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At least 253 records · Page 14

Fundamental physics with ESPRESSO: a new determination of the D/H ratio towards PKS1937-101

ABSTRACT Primordial abundances of light elements are sensitive to the physics of the early Universe and can directly constrain cosmological quantities, such as the baryon-to-photon ratio $\eta _{10}$, the baryon density, and the number of neutrino families. Deuterium is especially suited for these studies: its primordial abundance is sensitive and monotonically dependent on $\eta _{10}$, allowing an independent measurement of the cosmic baryon density that can be compared, for instance, against the Planck satellite data. The primordial deuterium abundance can be measured in high H i column density absorption systems towards distant quasars. We report here a new measurement, based on high-resolution ESPRESSO data, of the primordial D i abundance of a system at redshift $z \sim 3.572$, towards PKS1937-101. Using only ESPRESSO data, we find a D /H ratio of $2.638\pm 10^{-5}$, while including the available UVES data improves the precision, leading to a ratio of $2.608 \pm 10^{-5}$. The results of this analysis agree with those of the most precise existing measurements. We find that the relatively low column density of this system ($\log {N_{\rm H_I}/ {\rm cm}^{-2}}\sim 18$) introduces modelling uncertainties, which become the main contributor to the error budget.

Guarneri, Francesco (ORCID:0000000347409762)↗

Scalable Hybrid Learning Techniques for Scientific Data Compression

Data compression is becoming critical for storing scientific data because many scientific applications need to store large amounts of data and post process this data for scientific discovery. Unlike image and video compression algorithms that limit errors to primary data (PD), scientists require compression techniques that accurately preserve derived quantities of interest (QoIs). Here, this article presents a physics-informed compression technique implemented as an end-to-end, scalable, GPU-based pipeline for data compression that addresses this requirement. Our hybrid compression technique combines machine learning techniques and standard compression methods. Specifically, we combine an autoencoder, an error-bounded lossy compressor to provide guarantees on raw data error, and a constraint satisfaction post-processing step to preserve the QoIs within a minimal error (generally less than floating point error). The effectiveness of the data compression pipeline is demonstrated by compressing nuclear fusion simulation data generated by a large-scale fusion code, XGC, which produces hundreds of terabytes of data in a single day. Our approach works within the ADIOS framework and results in compression by a factor of more than 150 while requiring only a few percent of the computational resources necessary for generating the data, making the overall approach highly effective for practical scenarios.

ITER↗

Development of a Discrepancy Checker for the Digital Twin in a Supervisory Control System for a Thermal Energy Delivery System

Defined as a virtual representation of a physical object, process, or service, and used to support real-world decision-making, a digital twin (DT) can be utilized to combine classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems, and to enable optimal autonomous operations. However, a DT’s usefulness largely depends on its ability to adequately mirror the state of its physical counterpart, and this adequacy should be reflected by the level of uncertainty in the underlying simulation models when estimating and predicting quantities of interest (QOIs). Moreover, simulation models in a DT may involve multiple fidelities of representations—ranging from physics-based models to data-driven ones—but classical uncertainty quantification (UQ) methods struggle to handle numerous uncertainty sources, nor are they designed for real-time applications. This work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system applied to a thermal energy delivery system (TEDS) at Idaho National Laboratory. The discrepancy checker was developed using metadata from an automated DT development process, and these metadata included different combinations of physical model forms and model parameters, training data and hyperparameters for surrogate models, and design parameters for supervisory control systems. Next, correlations between the uncertainty results and the metadata were established and then applied to the DT operations. The discrepancy checker evaluates the discrepancies between model predictions from virtual and sensor measurements and backtraces them to the corresponding major sources of uncertainty. The discrepancy checker showed reasonable performance in detecting discrepancies and diagnosing sources of uncertainty in testing scenarios.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Elimination of the linearization error in APW/LAPW basis set: Dirac-Kohn-Sham equations

Here, a detailed account of the implementation of equations of the relativistic density functional theory (RDFT) using basis sets of APW/LAPW type with flexible extensions provided by local orbitals is given. Earlier discoveries of the importance of the high derivative local orbital (HDLO) extension of the APW/LAPW basis set for enhancing the accuracy of DFT calculations are confirmed using a fully relativistic approach and α – U as an example. High energy local orbitals (HELO's), however indispensable for GW calculations, are considerably less efficient in enhancing the accuracy of DFT applications. It is shown that a simplified approach to the relativistic effects, namely considering them only inside the muffin-tin (MT) spheres, produces basically identical results (as compared to fully relativistic approach) for the electronic free energy of the five materials considered in this work. By comparing the effect of the simplified approach on the electronic free energy with its effect on the electronic kinetic energy we conclude that the insensitivity of the free energy to the way we describe the relativistic effects in the interstitial region is related to the variational property of this quantity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Preface to the Proceedings of the 23rd Topical Conference on High-Temperature Plasma Diagnostics

Measurements of phenomena advance our understanding of the physical universe. As our understanding grows, more precise measurements are required, as are measurements of new quantities. Diagnosis of a plasma requires developing new instruments, also called diagnostics, as well as new ways to analyze, interpret, synthesize, and correlate their measurements. Further, as computing power increases and multi-physics codes improve their accuracy, more precise measurements are needed to guide future code developments and to validate predictions of these simulation codes. The Topical Conference on High-Temperature Plasma Diagnostics is focused on presenting and documenting the most recent advances in these instrumentation areas for plasmas. The 23rd occurrence of this biennial conference took place on December 14–17, 2020, and was hosted by Los Alamos National Laboratory. Originally scheduled for June 2020 in Santa Fe, New Mexico, the conference was postponed and then held virtually due to the global COVID-19 pandemic. Conference times were adjusted and presentations were scheduled to meet the needs of attendees in Europe, the USA, and Asia.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

PandAna: A Python Analysis Framework for Scalable High Performance Computing in High Energy Physics

Modern experiments in high energy physics analyze millions of events recorded in particle detectors to select the events of interest and make measurements of physics parameters. These data can often be stored as tabular data in files with detector information and reconstructed quantities. Current techniques for event selection in these files lack the scalability needed for high performance computing environments. We describe our work to develop a high energy physics analysis framework suitable for high performance computing. This new framework utilizes modern tools for reading files and implicit data parallelism. Framework users analyze tabular data using standard, easy-to-use data analysis techniques in Python while the framework handles the file manipulations and parallelism without the user needing advanced experience in parallel programming. In future versions, we hope to provide a framework that can be utilized on a personal computer or a high performance computing cluster with little change to the user code.

Groh, Micah↗

Microscopic Imprints of Learned Solutions in Tunable Networks

In physical networks trained using supervised learning, physical parameters are adjusted to produce desired responses to inputs. An example is an electrical contrastive local learning network of nodes connected by edges that adjust their conductances during training. When an edge conductance changes, it upsets the current balance of every node. In response, physics adjusts the node voltages to minimize the dissipated power. Learning in these systems is therefore a coupled double-optimization process, in which the network descends both a cost landscape in the high-dimensional space of edge conductances and a physical landscape—the power dissipation—in the high-dimensional space of node voltages. Because of this coupling, the physical landscape of a trained network contains information about the learned task. Here, we derive a structure-function relation for trained tunable networks and demonstrate that all the physical information relevant to the trained input-output relation can be captured by a tuning susceptibility, an experimentally measurable quantity. We supplement our theoretical results with simulations to show that the tuning susceptibility is correlated with functional importance and that we can extract physical insight into how the system performs the task from the conductances of highly susceptible edges. Our analysis is general and can be applied directly to mechanical networks, such as networks trained for protein-inspired function such as allostery.

36 MATERIALS SCIENCE↗

Multi-output multilevel best linear unbiased estimators via semidefinite programming

Multifidelity forward uncertainty quantification (UQ) problems often involve multiple quantities of interest and heterogeneous models (e.g., different grids, equations, dimensions, physics, surrogate and reduced-order models). While computational efficiency is key in this context, multi-output strategies in multilevel/multifidelity methods are either sub-optimal or non-existent. In this paper we extend multilevel best linear unbiased estimators (MLBLUE) to multi-output forward UQ problems and we present new semidefinite programming formulations for their optimal setup. Not only do these formulations yield the optimal number of samples required, but also the optimal selection of low-fidelity models to use. While existing MLBLUE approaches are single-output only and require a non-trivial nonlinear optimization procedure, the new multi-output formulations can be solved reliably and efficiently. Here, we demonstrate the efficacy of the new methods and formulations in practical UQ problems with model heterogeneity.

97 MATHEMATICS AND COMPUTING↗

Disentangling quantum matter with measurements

Measurements destroy entanglement. Building on ideas used to study ‘quantum disentangled liquids,’ we explore the use of this effect to characterize states of matter. In this work, we focus on systems with multiple components, such as charge and spin in a Hubbard model or local moments and conduction electrons in a Kondo lattice model. In such systems, measurements of (a subset of) one of the components can leave behind a quantum state of the other that is easy to understand, for example in terms of scaling of entanglement entropy of subregions. We bound the outcome of this protocol, for any choice of measurement, in terms of more standard information-theoretic quantities. We apply this quantum disentangling protocol to several problems of physical interest, including gapless topological phases, heavy fermions, and scar states in the Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fireball antinucleosynthesis

The tentative identification of approximately ten relativistic antihelium ( He ¯ ) cosmic-ray events at AMS-02 would, if confirmed, challenge our understanding of the astrophysical synthesis of heavy antinuclei. We propose a novel scenario for the enhanced production of such antinuclei that is triggered by isolated, catastrophic injections of large quantities of energetic Standard Model (SM) antiquarks in our galaxy by physics beyond the Standard Model (BSM). We demonstrate that SM antinucleosynthetic processes that occur in the resulting rapidly expanding, thermalized fireballs of SM plasma can, for a reasonable range of parameters, produce the reported tentative ∼ 2 : 1 ratio of He ¯ 3 to He ¯ 4 events at AMS-02, as well as their relativistic boosts. Moreover, we show that this can be achieved without violating antideuterium or antiproton flux constraints for the appropriate antihelium fluxes. A plausible BSM paradigm for the catastrophic injections is the collision of macroscopic composite dark-matter objects carrying large net antibaryon number. Such a scenario would require these objects to be cosmologically stable, but to destabilize upon collision, promptly releasing a fraction of their mass energy into SM antiparticles within a tiny volume. We show that, in principle, the injection rate needed to attain the necessary antihelium fluxes and the energetic conditions required to seed the fireballs appear possible to obtain in such a paradigm. We leave open the question of constructing a BSM particle physics model to realize this, but we suggest two concrete scenarios as promising targets for further investigation. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Panel Session 145: Challenges and Opportunities in Establishing a System for Transportation of SNF/UNF

Issues associated with establishing a SNF Transportation System in the U.S. are complex. In part, this is because in the US when discussing SNF, there are two distinct categories. The two categories represent significant differences in ownership, transportation-regulator, and even the physical characteristics of the SNF. Specifically, the physical differences in the SNF include size of the rods, associated quantities to be shipped, cladding material, and radionuclide content/enrichment. The first is commercial SNF (i.e., that associated with nuclear power plants), owned by utilities, until a permanent repository is built with DOE obligated by law to then assume the responsibility for shipping and ownership of the SNF. Since no-permanent repository currently exists, most commercial SNF is stored near the reactor in which it was installed, hence requiring no shipments. Although current shipments of commercial SNF are very limited, the few that do occur are generally performed to support a utilities SNF consolidation effort utility and for post irradiation examination/testing. However, with approximately 83,000 metric tons currently being stored at more than 70 sites around the U.S., when a permanent repository becomes available, the required number of shipments will be extensive. The second category is DOE and research reactor fuel. These fuel rods are generally much smaller in length than commercial fuel rods, with the quantity of rods transported in a shipment significantly less than the number of rods in a typical commercial fuel assembly. Currently, most of the SNF shipments within the U.S come from this category. DOE is currently managing about 2500 metric tons of heavy metal of SNF. This panel focused on updates and status of transportation of SNF/UNF. Panelists provided updates and information on continuing impacts, risk assessment, equipment (rail cars, handling, securement), possible rail routing, and proposed inspection equipment/routing prior to shipments. Panelists with presentations: Preparing for Nuclear Waste Transportation (Daniel Ogg); Challenges and Opportunities in Establishing a System for Transportation of SNF/UNF (Kathy Langan); UNF Transportation: Challenges and Opportunities (Michael Valenzano)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A path to scaling helium-3 spin-exchange optical pumping

Polarized 3 He has contributed to breakthroughs in particle physics, neutron scattering, and lung imaging, mostly by optical pumping of liter quantities in valved cells or in sealed cells pumped in situ. Only metastability exchange optical pumping currently meets the demand for delivering large quantities of highly polarized 3 He to external volumes. Our development program is under way to achieve medium to large-scale spin-exchange optical pumping of 3 He. Thin-walled aluminosilicate cells placed in contact with thermal reservoirs inside a pressure vessel were optically pumped with kilowatt-scale lasers spectrally narrowed to match pressure-broadened absorption linewidths. We report here the key elements of this program and significant milestones: multi-liter volume valved cells that provide long longitudinal lifetimes that reached polarization as high as 85% inside a thermally stable and pressurized environment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Rotor Magnet Fault Analysis in Permanent Magnet AC Machines Under Load Conditions - All Electric Transportation Systems

This paper studies the performance of a Permanent Magnet (PM) alternating-current (AC) machine when subjected to faults under load conditions. The effect of varying load torques, and unbalances are found to be potential causes of rotor faults, inducing physical magnet defects or broken rotor-PMs. The consequent and immediate impact on the machine quantities is observed through anomalous change in torque-speed characteristics and other vital signatures such as machine back-EMF/flux and motor current signatures (MCS). The present research study develops and illustrates a method to diagnose physical magnet defects (fault) in PMAC machines by estimating the machine torque/back-EMF constant, Ke. The constant Ke is a measure of magnet strength exhibiting the health of rotor PMs, indicative of faults. Advanced research studies and investigations are carried out to establish motor approximations and signature-based analysis as significant viable tools for diagnosing machine faults even under load conditions.

alternating current↗

Radiative classical gravitational observables at $ \mathcal{O} $(G 3 ) from scattering amplitudes

We compute classical gravitational observables for the scattering of two spinless black holes in general relativity and N =8 supergravity in the formalism of Kosower, Maybee, and O’Connell (KMOC). We focus on the gravitational impulse with radiation reaction and the radiated momentum in black hole scattering at $ \mathcal{O} $(G 3 ) to all orders in the velocity. These classical observables require the construction and evaluation of certain loop-level quantities which are greatly simplified by harnessing recent advances from scattering amplitudes and collider physics. In particular, we make use of generalized unitarity to construct the relevant loop integrands, employ reverse unitarity, the method of regions, integration-by-parts (IBP), and (canonical) differential equations to simplify and evaluate all loop and phase-space integrals to obtain the classical gravitational observables of interest to two-loop order. The KMOC formalism naturally incorporates radiation effects which enables us to explore these classical quantities beyond the conservative two-body dynamics. From the impulse and the radiated momentum, we extract the scattering angle and the radiated energy. Finally, we discuss universality of the impulse in the high-energy limit and the relation to the eikonal phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

QED corrections to the thermal neutrino interaction rate

Abstract Motivated by precision computations of neutrino decoupling at MeV temperatures, we show how QED corrections to the thermal neutrino interaction rate can be related to the electron-positron spectral function as well as an effective$$\overline{\nu }\nu \gamma $$vertex. The spectral function is needed both in a timelike and in a spacelike domain, and for both of its physical polarization states (transverse and longitudinal with respect to spatial momentum). Incorporating an NLO evaluation of this spectral function, an estimate of the$$\overline{\nu }\nu \gamma $$vertex, and HTL resummation of scatterings mediated by soft Bose-enhancedt-channel photons, we compute the interaction rate as a function of the neutrino momentum and flavour. Effects on the – (0. . .2)% level are found, noticeably smaller than a previous estimate of a related quantity.

Physics↗

Laser Disdrometer Quantities (LDQUANTS) and Video Disdrometer Quantities (VDISQUANTS) Value-Added Products Report

Disdrometers are useful instruments that measure the distribution of raindrop sizes (drop size distribution: DSD) and the associated rainfall rates/accumulation as those raindrops fall to the ground. These DSDs are a quantity of interest to members of the modeler and observational communities. However, use of disdrometer data for model evaluation, radar monitoring, or other activities requires careful quality control and processing for key DSD properties of interest (e.g., the number concentration of drops) to ensure appropriate physical (scattering, fall speed) assumptions. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Laser Disdrometer Quantities and Video Disdrometer Quantities Value-Added Product (LDQUANTS/VDISQUANTS VAP) uses standard methods from Tokay et al. (e.g., 2013, 2014) to filter drops with unrealistic fall speeds. Further, it estimates several microphysical/geophysical quantities of parameterized DSDs (gamma or exponential assumption type fitting methods) as in previous disdrometer studies and ARM long-term efforts (e.g., Testud et al. 2001, Giangrande et al. 2014, Thompson et al. 2015). Disdrometers are also beneficial for cross-checks with other instrumentation, including rain gauges and radars. To support research interests and related radar monitoring activities, this product calculates radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR, etc.), using T-Matrix scattering and additional wavelength, temperature, and drop shape assumptions (e.g., Thurai et al. 2007). All of these efforts allow disdrometer data sets to become more useful and easily handled by modeling and observational studies, or routine instrumentation checks.

47 OTHER INSTRUMENTATION↗

Integrability technique for fluid flow induced deformation of a boundary hair

The deformation of a dense carpet of hair due to Stokes flow in a channel can be described by a nonlinear integrodifferential equation for the shape of a single hair, which possesses several solutions for a given choice of parameters. Although it was posed in a previous study and it bears a resemblance to the pendulum problem from mechanics, this equation has not been analytically solved until now. Despite the presence on an integral with a nonlinear functional dependence on the dependent variable, the system is integrable. We compare the analytically obtained solution to a finite-difference numerical approach, identify the physically realizable solution branch, and briefly study the solution structure through a conserved energylike quantity. Time-dependent fluid-structure interactions are a rich and complex subject to investigate, and we argue that the solution discussed herein can be used as a basis for understanding these systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗