Search NASA⌕ Search

SEARCH · Search NASA

Results for “substructuring”

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.

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

At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Search for decaying dark matter in the Virgo cluster of galaxies with HAWC

The decay or annihilation of dark matter particles may produce a steady flux of very-high-energy gamma rays detectable above the diffuse background. Nearby clusters of galaxies provide excellent targets to search for the signatures of particle dark matter interactions. In particular, the Virgo cluster spans several degrees across the sky and can be efficiently probed with a wide field-of-view instrument. The High Altitude Water Cherenkov (HAWC) observatory, due to its wide field of view and sensitivity to gamma rays at an energy scale of 300 GeV–100 TeV is well-suited for this search. Using 2141 days of data, we search for γ -ray emission from the Virgo cluster, assuming well-motivated dark matter substructure models. Our results provide some of the strongest constraints on the decay lifetime of dark matter for masses above 10 TeV. Published by the American Physical Society 2024

Albert, A.↗
DOE OSTI2024

Gravitational waves from stochastic scalar fluctuations

Here, we present a novel mechanism for gravitational wave generation in the early Universe. Light spectator scalar fields during inflation can acquire a blue-tilted power spectrum due to stochastic effects. We show that this effect can lead to large curvature perturbations at small scales (induced by the spectator field fluctuations) while maintaining the observed, slightly red-tilted curvature perturbations at large cosmological scales (induced by the inflaton fluctuations). Along with other observational signatures, such as enhanced dark matter substructure, large curvature perturbations can induce a stochastic gravitational wave background (SGWB). The predicted strength of SGWB in our scenario, Ω GW ⁢ℎ 2 ≃10 -20 -10 -15 , can be observed with future detectors, operating between 10 -5 Hz and 10 Hz. We note that, in order to accommodate the newly reported NANOGrav observation, one could consider the same class of spectator models. At the same time, one would need to go beyond the simple benchmark considered here and consider a regime in which a misalignment contribution is also important.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Entanglement and Bell inequalities with boosted t t ¯

The Large Hadron Collider provides a unique opportunity to study quantum entanglement and violation of Bell inequalities at the highest energy available today. In this paper, we will investigate these quantum correlations with top quark pair production, which represents a system of two-qubits. The semileptonic top pair channel has a factor of 6 increase in statistics and easier reconstruction with respect to the dileptonic channel. Although measuring the spin polarization of the hadronic top quark is known to be challenging, our study indicates that it is feasible to reconstruct the spin density matrix of the two-qubit system using an optimal hadronic polarimeter. This is achieved with the aid of jet substructure techniques and NN-inspired reconstruction methods, which improve the mapping between subjets and quarks. We find that entanglement can already be observed at more than the 5 σ level with existing data, and violation of Bell inequalities may be probed above the 4 σ level at the HL-LHC with 3 ab − 1 of data. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Data-driven and model-agnostic approach to solving combinatorial assignment problems in searches for new physics

We present a novel approach to solving combinatorial assignment problems in particle physics. The correct assignment of decay products to parent particles is achieved in a model-agnostic fashion by introducing a neural network architecture, asswd-, which combines a custom layer based on attention mechanisms and dual autoencoders. We demonstrate how the network, trained purely on background events in an unsupervised setting, is capable of reconstructing correctly hypothetical new particles regardless of their mass, decay multiplicity, and substructure, and produces simultaneously an anomaly score that can be used to efficiently suppress the background. This model allows the extension of the suite of searches for localized excesses to include nonresonant particle pair production where the reconstruction of the two resonant masses is thwarted by combinatorics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Energy dependent nuclear suppression from gluon saturation in exclusive vector meson production

We calculate exclusive J / ψ photoproduction at high energies in the color glass condensate approach. The results are compared to the center-of-mass energy dependent γ + A → J / ψ + A cross sections extracted from measurements in ultraperipheral heavy ion collisions at RHIC and LHC. We predict strong saturation-driven nuclear suppression at high energies, while LHC data prefer even stronger suppression. We explore effects of nucleon shaped fluctuations and show that the most recent measurement of the | t | -differential incoherent J / ψ cross section prefers large event-by-event fluctuations of the nucleon substructure in heavy nuclei, comparable to that found for a free proton. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Jet suppression and azimuthal anisotropy from RHIC to LHC

Azimuthal anisotropies of high- p T particles produced in heavy-ion collisions are understood as an effect of a geometrical selection bias. Particles oriented in the direction in which the QCD medium formed in these collisions is shorter suffer less energy loss, and thus, are over-represented in the final ensemble compared to those oriented in the direction in which the medium is longer. In this work we present the first semianalytical predictions, including propagation through a realistic, hydrodynamical background, of the elliptic azimuthal anisotropy for jets, obtaining a quantitative agreement with available experimental data as a function of the jet p T , its cone size R , and the collisions centrality. Jets are multipartonic, extended objects and their energy loss is sensitive to substructure fluctuations. This sensitivity is determined by the physics of color coherence that relates to the ability of the medium to resolve those partonic fluctuations. Specifically, color dipoles with an angular separation smaller than a critical angle, θ c , are not resolved by the medium and they effectively act as a coherent source of energy loss. We find that elliptic jet azimuthal anisotropy has a specially strong dependence on coherence physics due to the marked length dependence of θ c . By combining our predictions for the collision systems and center-of-mass energies studied at RHIC and the LHC, covering a wide range of typical values of θ c , we show that the relative size of elliptic jet azimuthal anisotropies for jets with different cone sizes R follows a universal trend that indicates a transition from a coherent regime of jet quenching to a decoherent regime. These results suggest a way forward to reveal the role played by the physics of jet color decoherence in probing deconfined QCD matter. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Infrared-safe energy weighting does not guarantee small nonperturbative effects

Infrared and collinear (IRC) safety has long been used a proxy for robustness when developing new jet substructure observables. This guiding philosophy has been carried into the deep learning era, where IRC-safe neural networks have been used for many jet studies. For graph-based neural networks, the most straightforward way to achieve IRC safety is to weight particle inputs by their energies. However, energy-weighting by itself does not guarantee that perturbative calculations of machine-learned observables will enjoy small nonperturbative corrections. Here, in this paper, we demonstrate the sensitivity of IRC-safe networks to nonperturbative effects, by training an energy flow network (EFN) to maximize its sensitivity to hadronization. We then show how to construct Lipschitz energy flow networks (L-EFNs), which are both IRC safe and relatively insensitive to nonperturbative corrections. We demonstrate the performance of L-EFNs on generated samples of quark and gluon jets, and showcase fascinating differences between the learned latent representations of EFNs and L-EFNs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Anomaly detection in collider physics via factorized observables

To maximize the discovery potential of high-energy colliders, experimental searches should be sensitive to unforeseen new physics scenarios. This goal has motivated the use of machine learning for unsupervised anomaly detection. In this paper, we introduce a new anomaly detection strategy called : factorized observables for regressing conditional expectations. Our approach is based on the inductive bias of factorization, which is the idea that the physics governing different energy scales can be treated as approximately independent. Assuming factorization holds separately for signal and background processes, the appearance of nontrivial correlations between low- and high-energy observables is a robust indicator of new physics. Under the most restrictive form of factorization, a machine-learned model trained to identify such correlations will in fact converge to the optimal new physics classifier. We test on a benchmark anomaly detection task for the Large Hadron Collider involving collimated sprays of particles called jets. By teasing out correlations between the kinematics and substructure of jets, our method can reliably extract percent-level signal fractions. This strategy for uncovering new physics adds to the growing toolbox of anomaly detection methods for collider physics with a complementary set of assumptions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Scrutinizing the isotropic gamma-ray background in search of dark matter

The isotropic gamma-ray background (IGRB), measured by the Fermi Large Area Telescope, is the result of several classes of extragalactic astrophysical sources. Those sources include blazars, start-forming galaxies and radio galaxies. Also, ultrahigh-energy cosmic rays interacting with the infrared background contribute to the isotropic background. Using information from Fermi’s gamma-ray sources catalog and the results of dedicated studies of these classes of sources, from observations at the infrared and radio, we model their contribution to the IGRB. In addition to conventional astrophysical sources, dark matter may be a component of the IGRB. We combine our model of conventional astrophysical sources and of dark matter annihilation in distant galaxies, marginalizing over relevant uncertainties, to derive constraints on the dark matter annihilation cross section, from the measured IGRB. In calculating the contribution from dark matter we include the flux from extragalactic halos and their substructure and also the subdominant contribution from the Milky Way’s halo at high galactic latitudes. The resulting constraints are competitive with the strongest current constraints from the dwarf spheroidal galaxies. Under certain dark matter assumptions, we also find an indication for a small excess flux in the isotropic background. Here, our results are consistent with the gamma-ray excess at GeV energies toward the galactic center.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Moment extraction using an unfolding protocol without binning

Deconvolving (“unfolding”) detector distortions is a critical step in the comparison of cross-section measurements with theoretical predictions in particle and nuclear physics. However, most existing approaches require histogram binning while many theoretical predictions are at the level of statistical moments. We develop a new approach to directly unfold distribution moments as a function of another observable without having to first discretize the data. Our moment unfolding technique uses machine learning and is inspired by Boltzmann weight factors and generative adversarial networks (GANs). We demonstrate the performance of this approach using jet substructure measurements in collider physics. With this illustrative example, we find that our moment unfolding protocol is more precise than bin-based approaches and is as or more precise than completely unbinned methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Collinear limit of the four-point energy correlator in N = 4 supersymmetric Yang-Mills theory

We present a compact formula, expressed in terms of classical polylogarithms up to weight three, for the leading order four-point energy correlator in maximally supersymmetric Yang-Mills theory, in the limit where the four detectors are collinear. This formula is derived by combining a simplified, manifestly dual conformal invariant form of the 1 → 4 splitting function obtained from the square of the tree-level five-particle form factor of stress-tensor multiplet operators, with a novel integration-by-parts algorithm operating directly on Feynman parameter integrals. Our results provide valuable data for exploring the structure of physical observables in perturbation theory, and for calculations of jet substructure observables in quantum chromodynamics. Published by the American Physical Society 2024

Chicherin, Dmitry (ORCID:000000028985084X)↗
DOE OSTI2025

Enhancing charge ratio sensitivity to hadronization effects via jet selections on resolved SoftDrop splitting

The study of quantum chromodynamics (QCD) at ultrarelativistic energies can be performed in a controlled environment through lepton-hadron deep inelastic scatterings. In such collisions, the high-energy partonic emissions that follow from the ejected hard partons are accurately described by perturbative QCD. However, the lower energy scales at which quarks and gluons experience color confinement, i.e., hadronization mechanism, fall outside the validity regions for perturbative calculations, requiring phenomenological models tuned to data to describe it. As such, hadronization physics cannot be currently derived from first principles alone. Monte Carlo event generators are useful tools to describe these processes as they simulate both the perturbative and the nonperturbative interactions, with model-dependent energy scales that control parton dynamics. This work employs jets—experimental reconstructions of final-state particles likely to have a common partonic origin—to inspect this transition further. Although originally proposed to circumvent hadronization effects, we show that jets can be utilized as probes of nonperturbative phenomena via their substructure. The charge correlation ratio was recently shown to be sensitive to hadronization effects. Our work further improves this sensitivity to nonperturbative scales by introducing a new selection based on the relative placement of the within the clustering tree, defined as the unclustering that resolves the jet’s leading charged particles. Published by the American Physical Society 2025

Apolinário, Liliana (ORCID:0000000335009681)↗
DOE OSTI2025

Method to simultaneously facilitate all jet physics tasks

Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of jet physics are proceeding in parallel. We show that specially constructed machine learning models trained for a specific jet classification task can improve the accuracy, precision, or speed of all other jet physics tasks. This is demonstrated by training on a particular multiclass generation and classification task and then using the learned representation for different generation and classification tasks, for datasets with a different (full) detector simulation, for jets from a different collision system ($pp$ versus $ep$), for generative models, for likelihood ratio estimation, and for anomaly detection. We consider our omnilearn approach thus as a jet-physics foundation model. It is made publicly available for use in any area where state-of-the-art precision is required for analyses involving jets and their substructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Conformal collider physics meets LHC data

The remarkably high energies of the Large Hadron Collider (LHC) have allowed for the first measurements of the shapes and scalings of multipoint correlators of energy flow operators, ⟨ Ψ | E ( n → 1 ) E ( n → 2 ) ⋯ E ( n → k ) | Ψ ⟩ , providing new insights into the Lorentzian dynamics of quantum chromodynamics (QCD). In this letter, we use recent advances in effective field theory to derive a rigorous factorization theorem for the light-ray density matrix, ρ = | Ψ ⟩ ⟨ Ψ | , inside high transverse momentum jets at the LHC. Using the light-ray operator product expansion, the scaling behavior of multipoint correlators can be computed from the expectation value of the twist-2 spin- J light-ray operators, O [ J ] , in this state, Tr [ ρ O [ J ] ] . We compute the light-ray density matrix at next-to-leading order, and combine this with results for the next-to-leading logarithmic scaling behavior of the correlators up to six-points, comparing with CMS open data. This theoretical accuracy allows us to resolve the quantum scaling dimensions of QCD light-ray operators inside jets at the LHC. Our factorization theorem for the light-ray density matrix at the LHC completes the link between recent developments in the study of energy correlators and LHC phenomenology, opening the door to a wide variety of precision jet substructure studies. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2010

Hierarchy in the phase space and dark matter astronomy

We develop a theoretical framework for describing the hierarchical structure of the phase space of cold dark matter haloes, due to gravitationally bound substructures. Because it includes the full hierarchy of the cold dark matter initial conditions and is hence complementary to the halo model, the stable clustering hypothesis is applied for the first time here to the small-scale phase-space structure. As an application, we show that the particle dark matter annihilation signal could be up to 2 orders of magnitude larger than that of the smooth halo within the Galactic virial radius. The local boost is inversely proportional to the smooth halo density, and thus is O(1) within the solar radius, which could translate into interesting signatures for dark matter direct detection experiments: The temporal correlation of dark matter detection can change by a factor of 2 in the span of 10 years, while there will be significant correlations in the velocity space of dark matter particles. This can introduce O(1) uncertainty in the direction of local dark matter wind, which was believed to be a benchmark of directional dark matter searches or the annual modulation signal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Impact of dark matter microhalos on signatures for direct and indirect detection

Detecting dark matter as it streams through detectors on Earth relies on knowledge of its phase space density on a scale comparable to the size of our Solar System. Numerical simulations predict that our galactic halo contains an enormous hierarchy of substructures, streams and caustics, the remnants of the merging hierarchy that began with tiny Earth-mass microhalos. If these bound or coherent structures persist until the present time, they could dramatically alter signatures for the detection of weakly interacting elementary particle dark matter. Using numerical simulations that follow the coarse grained tidal disruption within the Galactic potential and fine grained heating from stellar encounters, we find that microhalos, streams, and caustics have a negligible likelihood of impacting direct detection signatures implying that dark matter constraints derived using simple smooth halo models are relatively robust. We also find that many dense central cusps survive, yielding a small enhancement in the signal for indirect detection experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Signatures of clumpy dark matter in the global 21 cm background signal

We examine the extent to which the self-annihilation of supersymmetric neutralino dark matter, as well as light dark matter, influences the rate of heating, ionization, and Lyman-{alpha} pumping of interstellar hydrogen and helium and the extent to which this is manifested in the 21 cm global background signal. We fully consider the enhancements to the annihilation rate from dark matter halos and substructures within them. We find that the influence of such structures can result in significant changes in the differential brightness temperature, {delta}T{sub b}. The changes at redshifts z<25 are likely to be undetectable due to the presence of the astrophysical signal; however, in the most favorable cases, deviations in {delta}T{sub b}, relative to its value in the absence of self-annihilating dark matter, of up to {approx_equal}20 mK at z=30 can occur. Thus we conclude that, in order to exclude these models, experiments measuring the global 21 cm signal, such as EDGES and CORE, will need to reduce the systematics at 50 MHz to below 20 mK.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗