SEARCH · Engineering Papers

Results for “High Energy Physics”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Domain-adversarial graph neural networks for Λ hyperon identification with CLAS12

Machine learning methods and in particular Graph Neural Networks (GNNs) have revolutionized many tasks within the high energy physics community. Particularly in the realm of jet tagging, GNNs and domain adaptation have been especially successful. However, applications with lower energy events have not received as much attention. Here, we report on the novel use of GNNs and a domain-adversarial training method to identify Λ hyperon events with the CLAS12 experiment at Jefferson Lab. The GNN method we have developed increases the purity of the Λ yield by a factor of 1.95 and by 1.82 using the domain-adversarial training. This work also provides a good benchmark for developing event tagging machine learning methods for the Λ and other channels at CLAS12 and other experiments, such as the planned Electron Ion Collider.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Impact of proton irradiation on 4H-SiC Low Gain Avalanche Detectors (LGADs)

Silicon carbide (SiC) particle detectors have the potential to provide time resolutions and robust performance in extreme environments which exceed that of silicon detectors. In this work 4H-SiC low gain avalanche detectors (LGADs) and complementary PiN diodes were irradiated with 2.5 GeV protons at fluences up to 3.33 × 10 14 p/cm 2 . The electrostatic performance of both irradiated and non-irradiated devices was evaluated using I-V and C-V measurements. Moreover, charge collection measurements using α particles were also conducted. SiC LGADs displayed a loss in rectification, high ON-state resistances >10 10 Ω-cm 2 , and the complete removal of gain when exposed to the highest proton fluence. Additionally, the reductions in capacitance and OFF-state current pointed to compensation of the gain layer as a gain reducing mechanism. The introduction of radiation-induced defects also hinders carrier acceleration, which reduces impact ionization and further gain reduction. LGADs exposed to a fluence of 1 × 10 14 p/cm 2 experienced a partial recovery in gain (originally having a value of ∼ 2) with a value of ∼ 1.65 when applying a bias of 500 V. Charge trapping was also seen in the reduction of charge collection efficiency (CCE) to ∼ 65% for the PiN diode. However, despite the reduction in device performance, the demonstration of a measurable signal after irradiation points to the potential of SiC LGAD detectors for future high energy physics applications.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Studying AC-LGAD strip sensors from laser and testbeam measurements

Here, this paper presents the setup assembled to characterize and measure the spatial and timing resolutions of AC-coupled Low Gain Avalanche Diodes (AC-LGADs), using a 1060 nm laser source to deposit initial charges with a defined calibration methodology. The results were compared to those obtained with a 120 GeV proton beam. Despite the differences in the charge deposition mechanism between the laser and proton beam, the spatial and temporal resolutions were found to be compatible between the two sources after calibration. With 4D tracking detectors expected to play a vital role in upcoming collider experiments, we foresee this work as a way to evaluate the performance of semiconductor sensors that can augment testbeam measurements and accelerate R&D efforts. Additionally, simulation studies using Silvaco TCAD and Weightfield2 were carried out to understand the various contributing factors to the total time resolution in AC-LGAD sensors, measured using the laser source.

FOS: Physical sciences↗

DOE OSTI2022

Design of the cryostat for High Field Vertical Magnet Testing Facility at Fermilab

High Field Vertical Magnet Test Facility (HFVMTF) is a joint project between the Office of High Energy Physics (HEP) and the Office of Fusion Energy Sciences (FES). Its construction is currently under way at Fermi National Accelerator Laboratory (Fermilab). As a part of the project a new double bath superfluid helium cryostat has been designed. The cryostat can accommodate magnets with up to 20 tonne weight and 1.3 m diameter. This paper discusses challenges and solutions for cryostat, lambda plate and heat exchanger design, and presents results of performance analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Cryogenic and safety design of the future high field cable test facility at Fermilab

The HFVMTF (High Field Vertical Magnet Test Facility) is a new experimental facility under development at Fermi National Accelerator Laboratory (FNAL) to test large superconducting magnets (up to 20 tons weight and 1.3 m diameter) in a double bath superfluid helium cryostat (1.9 K and 1.2 bar). Coupled with a superconducting dipole magnet fabricated by Lawrence Berkeley National Laboratory (LBNL), this facility will be able to test future high-temperature superconductor (HTS) cables under a background magnetic field of 15 T for fusion magnets. This paper describes the design of the cryostat and its 1.4-meter diameter lambda plate, as well as the different components for a safe operation of the facility, even during critical events such a magnet quench or a vacuum breaking situation. The project is funded by US DOE Offices of Science, High Energy Physics (HEP), and Fusion Energy Sciences (FES).

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Indexed improvements for real-time trotter evolution of a (1 + 1) field theory using NISQ quantum computers

Today's quantum computers offer the possibility of performing real-time calculations for quantum field theory scattering processes motivated by high energy physics. In order to follow the successful roadmap which has been established for the calculation of static properties at Euclidean time, it is crucial to develop new algorithmic methods to deal with the limitations of current noisy intermediate-scale quantum (NISQ) devices and to establish quantitative measures of the progress made with different devices. In this paper, we report recent progress in these directions. We show that nonlinear aspects of the trotter errors allow us to take much larger step then suggested by low-order analysis. This is crucial to reach physically relevant time scales with today's NISQ technology. We propose to use an index averaging absolute values of the difference between the accurately calculated trotter evolution of site occupations and their actual measurements on NISQ machines (G index) as a measure to compare results that have been obtained from different hardware platforms. Using the transverse Ising model in one spatial dimension with four sites we apply this metric across several hardware platforms. We study the results including readout mitigation and Richardson extrapolations and show that the mitigated measurements are very effective based on the analysis of the trotter step size modifications. Furthermore, we discuss how this advance in the trotter step size procedures can improve quantum computing physics scattering results and how this technical advance can be applied to other machines and noise mitigation methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Amortized simulation-based frequentist inference for tractable and intractable likelihoods

Abstract High-fidelity simulators that connect theoretical models with observations are indispensable tools in many sciences. If the likelihood is known, inference can proceed using standard techniques. However, when the likelihood is intractable or unknown, a simulator makes it possible to infer the parameters of a theoretical model directly from real and simulated observations when coupled with machine learning. We introduce an extension of the recently proposed likelihood-free frequentist inference ( LF2I ) approach that makes it possible to construct confidence sets with the p -value function and to use the same function to check the coverage explicitly at any given parameter point. Like LF2I , this extension yields provably valid confidence sets in parameter inference problems for which a high-fidelity simulator is available. The utility of our algorithm is illustrated by applying it to three pedagogically interesting examples: the first is from cosmology, the second from high-energy physics and astronomy, both with tractable likelihoods, while the third, with an intractable likelihood, is from epidemiology 3 3 Code to reproduce all of our results is available on https://github.com/AliAlkadhim/ALFFI . .

Computer Science↗

DOE OSTI2026

Towards a self-driving trigger at the LHC: adaptive response in real time

Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.

Emami, Shaghayegh [Michigan U.] (ORCID:00090007589↗

DOE OSTI2026

Improving statistical precision in Monte Carlo samples with negative weights via reweighting and uncertainty quantification

High statistical precision is critical for Monte Carlo (MC) samples in high energy physics and is degraded by negatively weighted events. This paper investigates a procedure to learn the relationship between the negative and positive weight distributions of any sample, allowing the reduction of statistical uncertainty by reweighting kinematically equivalent events with the same sign. A robust uncertainty quantification method is required for the practical application of such method. Two methods for the estimation of the reweighting uncertainty are developed: one at the event and another one at the final observable level. The latter method is strongly favored. The gains in statistical precision are then quantified. The method is demonstrated on Sherpa vector boson plus jets samples when using all generated events and when restricted to the signal region of a mock analysis. It is demonstrated to significantly reduce stochastic behavior in sparse MC samples while decreasing the overall uncertainty with a sufficiently well-known reweighting function.

Monte Carlo methods↗

DOE OSTI2021

Multifunctional Superconducting Nanowire Quantum Sensors

Superconducting nanowire single-photon detectors (SNSPDs) offer high-quantum-efficiency and low-dark-count-rate single-photon detection. In a growing number of cases, large magnetic fields are being incorporated into quantum microscopes, nanophotonic devices, and sensors for nuclear and high-energy physics that rely on SNSPDs, but superconducting devices generally perform poorly in large magnetic fields. Here, we demonstrate robust performance of amorphous SNSPDs in magnetic fields of up to ±6 T with a negligible dark-count rate and unchanged quantum efficiency at typical bias currents. Critically, we also show that the SNSPD can be used as a magnetometer with a sensitivity of better than 100μT/√Hz and as a thermometer with a sensitivity of 20μK/√Hz at 1 K. Thus, a single-photon detector integrated into a quantum device can be used as a multifunctional quantum sensor capable of describing the temperature and magnetic field on chip simply by varying the bias current to change the operating modality from single-photon detection to thermometry or magnetometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Vortical effects in chiral band structures

The chiral vortical effect is a chiral anomaly-induced transport phenomenon characterized by an axial current in a uniformly rotating chiral fluid. It is well understood for Weyl fermions in high energy physics, but its realization in condensed matter band structures, including those of Weyl semimetals, has been controversial. In this work, we develop the Kubo response theory for electrons in a general band structure subject to space- and time-dependent rotation or vorticity relative to the background lattice. For continuum Hamiltonians, we recover the chiral vortical effect in the static limit and the transport or uniform limit when the fluid, strictly, is not a Fermi liquid. In the transport limit of a Fermi liquid, we describe an effect that we dub the gyrotropic vortical effect. The latter is governed by Berry curvature of the occupied bands while the former contains an additional contribution from the magnetic moment of electrons on the Fermi surface. The two vortical effects can be understood as kinematic analogs of the well-known chiral and gyrotropic magnetic effects in chiral band structures. As a result, we address recent controversies in the field and conclude by describing device geometries that exploit Ohmic or Seebeck transport to drive the vortical effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Deep exclusive meson production as a probe to the puzzle of Λ hyperon polarization

In the 1970s, an unexpected transverse Λ polarization in unpolarized proton-beryllium collisions was discovered, which initiated extensive studies on spin phenomena in high-energy physics. Over the past five decades, similar transverse Λ polarization has been observed across various collision systems, including lepton-hadron deep-inelastic scattering, hadron-hadron collisions, and electron-positron collisions. Despite numerous promising theoretical models, the fundamental mechanism underlying this polarization phenomenon remains inconclusive to this day. However, in both longitudinally and transversely polarized lepton-hadron and hadron-hadron collisions, it is found that the Λ hyperon is polarized with respect to the initial parton spin direction. How the Λ hyperon acquires its spin has become one of the most crucial questions to address in order to resolve this puzzle. In this paper, I propose to use an exclusive process that can be measured at the Electron-Ion Collider, the deep exclusive meson production, to explicitly test the mechanism of Λ polarization. The outcomes of this experimental measurement are anticipated to unveil the dominant mechanism by which Λ obtains its spin, eliminating many of the ambiguities that have been encountered in previous studies. Finally, experimental challenges and requirements are discussed. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Efficient neutrino oscillation parameter inference using Gaussian processes

The unified approach of Feldman and Cousins allows for exact statistical inference of small signals that commonly arise in high energy physics. It has gained widespread use, for instance, in measurements of neutrino oscillation parameters in long-baseline experiments. However, the approach relies on the Neyman construction of the classical confidence interval and is computationally intensive as it is typically done in a grid-based fashion over the entire parameter space. In this article, we propose an efficient algorithm for the Feldman-Cousins approach using Gaussian processes to construct confidence intervals iteratively. Further, we show that in the neutrino oscillation context, one can obtain confidence intervals fives times faster in one dimension and ten times faster in two dimensions, while maintaining an accuracy above 99.5%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz-boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used in high energy physics analyses. It uses minimally processed detector data as input and directly outputs particle properties of interest. The new technique is demonstrated for the reconstruction of the invariant mass of particles decaying in the CMS detector. The decay of a hypothetical scalar particle A into two photons, A → γ γ , is chosen as a benchmark decay. Lorentz boosts γ L = 60 – 600 are considered, ranging from regimes where both photons are resolved to those where the photons are closely merged as one object. A training method using domain continuation is introduced, enabling the invariant mass reconstruction of unresolved photon pairs in a novel way. The new technique is validated using π 0 → γ γ decays in LHC collision data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Highly-efficient quantum Fourier transformations for certain non-Abelian groups

Quantum Fourier transformations are an essential component of many quantum algorithms, from prime factoring to quantum simulation. While the standard Abelian QFrT is well studied, important variants corresponding to non-Abelian groups of interest have seen less development. In particular, fast non-Abelian Fourier transformations are important components for both quantum simulations of field theories as well as approaches to the non-Abelian hidden subgroup problem. In this work, we present fast quantum Fourier transformations for a number of non-Abelian groups of interest for high energy physics, B T , B O , 6 Δ ( 27 ) , Δ ( 54 ) , and Σ ( 36 × 3 ) . For each group, we derive explicit quantum circuits and estimate resource scaling for fault-tolerant implementations. Our work shows that the development of a fast Fourier transformation can substantively reduce simulation costs by an up to three orders of magnitude for the finite groups that we have investigated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Flow matching beyond kinematics: Generating jets with particle identification and trajectory displacement information

We introduce the first generative model trained on the etlass dataset. Our model generates jets at the constituent level, and it is a permutation-equivariant continuous normalizing flow (CNF) trained with the flow matching technique. It is conditioned on the jet type, so that a single model can be used to generate the ten different jet types of etlass. For the first time, we also introduce a generative model that goes beyond the kinematic features of jet constituents. The etlass dataset includes more features, such as particle-ID and track impact parameter, and we demonstrate that our CNF can accurately model all of these additional features as well. Our generative model for etlass expands on the versatility of existing jet generation techniques, enhancing their potential utility in high-energy physics research, and offering a more comprehensive understanding of the generated jets. Published by the American Physical Society 2025

Birk, Joschka (ORCID:0000000219310127)↗

DOE OSTI2025

Probing celestial energy and charge correlations through real-time quantum simulations: Insights from the Schwinger model

Motivated by recent developments in the application of light-ray operators (LROs) in high energy physics, we propose a new strategy to study correlation functions of LROs through real-time quantum simulations. We argue that quantum simulators provide an ideal laboratory to explore the properties LROs in lower-dimensional quantum field theories. This is exemplified in the 1 + 1 -d Schwinger model, employing tensor network methods, focusing on the calculation of energy and charge correlators. Despite some challenges in extracting the necessary correlation functions from the lattice, the methodology used can be extended to real quantum devices. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Symmetry Breaking and Error Correction in Open Quantum Systems

Symmetry-breaking transitions are a well-understood phenomenon of closed quantum systems in quantum optics, condensed matter, and high energy physics. However, symmetry breaking in open systems is less thoroughly understood, in part due to the richer steady-state and symmetry structure that such systems possess. For the prototypical open system—a Lindbladian—a unitary symmetry can be imposed in a “weak” or a “strong” way. We characterize the possible $\mathbb{Z}_n$ symmetry-breaking transitions for both cases. In the case of $\mathbb{Z}_2$, a weak-symmetry-broken phase guarantees at most a classical bit steady-state structure, while a strong-symmetry-broken phase admits a partially protected steady-state qubit. Viewing photonic cat qubits through the lens of strong-symmetry breaking, we show how to dynamically recover the logical information after any gap-preserving strong-symmetric error; such recovery becomes perfect exponentially quickly in the number of photons. Further, our study forges a connection between driven-dissipative phase transitions and error correction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗