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At least 757 records · Page 42

The Weak Form Is Stronger Than You Think

The weak form is a ubiquitous, well-studied, and widely-utilized mathematical tool in modern computational and applied mathematics. In this work we provide a survey of both the history and recent developments for several fields in which the weak form can play a critical role. In particular, we highlight several recent advances in weak form versions of equation learning, parameter estimation, and coarse graining, which offer surprising noise robustness, accuracy, and computational efficiency. We note that this manuscript is a companion piece to our October 2024 SIAM News article of the same name. Here we provide more detailed explanations of mathematical developments as well as a more complete list of references. Lastly, we note that the software with which to reproduce the results in this manuscript is also available on our group's GitHub website https://github.com/MathBioCU .

26A33, 35D30, 62FXX, 62JXX, 65L09, 65M32, 68Q32,↗

Cryogenic User Facilities for R&D on Noble Liquid Detectors and Low Temperature Devices

Cryogenic test facilities are critical infrastructure for physics experiments in a variety of fields, perhaps most notably for particle detection with noble liquid detectors, low-temperature device development, and quantum information research. However, considerable investment and technical knowledge are required to construct and operate such facilities. This white paper discusses proposals for user facilities aimed at broadening the availability of testing capabilities for the scientific community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ultimate Colliders

Our understanding of the Universe critically depends on the fundamental knowledge of particles and fields, which represents a central endeavor of modern high-energy physics. Energy frontier particle colliders - arguably, among the largest, most complex and advanced scientific instruments of modern times - for many decades have been at the forefront of scientific discoveries in high-energy physics. Due to technology advances and beam physics breakthroughs, the colliding beam facilities have progressed immensely and now operate at energies and luminosities many orders of magnitude greater than the pioneering instruments of the early 1960s. While the Large Hadron Collider and the Super-KEKB factory represent the frontier hadron and lepton colliders of today, respectively, future colliders are an essential component of a strategic vision for particle physics. Conceptual studies and technical developments for several exciting near- and medium-term future collider options are underway internationally. Analysis of numerous proposals and studies for far-future colliders indicate the limits of the collider beam technology due to machine size, cost, and power consumption, and call for a paradigm shift of the particle physics research at ultra-high energy but low luminosity colliders approaching or exceeding 1 PeV center-of-mass energy scale.

43 PARTICLE ACCELERATORS↗

Universality of Shallow Global Quenches in Critical Spin Chains

Measuring universal data in the strongly correlated regime of quantum critical points remains a fundamental objective for quantum simulators. In foundational work, Calabrese and Cardy demonstrated how these data govern the dynamics of certain global quenches to 1+1-dimensional conformal field theories. While the quasiparticle picture they introduce has been widely successful in both theory and experiment, their seminal prediction that the critical exponents are simply encoded in the relaxation rates of local observables is challenging to investigate experimentally. In this Letter, we examine the critical quench dynamics of local observables from two types of readily accessible initial conditions: ground states and finite-temperature ensembles. Here, we identify universal scaling collapses and scaling functions, utilizing a combination of conformal perturbation theory and tensor network numerics. For the finite-temperature quenches, we determine a regime in which the conformal field theory results are recovered, thereby allowing universal quantum critical data to be extracted from realistic quenches.

Quantum many-body systems↗

Near-field imaging of optical resonances in silicon metasurfaces using photoelectron microscopy

Precise control of light–matter interactions at the nanoscale lies at the heart of nanophotonics. However, experimental examination at this length scale is challenging since the corresponding electromagnetic near-field is often confined within volumes below the resolution of conventional optical microscopy. In semiconductor nanophotonics, electromagnetic fields are further restricted within the confines of individual subwavelength resonators, limiting access to critical light–matter interactions in these structures. In this work, we demonstrate that photoelectron emission microscopy (PEEM) can be used for polarization-resolved near-field spectroscopy and imaging of electromagnetic resonances supported by broken-symmetry silicon metasurfaces. We find that the photoemission results, enabled through an in situ potassium surface layer, are consistent with full-wave simulations and far-field reflectance measurements across visible and near-infrared wavelengths. In addition, we uncover a polarization-dependent evolution of collective resonances near the metasurface array edge taking advantage of the far-field excitation and full-field imaging of PEEM. Here, we deduce that coupling between eight resonators or more establishes the collective excitations of this metasurface. All told, we demonstrate that the high-spatial resolution hyperspectral imaging and far-field illumination of PEEM can be leveraged for the metrology of collective, non-local, optical resonances in semiconductor nanophotonic structures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Long-Term Methane Emissions Rate Quantification and Alert System for Natural Gas Storage Wells and Fields

The Department of Energy (DOE) National Energy Technology Laboratory (NETL) and other critical stakeholders (e.g., U.S. Environmental Protection Agency (USEPA), state regulators, and industry) seek to more accurately characterize and quantify methane emissions from natural gas storage wells. These efforts will reduce uncertainties in estimates of these emissions in USEPA’s current Green House Gas Inventory (GHGI) under their Greenhouse Gas Reporting Program (GHGRP; EPA, 2016). Emission factors currently used to estimate methane emissions from gas storage wells are the same factors used for onshore natural gas production wells (USEPA, 2016). This study has developed a robust and representative dataset of emissions from disaggregated gas station wellhead components and related emission factors that will inform future enhancements to the GHGI and GHGRP. Extensive methane emissions measurements and meteorological data were collected from three active storage facilities representing two of the three types of storage facilities (i.e., depleted gas reservoir and salt cavern) to support development of emissions factors specifically for gas storage wells and associated components. Methane emissions were quantified from both above-ground components (e.g., pipe fittings and valves) and seepage from the ground surface in proximity to gas storage wellheads.

03 NATURAL GAS↗

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗

Two-dimensional quantum universality in the spin-1/2 triangular-lattice quantum antiferromagnet Na 2 BaCo(PO 4 ) 2

An interplay of geometrical frustration and strong quantum fluctuations in a spin-1/2 triangular-lattice antiferromagnet (TAF) can lead to exotic quantum states. Here, we report the neutron-scattering, magnetization, specific heat, and magnetocaloric studies of the recently discovered spin-1/2 TAF Na 2 BaCo(PO 4 ) 2 , which can be described by a spin-1/2 easy axis XXZ model. The zero-field neutron diffraction experiment reveals an incommensurate antiferromagnetic ground state with a significantly reduced ordered moment of about 0.54(2) μ B /Co. Different magnetic phase diagrams with magnetic fields in the a b plane and along the easy c -axis were extracted based on the magnetic susceptibility, specific heat, and elastic neutron-scattering results. In addition, two-dimensional (2D) spin dispersion in the triangular plane was observed in the high-field polarized state, and microscopic exchange parameters of the spin Hamiltonian have been determined through the linear spin wave theory. Consistently, quantum critical behaviors with the universality class of d = 2 and ν z = 1 were established in the vicinity of the saturation field, where a Bose–Einstein condensation (BEC) of diluted magnons occurs. The newly discovered quantum criticality and fractional magnetization phase in this ideal spin-1/2 TAF present exciting opportunities for exploring exotic quantum phenomena.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Critical Review of Machine Learning of Energy Materials

Abstract Machine learning (ML) is rapidly revolutionizing many fields and is starting to change landscapes for physics and chemistry. With its ability to solve complex tasks autonomously, ML is being exploited as a radically new way to help find material correlations, understand materials chemistry, and accelerate the discovery of materials. Here, an in‐depth review of the application of ML to energy materials, including rechargeable alkali‐ion batteries, photovoltaics, catalysts, thermoelectrics, piezoelectrics, and superconductors, is presented. A conceptual framework is first provided for ML in materials science, with a broad overview of different ML techniques as well as best practices. This is followed by a critical discussion of how ML is applied in energy materials. This review is concluded with the perspectives on major challenges and opportunities in this exciting field.

Chen, Chi↗

Large Area Near‐Field Thermophotovoltaics for Low Temperature Applications

Abstract Thermophotovoltaics, devices that convert thermal infrared photons to electricity, offer a key pathway for a variety of critical renewable energy technologies including thermal energy storage, waste heat recovery, and direct solar‐thermal power generation. However, conventional far‐field devices struggle to generate reasonable powers at lower temperatures. Near‐field thermophotovoltaics provide a pathway to substantially higher powers by leveraging photon tunneling effects. Here a large area near‐field thermophotovoltaic device is presented, created with an epitaxial co‐fabrication approach, that consists of a self‐supported 0.28 cm 2 emitter‐cell pair with a 150 nm gap. The device generates 1.22 mW at 460 °C, a 25‐fold increase over the same cell measured in a far‐field configuration. Furthermore, the near‐field device demonstrates short circuit current densities greater than the far‐field photocurrent limit at all the temperatures tested, confirming the role of photon tunneling effects in the performance enhancement. Modeling suggests several practical directions for cell improvements and further increases in power density. These results highlight the promise of near‐field thermophotovoltaics, especially for low temperature applications.

36 MATERIALS SCIENCE↗

Magnetic field dependence of the spin fluctuations in CeCu 5.8 ⁢Ag 0.2

Quantum phase transitions are among the most intriguing phenomena that can occur when the electronic ground state of correlated metals are tuned by external parameters such as pressure, magnetic field, or chemical substitution. Such transitions between distinct states of matter are driven by quantum fluctuations, and can give rise to macroscopically coherent phases that are at the forefront of condensed matter research. However, the nature of the critical fluctuations, and thus the fundamental physics controlling many quantum phase transitions, remain poorly understood in numerous strongly correlated metals. Here we study the model material CeCu 5.8⁢ Ag 0.2 to gain insight into the implications of critical fluctuations originating from different regions in reciprocal space. By employing an external magnetic field along the crystallographic 𝑎 and 𝑐 axis as auxiliary tuning parameter, we observe a pronounced anisotropy in the suppression of the quantum critical fluctuations, reflecting the spin anisotropy of the long-range ordered ground state at larger silver concentration. Coupled with the temperature dependence of the quantum fluctuations, these results suggest that the quantum phase transition in CeCu 5.8⁢ Ag 0.2 is driven by three-dimensional spin-density wave fluctuations.

Boraley, Xavier [Paul Scherrer Inst. (PSI), Villig↗

Dimits shift, avalanche-like bursts, and solitary propagating structures in the two-field flux-balanced Hasegawa–Wakatani model for plasma edge turbulence

We show that the recently introduced two-field flux-balanced Hasegawa–Wakatani (BHW) model captures the key features of drift-wave turbulent transport mediated by zonal flows observed in more complete and accurate gyrokinetic simulations, such as the existence of a nonlinear upshift of the threshold for drift wave turbulence driven transport, often called the Dimits shift, as well as non-local transport with avalanche bursts and solitary propagating structures. Because of the approximations made in the BHW model, these observations are made for the particle flux instead of the heat flux more commonly studied in ion temperature gradient (ITG) driven turbulence in fluid or gyrokinetic codes. Many of these features are not seen in other Hasegawa–Wakatani models, which confirm the critical role of the electron dynamics parallel to the magnetic field lines. To address questions regarding the role of boundary conditions on the drift-wave zonal flow dynamics, we apply our model to both a channel domain geometry and the more typical doubly periodic geometry. We only observe strong soliton-like solutions in the particle flux for the channel geometry, in the vicinity of the boundaries, where strong velocity shear and density gradients are generated, which are absent in the doubly periodic simulations. Changing the aspect ratio of the simulation domain also has a significant effect. In domains which are elongated in the radial direction, more complex multi-scale dynamics takes place, with multiple zonal jets interacting with each other, and large scale avalanches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Designing an Optimal LSST Deep Drilling Program for Cosmology with Type Ia Supernovae

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) is forecast to collect a large sample of Type Ia supernovae (SNe Ia) expected to be instrumental in unveiling the nature of dark energy. The feat, however, requires accurately measuring the two components of the Hubble diagram, distance modulus and redshift. Distance is estimated from SN Ia parameters extracted from light-curve fits, where the average quality of light curves is primarily driven by survey parameters. An optimal observing strategy is thus critical for measuring cosmological parameters with high accuracy. We present in this paper a three-stage analysis to assess the impact of the deep drilling (DD) strategy parameters on three critical aspects of the survey: redshift completeness, the number of well-measured SNe Ia, and cosmological measurements. We demonstrate that the current DD survey plans (internal LSST simulations) are characterized by a low completeness (z ~ 0.55–0.65), and irregular and low cadences (several days), which dramatically decrease the size of the well-measured SN Ia sample. We propose a method providing the number of visits required to reach higher redshifts. We use the results to design a set of optimized DD surveys for SN Ia cosmology taking full advantage of spectroscopic resources for host galaxy redshift measurements. The most accurate cosmological measurements are achieved with deep rolling surveys characterized by a high cadence (1 day), a rolling strategy (at least two seasons of observation per field), and ultradeep (z ≳ 0.8) and deep (z ≳ 0.6) fields. A deterministic scheduler including a gap recovery mechanism is critical to achieving a high-quality DD survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Suppression of ferromagnetism governed by a critical lattice parameter in CeTiGe 3 with hydrostatic pressure or V substitution

We combine structural and magnetic measurements to compare the different magnetic phase diagrams between the pressure and substitution studies in CeTiGe 3 . We report on the structural, magnetic, and electrical transport properties of single crystals of CeTi 1–x V x Ge 3 (x = 0, 0.1, 0.2, 0.3, 0.4, 0.9, and 1), and of polycrystalline samples (x = 0.5, 0.6, 0.7, 0.8), as well as structural properties of CeTiGe 3 under pressure up to 9 GPa. The ferromagnetic ordering in CeTiGe 3 is suppressed with V doping in CeTi 1–x V x Ge 3 , and suggests a possible ferromagnetic quantum critical point near x = 0.45. We perform a detailed crystalline electric field (CEF) analysis, and the magnetic susceptibility data in pure CeTiGe 3 and CeVGe 3 can be well explained by the CEF model. The proposed CEF energy levels suggest that there is a gradual change of the ground state from |±5/2 in CeTiGe 3 to |±1/2 in CeVGe 3 , and a suppression of CEF splitting energies near the quantum critical region. When hydrostatic pressure is used instead of chemical substitution, the quantum critical point is avoided by the appearance of magnetic phases above around 4.1 GPa. In the substitution study, the ferromagnetic and antiferromagnetic regions are well separated, whereas they touch in the pressure study. We observe a different trend in the temperature dependence of the resistivity maximum in both studies, suggesting that the CEF splitting energy is suppressed by V substitution but enhanced by pressure. Here, we also observe different responses in lattice constants between the two studies, highlighting the fact that substitution effects cannot be reduced to chemical pressure effects only. Nevertheless, when the magnetic phase diagrams of both hydrostatic pressure and substitution are compared, we find a common critical lattice constant c = 5.78 Å where the ferromagnetic ordering is suppressed in both studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Regional Feedstock Partnership Biomass Quality Assessment Final Report

The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years

09 BIOMASS FUELS↗

Far-field speckle correlations as a function of object position for microscopically distinguishing objects hidden in a randomly scattering medium

Super-resolution optical sensing is of critical importance in science and technology and has required prior information about an imaging system or obtrusive near-field probing. Additionally, coherent imaging and sensing in heavily scattering media such as biological tissue has been challenging, and practical approaches have either been restricted to measuring the field transmission of a single point source, or to where the medium is thin. We present the concept of far-subwavelength spatial sensing with relative object motion in speckle as a means to coherently sense through heavy scatter. Experimental results demonstrate the ability to distinguish nominally identical objects with nanometer-scale translation while hidden in randomly scattering media, without the need for precise or known location and with imprecise replacement. The theory and supportive illustrations presented provide the basis for super-resolution sensing and the possibility of virtually unlimited spatial resolution, including through thick, heavily scattering media with relative motion of an object in a structured field. This work provides enabling opportunities for material inspection, security, and biological sensing.

Hastings, Ryan L. (ORCID:0009000095977807)↗

Precision study of the massive Schwinger model near quantum criticality

We perform a numerical analysis of the massive Schwinger model in the presence of a background electric field. Using the Density Matrix Renormalization Group approach, we efficiently compute the spectrum of the Schwinger model on a staggered lattice with up to 3000 qubits. As a result, we achieve a precise computation of the critical mass of the massive Schwinger model to five digits using four different “criticality criteria,” observing perfect agreement among them Additionally, we discuss the effect of a four-fermion operator deformation of the Schwinger model and compute the critical mass for various values of the deformation parameter.

Critical phenomena↗

Data-driven assessment of magnetic charged particle confinement parameter scaling in magnetized liner inertial fusion experiments on Z

In magneto-inertial fusion, the ratio of the characteristic fuel length perpendicular to the applied magnetic field R to the α-particle Larmor radius $ϱ_α$ is a critical parameter setting the scale of electron thermal-conduction loss and charged burn-product confinement. Here, using a previously developed deep-learning-based Bayesian inference tool, we obtain the magnetic-field fuel-radius product BR ∝ R / $ϱ_α$ from an ensemble of 16 magnetized liner inertial fusion (MagLIF) experiments. Observations of the trends in BR are consistent with relative trade-offs between compression and flux loss as well as the impact of mix from 1D resistive radiation magneto-hydrodynamics simulations in all but two experiments, for which 3D effects are hypothesized to play a significant role. Finally, we explain the relationship between BR and the generalized Lawson parameter χ. Our results indicate the ability to improve performance in MagLIF through careful tuning of experimental inputs, while also highlighting key risks from mix and 3D effects that must be mitigated in scaling MagLIF to higher currents with a next-generation driver.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗