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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning and LHC event generation

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applications of modern machine learning to event generation and simulation-based inference, including conceptional developments driven by the specific requirements of particle physics. New ideas and tools developed at the interface of particle physics and machine learning will improve the speed and precision of forward simulations, handle the complexity of collision data, and enhance inference as an inverse simulation problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Comparing event generator predictions and ab-initio calculations of $\nu$-$^{12}$C neutral current quasi-elastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event Generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs use to predict kinematic observables for a range of neutrino energies. These simulations may lack physics captured by more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the physics contained in EG simulations. Neutral current quasi-elastic (NCQE) scattering events for neutrinos and anti-neutrinos on a $^{12}$C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the Relativistic Fermi Gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Comparing event generator predictions and ab initio calculations of ν- 12 C neutral-current quasielastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs are used to predict kinematic observables for a range of neutrino energies. These simulations make use of simple models of nucleon dynamics. As such, they may fail to capture features of more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the adequacy of the implementation of two nuclear physics models in EG simulations. Neutral-current quasielastic (NCQE) scattering events for neutrinos and antineutrinos on a 12 C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the relativistic Fermi gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. The peak of the cross section dσ/(dΩ dω) is consistent in energy transfer, ω, for RFG and CBF simulations. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two. These results demonstrate the importance of benchmarking EGs so their nuclear physics implementations can be improved for the analysis of future experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Phenomenological Chiral Perturbation Theory for Event Generators

Understanding neutrino induced single pion production off of nucleons is crucial for accelerator-based neutrino oscillation experiments. To this end, we use chiral perturbation theory to determine the forms of meson and baryon interactions and then modify the vertices using form factors. We implement this single pion production model in an event generator pipeline that will be available to the wider community.

Toman, Miša [UC, Irvine] (ORCID:0009000326471281)↗
DOE OSTI2026

Thermal Compton Scattering of Electron Beams on Blackbody Photons: A Monte Carlo Event Generator for Multi-Turn Tracking at the Electron-Ion Collider

Compton scattering of ultra-relativistic electrons on thermal (blackbody) photons is typically a subdominant process in electron storage rings, but at sufficiently high electron energy and low residual gas pressure it can become competitive with beam-gas scattering and contribute to dis tributed losses and backgrounds. We present a self-contained Monte Carlo event generator for thermal Compton scattering designed for integration into multi-turn tracking workflows. The im plementation follows H. Burkhardt’s proposal method: trial scattering angles are sampled from the Thomson differential cross section and accepted/rejected using the Klein-Nishina to Thomson ratio, yielding the correct Compton spectrum while retaining simple absolute-rate normalization. Ther mal photon energies are sampled from the blackbody photon-number spectrum via an exact mixture representation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Neutrino physics is entering a precision era in which measurements of neutrino oscillations, astrophysical neutrinos from supernovae and other sources, and coherent neutrino scattering will provide insight on the nature of neutrino masses, the presence of CP violation, and perhaps more exotic new physics in the neutrino sector. Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies that uses a combination of lattice QCD, nuclear effective theories, phenomenological models, and neutrino event generators to make reliable theory predictions for experimentally relevant nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. This white paper discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Study of Short-Range nuclear Correlations in light nuclei using the BeAGLE event generator

Nuclear dynamics at short distances among nucleons is one of the most outstanding phenomena in nuclear physics. Understanding the role of QCD in generating nuclear forces is important for uncovering the underlying physics of Short-Range Correlations (SRCs). In recent years, SRCs has been observed from light to heavy nuclei using fixed target experiments at Jefferson lab via high energy electron-nucleus scattering. In this talk, I will talk about the opportunity of studying SRCs using light nuclei with collider experiments, e.g., the Electron-Ion Collider (EIC). The experimental technique of studying the light nuclei can be based on exclusive processes with tagging final-state particles, in order to fully control the initial state of the target wavefunction. In particular, incoherent diffractive production of J/\psi J / ψ particle off deuteron will be presented. In addition, the spectral function in light nuclei has been recently modeled in the BeAGLE event generator, where the decay kinematics of the light nuclei and their influence on the very forward detector design at the EIC will be discussed.

Tu, Zhoudunming↗
DOE OSTI2025

Event-driven readout development: testing of the EDWARD65P1 chip with integrated event generators

Building on a prototype readout integrated circuit for segmented silicon sensors with the EDWARD event-driven readout architecture, the front-end in each pixel was replaced by a hardware generator to verify readout performance, ensuring no data loss, consistent priority handling, and speed verification. Here, this generator produces Poisson-distributed readout requests with individually tunable rates per pixel via a digitally controlled oscillator. The resulting EDWARD65P1 test ASIC is a 32×32 pixel matrix with a 100 μm pitch, equipped with digital event generators simulating radiation hits at user-defined rates. Test results for this new design are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Universal Monte Carlo Event Generator

With the Jefferson Lab 12 GeV physics program underway and plans for the future Electron-Ion Collider (EIC), the nuclear physics community is entering a new era of exploration of QCD phenomena involving extensive data taking and event-level processing. This brings with it the potential for unprecedented access to multidimensional particle momentum distributions (PMDs) that can be connected to various theoretical frameworks by unfolding the emergent quantum mechanical properties of QCD using the PMDs. In practice, the PMDs are rendered as discretized histograms (typically one- or two-dimensional projections), and detector effects must be taken into account to unfold the pure detector effect-free PMDs that can be connected with theory. One of the challenges in this new era is obtaining faithful reconstructions of the multidimensional PMDs that preserve all of the inherent particle correlations. In this LDRD project we developed a novel approach using machine learning (ML) that solves this challenge, by avoiding entirely the need to use histograms as the main numerical technique to obtain the detector effect-free PMDs. The new approach is, moreover, scalable to higher dimensional PMDs. The central idea involves training neural networks (NNs) to generate synthetic event-level data (momenta 4-vectors of final state particles) to preserve all correlations among the particles. This is achieved by converting the trial synthetic vertex-level events to detector-level events using detector simulators. The NNs are then tuned using a specialized distance metric between the synthetic detector events and the real detector events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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

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

Accelerating Neutrino Event Generation in MARLEY Using CUDA-Based RNG and GPU Parallelization

MARLEY is a simulation tool that helps scientists study how low-energy neutrinos interact with matter. To work properly, MARLEY uses random numbers thousands of times in each simulation. These random numbers are important for modeling things like how neutrinos collide with atoms and what particles they produce. Right now, MARLEY runs on a regular computer processor (CPU) and uses a built-in random number generator called the Mersenne Twister. This setup works, but it can be slow, especially when trying to simulate many events. This research focuses on making MARLEY run faster by moving the random number generation and some of the repetitive calculations from the CPU to a graphics processing unit (GPU), which can handle many tasks at the same time. We use CUDA (a tool for programming NVIDIA GPUs) and cuRAND (a GPU-based random number library) to test faster alternatives to the current random number system. We compare different GPU-based generators, like curand_mtgp32, xorwow, and philox, to see which ones are the quickest and still give reliable results. Early tests show that using the GPU can make MARLEY simulations much faster. This project not only helps improve current simulation performance but also moves closer to a full simulation chain where all stages can run on modern GPU hardware.

Dunkley, Kimieka [Florida A-M]↗
DOE OSTI2022

DarkNews: a Python-based event generator for heavy neutral lepton production in neutrino-nucleus scattering

We introduce DarkNews, a lightweight Python-based Monte-Carlo generator for beyond-the-Standard-Model neutrino-nucleus scattering. The generator handles the production and decay of heavy neutral leptons via additional vector or scalar mediators, as well as through transition magnetic moments. DarkNews samples pre-computed neutrino-nucleus upscattering cross sections and heavy neutrino decay rates to produce dilepton and single-photon events in accelerator neutrino experiments. We present two case studies with differential distributions for models that can explain the MiniBooNE excess. The aim of this code is to aid the neutrino theory and experimental communities in performing searches and sensitivity studies for new particles produced in neutrino upscattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Achilles and GENIE Model Comparisons Between Quasi-Elastic Proton Exclusive Events in DUNE PRISM ND-LAr

In this study, we analyze simulated CCQE proton exclusive events in DUNE s ND-LAr using Achilles and GENIE Monte Carlo event generators. We generate events using muon neutrino exclusive flux files of DUNE s on-axis and 20m off-axis PRISM positions and compare various kinematics of proton exclusive events between the event generators. Events are further analyzed in categories according to the number of final-state protons. This study was motivated by QE s dominance in statistics for off-axis events over other channels in which off-axis events are very useful for characterizing DUNE s flux. Furthermore, our motivation for comparing results between generators is driven by off-axis QE neutrino spectra peaking below 1 GeV. In this region, many low-energy proton events are produced in which models have been shown to have disagreements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Monte Carlo event generator for initial conditions of conserved charges in nuclear geometry

At top collider energies where baryon stopping is negligible, the initial state of heavy-ion collisions is overall charge neutral and predominantly composed of gluons. Nevertheless, there can also be significant local fluctuations of the baryon number, strangeness, and electric charge densities about zero, perturbatively corresponding to the production of quark/antiquark pairs. These previously ignored local charge fluctuations can permit the study of charge diffusion in the quark-gluon plasma (QGP), even at top collider energies. In this paper we present a new model denoted ICCING (initial conserved charges in nuclear geometry) which can reconstruct the initial conditions of conserved charges in the QGP by sampling a (g→q¯q) splitting probability over the initial energy density. We find that the new charge distributions generally differ from the bulk energy density; in particular, the strangeness distribution is significantly more eccentric than standard bulk observables and appears to be associated with the geometry of hot spots in the initial state. The new information provided by these conserved charges opens the door to studying a wealth of new charge- and flavor-dependent correlations in the initial state and ultimately the charge transport parameters of the QGP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Pre-equilibrium evolution of conserved charges with initial conditions in the ICCING Monte Carlo event generator

Heavy-ion collisions can be well described through relativistic viscous hydrodynamics, but questions still remain when hydrodynamics is applicable because the initial state may begin very far from equilibrium. Thus, a pre-equilibrium evolution phase is used to bridge the gap between the initial state and hydrodynamics. KøMPøST is one such pre-equilibrium model that propagates the energy-momentum tensor by decomposing it into the background and fluctuations around that background, whose evolution is captured by Green's functions. We extend this formalism to include conserved charges and calculate the corresponding nonequilibrium Green's functions in the relaxation-time approximation. The ICCING algorithm initializes conserved charges in the initial state by sampling $g$ → $q$$\overline{q}$ splitting probabilities and is, thus, perfectly positioned to implement Green's functions for charge propagation. As a result, we show that this method alters the initial-state charge geometries and is applicable in central to mid-central collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗