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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

High Thermal Conductivity, Radiation Resistant Adhesive for High Energy Physics

High Energy Physics systems include particle detector electronics that are integrated with cooling channels and structural housings. Adhesives used to bond these devices to the cooling lines and housings should contribute to cooling by conducting heat away from the electronics and preventing hot spots from developing in either the electronics or the housing. Effective cooling can produce order of magnitude reduction in electronics failure rates. During Phase I, Surmet demonstrated feasibility of a novel radiation-tolerant high-thermal-conductivity adhesive for HEP systems. This was achieved through use of suitable high thermal conductivity fillers to resin adhesive. Feasibility of the technology was demonstrated through key processing and characterization/testing work. The novel filled adhesive was produced in thin-film form to promote heat removal performance and simplify assembly. It was shown to have thermal conductivity >35x that of conventional epoxies. It was shown to successfully withstand strong gamma and proton irradiation. This was demonstrated through density and microstructural characterization as well as thermal conductivity and strength measurement, before and after irradiation. Finally, production of the novel filled adhesive relies on mature processing techniques, simplifying the transition to scale-up and commercialization. During the course of Phase I, Surmet held discussions with a number of researchers working on DOE HEP systems, to understand requirements. These discussions guided the Phase I research, and will be used to plan out follow-on Phase II work. In Phase II research, we will optimize the filled adhesive and tailor it to various product forms to address the multiple applications. Surmet has teamed with a major filled-resin products manufacturer who sees a high commercialization potential for our technology. This team-up will promote development of technology that is well suited for commercialization beyond Phase II.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Data preservation in high energy physics

Data preservation is a mandatory specification for any present and future experimental facility and it is a cost-effective way of doing fundamental research by exploiting unique data sets in the light of the continuously increasing theoretical understanding. This document summarizes the status of data preservation in high energy physics. The paradigms and the methodological advances are discussed from a perspective of more than ten years of experience with a structured effort at international level. The status and the scientific return related to the preservation of data accumulated at large collider experiments are presented, together with an account of ongoing efforts to ensure long-term analysis capabilities for ongoing and future experiments. Transverse projects aimed at generic solutions, most of which are specifically inspired by open science and FAIR principles, are presented as well. A prospective and an action plan are also indicated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Laboratory for Nuclear Science. High Energy Physics Program

High energy and nuclear physics research at MIT is conducted within the Laboratory for Nuclear Science (LNS). Almost half of the faculty in the MIT Physics Department carry out research in LNS at the theoretical and experimental frontiers of subatomic physics. Since 2004, the U.S. Department of Energy has funded the high energy physics research program through grant DE-FG02-05ER41360 (other grants and cooperative agreements provided decades of support prior to 2004). The Director of LNS serves as PI. The grant supports the research of four groups within LNS as “tasks” within the umbrella grant. Brief descriptions of each group are given here. A more detailed report from each task follows in later sections. Although grant DE-FG02-05ER41360 has ended, DOE continues to fund LNS high energy physics research through five separate grants (a research grant for each of the four groups, as well as a grant for AMS Operations). We are pleased to continue this longstanding partnership.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Constraints on Future Analysis Metadata Systems in High Energy Physics

In high energy physics (HEP), analysis metadata comes in many forms—from theoretical cross-sections, to calibration corrections, to details about file processing. Correctly applying metadata is a crucial and often time-consuming step in an analysis, but designing analysis metadata systems has historically received little direct attention. Among other considerations, an ideal metadata tool should be easy to use by new analysers, should scale to large data volumes and diverse processing paradigms, and should enable future analysis reinterpretation. This document, which is the product of community discussions organised by the HEP Software Foundation, categorises types of metadata by scope and format and gives examples of current metadata solutions. Important design considerations for metadata systems, including sociological factors, analysis preservation efforts, and technical factors, are discussed. A list of best practices and technical requirements for future analysis metadata systems is presented. These best practices could guide the development of a future cross-experimental effort for analysis metadata tools.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

REPORT OF RESEARCH ACCOMPLISHMENTS AND FUTURE GOALS HIGH ENERGY PHYSICS

Caltech High Energy Physics (HEP) has a broad program in both experimental and theoretical physics. We are known for our creativity and leadership. The future is uncertain and we strive to be involved in all the major areas of experimental and theoretical HEP physics so no matter where the important discoveries occur we are well positioned to play an important role. An outstanding group of postdoctoral scholars, graduate students, staff scientists, and technical and administrative personnel support our efforts in experimental and theoretical physics. The PI’s on this grant are involved in the following program of experimental and theoretical activities: I) EXPERIMENTAL PHYSICS Our CMS group, led by Harvey Newman and Maria Spiropulu, has played a key role in the discovery and interpretation of the Higgs boson and in searches for new physics. They have important hardware responsibilities in both ECAL and HCAL and are also involved in the upgrades needed for the High Luminosity LHC. Newman's group also develops and operates Grid-based computing, networking, and collaborative systems for CMS and the US HEP community. The charged lepton (Mu2e) and quark BaBar flavor physics group is led by David Hitlin and Frank Porter. On Mu2e they have been instrumental in the design of the calorimeter. Construction responsibilities include one third of the crystals and associated readout as well as the calibration system. They also will have responsibility for a major part of the online system software. Although data taking ceased in 2008 the Caltech BaBar group is active on several new forefront analyses. The neutrino group is led by Ryan Patterson. They are central to NOvA's core oscillation physics program, to calibration, and to detector readiness being responsible for the production and installation of 12,000 APD arrays. They have key roles in neutrino appearance and disappearance analysis in MINOS and MINOS+. Sunil Golwala leads the dark matter direct detection effort. Areas of activity include: CDMS II data analysis, contributions to SuperCDMS Soudan operations and analysis, R&D towards SuperCDMS SNOLAB, development of a novel screener for radiocontamination (the BetaCage), and development of new WIMP detector concepts. Ren-Yuan Zhu leads the HEP crystal laboratory for the advanced detector R&D effort. The crystal lab is involved in development of novel scintillating crystals and has proposed several crystal based detector concepts for future HEP experiments at the energy and intensity frontiers. Its current research effort is concentrated on development of fast crystal scintillators with good radiation hardness and low cost. II) THEORETICAL PHYSICS The main theme of Sergei Gukov's current research is the relation between the geometry of quantum group invariants and their categorification, on the one hand, and the physics of supersymmetric gauge theory and string theory, on the other. Anton Kapustin's research spans a variety of topics in non-perturbative Quantum Field Theory (QFT). His main areas of interest are supersymmetric gauge theories, non-perturbative dualities in QFT, disorder operators, Topological Quantum Field Theory, and non-relativistic QFT. He is also interested in the foundations and possible generalizations of Quantum Mechanics. Hirosi Ooguri's current research has two main components. One is to find exact results in Calabi-Yau compactification of string theory. Another is to explore applications of the AdS/CFT correspondence. He also plans to continue his project with Caltech postdoctoral fellows on BPS spectra of supersymmetric gauge theories in diverse dimensions. John Preskill works on quantum information science. This field may lead to important future technologies, and also lead to new understanding of issues in fundamental physics John Schwarz has been exploring a number of topics in superstring theory/M-theory, supersymmetric gauge theory, and their AdS/CFT relationships. Much of the motivation for these studies is the desire to gain a deeper understanding of superstring theory and M-theory. The research interests of Mark Wise span particle physics, cosmology and nuclear physics. His recent work has centered on extensions of the standard model where baryon number and lepton number are gauged and extensions of the standard model that have novel sources of baryon number violation and new sources of charged lepton flavor violation

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

FSU High Energy Physics

The High Energy Physics group at Florida State University (FSU), which was established in 1958, is engaged in the study of the fundamental constituents of matter and the laws by which they interact. The group comprises theoretical and experimental physicists, who sometimes collaborate on projects of mutual interest. The report highlights the main recent achievements of the group. Significant, recent, achievements of the group’s theoretical physicists include progress in making precise predictions in the theory of the Higgs boson and its associated processes, and in the theoretical understanding of mathematical quantities called parton distribution functions that are related to the structure of composite particles such as the proton. These functions are needed to compare data from particle collisions, such as the proton-proton collisions at the CERN Large Hadron Collider (LHC), with theoretical predictions. The report also describes the progress in providing analogous functions for heavy nuclei, which find application in neutrino physics. The report highlights progress in understanding quantum field theory on a lattice of points in space and time (an area of study called lattice field theory), the progress in constructing several theories of potential new physics that can be tested at the LHC, and interesting new ideas in the theory of the inflationary expansion of the very early universe. The focus of the experimental physicists is the Compact Muon Solenoid (CMS) experiment at CERN. The report, however, also includes results from the D0 experiment at Fermilab to which the group made numerous contributions over a period of many years. The experimental group is particularly interested in looking for new physics at the LHC that may provide the necessary insight to extend the standard model (SM) of particle physics. Indeed, the search for new physics is the primary task of contemporary particle physics, one motivated by the need to explain certain facts, such as the non-zero neutrino masses or the overwhelming astrophysical evidence for an invisible form of matter, called dark matter, that has had a marked effect on the evolution of structure in the universe. The report highlights the main, recent, experimental achievements of the experimental group, which include the investigation of properties of the W and Z bosons; the search for new heavy stable charged particles and the search for a proposed property of nature called supersymmetry in proton-proton collisions that yield high energy photons. In addition, we report a few results from a more general search for supersymmetry at the LHC, initiated by the group. The report also highlights the group's significant contributions, both theoretical and experimental, to the 2012 discovery of the Higgs boson and the measurement of its properties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics

High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapidly increasing fraction of floating point computing power in leadership-class computing facilities and traditional data centers coming from new accelerator architectures, such as GPUs. HEP experiments are now faced with the untenable prospect of rewriting millions of lines of x86 CPU code, for the increasingly dominant architectures found in these computational accelerators. This task is made more challenging by the architecture-specific languages and APIs promoted by manufacturers such as NVIDIA, Intel and AMD. Producing multiple, architecture-specific implementations is not a viable scenario, given the available person power and code maintenance issues. The Portable Parallelization Strategies team of the HEP Center for Computational Excellence is investigating the use of Kokkos, SYCL, OpenMP, std::execution::parallel and alpaka as potential portability solutions that promise to execute on multiple architectures from the same source code, using representative use cases from major HEP experiments, including the DUNE experiment of the Long Baseline Neutrino Facility, and the ATLAS and CMS experiments of the Large Hadron Collider. This cross-cutting evaluation of portability solutions using real applications will help inform and guide the HEP community when choosing their software and hardware suites for the next generation of experimental frameworks. We present the outcomes of our studies, including performance metrics, porting challenges, API evaluations, and build system integration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Machine Learning in High Energy Physics Community White Paper

Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas in machine learning in particle physics with a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

High Energy Physics Network Requirements Review (Final Report, July-October 2020)

Throughout 2020, ESnet and the Office of High Energy Physics (HEP) of the DOE SC organized an ESnet requirements review of HEP-supported activities. Preparation for this event included identification of key stakeholders: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents about their relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments

This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experiments conducted at the High Luminosity Large Hadron Collider. We present our approach for developing a compact neuromorphic model that filters out the sensor data based on the particle's transverse momentum with the goal of reducing the amount of data being sent to the downstream electronics. The incoming charge waveforms are converted to streams of binary-valued events, which are then processed by the SNN. We present our insights on the various system design choices - from data encoding to optimal hyperparameters of the training algorithm - for an accurate and compact SNN optimized for hardware deployment. Our results show that an SNN trained with an evolutionary algorithm and an optimized set of hyperparameters obtains a signal efficiency of about 91% with nearly half as many parameters as a deep neural network.

R. Kulkarni, Shruti↗
DOE OSTI2025

High Energy Physics Network Requirements Review: Final Report, July 2024–December 2024

The world-class research infrastructure at the US Department of Energy (DOE) Office of Science (SC) provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance the core DOE mission in science and technology for its SC program to stimulate rich scientific discoveries and enhance its innovation ecosystem. Research communities gather and flourish around each user facility, bringing together new and enhanced perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by the SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high-performance data, networking, and computing solutions. The ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements review methodology. Between July and December 2024, the Energy Sciences Network (ESnet) and the Office of High Energy Physics (HEP) of the DOE-SC organized an ESnet requirements review of HEP-supported program activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Noise propagation effects in power supply distribution systems for high-energy physics experiments

High-energy physics experiments are supplied by thousands of power supply units placed in distant areas from the front-end electronics. The power supply units and the front-end electronics are connected through long power cables that propagate the output noise from the power supplies to the detector. Here, this paper addresses the effect of long cables on the noise propagation and the impact that those cables have on the conducted emission levels required for the power supplies and the selection of EMI filters for the front-end electronic low-voltage input. Lastly, this analysis is part of the electromagnetic compatibility based design focused on functional safety to define the type of cable, shield connections, EMI filters and power supply specifications required to ensure the successful integration of the detector and, specifically, to achieve the designed performance of the front-end electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

An approach to light distribution for the calibration of high energy physics calorimeters

In high energy physics experiments, calorimeters are calibrated to produce precise and accurate results. Laser light can be used for calibration when the detectors are sensitive to photons in that particular energy range, which is often the case. Moreover, it is not unusual that detection systems consist of hundreds of channels that have to be calibrated independently, which produce stringent requirements on the light distribution system in terms of temporal and spatial stability, energy distribution and timing. Furthermore, the economic factor and the ease of production have to be taken into account. Overall, we present a prototype light distribution system, based on a series of optical beamsplitters, developed for the Muon g-2 experiment at Fermilab.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Status Report of the DPHEP Collaboration: A Global Effort for Sustainable Data Preservation in High Energy Physics

Data from High Energy Physics (HEP) experiments are collected with significant financial and human effort and are mostly unique. An inter-experimental study group on HEP data preservation and long-term analysis was convened as a panel of the International Committee for Future Accelerators (ICFA). The group was formed by large collider-based experiments and investigated the technical and organizational aspects of HEP data preservation. An intermediate report was released in November 2009 addressing the general issues of data preservation in HEP and an extended blueprint paper was published in 2012. In July 2014 the DPHEP collaboration was formed as a result of the signature of the Collaboration Agreement by seven large funding agencies (others have since joined or are in the process of acquisition) and in June 2015 the first DPHEP Collaboration Workshop and Collaboration Board meeting took place. This status report of the DPHEP collaboration details the progress during the period from 2013 to 2015 inclusive.

Amerio, Silvia↗
DOE OSTI2021

PandAna: A Python Analysis Framework for Scalable High Performance Computing in High Energy Physics

Modern experiments in high energy physics analyze millions of events recorded in particle detectors to select the events of interest and make measurements of physics parameters. These data can often be stored as tabular data in files with detector information and reconstructed quantities. Current techniques for event selection in these files lack the scalability needed for high performance computing environments. We describe our work to develop a high energy physics analysis framework suitable for high performance computing. This new framework utilizes modern tools for reading files and implicit data parallelism. Framework users analyze tabular data using standard, easy-to-use data analysis techniques in Python while the framework handles the file manipulations and parallelism without the user needing advanced experience in parallel programming. In future versions, we hope to provide a framework that can be utilized on a personal computer or a high performance computing cluster with little change to the user code.

Groh, Micah↗
DOE OSTI2016

High Energy Physics Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and High Energy Physics, June 10-12, 2015, Bethesda, Maryland

The U.S. Department of Energy (DOE) Office of Science (SC) Offices of High Energy Physics (HEP) and Advanced Scientific Computing Research (ASCR) convened a programmatic Exascale Requirements Review on June 10–12, 2015, in Bethesda, Maryland. This report summarizes the findings, results, and recommendations derived from that meeting. The high-level findings and observations are as follows. Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude — and in some cases greater — than that available currently. The growth rate of data produced by simulations is overwhelming the current ability of both facilities and researchers to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. Data rates and volumes from experimental facilities are also straining the current HEP infrastructure in its ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. A close integration of high-performance computing (HPC) simulation and data analysis will greatly aid in interpreting the results of HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. Long-range planning between HEP and ASCR will be required to meet HEP’s research needs. To best use ASCR HPC resources, the experimental HEP program needs (1) an established, long-term plan for access to ASCR computational and data resources, (2) the ability to map workflows to HPC resources, (3) the ability for ASCR facilities to accommodate workflows run by collaborations potentially comprising thousands of individual members, (4) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, (5) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

FAIR Framework for Physics-Inspired AI in High Energy Physics (Final Technical Report)

The main deliverable of this proposal was to publish data from high energy physics experiments in a FAIR format so that non-specialists could develop machine learning technologies using our data. The Minnesota team of Profs. Cushman, Furmanski and Rusack, from the high energy experiments CDMS, Micro-Boone and CMS, respectively, and Prof J. Sun from Computer Science worked to organize the data, to provide code to access the data, and where relevant provide documentation describing the data. The FAIR4HEP collaboration was formed with groups from UC San Diego, MIT, and the University of Illinois, with the principal investigator was Dr. Huerta. Collectively we collaborated on the publication of datasets from the LHC experiments. Members of the Minnesota group contributed to the common papers published by the collaboration

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗