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All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Two-dimensional Imaging Velocity Interferometry: Technique and Data Analysis

We describe the data analysis procedures for an emerging interferometric technique for measuring motion across a two-dimensional image at a moment in time, i.e. a snapshot 2d-VISAR. Velocity interferometers (VISAR) measuring target motion to high precision have been an important diagnostic in shockwave physics for many years Until recently, this diagnostic has been limited to measuring motion at points or lines across a target. We introduce an emerging interferometric technique for measuring motion across a two-dimensional image, which could be called a snapshot 2d-VISAR. If a sufficiently fast movie camera technology existed, it could be placed behind a traditional VISAR optical system and record a 2d image vs time. But since that technology is not yet available, we use a CCD detector to record a single 2d image, with the pulsed nature of the illumination providing the time resolution. Consequently, since we are using pulsed illumination having a coherence length shorter than the VISAR interferometer delay ({approx}0.1 ns), we must use the white light velocimetry configuration to produce fringes with significant visibility. In this scheme, two interferometers (illuminating, detecting) having nearly identical delays are used in series, with one before the target and one after. This produces fringes with at most 50% visibility, but otherwise has the same fringe shift per target motion of a traditional VISAR. The 2d-VISAR observes a new world of information about shock behavior not readily accessible by traditional point or 1d-VISARS, simultaneously providing both a velocity map and an 'ordinary' snapshot photograph of the target. The 2d-VISAR has been used to observe nonuniformities in NIF related targets (polycrystalline diamond, Be), and in Si and Al.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Impact response of US Army and National Football League helmet pad systems

Lawrence Livermore National Laboratory [LLNL] was tasked to compare the impact response of NFL helmet pad systems and U.S. Army pad systems compatible with an Advanced Combat Helmet [ACH] at impact velocities up to 20 ft/s. This was a one-year study funded by the U.S. Army and JIEDDO. The Army/JIEDDO point of contact is COL R. Todd Dombroski, DO, JIEDDO Surgeon. LLNL was chosen by committee to perform the research based on prior published computational studies of the mechanical response of helmets and skulls to blast. Our collaborators include the U.S. Army Aeromedical Research Laboratory [USAARL] (a DoD laboratory responsible for impact testing helmets), Team Wendy and Oregon Aero (current and former ACH pad manufacturers), Riddell and Xenith (NFL pad manufacturers), and d3o (general purpose sports pad manufacturer). The manufacturer-supplied pad systems that were studied are shown in the figure below. The first two are the Army systems, which are bilayer foam pads with both hard and soft foam and a water-resistant airtight wrapper (Team Wendy) or a water-resistant airtight coating (Oregon Aero). The next two are NFL pad systems. The Xenith system consists of a thin foam pad and a hollow air-filled cylinder that elastically buckles under load. The Riddell system is a bilayer foam pad that is encased in an inflatable airbag with relief channels to neighboring pads in the helmet. The inflatable airbag is for comfort and provides no enhancement to impact mitigation. The d3o system consists of a rate-sensitive homogeneous dense foam. LLNL performed experiments to characterize the material properties of the individual foam materials and the response of the complete pad systems, to obtain parameters needed for the simulations. LLNL also performed X-ray CT scans of an ACH helmet shell that were used to construct a geometrically accurate computational model of the helmet. Two complementary sets of simulations were performed. The first set of simulations reproduced the experimental helmet impact certification tests performed by USAARL, who provided data for comparison. The goal of this set of simulations was to demonstrate the overall validity of LLNL's computational analyses and methods and understand the general physics of helmet impacts. In these tests and the corresponding simulations, an inverted ACH containing pads and a head-form are dropped onto a hemispherical anvil, at 10 and 14.14 ft/s impact velocities. The simulations predicted peak accelerations (the metric used by USAARL for comparing the performance of pad systems), rebound velocities, and impact durations consistent with the experimental data, thus demonstrating the validity and relevance of the simulation methods. Because the NFL pad systems are approximately double the thickness of the U.S. Army pads, they do not fit into the ACH. As a result, the NFL pads could not be simply placed into an ACH shell in either a simulation or an experiment without modifying their size and shape. Since impact mitigation depends critically on the available stopping distance and the area over which the stopping force is applied, it is important to consider identically shaped pads in order to compare their performance in a fair and meaningful manner. Consequently, the second set of simulations utilized a simplified simulation geometry consisting of a 5 kg cylindrical impactor (equal in mass to a head) striking equally sized pads from each manufacturer. The simulated bilayer foam pads had the same proportions of hard and soft foam as the actual pad systems, while the Xenith pads were simulated as a bilayer foam pad with material properties adjusted to give the same response as the actual Xenith pads. The effects of trapped air were included in the simulations of the Team Wendy and Oregon Aero pads. All simulations used material properties derived from the experiments conducted at LLNL. The acceleration history of the center of mass of the impactor was used to calculate the Head Injury Criterion (HIC) for each simulation, to assess the pad performance. The HIC is a well-established metric that combines both acceleration and duration of impact to assess the danger of injury, and is a more robust measure than peak acceleration. Our key findings are: (1) The performance of a pad depends on the range of impact velocities. At lower impact velocity, softer pads perform better. At higher impact velocity, harder pads perform better; (2) Thicker pads perform better at all velocities, but especially at high velocities; and (3) For comparable thicknesses, neither the NFL systems nor the Oregon Aero pads outperform the Team Wendy pads currently used in the ACH system in militarily-relevant impact scenarios (impact speeds less than 20 ft/s). The second finding suggests a commercial off-the-shelf solution for mitigating impact-related traumatic brain injury to soldiers.

42 ENGINEERING↗
DOE OSTI2026

LDRD FY25 Program Overview

As Lawrence Livermore National Laboratory’s (LLNL’s) Laboratory Directed Research and Development (LDRD) program enters its fifth decade of leading-edge research and development, its impact and importance have never been stronger. The program continues to advance strategic investments in pioneering science, technology, and engineering, ensuring LLNL will be ready to deliver on our mission as it evolves over the coming decades. Investing in LDRD research, and the people who perform this critical work, gives LLNL the ability to sustain our role as a leader in the Department of Energy and National Nuclear Security Administration enterprise. The LDRD program enables high-risk, high-payoff research that anticipates emerging threats and future mission needs. By nurturing the ingenuity of the Lab’s greatest asset, its people, LDRD funding advances not only our research but also grows and nurtures our workforce: engaging future innovators with student mentoring, challenging postdoctoral researchers to apply their skills to support national security, and strengthening the leadership skills of early career staff. This annual report documents how LDRD investments advance LLNL’s science, technology, and engineering across our mission space. To assess LDRD’s impact we track both short and long-term metrics such as peer-reviewed publications, number of students, or professional fellows. In addition to reviewing these metrics, I encourage you to delve deeper into the breadth of science and technology that illustrate the strategic value of this research portfolio. For instance, a recent exploratory research project used advanced manufacturing to construct miniaturized three-dimensional ion traps for a quantum computer with reduced quantum error rates to enable applications that address national security missions and support basic science. Another project has delved into studying detonation by examining deflagration to enhance the safety and security of the nuclear weapons stockpile. LDRD researchers are also deploying AI agents on two of the world’s most powerful supercomputers to automate and accelerate inertial confinement fusion experiments. Other teams are delivering more accurate optical constants to enable improved validation for aluminum to advance atomic and molecular physics models. LDRD-driven discoveries of how metals deform under extreme conditions strengthen our ability to model and design materials for demanding national security environments. National security challenges are increasingly complex and continuously evolving. LDRD focuses our most innovative science and technology on these challenges, ensuring the Laboratory is developing creative, forward-leaning solutions for our nation and the world. The following pages feature highlights of published scientific advances, patents, and honors that stem from LDRD investments. As you read this report, I hope you will understand how these investments position the Laboratory, and our partners, to meet the demands of the decades ahead.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Criticality safety enhancements for SCALE 6.2 and beyond

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. Since 1980, regulators, industry, and research institutions around the world have relied on SCALE for nuclear safety analysis and design. SCALE 6.2 provides several new capabilities and significant improvements in many existing features for criticality safety analysis. Enhancements are realized for nuclear data; multigroup resonance self-shielding; continuous-energy Monte Carlo analysis for sensitivity/uncertainty analysis, radiation shielding, and depletion; and graphical user interfaces. An overview of these capabilities is provided in this paper, and additional details are provided in several companion papers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Comparing Measured (a,n) Thick Target Yields to MCNP6 using TENDL 2012 Libraries - Paper 31

MCNP6, due to the heritage of MCNPX, has always possessed the capability to transport the light ions, such as alpha particles. Two types of competing physics take place during the particle transport: atomic and nuclear physics. Charged particles lose energy to media due to Coulombic interactions. MCNP6 models Coulombic interactions through the use of the continuous slowing down approximation. Stopping powers are calculated at a variety of energies using the Bethe-Bloch formula with Sternheimer and Peierls density effect correction. For energies less than 1.31 MeV/AMU, a low-energy SPAR model is used. When the energy of the particle is high enough, there is a transition from nuclear interactions to nucleon interactions. MCNP6 possess various physics models to account for these types of intra-nuclear cascades. These models are less accurate at low energies. Even though MCNP6 will transport these light ions to low energies (i.e. less than 20 MeV), most of the available model physics in MCNP6, for nuclear interactions, has a suggested minimum energy of ∼20-200 MeV. The result of the poorer prediction at low energies causes important light ion events, such as F-19(a,n)Na-22 from U-234 decay in UF{sub 6}, to produce orders of magnitude fewer neutrons in MCNP6 than should be emitted. As with neutrons, ACE (A Compact ENDF) formatted light ion libraries have been developed from several different evaluations. These libraries possess better physics at low energies where the physics models break down. The TENDL 2012 evaluations possess alpha transport libraries, in ACE format, such that they can easily be used with codes like MCNP6 that read ACE formatted cross sections. As a result, a capability was developed for MCNP6 to read and implement these library cross sections when the light ion reached energies below the library upper energy cutoff. Perfectly modelling an experiment for benchmark comparisons to a code calculation can be tricky. For complex setups, systematic error is always possible; and usually a hefty uncertainty analysis is required to quantify just the geometry setup and material combination choices. For an (a,n) interaction, a thick target yield is defined as the amount of neutrons emitted given that the alpha ranges out in the material. For alpha transport at low energy <10 MeV, in reasonably dense materials (>1-2 g/cc), with a material dimension length larger than a few hundred microns, alpha particles will tend to completely stop and range out in the material. For Li, Be, B, C, N, O, F, Na, Mg and Al thick target yields exist in 200 keV intervals from 1 to 9.8 MeV (most of the elements do have (a,n) thresholds above 1 MeV). Because modelling a thick target yield in MCNP6 is much easier than attempting to account for the complexity of systematic error from a full out experiment, we present here comparisons of (a,n) thick target yields to those calculated in MCNP6 using the TENDL 2012 alpha library evaluations.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems

Uncertainty quantification techniques such as the time-dependent generalized polynomial chaos (TD-gPC) use an adaptive orthogonal basis to better represent the stochastic part of the solution space (aka random function space) in time. However, because the random function space is constructed using tensor products, TD-gPC-based methods are known to suffer from the curse of dimensionality. Here, we introduce a new numerical method called the flow-driven spectral chaos (FSC) which overcomes this curse of dimensionality at the random-function-space level. The proposed method is not only computationally more efficient than existing TD-gPC-based methods but is also far more accurate. The FSC method uses the concept of enriched stochastic flow maps to track the evolution of a finite-dimensional random function space efficiently in time. To transfer the probability information from one random function space to another, two approaches are developed and studied herein. In the first approach, the probability information is transferred in the mean-square sense, whereas in the second approach the transfer is done exactly using a new theorem that was developed for this purpose. The FSC method can quantify uncertainties with high fidelity, especially for the long-time response of stochastic dynamical systems governed by ODEs of arbitrary order. Six representative numerical examples, including a nonlinear problem (the Van-der-Pol oscillator), are presented to demonstrate the performance of the FSC method and corroborate the claims of its superior numerical properties. Finally, a parametric, high-dimensional stochastic problem is used to demonstrate that when the FSC method is used in conjunction with Monte Carlo integration, the curse of dimensionality can be overcome altogether.

(nonlinear) stochastic dynamical systems↗
DOE OSTI2020

Deformation of Lie–Poisson algebras and chirality

Linearization of a Hamiltonian system around an equilibrium point yields a set of Hamiltonian symmetric spectra: If λ is an eigenvalue of the linearized generator, -λ and $\barλ$ (hence, -$\barλ$) are also eigenvalues—the former implies a time-reversal symmetry, while the latter guarantees the reality of the solution. However, linearization around a singular equilibrium point (which commonly exists in noncanonical Hamiltonian systems) works out differently, resulting in breaking of the Hamiltonian symmetry of spectra; time-reversal asymmetry causes chirality. This interesting phenomenon was first found in analyzing the chiral motion of the rattleback, a boat-shaped top having misaligned axes of inertia and geometry [Z. Yoshida et al., Phys. Lett. A 381, 2772–2777 (2017)]. To elucidate how chiral spectra are generated, we study the three-dimensional Lie–Poisson systems and classify the prototypes of singularities that cause symmetry breaking. The central idea is the deformation of the underlying Lie algebra; invoking Bianchi’s list of all three-dimensional Lie algebras, we show that the so-called class-B algebras, which are produced by asymmetric deformations of the simple algebra s o ( 3 ) , yield chiral spectra when linearized around their singularities. The theory of deformation is generalized to higher dimensions, including the infinite-dimensional Poisson manifolds relevant to fluid mechanics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

EVALUATION OF ZERO-POWER, ELEVATED-TEMPERATURE MEASUREMENTS AT JAPAN’S HIGH TEMPERATURE ENGINEERING TEST REACTOR

The High Temperature Engineering Test Reactor (HTTR) of the Japan Atomic Energy Agency (JAEA) is a 30 MWth, graphite-moderated, helium-cooled reactor that was constructed with the objectives to establish and upgrade the technological basis for advanced high-temperature gas-cooled reactors (HTGRs) as well as to conduct various irradiation tests for innovative high-temperature research. The core size of the HTTR represents about one-half of that of future HTGRs, and the high excess reactivity of the HTTR, necessary for compensation of temperature, xenon, and burnup effects during power operations, is similar to that of future HTGRs. During the start-up core physics tests of the HTTR, various annular cores were formed to provide experimental data for verification of design codes for future HTGRs. The experimental benchmark performed and currently evaluated in this report pertains to the data available for two zero-power, warm-critical measurements with the fully-loaded HTTR core. Six isothermal temperature coefficients for the fully-loaded core from approximately 340 to 740 K have also been evaluated. These experiments were performed as part of the power-up tests (References 1 and 2). Evaluation of the start-up core physics tests specific to the fully-loaded core (HTTR-GCR-RESR-001) and annular start-up core loadings (HTTR-GCR-RESR-002) have been previously evaluated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Newly Available Reactor Physics Benchmark data in the March 2011 Edition of the IRPhEP Handbook

The International Reactor Physics Experiment Evaluation Project (IRPhEP) was established to preserve integral reactor physics experimental data, including separate or special effects data for nuclear energy and technology applications. Numerous experiments that have been performed worldwide, represent a large investment of infrastructure, expertise, and cost, and are valuable resources of data for present and future research. These valuable assets provide the basis for recording, development, and validation of methods. If the data are compromised, it is unlikely that any of these measurements would be repeated in the future. The purpose of the IRPhEP is to provide an extensively peer-reviewed set of reactor physics-related integral data that can be used by reactor designers and safety analysts to validate the analytical tools used to design next-generation reactors and establish the safety basis for operation of these reactors. Contributors from around the world collaborate in the evaluation and review of selected benchmark experiments for inclusion in the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook). Several new evaluations have been prepared for inclusion in the March 2011 edition of the IRPhEP Handbook.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Brochure on the 2024 ASCR Workshop on Analog Computing for Science

Analog computing fundamentally differs from digital by representing data with fully continuous physical quantities, such as voltages, probabilities, chemical concentrations, or light intensities, rather than encoding values in discrete binary states. While digital computing has historically excelled in precision, scalability, and noise resistance, newer analog approaches are gaining interest for their potential to dramatically improve energy efficiency and processing speed. Analog systems can inherently solve mathematical problems through their physical behavior and offer distinct advantages in scenarios where continuous operations are more effective than Boolean logic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The most irrational rational theories

We propose a two-parameter family of modular invariant partition functions of two-dimensional conformal field theories (CFTs) holographically dual to pure threedimensional gravity in anti de Sitter space. Our two parameters control the central charge, and the representation of SL(2, $\mathbb{Z}$). At large central charge, the partition function has a gap to the first nontrivial primary state of $\frac{c}{24}$. As the SL(2, $\mathbb{Z}$) representation dimension gets large, the partition function exhibits some of the qualitative features of an irrational CFT. This, for instance, is captured in the behavior of the spectral form factor. As part of these analyses, we find similar behavior in the minimal model spectral form factor as c approaches 1.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

FITEVT: A FORTRAN program for arrival-time analysis of nuclear-decay events

FITEVT is a FORTRAN program designed to analyze recorded arrival times of nuclear-decay events affected by dead-time. Here, the primary goal of the program is precise and accurate determination of half-lives. Its method involves imposition of a known sufficiently long extending dead-time to the recorded event sequence, so that the original dead-time effects are completely obliterated and the remaining live-times of the survived events are known exactly. Upon completion of the analysis, the arrival-time spectrum and the live-time spectrum are predicted and compared to those constructed from the survived events.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pass-efficient methods for compression of high-dimensional turbulent flow data

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential equation (PDE) systems. Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory. To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored. Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., or the execution of the PDE solver is expensive, the number of passes made over the data must be minimized. In the interest of addressing this problem, this work focuses on the utility of pass-efficient, parallelizable, low-rank, matrix decomposition methods in compressing high-dimensional simulation data from turbulent flows. Additionally, a particular emphasis is placed on using coarse representation of the data – compatible with the PDE discretization grid – to accelerate the construction of the low-rank factorization. This includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition. The methods are described extensively and numerical experiments on two turbulent channel flow data are performed. In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics. In the particle-laden case, compression factors of 100 are achieved and the compressed data is used to recover particle velocities. These results show that these compression methods can enable efficient computation of various quantities of interest in both the carrier and disperse phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

The classical equations of motion of quantized gauge theories, Part 2: Electromagnetism

In this and companion papers, we show that quantum field theories with gauge symmetries permit a broader class of classical dynamics than typically assumed. In this article, we show that the quantization of electromagnetism permits the existence of classical electric field states that do not obey Gauss’s law. These states are gauge invariant and their time evolution can be consistently described using the Schrödinger equation. The time evolution of these states is such that at the classical level, the full set of Maxwell’s equations would appear to hold, with the physical effects of these states being attributable to an auxiliary, static “shadow” charge density with no internal degrees of freedom. This density could affect the dynamics of charged particles in our universe and it may thus be of observational interest.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Exact ground states of a staggered supersymmetric model for lattice fermions

We study a supersymmetric model for strongly interacting lattice fermions in the presence of a staggering parameter. The staggering is introduced as a tunable parameter in the manifestly supersymmetric Hamiltonian. We obtain analytic expressions for the ground states in the limit of small and large staggering for the model on the class of doubly decorated lattices. On this type of lattice there are two ground states, each with a different density. In one limit we find these ground states to be a simple Wigner crystal and a valence bond solid state. In the other limit we find two types of quantum liquids. As a special case, we investigate the quantum liquid state on the one dimensional chain in detail. It is characterized by a massless kink that separates two types of order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

SU(2) lattice gluon propagators at finite temperatures in the deep infrared region and Gribov copy effects

We study numerically the SU(2) Landau gauge transverse and longitudinal gluon propagators at nonzero temperatures T both in confinement and deconfinement phases. Special attention is paid to the Gribov copy effects in the IR region. Applying a powerful gauge fixing algorithm, we find that the Gribov copy effects for the transverse propagator D{sub T}(p) are very strong in the infrared, while the longitudinal propagator D{sub L}(p) shows very weak (if any) Gribov copy dependence. The value D{sub T}(0) tends to decrease with growing lattice size; however, D{sub T}(0) is nonzero in the infinite volume limit, in disagreement with the suggestion made in [I. Zahed and D. Zwanziger, Phys. Rev. D 61, 037501 (2000).]. We show that in the infrared region, D{sub T}(p) is not consistent with the pole-type formula not only in the deconfinement phase but also for T<T{sub c}. We introduce a new definition of the magnetic infrared mass scale ('magnetic screening mass') m{sub M}. The electric mass m{sub E} has been determined from the momentum space longitudinal gluon propagator. We study also the (finite) volume and temperature dependence of the propagators as well as discretization errors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗