting code for exoplanetary systems that uses a combination of absolute astrometry, relative astrometry, and radial velocities (RVs) to fit one or more Keplerian orbits to a system. For this dataset, we used HGCA absolute astrom- etry measurements for the star and the three measured epochs of relative astrometry for the companion from CHARIS and MEC. We do not consider RV limits since previous data has had a limited time baseline and poor precision. A Gaussian prior of 2. 1 ± 0. 15 M was chosen for the primary in concordance with literature values derived from isochrone fitting  (De Rosa et al. 2014; David & Hillenbrand 2015; Stone et al.
5 M with a semimajor axis of ∼ 9 au that is excluded by our spectral analysis. Future RV measurements, Gaia astrometry, and relative astrometry from high-contrast imaging will help to better constrain this orbit. This result demonstrates the efficacy of Stochastic Speckle Discrimination (SSD) in identifying faint companions. SSD increases the SNR of HIP 109427 B by about a factor of 3 versus the total intensity image (comparable to the CHARIS SNR of this target) without the use of any additional PSF subtraction techniques. This technique is especially effective at small angular separations (inside 10 λ/D) where algorithms exploiting traditional observing strategies like ADI and SDI suffer. Work expanding the SSD framework to be agnostic to bin size and to directly fit an off-axis Poisson source has been shown to be effective on simulated data and is currently being adapted for use on real datasets  (Walter et al.
2019). Current hurdles in adapting this technique likely stem from key differences between the simulated dataset and real on-sky data. Specifically, we are exploring the effects of variable Strehl during an observation and speckle chromaticity. Once effectively adapted to real data, this new bin-free SSD technique will allow us to not only remove bin size as a variable in our analysis, but also to directly extract the component of the intensity attributable to the companion itself. Unlike the Ic/Is maps in this work, which are limited to highlighting regions of an image that contain a companion of comparable brightness to the surrounding speckle field, this information could then be fed into other traditional post-processing techniques (such as ADI and SDI) to further improve the SNR of faint companion detections and help image companions buried beneath the speckle noise.
6. ACKNOWLEDGEMENTS S. S. and N. F. are supported by a grant from the  Heising-Simons Foundation. K. K. D. is supported by the  NSF   Astronomy and Astrophysics Postdoctoral Fellowship program  under award #  1801983. J. P. S. and N. Z. are both supported by a  NASA Space Technology Research Fellowship. I. L. is supported by the  National Science Foundation Graduate Research Fellowship  under grant #  1650114. T. C. was supported by a  NASA Senior Postdoctoral Fellowship  and  NASA/Keck  grant  LK-2663-948181. M. T. is supported by  JSPS KAK-ENHI  grant #  18H05442 , #  15H02063 , and #  22000005. We thank the  Subaru and NASA Keck Time Allocation Committees  for their generous support of this program and  Chas Beichman  and  Dawn Gelino  for graciously supporting additional NIRC2 time. This work makes use of the  Keck Observatory Archive (KOA) , a joint development between the W.
However, predictions of neutrino fluence are highly model-dependent. For instance, a cosmic string model  [5] , which uses new physics predicts a fluence of Φ ν ∼ 10 7 -10 8 cm -2  [3] , which is many orders of magnitude higher than that expected from the fireball scenarios. Searches for neutrinos associated with GRBs have been conducted by SK  [4, 6] , Kam-LAND  [7] , Borexino  [8] , IceCube  [9] , ANITA  [10] , ANTARES  [11] , SNO  [12]  and BUST  [13]. As yet, no clear evidence has been observed for a neutrino signal originating from a GRB. This paper describes a new search with an increased number of GRBs and a longer exposure of SK data. This paper is organized as follows. In Section 2, we describe the search method including the GRB catalog, the SK detector, data reduction, and analysis methods.
Search Method In order to search for a possible GRB neutrino signal, we looked for correlations between GRBs in the Gamma-ray Coordinates Network (GCN) database  [14]  and SK data taken from 2008 December 7 to 2017 May 31. We have adopted the GRBweb online catalog  [15] , which was developed for neutrino searches with the IceCube observatory. The catalog is compiled from GCN circulars that archive satellite reports. It contains important information about GRB events, including duration (t90), distance from Earth, trigger time (t0), start time (t1) and end time (t2). To avoid confusion with other variables, this paper will refer to the start and end times as t s and t e. GRB events with a t90 duration less than 2 seconds are defined as 'short GRBs', while GRBs with greater duration are classified as 'long GRBs'.
For one GRB (GRB140616A), three neutrino candidate events are found in the fixed search window. Additional checks were performed to determine whether these events constituted a signal. We found that the energy distribution and the transverse distances of these three events are consistent with those of spallation products; thus, we concluded that these events are most likely to be residual spallation events (see Fig. 6   Fig. 6 : Timing and energy data for SK events within a ±1000 sec window around GRB140616A. The dashed line shows the GRB trigger time (t0).
As shown in Table  3 , the number of expected background events N exp in the usual background window is zero; the enlarged background window is required to obtain an estimate of the background. The live time of the enlarged background window is 2826 days. The N obs events are not unique to individual energy regions. Due to the finite energy resolution, there is overlap between some regions. For instance, the same four events constitute N obs for the 38 MeV and 53 MeV regions (see the 65 MeV and 80 MeV regions. For all energy regions, N obs is consistent with the expected background. The fluence limit using data associated with all GRBs is listed in Table  3. Our sample consists of 1813 long GRBs and 323 short GRBs. Fluence limits were calculated for each of these subsamples. Table  4  and Table  5  show the number of observed events, the number of expected background events (assuming that the background rate is same for both long and short GRB subsamples), N 90 , and the neutrino fluence limit for long and short GRBs, respectively.
We compare our limits using data associated with all GRBs divided by number of GRB to those obtained from previous studies at SK  [4]  and Borexino  [8]. This comparison is shown in Fig. 16. It can be seen that this analysis gives better fluence limits in the energy region of 28-80 MeV. In the previous SK study, N 90 was obtained by counting the number of events in the fixed energy range from 7 MeV to 80 MeV; this was done to get the limit at each energy point. As a result, the N 90 reported in the previous analysis has a larger value than in the current analysis. This effect is more pronounced in the larger energy region (>28 MeV). The fluence limit at neutrino energy E ν is obtained by replacing λ(E ν ) in eq. 4 by a delta function δ(E ν -E ν ).
Conclusion A correlation analysis was used to search for neutrinos associated with GRBs. In this study, SK data from December 2008 to March 2017 was searched for neutrino candidates in coincidence with a set of 2208 GRBs. After applying the event reduction to the SK data sample, 250 candidate events remained in a fixed search window of ±500 sec around each GRB trigger time. This search window corresponds to a total livetime of 25. 6 days. The background expected in each 1000 sec search window was estimated to be 0. 114 events. No statistically significant excess was observed within the search window, and the energy distribution of the events is consistent with background. Three candidate events observed in coincidence with GRB140616A seem to be caused by the spallation of oxygen nuclei by cosmic ray muons.
This analysis combined the fixed-window data from all 2208 GRBs to create a sample with large statistics. No significant excess was observed in the stacked data, and so we used this sample to calculate the upper limit to the neutrino fluence. The fluence limit per GRB from 8 MeV to 100 MeV is 5. 07 × 10 5 cm -2. For 189 GRBs whose distance from Earth are known, the upper limits on the total energy emitted by neutrinos at the source was calculated as a function of the distance to these GRBs. An energy-dependent fluence limit was also calculated for the full set of GRBs as well as subsets based on GRB duration. The high detection efficiency and large statistics sample used in this study resulted in a world-leading fluence limit between 28 MeV to 80 MeV.