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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

First Calorimetric Energy Reconstruction of Beam Events with ARAPUCA Light Detector in ProtoDUNE-SP

ProtoDUNE Single Phase at CERN is the large scale prototype for the far detector of the future DUNE experiment. ProtoDUNE is in stable operation since Oct. 2018 at the CERN Neutrino Platform. Test beam data in the energy range of sub-GeV to a few GeV were collected in fall 2018 providing a set of key measurements. Particles (electrons, protons, pions, muons and kaons) are identified combining information from a set of beam-line detectors (Time of Flight, Cherenkov) and TPC reconstruction. Three different technologies are implemented in the protoDUNE photon detector system (PDS). Results from the ARAPUCA response, one of the PDS components, are presented providing first calorimetric energy measurements and particle ID of beam events from LAr scintillation light signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Reconstruction of events recorded with the surface detector of the Pierre Auger Observatory

Cosmic rays arriving at Earth collide with the upper parts of the atmosphere, thereby inducing extensive air showers. When secondary particles from the cascade arrive at the ground, they are measured by surface detector arrays. We describe the methods applied to the measurements of the surface detector of the Pierre Auger Observatory to reconstruct events with zenith angles less than $60^\circ$ using the timing and signal information recorded using the water-Cherenkov detector stations. In addition, we assess the accuracy of these methods in reconstructing the arrival directions of the primary cosmic ray particles and the sizes of the induced showers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE simulation

Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and dQ/dx (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30% for charged-current ν e interactions. Therefore, this pattern recognition achieves 80–90% reconstruction efficiencies for primary leptons, after a 65.8% (72.9%) vertex efficiency for charged-current ν e (ν μ ) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20% energy reconstruction resolutions for charged-current neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Estimation of combinatoric background in seaquest using an event-mixing method

All experiments observing dilepton pairs (e.g. e + e -, μ + μ - ) must confront the existence of a combinatoricbackground caused by the combining of tracks not arising from the same physics vertex. Some method must be devised to calculate and remove this background. In this document we describe a particular event-mixing method relying on many of the unique aspects of the SeaQuest spectrometer and data. The method described here calculates the combinatoric background with correct normalization; i.e., there is no need to assign a floating normalization factor that is then determined in a subsequent fitting procedure. Numerous tests are applied to demonstrate the reliability of the method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Predicting the single-site and multi-site event discrimination power of dual-phase time projection chambers

Dual-phase xenon time projection chambers (TPCs) are widely used in searches for rare dark matter and neutrino interactions, in part because of their excellent position reconstruction capability in 3D. Despite their millimeter-scale resolution along the charge drift axis, xenon TPCs face challenges in resolving single-site (SS) and multi-site (MS) interactions in the transverse plane. In this paper, we build a generic TPC model with an idealized signal readout, and use Fisher Information (FI) to predict its theoretical capability of differentiating SS and MS events using the electroluminescence signal. We also demonstrate via simulation that, when only statistical photon noise is present, the theoretical limits can be approached with conventional reconstruction algorithms like maximum likelihood estimation, and with a convolutional neural network classifier. The implications of this study on future TPC experiments will be discussed.

Physics↗
DOE OSTI2021

How do intermittency and simultaneous processes obfuscate the Arctic influence on midlatitude winter extreme weather events?

Abstract Pronounced changes in the Arctic environment add a new potential driver of anomalous weather patterns in midlatitudes that affect billions of people. Recent studies of these Arctic/midlatitude weather linkages, however, state inconsistent conclusions. A source of uncertainty arises from the chaotic nature of the atmosphere. Thermodynamic forcing by a rapidly warming Arctic contributes to weather events through changing surface heat fluxes and large-scale temperature and pressure gradients. But internal shifts in atmospheric dynamics—the variability of the location, strength, and character of the jet stream, blocking, and stratospheric polar vortex (SPV)—obscure the direct causes and effects. It is important to understand these associated processes to differentiate Arctic-forced variability from natural variability. For example in early winter, reduced Barents/Kara Seas sea-ice coverage may reinforce existing atmospheric teleconnections between the North Atlantic/Arctic and central Asia, and affect downstream weather in East Asia. Reduced sea ice in the Chukchi Sea can amplify atmospheric ridging of high pressure near Alaska, influencing downstream weather across North America. In late winter southward displacement of the SPV, coupled to the troposphere, leads to weather extremes in Eurasia and North America. Combined tropical and sea ice conditions can modulate the variability of the SPV. Observational evidence for Arctic/midlatitude weather linkages continues to accumulate, along with understanding of connections with pre-existing climate states. Relative to natural atmospheric variability, sea-ice loss alone has played a secondary role in Arctic/midlatitude weather linkages; the full influence of Arctic amplification remains uncertain.

Environmental Sciences & Ecology↗
DOE OSTI2025

Taxogenomic analysis of Pichia senei sp. nov. and new insights into hybridization events in the Pichia cactophila species complex

Three strains of a novel yeast species were isolated from necrotic cactus tissues of Cereus saddianus and Micranthocereus dolichospermaticus and from phytotelmata of Bromelia karatas. DNA sequence analysis of the Internal Transcribed Spacer (ITS) region and D1/D2 domains of the large subunit ribosomal RNA, along with whole genome phylogenomic analysis, showed that this yeast is most closely related to Pichia insulana, Pichia cactophila, and Pichia inconspicua. The new species differs by 10–13 nucleotide substitutions from these species in D1/D2 sequences and exhibits <90% genome-wide average nucleotide identity to them. The name Pichia senei sp. nov. is proposed for the novel species, which is homothallic and produces asci with one to four hat-shaped ascospores. The holotype is CBS 16311 (MycoBank MB 858723). Taxogenomic analyses of the P. cactophila species complex, including P. senei, provide new insights about the hybridizations events that shaped this group. Pichia insulana and P. inconspicua are identified as the parental lineages that originated P. cactophila, and P. senei also appears closely related to one of the progenitors of P. inconspicua. We assess phylogeny, heterozygosity, and ploidy to explore the processes shaping diversity, showing how genomic data support yeast species delimitation and reveal complex hybridization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The Ancient Salicoid Genome Duplication Event: A Platform for Reconstruction of De Novo Gene Evolution in Populus trichocarpa

Orphan genes are characteristic genomic features that have no detectable homology to genes in any other species and represent an important attribute of genome evolution as sources of novel genetic functions. Here, we identified 445 genes specific to Populus trichocarpa. Of these, we performed deeper reconstruction of 13 orphan genes to provide evidence of de novo gene evolution. Populus and its sister genera Salix are particularly well suited for the study of orphan gene evolution because of the Salicoid whole-genome duplication event which resulted in highly syntenic sister chromosomal segments across the Salicaceae. We leveraged this genomic feature to reconstruct de novo gene evolution from intergenera, interspecies, and intragenomic perspectives by comparing the syntenic regions within the P. trichocarpa reference, then P. deltoides, and finally Salix purpurea. Furthermore, we demonstrated that 86.5% of the putative orphan genes had evidence of transcription. Additionally, we also utilized the Populus genome-wide association mapping panel, a collection of 1,084 undomesticated P. trichocarpa genotypes to further determine putative regulatory networks of orphan genes using expression quantitative trait loci (eQTL) mapping. Functional enrichment of these eQTL subnetworks identified common biological themes associated with orphan genes such as response to stress and defense response. We also identify a putative cis-element for a de novo gene and leverage conserved synteny to describe evolution of a putative transcription factor binding site. Overall, 45% of orphan genes were captured in trans-eQTL networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In with the old, in with the new: machine learning for time to event biomedical research

The predictive modeling literature for biomedical applications is dominated by biostatistical methods for survival analysis, and more recently some out of the box machine learning approaches. In this article, we show a presentation of a machine learning method appropriate for time-to-event modeling in the area of prostate cancer long-term disease progression. Using XGBoost adapted to long-term disease progression, we developed a predictive model for 118 788 patients with localized prostate cancer at diagnosis from the Department of Veterans Affairs (VA). Our model accounted for patient censoring. Harrell’s c-index for our model using only features available at the time of diagnosis was 0.757 95% confidence interval [0.756, 0.757]. Our results show that machine learning methods like XGBoost can be adapted to use accelerated failure time (AFT) with censoring to model long-term risk of disease progression. Furthermore, the long median survival justifies and requires censoring. Overall, we show that an existing machine learning approach can be used for AFT outcome modeling in prostate cancer, and more generally for other chronic diseases with long observation times.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Transitional events in the spectrophotometric regime between stripped envelope and superluminous supernovae

ABSTRACT The division between stripped-envelope supernovae (SE-SNe) and superluminous supernovae (SLSNe) is not well-defined in either photometric or spectroscopic space. While a sharp luminosity threshold has been suggested, there remains an increasing number of transitional objects that reach this threshold without the spectroscopic signatures common to SLSNe. In this work, we present data and analysis on four SNe transitional between SE-SNe and SLSNe; the He-poor SNe 2019dwa and 2019cri, and the He-rich SNe 2019hge and 2019unb. Each object displays long-lived and variable photometric evolution with luminosities around the SLSN threshold of Mr < −19.8 mag. Spectroscopically however, these objects are similar to SE-SNe, with line velocities lower than either SE-SNe and SLSNe, and thus represent an interesting case of rare transitional events.

Prentice, S. J. (ORCID:0000000304866242)↗
DOE OSTI2024

A dark siren measurement of the Hubble constant using gravitational wave events from the first three LIGO/Virgo observing runs and DELVE

The current and next observation seasons will detect hundreds of gravitational waves (GWs) from compact binary systems coalescence at cosmological distances. When combined with independent electromagnetic measurements, the source redshift will be known, and we will be able to obtain precise measurements of the Hubble constant H_0 via the distance–redshift relation. However, most observed mergers are not expected to have electromagnetic counterparts, which prevents a direct redshift measurement. In this scenario, one possibility is to use the dark sirens method that statistically marginalizes over all the potential host galaxies within the GW location volume to provide a probabilistic source redshift. Here we presented H_0 measurements using two new dark sirens compared to previous analyses using DECam data: GW190924|$\_$|021846 and GW200202|$\_$|154313. The photometric redshifts of the possible host galaxies of these two events are acquired from the DECam Local Volume Exploration Survey (DELVE) carried out on the Blanco telescope at Cerro Tololo. The combination of the H_0 posterior from GW190924|$\_$|021846 and GW200202|$\_$|154313 together with the bright siren GW170817 leads to |$H_{0} = 68.84^{+15.51}_{-7.74}\, \rm {km\, s^{-1}\, Mpc^{-1}}$|⁠. Including these two dark sirens improves the 68 per cent confidence interval (CI) by 7 per cent over GW170817 alone. This demonstrates that the addition of well-localized dark sirens in such analysis improves the precision of cosmological measurements. Using a sample containing 10 well-localized dark sirens observed during the third LIGO/Virgo observation run, without the inclusion of GW170817, we determine a measurement of |$H_{0} = 76.00^{+17.64}_{-13.45}\, \rm {km\, s^{-1}\, Mpc^{-1}}$|⁠.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Transient fading X-ray emission detected during the optical rise of a tidal disruption event

ABSTRACT We report on the SRG/eROSITA detection of ultra-soft ($kT=47^{+5}_{-5}$ eV) X-ray emission (LX =$2.5^{+0.6}_{-0.5} \times 10^{43}$ erg s−1) from the tidal disruption event (TDE) candidate AT 2022dsb ∼14 d before peak optical brightness. As the optical luminosity increases after the eROSITA detection, then the 0.2–2 keV observed flux decays, decreasing by a factor of ∼39 over the 19 d after the initial X-ray detection. Multi-epoch optical spectroscopic follow-up observations reveal transient broad Balmer emission lines and a broad He ii 4686 Å emission complex with respect to the pre-outburst spectrum. Despite the early drop in the observed X-ray flux, the He ii 4686 Å complex is still detected for ∼40 d after the optical peak, suggesting the persistence of an obscured hard ionizing source in the system. Three outflow signatures are also detected at early times: (i) blueshifted H α emission lines in a pre-peak optical spectrum, (ii) transient radio emission, and (iii) blueshifted Ly α absorption lines. The joint evolution of this early-time X-ray emission, the He ii 4686 Å complex, and these outflow signatures suggests that the X-ray emitting disc (formed promptly in this TDE) is still present after optical peak, but may have been enshrouded by optically thick debris, leading to the X-ray faintness in the months after the disruption. If the observed early-time properties in this TDE are not unique to this system, then other TDEs may also be X-ray bright at early times and become X-ray faint upon being veiled by debris launched shortly after the onset of circularization.

Malyali, A. (ORCID:0000000288514019)↗
DOE OSTI2021

Optical follow-up observation for GW event S190510g using Subaru/Hyper Suprime-Cam

Abstract A gravitational wave event, S190510g, which was classified as a binary-neutron-star coalescence at the time of preliminary alert, was detected by LIGO/Virgo collaboration on 2019 May 10. At 1.7 hours after the issue of its preliminary alert, we started a target-of-opportunity imaging observation in the Y band to search for its optical counterpart using the Hyper Suprime-Cam (HSC) on the Subaru Telescope. The observation covers a 118.8 deg2 sky area corresponding to $11.6\%$ confidence in the localization skymap released in the preliminary alert and $1.2\%$ in the updated skymap. We divided the observed area into two fields based on the availability of HSC reference images. For the fields with the HSC reference images, we applied an image subtraction technique; for the fields without the HSC reference images, we sought individual HSC images by matching a catalog of observed objects with the PS1 catalog. The search depth is 22.28 mag in the former method and the limit of search depth is 21.3 mag in the latter method. Subsequently, we performed visual inspection and obtained 83 candidates using the former method and 50 candidates using the latter method. Since we only have the one-day photometric data, we evaluated the probability of candidates being located inside the 3D skymap by estimating their distances with photometry of associated extended objects. We found three candidates are likely located inside the 3D skymap and concluded they could be a counterpart of S190510g, while most of the 133 candidates were likely to be supernovae because the number density of candidates was consistent with the expected number of supernova detections. By comparing our observational depth with a light-curve model of such a kilonova reproducing AT2017gfo, we show that early deep observations with the Subaru/HSC can capture the rising phase of the blue component of a kilonova at the estimated distance of S190510g (∼230 Mpc).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

KamNet: An integrated spatiotemporal deep neural network for rare event searches in KamLAND-Zen

Rare event searches allow us to search for new physics at energy scales inaccessible with other means by leveraging specialized large-mass detectors. Machine learning provides a new tool to maximize the information provided by these detectors. The information is sparse, which forces these algorithms to start from the lowest level data and exploit all symmetries in the detector to produce results. In this work we present KamNet, which harnesses breakthroughs in geometric deep learning and spatiotemporal data analysis to maximize the physics reach of KamLAND-Zen, a kiloton scale spherical liquid scintillator detector searching for 0⁢νβ⁢β. Using a simplified background model for KamLAND, we show that KamNet outperforms a conventional convolutional neural network (CNN) on benchmarking Monte Carlo simulations with an increasing level of robustness. Using simulated data, we then demonstrate KamNet's ability to increase KamLAND-Zen's sensitivity to 0ν⁢ββ and 2⁢ν⁢β⁢β decay to excited states. A key component of this work is the addition of an attention mechanism to elucidate the underlying physics KamNet is using for the background rejection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Event generation with normalizing flows

We present a novel integrator based on normalizing flows which can be used to improve the unweighting efficiency of Monte-Carlo event generators for collider physics simulations. In contrast to machine learning approaches based on surrogate models, our method generates the correct result even if the underlying neural networks are not optimally trained. We exemplify the new strategy using the example of Drell-Yan type processes at the LHC, both at leading and partially at next-to-leading order QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quasielastic electromagnetic scattering cross sections and world data comparisons in the GENIE Monte Carlo event generator

The usage of Monte Carlo neutrino event generators (MC$\textit{ν}$EGs) is a norm within the high-energy $\textit{ν}$ scattering community. The relevance of quasielastic (QE) energy regimes to $\textit{ν}$ oscillation experiments implies that accurate calculations of $\textit{ν}$A cross sections in this regime will be a key contributor to reducing the systematic uncertainties affecting the extraction of oscillation parameters. In spite of this, many MC$\textit{ν}$EGs utilize highly phenomenological, parametrized models of QE scattering cross sections. Moreover, a culture of validation of MC$\textit{ν}$EGs against prolific electron ($\textit{e}$) scattering data has been historically lacking. In this work, we implement new eA cross sections obtained from nuclear ab initio approaches in GENIE, the primary MC$\textit{ν}$EG utilized by the FNAL community. In particular, we utilize results from quantum MC methods which solve the many-body nuclear problem in the short-time approximation (STA), allowing consistent retention of two-nucleon dynamics which are crucial to explain available nuclear electromagnetic (electroweak) data over a wide range of energy and momentum transfers. This new implementation in GENIE is fully tested against the world QE electromagnetic data, finding agreement with available data below ~2 GeV of beam energy with the aid of a scaling function formalism. The STA is currently limited to study $\textit{A}$ ≤ 12 nuclei, however, its semi-inclusive multibody identity components are exportable to other many-body computational techniques such as auxiliary field diffusion MC which can reach $\textit{A}$ ≤ 40 systems while continuing to realize the factorization contained within the STA’s multinucleon dynamics. Together, these developments promise to make future experiments such as DUNE more accurate in their assessment of MC$\textit{ν}$EG systematics, $\textit{ν}$ properties, and potentially empower the discovery of physics beyond the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Measurements of jet observables sensitive to $\textit{b}$-quark fragmentation in $t\bar{t}$ events at the LHC with the ATLAS detector

Several observables sensitive to the fragmentation of $\textit{b}$ quarks into $\textit{b}$ hadrons are measured using 36 fb -1 of $\sqrt{s}$ = 13 TeV proton-proton collision data collected with the ATLAS detector at the LHC. Jets containing b hadrons are obtained from a sample of dileptonic $t\bar{t}$ events, and the associated set of charged-particle tracks is separated into those from the primary $\textit{pp}$ interaction vertex and those from the displaced b-decay secondary vertex. This division is used to construct observables that characterize the longitudinal and transverse momentum distributions of the $\textit{b}$ hadron within the jet. The measurements have been corrected for detector effects and provide a test of heavy-quark-fragmentation modeling at the LHC in a system where the top-quark decay products are color connected to the proton beam remnants. The unfolded distributions are compared with the predictions of several modern Monte Carlo parton-shower generators and generator tunes, and a wide range of agreement with the data is observed, with $\textit{p}$ values varying from 5 × 10 -4 to 0.98. These measurements complement similar measurements from $e^+e^-$ collider experiments in which the $\textit{b}$ quarks originate from a color singlet $Z/γ^{\ast}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for pair production of higgsinos in events with two Higgs bosons and missing transverse momentum in $\sqrt{𝑠}$ = 13 TeV 𝑝⁢𝑝 collisions at the ATLAS experiment

This paper presents a search for pair production of higgsinos, the supersymmetric partners of the Higgs bosons, in scenarios with gauge-mediated supersymmetry breaking. Each higgsino is assumed to decay into a Higgs boson and a nearly massless gravitino. The search targets events where each Higgs boson decays into $b\bar{b}$, leading to a reconstructed final state with at least three energetic 𝑏-jets and missing transverse momentum. Two complementary analysis channels are used, with each channel specifically targeting either low or high values of the higgsino mass. The low-mass (high-mass) channel exploits 126 (139) fb −1 of $\sqrt{𝑠}$ = 13 TeV data collected by the ATLAS detector during Run 2 of the Large Hadron Collider. No significant excess above the Standard Model prediction is found. At 95% confidence level, masses between 130 GeV and 940 GeV are excluded for higgsinos decaying exclusively into Higgs bosons and gravitinos. Exclusion limits as a function of the higgsino decay branching ratio to a Higgs boson are also reported.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗