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DOE OSTI2023

Search for long-lived particles using out-of-time trackless jets in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for long-lived particles decaying in the outer regions of the CMS silicon tracker or in the calorimeters is presented. The search is based on a data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the CMS detector at the LHC in 2016–2018, corresponding to an integrated luminosity of 138 fb −1 . A novel technique, using nearly trackless and out-of-time jet information combined in a deep neural network discriminator, is employed to identify decays of long-lived particles. The results are interpreted in a simplified model of chargino-neutralino production, where the neutralino is the next-to-lightest supersymmetric particle, is long-lived, and decays to a gravitino and either a Higgs or Z boson. This search is most sensitive to neutralino proper decay lengths of approximately 0.5 m, for which masses up to 1.18 TeV are excluded at 95% confidence level. The current search is the best result to date in the mass range from the kinematic limit imposed by the Higgs boson mass up to 1.8 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

High-level hadronic tau lepton triggers of the CMS experiment in proton-proton collisions at √(s) = 13.6 TeV

The trigger system of the CMS detector is pivotal in the acquisition of data for physics measurements and searches. Studies of final states characterized by hadronic decays of tau leptons require the reconstruction and the identification of genuine tau leptons against quark- and gluon-initiated jets at the trigger level. This is a difficult task, particularly as improvements to the LHC have resulted in an increased number of interactions per bunch crossing in recent years. To address this challenge, a series of machine-learning algorithms with high identification efficiency and low computational cost have been incorporated into the high-level trigger for hadronically decaying tau leptons. In this paper, these developments and the trigger performance are summarized using data collected by the CMS experiment in proton-proton collisions at √(s) = 13.6 TeV in 2022–2023, corresponding to an integrated luminosity of 62 fb -1 .

Particle identification methods↗

DOE OSTI2023

Deep Search for Gamma-Ray Emission from the Accreting X-Ray Pulsar 1A 0535+262

Binary systems are a well-established subclass of gamma-ray sources. The high mass X-ray binary pulsar 1A 0535+262 has been considered to be a possible gamma-ray emitter for a long time, although former gamma-ray searches using the Fermi Large Area Telescope (LAT) and VERITAS data resulted in upper limits only. We aim at a deep search for gamma-ray emission and pulsations from 1A 0535+262 using more than 13 yr of Fermi-LAT data. The analysis was performed for both the whole Fermi-LAT data set, as well as for the X-ray outbursts that 1A 0535+262 has experienced since the launch of Fermi. Various X-ray observations have been used to generate the ephemeris for the pulsation search. We also investigate the long-term gamma-ray flux variability and perform orbital phase-resolved analysis for the outbursts. We did not detect any steady or pulsed gamma-ray emission from 1A 0535+262 during the whole Fermi-LAT mission span or its X-ray outbursts. We thus derived the deepest gamma-ray luminosity upper limits to date at the 95% confidence level to be around (2.3–4.7) × 10 32 erg s -1 depending on different spectral indices assumed, which results in a ratio of L γ to L X (2–150 keV) being (1.9–3.9) × 10 -6 .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Measuring dark neutrinos and light using external and internal components of LArTPCs

The so-called MiniBooNE low-energy excess has been a long-standing questionfor beyond Standard Model (BSM) physics in the neutrino field. The ShortBaseline Neutrino (SBN) program was proposed to investigate and provide furtherinsights into this excess. The SBN program utilises Liquid Argon Time ProjectionChamber (LArTPC) technology, which allows for precise measurements of neutrinointeractions and holds great potential for addressing significant open questions inthe field. Within the SBN program, the Short Baseline Near Detector (SBND) plays acrucial role as one of the near detector, positioned just 110 meters from the neutrinosource. Being located on the surface, SBND is exposed to cosmic-ray background,and to mitigate this, the Cosmic Ray Tagger (CRT) system has been implemented toidentify and veto cosmic background events, thereby enhancing the purity of neutrinointeractions. Additionally, the CRT system can be used to search for BSM signatures,such as the dark neutrinos, which have been proposed to explain the MiniBooNElow-energy excess. This thesis presents a novel approach for searching for darkneutrinos using existing SBND CRT data, collected with a unique setup called theCRT Beam Telescope. An extended model-independent search based on the darkneutrino analysis is also presented. The sensitivity plot for the CRT Beam Telescopeis compared with an estimated MiniBooNE exclusion limit. Furthermore, this thesiscovers the commissioning work conducted for the SBND CRT system, which is vitalfor ensuring optimal performance. The LArTPC technology also benefits from liquidargon’s excellent scintillation properties, producing abundant scintillation light. Thisthesis describes a method developed to understand the detector response to thescintillation light produced across the LArTPC, enhancing our understanding of thedetector’s performance and facilitating more accurate measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Searches for new phenomena in events with two leptons, jets, and missing transverse momentum in 139 fb –1 of √s = 13 TeV $pp$ collisions with the ATLAS detector

Searches for new phenomena inspired by supersymmetry in final states containing an e + e – or μ + μ – pair, jets, and missing transverse momentum are presented. These searches make use of proton–proton collision data with an integrated luminosity of 139 fb –1 , collected during 2015–2018 at a centre-of-mass energy √s = 13 TeV by the ATLAS detector at the Large Hadron Collider. Two searches target the pair production of charginos and neutralinos. One uses the recursive-jigsaw reconstruction technique to follow up on excesses observed in 36.1 fb –1 of data, and the other uses conventional event variables. The third search targets pair production of coloured supersymmetric particles (squarks or gluinos) decaying through the next-to-lightest neutralino ($\tilde{χ}$$^{0}_{2}$) via a slepton ($\tilde{ℓ}$) or Z boson into ℓ + ℓ – $\tilde{χ}$$^{0}_{1}$ , resulting in a kinematic endpoint or peak in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectations. Results are interpreted using simplified models and exclude masses up to 900 GeV for electroweakinos, 1550 GeV for squarks, and 2250 GeV for gluinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗

DOE OSTI2025

Search for dark matter from the center of the Earth with 10 years of IceCube data

The nature of dark matter remains unresolved in fundamental physics. Weakly Interacting Massive Particles (WIMPs), which could explain the nature of dark matter, can be captured by celestial bodies like the Sun or Earth, leading to enhanced self-annihilation into Standard Model particles including neutrinos detectable by neutrino telescopes such as the IceCube Neutrino Observatory. This article presents a search for muon neutrinos from the center of the Earth performed with 10 years of IceCube data using a track-like event selection. We considered a number of WIMP annihilation channels (χχ→τ+τ-$$\chi \chi \rightarrow \tau ^+\tau ^-$$/W+W-$$W^+W^-$$/bb¯$$b\bar{b}$$) and masses ranging from 10 GeV to 10 TeV. No significant excess over background due to a dark matter signal was found while the most significant result corresponds to the annihilation channel χχ→bb¯$$\chi \chi \rightarrow b\bar{b}$$ for the mass mχ=250$$m_{\chi }=250$$ GeV with a post-trial significance of 1.06σ$$1.06\sigma $$. Our results are competitive with previous such searches and direct detection experiments. Our upper limits on the spin-independent WIMP scattering are world-leading among neutrino telescopes for WIMP masses mχ>100$$m_{\chi }>100$$ GeV.

Abbasi, R↗

DOE OSTI2023

Search for non-resonant production of semi-visible jets using Run 2 data in ATLAS

Semi-visible jets, with a significant contribution to the event's missing transverse momentum, can arise in strongly interacting dark sectors. This results in an event topology where one of the jets can be aligned with the direction of the missing transverse momentum. The first search for semi-visible jets produced via a t-channel mediator exchange is presented. The analysis uses proton-proton collisions with an integrated luminosity of 139 fb —1 and a centre-of-mass energy of 13 TeV, collected with the ATLAS detector during the Run 2 of the LHC. No excess over Standard Model predictions is observed. Assuming a coupling strength of unity between the mediator, a Standard Model quark and a dark quark, mediator masses up to 2.7 TeV are excluded at the 95% confidence level. Upper limits on the coupling strength are also derived.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

The Event Detection System in the NEXT-White Detector

This article describes the event detection system of the NEXT-White detector, a 5 kg high pressure xenon TPC with electroluminescent amplification, located in the Laboratorio Subterráneo de Canfranc (LSC), Spain. The detector is based on a plane of photomultipliers (PMTs) for energy measurements and a silicon photomultiplier (SiPM) tracking plane for offline topological event filtering. The event detection system, based on the SRS-ATCA data acquisition system developed in the framework of the CERN RD51 collaboration, has been designed to detect multiple events based on online PMT signal energy measurements and a coincidence-detection algorithm. Implemented on FPGA, the system has been successfully running and evolving during NEXT-White operation. The event detection system brings some relevant and new functionalities in the field. A distributed double event processor has been implemented to detect simultaneously two different types of events thus allowing simultaneous calibration and physics runs. This special feature provides constant monitoring of the detector conditions, being especially relevant to the lifetime and geometrical map computations which are needed to correct high-energy physics events. Other features, like primary scintillation event rejection, or a double buffer associated with the type of event being searched, help reduce the unnecessary data throughput thus minimizing dead time and improving trigger efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Search for low-mass resonances decaying into two jets and produced in association with a photon or a jet at √s = 13 TeV with the ATLAS detector

A search is performed for localized excesses in the low-mass dijet invariant mass distribution, targeting a hypothetical new particle decaying into two jets and produced in association with either a high transverse momentum photon or a jet. The search uses the full Run 2 data sample from LHC proton-proton collisions collected by the ATLAS experiment at a center-of-mass energy of 13 TeV during 2015–2018. Two variants of the search are presented for each type of initial-state radiation: one that makes no jet flavor requirements and one that requires both of the jets to have been identified as containing b-hadrons. No excess is observed relative to the Standard Model prediction, and the data are used to set upper limits on the production cross section for a benchmark Z' model and, separately, for generic, beyond the Standard Model scenarios which might produce a Gaussian-shaped contribution to dijet invariant mass distributions. The results extend the current constraints on dijet resonances to the mass range between 200 and 650 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

rcsb-api : Python Toolkit for Streamlining Access to RCSB Protein Data Bank APIs

The Protein Data Bank (PDB) was founded in 1971 as the first open-access digital data resource in biology to serve as the single global archive for three-dimensional (3D) macromolecular structure data. Current PDB holdings exceed 230,000 experimentally determined structures of proteins, nucleic acids, viruses, and macromolecular machines. The RCSB Protein Data Bank RCSB.org research-focused web portal facilitates search, analyses, and visualization of every PDB structure along with more than one million Computed Structure Models from AlphaFold DB and the ModelArchive. It is powered by a set of publicly available Application Programming Interfaces (APIs) that both support RCSB.org users and provide programmatic access to PDB data. Given the breadth and levels of granularity encompassed in this rich data collection, efficiently accessing the information programmatically may be challenging for new users. RCSB PDB has developed a Python software package, rcsb-api , that facilitates easy and efficient use of RCSB PDB APIs within a Python environment. This software tool is designed to streamline access to the extensive corpus of data housed within the PDB, enabling researchers to search, retrieve, and analyze 3D biostructure data seamlessly. Its use will accelerate research in structural biology, molecular biology and biochemistry, drug discovery, and bioinformatics by providing more efficient tools for data integration and analysis. The new toolkit is available on GitHub (github.com/rcsb/py-rcsb-api) and published to the public Python package repository (PyPI) to foster wider usage and support basic and applied research in fundamental biology, biomedicine, and the energy sciences.

FAIR principles↗

DOE OSTI2023

Accelerating scientific discoveries through data-driven innovations

Developing artificial intelligence (AI) and machine learning (ML) methods that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these challenges and thereby accelerating scientific discoveries and industrial innovations, calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and is able to execute them in modern high-performance computing (HPC) environments at scale. This Patterns special collection "Accelerating scientific discoveries through data-driven innovations" features articles that showcase the promising roles of AI/ML and data-driven modeling in accelerating scientific discoveries and may inspire the next wave of data-driven innovations in various scientific domains.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Search for PeV Gamma-Ray Emission from the Southern Hemisphere with 5 Yr of Data from the IceCube Observatory

The measurement of diffuse PeV gamma-ray emission from the Galactic plane would provide information about the energy spectrum and propagation of Galactic cosmic rays, and the detection of a pointlike source of PeV gamma-rays would be strong evidence for a Galactic source capable of accelerating cosmic rays up to at least a few PeV. This paper presents several unbinned maximum-likelihood searches for PeV gamma-rays in the Southern Hemisphere using 5 yr of data from the IceTop air shower surface detector and the in-ice array of the IceCube Observatory. The combination of both detectors takes advantage of the low muon content and deep shower maximum of gamma-ray air showers and provides excellent sensitivity to gamma-rays between ~0.6 and 100 PeV. Our measurements of pointlike and diffuse Galactic emission of PeV gamma-rays are consistent with the background, so we constrain the angle-integrated diffuse gamma-ray flux from the Galactic plane at 2 PeV to 2.61 × 10 -19 cm -2 s -1 TeV -1 at 90% confidence, assuming an E -3 spectrum, and we estimate 90% upper limits on pointlike emission at 2 PeV between 10 -21 and 10 -20 cm -2 s -1 TeV -1 for an E -2 spectrum, depending on decl. Furthermore, we exclude unbroken power-law emission up to 2 PeV for several TeV gamma-ray sources observed by the High Energy Spectroscopic System and calculate upper limits on the energy cutoffs of these sources at 90% confidence. We also find no PeV gamma-rays correlated with neutrinos from IceCube's high-energy starting event sample. Lastly, these are currently the strongest constraints on PeV gamma-ray emission.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Untargeted, tandem mass spectrometry (LC/MS-MS) metaproteomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization. This package contains soil metaproteomics data in the context of site specific metagenomes from soil depth profiles in three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. These metaproteomes were collected in 2018 after 4.5 years of warming from five depth intervals (0-10 cm, 10-30 cm, 30-45 cm, 45-60 cm, 60-80 cm). For protein identification, the collected spectra were searched following a target-decoy search strategy against a database of metagenome predicted proteins (covering 96 samples from 2014 to 2021) representing the complete sequence diversity at the site. Data was searched with mass spectrometry database search tool (MS-GF+) using Pacific Northwest National Laboratory (PNNL)'s Data Management System (DMS) Processing pipeline. The metagenomes are published as part of another data package. Raw metaproteomic data and the data products from MS-GF+ are deposited in the Mass Spectrometry Interactive Virtual Environment (MassIVE) database under accession no. MSV000097826. Here we present a dataset that includes spectral counts for the detected proteins across samples (EMSL50964_BrodieAllMAGs_Globals_SC.txt), the sequences of the detected proteins, and sample metadata file that contains site information for the soil metaproteome samples.

Belowground Biogeochemistry Science Focus Area↗

DOE OSTI2024

Search for a third-generation leptoquark coupled to a τ lepton and a b quark through single, pair, and nonresonant production in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search is presented for a third-generation leptoquark (LQ) coupled exclusively to a τ lepton and a b quark. The search is based on proton-proton collision data at a center-of-mass energy of 13 TeV recorded with the CMS detector, corresponding to an integrated luminosity of 138 fb$^{−1}$. Events with τ leptons and a varying number of jets originating from b quarks are considered, targeting the single and pair production of LQs, as well as nonresonant t-channel LQ exchange. An excess is observed in the data with respect to the background expectation in the combined analysis of all search regions. For a benchmark LQ mass of 2 TeV and an LQ-b-τ coupling strength of 2.5, the excess reaches a local significance of up to 2.8 standard deviations. Upper limits at the 95% confidence level are placed on the LQ production cross section in the LQ mass range 0.5–2.3 TeV, and up to 3 TeV for t-channel LQ exchange. Leptoquarks are excluded below masses of 1.22–1.88 TeV for different LQ models and varying coupling strengths up to 2.5. The study of nonresonant ττ production through t-channel LQ exchange allows lower limits on the LQ mass of up to 2.3 TeV to be obtained.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Search for Double Beta Decays of Xe134 with EXO-200 Phase II

EXO-200 was a leading double beta decay experiment consisting of a single-phase, enriched liquid xenon time projection chamber filled with an admixture of 80.672% ^{136}Xe and 19.098% ^{134}Xe. The detector operated at the Waste Isolation Pilot Plant between 2010 and 2018 and was designed to search for double beta decay of ^{136}Xe. Data were acquired in two phases separated by a period of detector upgrades. We report on the search for 0νββ and 2νββ decay of ^{134}Xe with Phase II EXO-200 data, with median 90% CL exclusion sensitivity to half-life T_{1/2}^{0ν}≥3.7×10^{23} yr and T_{1/2}^{2ν}≥2.6×10^{21} yr, respectively. No statistically significant signal is observed for either decay mode. We set a world-leading lower limit on the half-life of the neutrinoless decay mode of ^{134}Xe of T_{1/2}^{0ν}≥8.7×10^{23} (90% CL) and the second strongest constraint on the two-neutrino decay of T_{1/2}^{2ν}≥2.9×10^{21} (90% CL), a threefold improvement over the EXO-200 Phase I measurement. New constraints are also set for the 2νββ and 0νββ decays of ^{134}Xe to the lowest excited state of ^{134}Ba.

Al Kharusi, S↗

DOE OSTI2023

Connecting People to Data: Enabling Data Connected Communities through Enhancements to the Geothermal Data Repository: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented a series of new features designed to connect people to data. These features, which are based on feedback from the GDR user community and surveys of the greater geothermal research community, are designed to improve data quality and empower members of all communities to better engage with geothermal data resources by providing universal access to data and by improving the connections between data providers, subject matter experts, and the communities of people using GDR data. This paper will explore some of the recent enhancements made to the GDR to improve data discoverability, reduce submission time, and result in better quality data submissions. These improvements include the ability for users to save a list of their favorite datasets, search for insight into geothermal datasets or data availability, or sign up to receive notifications of future updates to specific datasets. These improvements aim to enhance the overall user experience of the GDR while further connecting communities to the data they need to inform decisions, advance geothermal research, and develop innovative solutions to local energy problems.

DOE↗

DOE OSTI2023

Connecting People to Data: Enabling Data Connected Communities through Enhancements to the Geothermal Data Repository

access↗