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At least 793 records · Page 44

Observed and computed stellar line profiles - The roles played by partial redistribution, geometrical extent and expansion

Partial redistribution (PRD) radiative transfer is reviewed with emphasis on the complex interaction of observations and theoretical predictions of spectral line shapes. Although the physics of PRD was understood and formal solutions to the radiative transfer equation including PRD were published as early as 1962, more than a decade elapsed before the clear inconsistency between observed and theoretical profiles calculated with the restrictive assumption of complete redistribution stimulated the development and use of PRD semiempirical spectral analysis for the solar Lyman alpha, Ca II, and Mg II resonance lines. Work is summarized that led to 'realistic' plane parallel static chromospheric models for the sun and other late type stars, with emphasis on the determination of the temperature minimum at the base of the chromosphere and the physical basis for resonance line limb darkening, the brightness of the line wings, and the width of the emission features. Finally the various roles played by atmospheric extension and expansion (winds) in determining resonance line profile shapes are discussed, and the existing PRD calculations for late type stars are summarized.

Linsky, J. L.↗

A theoretical study of aerodynamic noise generation

Study focuses on physical mechanism of waves in fluid such as air. Strong interaction between energy of wave and fluid particle motion causes energy of wave to be dissipated. Dissipation depends not only on momentum, time-rate, and force, but also upon nature and magnitude of entropic-flow effects.

Peter, A. C.↗

The physics of gridded and conductive coated dielectrics for spacecraft

Theoretical aspects of electrostatic control and design of gridded and conductive film bonded polymers, for spacecraft Thermo-optical blankets are considered. Brief commentaries relative to the salient features of the primarily developed facility for and characterization of said polymers is also considered.

Okress, E. C.↗

Physics-tailored machine learning reveals unexpected physics in dusty plasmas

Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result, the effective forces between particles can be nonconservative and nonreciprocal. Machine learning (ML) models are a promising route to learn these complex forces, yet their structure should match the underlying physical constraints to provide useful insight. Here, we demonstrate and experimentally validate an ML approach that incorporates physical intuition to infer force laws in a laboratory dusty plasma. Trained on 3D particle trajectories, the model accounts for inherent symmetries, nonidentical particles, and learns the effective nonreciprocal forces between particles with exquisite accuracy (R 2 > 0.99). We validate the model by inferring particle masses in two independent yet consistent ways. The model’s accuracy enables precise measurements of particle charge and screening length, identifying large deviations from common theoretical assumptions. Our ability to identify unknown physics from experimental data demonstrates how ML-powered approaches can guide new routes of scientific discovery in many-body systems. Furthermore, we anticipate our ML approach to be a starting point for inferring laws from dynamics in a wide range of many-body systems, from colloids to living organisms.

Science & Technology - Other Topics↗

Close Proximity to a Quantum Phase Transition in TmZn2⁢GaO5

TmZn2⁢GaO5 is a newly synthesized triangular lattice magnet that exhibits a unique quantum phase characterized by strong Ising anisotropy, a pseudodoublet crystal electric field ground state, and a low-energy gapped excitation at the 𝐾 point. Unlike its well-known counterparts, TmMgGa⁢O4 and YbMgGa⁢O4, this material crystallizes in a distinct hexagonal structure, leading to a platform for investigating frustrated magnetism. Magnetic susceptibility, heat capacity, and inelastic neutron scattering measurements confirm the absence of long-range magnetic order down to 50 mK, placing TmZn2⁢GaO5 in a distinct region of the transverse-field Ising model phase diagram. Theoretical calculations based on spin-wave theory and mean-field modeling reproduce key experimental observations, reinforcing the material’s placement in a quantum disordered or multipolar state near a quantum critical point that separates it from the low-energy phase of TmMgGa⁢O4. These results highlight its potential for exploring quantum disordered states, anisotropic excitations, and exotic quantum phases in frustrated spin systems.

Ennis, Matthew [Department of Physics, Duke Univer↗

California Bridge to the Electron-Ion Collider (EIC) (Final Technical Report)

This report summarizes the activities and outcomes of DOE Grant DE-SC0022358, a traineeship program designed to prepare students for future nuclear physics research at the Electron-Ion Collider. The project leveraged the California EIC Consortium and statewide academic networks to provide immersive research experiences spanning universities and national laboratories. Participants engaged in theoretical, computational, and experimental research related to EIC physics and took part in professional meetings and collaborative research activities. The program supported student preparation for advanced study and research careers in nuclear physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Vector bosons and jets in proton collisions

Events with vector bosons produced in association with jets have been extensively studied at hadron colliders and provide high-accuracy tests of the standard model. A good understanding of these processes is of paramount importance for precision Higgs physics, as well as for searches for new physics. In particular, associated production of γ, W, or Z bosons with light-flavor and heavy-flavor jets is a powerful tool for testing perturbative QCD calculations, Monte Carlo event generators, and can also constrain the parametrizations used to describe the parton content of the proton. Furthermore, events with a W or Z boson produced with two well-separated jets can be used to distinguish between electroweak and strong production mechanisms, and to set limits on contributions of physics beyond the standard model. This review summarizes the historical theoretical developments and the state-of-the-art in the modeling of vector-boson-plus-jet physics while focusing on experimental results by the LHC collaborations in run 1 and run 2 and including comparisons with recent measurements at the Tevatron.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Heavy Flavor and Jet Studies for the Future Electron-Ion Collider to Explore the Hadronization Process

Heavy flavor production at the future Electron-Ion Collider (EIC) will allow us to precisely determine the quark/gluon fragmentation processes in vacuum and the nuclear medium especially within the poorly constrained kinematic region. Heavy flavor hadron and jet reconstructions with the recent EIC detector design have been studied in simulation. Results of corresponding physics projections such as the flavor dependent hadron nuclear modification factor R_{eA} R e A in electron+nucleus collisions will be shown. The statistical precision obtained by these proposed heavy flavor measurements for the future EIC provides a strong discriminating power in separating different theoretical predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Relativistic Magnetohydrodynamic Simulations of Giant Magnetar Bursts

Gradual crustal deformation can generate strongly twisted magnetic fields around magnetars, potentially triggering giant flares with total energies exceeding 10 44 erg. In this letter, we present the first relativistic magnetohydrodynamic simulation of a surface shear-driven magnetar eruption, capturing reconnection-driven plasma heating, the ejection of relativistically hot plasma, and the formation of a hot fireball confined within the inner magnetosphere. We find that magnetic reconnection in the equatorial current sheet launches a hot trailing outflow capable of powering the initial spike observed in giant flares, while simultaneously leaving behind a thermally stratified fireball with sufficient thermal energy to produce the pulsating, decaying tail. Together, these features provide a self-consistent physical framework for understanding the observed energetics of magnetar giant flares. The eruption also expels a magnetically dominated giant plasmoid carrying up to ∼9% of the magnetosphere’s total magnetic energy. Furthermore, our simulation demonstrates how the plasmoid drives the formation of a blast wave—an important ingredient in models linking magnetar eruptions to fast radio bursts.

79 ASTRONOMY AND ASTROPHYSICS↗

Enhancing Entanglement: Non-Markovian and Floquet Reservoir Engineering in Many-Qubit Superconducting Quantum Circuits

This is an experimental and theoretical project to leverage dissipation engineering under non-Markovian settings in order to aid in the preparation and stabilization of large, non-trivial, entangled quantum states. This project is a collaborative effort between the Painter group at Caltech and the Clerk group at the University of Chicago. By utilization of superconducting qubits coupled to the metamaterial waveguide described in the proposal, we tackle this goal via two parallel thrusts: (i) non-Markovian dynamics of a superconducting qubit strongly coupled to a slow-light waveguide reservoir and generation of 2D cluster states and (ii) many-qubit waveguide circuit QED for studying quantum many-body physics. In addition to device development and testing, we are also developing theoretical methods for understanding physics in the deep non-Markovian regime and driven-dissipative protocols for preparing and stabilizing the quantum many-body states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Contrastive learning for robust representations of neutrino data

In neutrino physics, analyses often depend on large simulated datasets, making it essential for models to generalize effectively to real-world detector data. Contrastive learning, a well-established technique in deep learning, offers a promising solution to this challenge. By applying controlled data augmentations to simulated data, contrastive learning enables the extraction of robust and transferable features. This improves the ability of models trained on simulations to adapt to real experimental data distributions. In this paper, we investigate the application of contrastive learning methods in the context of neutrino physics. Through a combination of empirical evaluations and theoretical insights, we demonstrate how contrastive learning enhances model performance and adaptability. Additionally, we compare it to other domain adaptation techniques, highlighting the unique advantages of contrastive learning for this field. Published by the American Physical Society 2025

Wilkinson, Alex (ORCID:0000000253404506)↗

Physics and Chemistry of Te and HgTe-based Ternary Melts

Historically, the theoretical treatment of the liquid phases has always been more difficult and complicated than that for solid and gas phases. A liquid has no lattice structure as crystalline solids and the atoms/molecules in the liquid can migrate through it relatively rapidly. On the other hand, it is also interacting with many other atoms/molecules so that the simplifications of the kinetic theory of gases cannot be employed. For more complicated liquids, such as the liquids of high ionicity and those containing hydrogen bonds and electric dipoles, the understanding is far from complete. At the same time, accurate information on the physics and chemistry of semiconductor melts is needed for the quantitative descriptions of the process of crystal growth from melt. The pre-crystallization phenomena in the liquid phase are critical because the properties of the grown crystals depend on the state and structure of the melt as well as the thermal history of the melt during solidification process. However, the data on the liquid phase, such as thermophysical properties of semiconductor melts are scarce, especially for the HgTe-based II-VI ternary compound semiconductors because of their high vapor pressure and extreme toxicity. Analysis of the thermophysical properties of the melt can provide information about structural transitions of the melt during the solidification process. From a broader point of view, the structure of liquids is much more complicated than the crystalline solids, especially the relaxation behavior through different thermal histories. The theory of hetero-phase fluctuations of liquids is applicable to any many-body systems including condensed-matter physics, field theory, physics of nuclear-matter, cosmology, biology and even sociology. This book summarizes the physics and chemistry from the experimental measurements and theoretical analyses of phase diagram, thermodynamic properties, density, thermal conductivity, viscosity, and electrical conductivity on the binary, pseudo-binary and ternary melts of the most advanced IR-detector material systems of HgCdTe and HgZnTe as well as the analyses of these results. The main objectives of this study are: (1) to provide the phase diagrams and thermodynamic properties of Hg-Cd-Te and Hg-Zn-Te systems through quantitatively fitting the experimental data by assuming an associated solution model for the liquid phase, (2) to experimentally measure the thermophysical properties of the Hg-Cd-Te and Hg-Zn-Te melts, including density, viscosity, electrical conductivity and thermal conductivity as functions of temperature and composition and (3) to enhance the fundamental knowledge of hetero-phase fluctuations and relaxation phenomena in the melts and extend our understanding of the solidification process in order to interpret the experimental results of crystal growth so as to improve the melt growth processes of the compound semiconductor. The physics and chemistry of Te and HgTe-based ternary melts were explored through the studies of the structural transformation during melting, the supercooling during solidification, the relaxation phenomena after rapid cooling of the melts and the metal-semiconductor transition in the melts through the analyses of electrical conductivity and Lorenz number. An in-depth study on the thermophysical properties and their time-dependent structural dynamic processes taking place in the vicinity of the solid-liquid phase transition of the narrow homogeneity range HgTe-based ternary semiconductors as well as the analysis of the homogenization process in the melt will also be presented.

Thermophysical properties↗

Magnetic Reconnection: Theoretical and Observational Perspectives: Preface

Magnetic reconnection is a fundamental plasma-physical process by which energy stored in a magnetic field is converted, often explosively, into heat and the kinetic energy of the charged particles that constitute the plasma. It occurs in a variety of astrophysical settings, ranging from the solar corona to pulsar magnetospheres and winds, as well as in laboratory fusion experiments, where it is responsible for sawtooth crashes. First proposed by R.G. Giovanelli in the late I 940s as the mechanism responsible for solar flares, magnetic reconnection was invoked at the beginning of the space age to explain not just solar flares but also the transfer of energy, mass, and momentum from the solar wind to Earth's magnetosphere and the subsequent storage and release of the transferred energy in the magnetotai\. During the half century or so that has followed the seminal theoretical works by J.W. Dungey, P.A. Sweet, E.N. Parker, and H.E. Petschek, in-situ measurements by Earth-orbiting satellites and remote-sensing observations of the solar corona have provided a growing body of evidence for the occurrence of reconnection at the Sun, in the solar wind, and in the near-Earth space environment. The last thirty years have also seen the development of laboratory reconnection experiments at a number of institutions. In parallel with the efforts of experimentalists in both space and laboratory plasma physics, theorists have investigated, analytically and with the help of increasingly powerful MHD, hybrid, and kinetic numerical simulations, the structure of the diffusion region, the factors controlling the rate, onset, and cessation of reconnection, and the detailed physics that enables the demagnetization of the ions and electrons and the topological reconfiguration of the magnetic field. Moreover, the scope of theoretical reconnection studies has been extended well beyond solar system and laboratory plasmas to include more exotic astrophysical plasma systems whose strong (10(exp 14)-10(exp 15) G) magnetic fields require that models of reconnection in these systems incorporate quantum electrodynamical, special relativistic, and radiative effects. The papers collected in this topical issue of Space Science Reviews cover different aspects of recent theoretical and observational work on magnetic reconnection in solar and space physics, astrophysics, and laboratory plasma physics. They derive from presentations given at a workshop on magnetic reconnection held in the Yosemite National Park, February 8-12,2010. The intent of the workshop was to stimulate, through a combination of tutorial talks, shorter focused talks, and extensive informal discussions, an interdisciplinary dialogue among members of the different research communities working on the problem of magnetic reconnection. One of the motivating considerations for holding the workshop was its relevance to NASA's Magnetospheric Multiscale (MMS) mission, scheduled for launch in 2014. The four identically instrumented MMS spacecraft are designed to study reconnect ion in Earth's magnetosphere and, specifically, to probe the electron diffusion region in order to determine the microphysical processes that enable the change in the topology of the magnetic field. Building on the achievements of the multi spacecraft Cluster and THEMIS missions, MMS will use the magnetosphere as an astrophysical plasma laboratory in which to test, through in-situ measurement of the plasma, energetic particles, and electric and magnetic fields, various models and theories that have emerged during the past twenty years, a period of extraordinarily productive theoretical and observational work.

Lewis, W. S.↗

Measurement of the muon anomalous precession frequency at the Muon g − 2 Experiment at Fermilab

The anomalous magnetic moment of the muon, $a_\mu = \frac{g-2}{2}$ is the fractional deviation of the muon $g$-factor from the value of 2. It emerges as the cumulative effect of the virtual particles participating in the muon interaction with a magnetic field via quantum loop corrections. Its value encodes all the possible interactions between the virtual particles and, for this reason, represents an important test of the Standard Model (SM). In particular, any deviation from the SM theoretical evaluation could be due to new physics contributions. The new Muon $g-2$ (E989) Experiment at Fermilab is currently operating to repeat and improve the previous E821 experiment at Brookhaven National Laboratory (BNL), aiming to reduce the experimental error by a factor of 4 to the final accuracy of 140 parts per billion (ppb). On April 7th, 2021, the E989 collaboration published the first result based on the first year of data taking (Run-1), measuring $a_\mu = 0.001~165~920~40(54)$ with a precision of 460 ppb. The measured value is consistent with the BNL measurement and strengthens the long-standing tension with the data-driven SM prediction to a combined discrepancy of 4.2$\sigma$. On the theory side, however, new efforts involving lattice-QCD techniques are starting to question the current consensus on the theoretical prediction, demanding new improvements on both the experimental and theoretical sides. The E989 collaboration is now finalizing the analysis of Run-2 and Run-3 data and a new publication is expected in the first half of 2023 with a combined statistical uncertainty of 200 ppb. The anomalous magnetic moment $a_\mu$ is measured as the ratio between the muon spin anomalous precession frequency, $\omega_a$, and the average magnetic field experienced by the muons as they circulate in the storage ring. This thesis presents a precession frequency analysis of the Run-1 data and an evaluation of the related systematic uncertainties. A new positron reconstruction developed for the analysis of the subsequent data-taking periods, aiming to reduce some of the major systematic uncertainties of the $\omega_a$ measurement, is presented. The author's involvement in the production of the Run-2/5 data and in the precise calibration of the detectors is discussed. Finally, the complete Run-1 $a_\mu$ result is presented.

43 PARTICLE ACCELERATORS↗

GFINNs: GENERIC formalism informed neural networks for deterministic and stochastic dynamical systems

Here we propose the GENERIC formalism informed neural networks (GFINNs) that obey the symmetric degeneracy conditions of the GENERIC formalism. GFINNs comprise two modules, each of which contains two components. We model each component using a neural network whose architecture is designed to satisfy the required conditions. The component-wise architecture design provides flexible ways of leveraging available physics information into neural networks. We prove theoretically that GFINNs are sufficiently expressive to learn the underlying equations, hence establishing the universal approximation theorem. We demonstrate the performance of GFINNs in three simulation problems: gas containers exchanging heat and volume, thermoelastic double pendulum and the Langevin dynamics. In all the examples, GFINNs outperform existing methods, hence demonstrating good accuracy in predictions for both deterministic and stochastic systems.

97 MATHEMATICS AND COMPUTING↗

PDF DECODER ANALYSIS CODE

SF-24-038"PDFdecoder", as a new application to explore parametrizations of parton distribution functions (PDFs) of the proton or other hadrons. The PDFs are fundamental quantities in particle physics which are necessary inputs to precise theoretical predictions for experiments at the Large Hadron Collider (LHC) and other facilities. As such, understanding how the PDFs are parametrized and associated uncertainties is a pressing need. The specific problem PDFdecoder confronts is the need of having a tractable and interpretably machine-learning (ML) framework to parametrize the PDFs and their uncertainties so as to understand how a given preferred parametrization is obtained. This problem has not been significantly addressed in the current literature. While other groups have used ML-based approaches to parametrize PDFs in the form of feed-forward neural networks, the question of tractability has not been explored in a PDF context. Our solution makes significant progress in this problem by using an array of encoder-decoder (essentially, autoencoder) architectures with varying constraints to the intermediate latent spaces based on interpretable physics. As a consequence, the trained models can be used as generative networks to produce interpretable predictions for the PDFs in a way that can be refined and studied further.

Hobbs, Timothy↗

Effect of variations in the doping profiles on the properties of doped multiple quantum well avalanche photodiodes

The purpose of this study is to use both theoretical and experimental evidence to determine the impact of doping imbalance and symmetry on the physical and electrical characteristics of doped multiple quantum well avalanche photodiodes (APD). Theoretical models have been developed to calculate the electric field valence and conduction bands, capacitance-voltage (CV), and carrier concentration versus depletion depth profiles. The models showed a strong correlation between the p- and n-doping balance inside the GaAs wells and the number of depleted stages and breakdown voltage of the APD. A periodic doping imbalance in the wells has been shown to result in a gradual increase (or decrease) in the electric field profile throughout the device which gave rise to partially depleted devices at low bias. The MQW APD structures that we modeled consisted of a 1 micron top p(+)-doped (3 x 10(exp 18) cm(exp -3)) GaAs layer followed by a 1 micron region of alternating layers of GaAs (500 A) and Al(0.42)Ga(0.58)As (500 A), and a 1 micron n(+) back layer (3 x 10(exp 18) cm(exp -3)). The GaAs wells were doped with p-i-n layers placed at the center of each well. The simulation results showed that in an APD with nine doped wells, and where the 50 A p-doped layer is off by 10% (p = 1.65 x 10(exp 18) cm(exp -3), n = 1.5 x 10(exp 18) cm(exp -3)), almost half of the MQW stages were shown to be undepleted at low bias which was a result of a reduction in the electric field near the p(+) cap layer by over 50% from its value in the balanced structure. Experimental CV and IV data on similar MBE grown MQW structures have shown very similar depletion and breakdown characteristics. The models have enabled us to better interpret our experimental data and to determine both the extent of the doping imbalances in the devices as well as the overall p- or n-type doping characteristics of the structures.

Menkara, H. M.↗