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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 OSTI2024

A Review of the Multiple-Readout Concept and Its Application in an Integrally Active Calorimeter

A comprehensive multi-jet physics program is anticipated for experiments at future colliders. Key physics processes necessitate detectors that can distinguish signals from W and Z bosons and the Higgs boson. Typical examples include channels with or pairs and processes involving new physics in those cases where neutral particles must be disentangled from charged ones due to the presence of W or Z bosons in their final states. Such a physics program demands calorimetric energy resolution at or beyond the limits of traditional calorimetric techniques. Multiple-readout calorimetry, which aims to reduce fluctuations in energy measurements of hadronic showers, is a promising approach. The first part of this article reviews dual- and triple-readout calorimetry within a mathematical framework describing the underlying compensating mechanism. The second part proposes a potential implementation using an integrally active and total absorption detector. This model serves as the basis for several Monte Carlo studies, illustrating how the response of a multiple-readout calorimeter depends on construction parameters. Among the layouts considered, one configuration operating in triple-readout mode shows the potential to achieve an energy resolution approaching .

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Neural Architecture Search is a powerful approach for automating model design, but existing methods struggle to accurately optimize for real hardware performance, often relying on proxy metrics such as bit operations. We present Surrogate Neural Architecture Codesign Package (SNAC-Pack), an integrated framework that automates the discovery and optimization of neural networks focusing on FPGA deployment. SNAC-Pack combines Neural Architecture Codesign's multi-stage search capabilities with the Resource Utilization and Latency Estimator, enabling multi-objective optimization across accuracy, FPGA resource utilization, and latency without requiring time-intensive synthesis for each candidate model. We demonstrate SNAC-Pack on a high energy physics jet classification task, achieving 63.84% accuracy with resource estimation. When synthesized on a Xilinx Virtex UltraScale+ VU13P FPGA, the SNAC-Pack model matches baseline accuracy while maintaining comparable resource utilization to models optimized using traditional BOPs metrics. This work demonstrates the potential of hardware-aware neural architecture search for resource-constrained deployments and provides an open-source framework for automating the design of efficient FPGA-accelerated models.

Weitz, Jason [UC, San Diego] (ORCID:00090004631535↗
DOE OSTI2025

Electron-Proton Scattering Event Generation using Structured Tokenization

Recent work such as Omnijet-$\alpha$ has demonstrated that effective tokenization combined with transformer-based architectures can produce effective foundation models for jet physics. While tokenization may help models capture generalizable event characteristics, it also introduces discretization errors that may compromise the precision required for downstream physics analyses. As the number and complexity of the particle features grow, these errors are likely to grow proportionally. In this study, we investigate new tokenization strategies to improve the application of generative transformer models to \textsc{Pythia8} simulations of electron-proton scattering at the Electron-Ion Collider. Specifically, we propose a feature-based structured tokenization approach that utilizes multiple tokens per particle, improving expressivity, while reducing the total number of unique tokens needed. We evaluate this method against grid-based binning, K-means clustering, and vector-quantized variational auto-encoders on the event simulations. Our results show that feature-based structured tokenization reduces discretization error, leading to more accurate generative modeling of particle-level events.

Goldenberg, Steven [Thomas Jefferson National Acce↗
DOE OSTI2025

ν-point energy correletors with F AST EEC: Small-x physics from LHC jets

In recent years, energy correlators have emerged as a powerful tool for studying jet substructure, with promising applications such as probing the hadronization transition, analyzing the quark-gluon plasma, and improving the precision of top quark mass measurements. The projected N-point correlator measures correlations between N final-state particles by tracking the largest separation between them, showing a scaling behavior related to DGLAP splitting functions. These correlators can be analytically continued in N, commonly referred to as ν-correlators, allowing access to non-integer moments of the splitting functions. Of particular interest is the ν → 0 limit, where the small momentum fraction behavior of the splitting functions requires resummation. Originally, the computational complexity of evaluating ν-correlators for M particles scaled as 2 2M , making it impractical for real-world analyses. However, by using recursion, we reduce this to M 2M , and through the FastEEC method of dynamically resolving subjets, M is replaced by the number of subjets. This breakthrough enables, for the first time, the computation of ν-correlators for LHC data. In practice, limiting the number of subjets to 16 is sufficient to achieve percent-level precision, which we validate using known integer-ν results and convergence tests for non-integer ν. We have implemented this in an update to FastEEC and conducted an initial study of power-law scaling in the perturbative regime as a function of ν, using CMS Open Data on jets. The results agree with DGLAP evolution, except at small ν, where the anomalous dimension saturates to a value that matches the BFKL anomalous dimension.

Energy correlators↗
DOE OSTI2024

Hadronization of heavy quarks

Heavy-flavor hadrons produced in ultrarelativistic heavy-ion collisions are a sensitive probe for studying hadronization mechanisms of the quark-gluon-plasma. In this paper, we survey how different transport models for the simulation of heavy-quark diffusion through a quark-gluon plasma in heavy-ion collisions implement hadronization and how this affects final state observables. Utilizing the same input charm-quark distribution in all models at the hadronization transition, we find that the transverse-momentum dependence of the nuclear modification factor of various charm hadron species has significant sensitivity to the hadronization scheme. In addition, the charm-hadron elliptic flow exhibits a nontrivial dependence on the elliptic flow of the hadronizing partonic medium.

Atomic, Nuclear and Particle Physics↗
DOE OSTI2025

Bayesian inference analysis of jet quenching using inclusive jet and hadron suppression measurements

The JETSCAPE Collaboration reports a new determination of the jet transport parameter $\hat{q}$ in the quark-gluon plasma (QGP) using Bayesian inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). This multi-observable analysis extends the previously published JETSCAPE Bayesian inference determination of $\hat{q}$, which was based solely on a selection of inclusive hadron suppression data. jetscape is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of $\hat{q}$ utilizes active learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data; on jet or hadron data separately; and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A simple model for jet quenching in Heavy Ion Physics

This is a simple python code to calculate jet quenching for nuclear modification factors in relativistic heavy-ion collisions. This code can be used to generate all results specified in RR0010127, to be submitted to Physical Review C.

Soltz, Ron↗
DOE OSTI2026

Charm quark evolution in the early stages of heavy-ion collisions

Heavy quarks are predominantly generated at the initial stage of relativistic heavy-ion collisions such that heavy flavor observables have the potential to provide information on the pre-equilibrium medium dynamics. In this study, we investigate the sensitivity of D-meson $R_{AA}$ and $v_2$ to early-time charm quark dynamics in Pb+Pb collisions at $\sqrt{s_{NN}}$=5.02 TeV. We employ the IP-Glasma+MUSIC+UrQMD framework to model the evolution of the bulk medium. Charm quarks are generated using PYTHIA with nuclear parton distribution functions and evolved using Langevin dynamics within MARTINI. We observe that even though there is significant momentum broadening in the earliest stage, D-meson $R_{AA}$ and $v_2$ are only weakly sensitive to pre-equilibrium interactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Production of $Υ(nS)$ mesons in Pb + Pb and $pp$ collisions at 5.02 TeV

A measurement of the production of vector bottomonium states, $Υ$(1S), $Υ$(2S), and $Υ$(3S), in Pb + Pb and $pp$ collisions at a center-of-mass energy per nucleon pair of 5.02 TeV is presented. The data correspond to integrated luminosities of 1.38 nb –1 of Pb + Pb data collected in 2018, 0.44 nb –1 of Pb + Pb data collected in 2015, and 0.26 fb –1 of $pp$ data collected in 2017 by the ATLAS detector at the Large Hadron Collider. The measurements are performed in the dimuon decay channel for transverse momentum ${p}_{T}^{μμ}$ < 30 GeV, absolute rapidity |$y^{μμ}$| < 1.5, and Pb + Pb event centrality 0–80%. The production rates of the three bottomonium states in Pb + Pb collisions are compared with those in $pp$ collisions to extract the nuclear modification factors as functions of event centrality, ${p}_{T}^{μμ}$, and $|y^{μμ}|$. In addition, the suppression of the excited states relative to the ground state is studied. The results are compared with theoretical model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Measurement of inclusive electrons from open heavy-flavor hadron decays in p + p collisions at s = 200 GeV with the STAR detector

We report a new measurement of the production cross section for inclusive electrons from open heavy-flavor hadron decays as a function of transverse momentum (p T ) at midrapidity (|y| < 0.7) in p + p collisions at √s = 200 GeV. Overall, the result is presented for 2.5 < P T < 10 GeV/c with an improved precision above 6 GeV/c with respect to the previous measurements, providing more constraints on perturbative QCD calculations. Moreover, this measurement also provides a high-precision reference for measurements of nuclear modification factors for inclusive electrons from open-charm and -bottom hadron decays in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗