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At least 415 records · Page 23

Magnetic excitations, nonclassicality, and quantum wake spin dynamics in the Hubbard chain

Recent work has demonstrated that quantum Fisher information (QFI), a witness of multipartite entanglement, and magnetic Van Hove correlations G(r,t), a probe of local real-space real-time spin dynamics, can be successfully extracted from inelastic neutron scattering on spin systems through accurate measurements of the dynamical spin structure factor S(k,ω). In this work, we apply theoretically these ideas to the half-filled Hubbard chain with nearest-neighbor hopping, away from the strong-coupling limit. This model has nontrivial redistribution of spectral weight in S(k,ω) going from the noninteracting limit (U = 0) to strong coupling (U→∞), where it reduces to the Heisenberg quantum spin chain. We use the density matrix renormalization group to find S(k,ω), from which QFI is then calculated. We find that QFI grows with U. With realistic energy resolution it becomes capable of witnessing bipartite entanglement above U=2.5 (in units of the hopping), where it also changes slope. This point is also proximate to slope changes of the bandwidth W(U) and the half-chain von Neumann entanglement entropy. We compute G(r,t) by Fourier transforming S(k,ω). The results indicate a crossover in the short-time short-distance dynamics at low U characterized by ferromagnetic light-cone wavefronts, to a Heisenberg-type behavior at large U featuring antiferromagnetic light cones and spatially period-doubled antiferromagnetism. We find this crossover has largely been completed by U=3. Our results thus provide evidence that, in several aspects, the strong-coupling limit of the Hubbard chain is reached qualitatively already at a relatively modest interaction strength. We discuss experimental candidates for observing the G(r,t) dynamics found at low U.

1-dimensional systems↗

Self-diagnosis of model suitability for continuous measurements of stream-dissolved organic carbon derived from in situ UV–visible spectroscopy

Application of high-frequency monitoring of dissolved organic carbon (DOC) is difficult in instances where training datasets are challenging to develop (e.g., remote locations) and the relationship between optical features and DOC concentration changes due to environmental or landscape shifts (e.g., climate or land-use change). We developed and compared three partial least squares (PLS) models using in situ water level measurements, conductivity, and UV–Vis spectral attenuation to predict DOC. Two site-specific models were developed using data from a hillslope-dominated forest or a low-relief wetland-pond-dominated stream catchment. The third model, using data from both sites, exhibited the best performance (DOC range = 4–15.5 mg C L −1 , mean = 8.38 mg C L −1 , training RMSE = 0.34 mg C L −1 , internal validation RMSE = 0.50 mg C L −1 , external validation RMSE = 2.43 mg C L −1 ). We further demonstrate using PLS model statistics to monitor performance and elucidate when and how models should be updated. These statistics, Hotelling's T 2 and squared prediction errors, are useful consistency checks for the predictions made and detect underlying inconsistencies that, if undetected, can reduce the robustness of DOC prediction. For example, via the T 2 statistic, we identified the summer–autumn transition as a period when DOC composition differed from what was represented in the training dataset. We also determined that elevated SUVA 254 values contributed to the overall bias observed in predictions made during the subsequent year as part of the external validation. This enabled the application of a bias correction that reduced the RMSE from 2.43 to 0.89 mg C L −1 . The method presented here could be applied to future monitoring programs enabling model updates to monitor DOC fluxes accurately from optical datasets (e.g., attenuance or fluorescence) in the face of developing datasets in remote locations or environmental change. In conclusion, implementation of this approach may also identify possible regime shifts or landscape and hydrologic change associated with climate and other environmental changes relevant to terrestrial to aquatic fluxes.

UV-VIS spectroscopy↗

MESA Isochrones and Stellar Tracks (MIST). III. The White Dwarf Cooling Sequence

We present a substantial update to the MESA Isochrones and Stellar Tracks (MIST) library, extending the MIST model grids and isochrones down the white dwarf (WD) cooling sequence with realistic physics for WD cooling timescales. This work provides a large grid of MESA models for carbon–oxygen core WDs with hydrogen atmospheres (spectral type DA/DC), descended from full prior stellar evolution calculations. The model tracks, isochrones, and WD cooling timescale contours are available on the MIST project website and at doi:10.5281/zenodo.15242047. Our WD models provide a very large, publicly available grid with detailed physics for WD cooling timescales: realistic interior and envelope compositions, with element diffusion and heavy-element sedimentation, nuclear burning at the base of the WD hydrogen envelope, core crystallization, and C/O phase separation. As a large grid of open-source stellar evolution models, these WD models provide both out-of-the-box model tracks for comparison with observations and a framework for building further WD models to investigate variations in WD physics.

Astronomy and AstroPhysics↗

Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model

This paper presents a novel methodology to use direct numerical simulation (DNS) to study the impact of isotropic homogeneous turbulence on the condensational growth of cloud droplets. As shown by previous DNS studies, the impact of turbulence increases with the computational domain size, that is, with the Reynolds number, because larger eddies generate higher and longer-lasting supersaturation fluctuations that affect growth of individual cloud droplets. The traditional DNS can only simulate a limited range of scales because of the excessive computational cost that comes from resolving all scales involved, that is, from large scales at which the turbulent kinetic energy (TKE) is introduced down to the Kolmogorov microscale, and from following every single droplet. The novel approach is referred to as the “scaled-up DNS”. The scaling up is done in two parts, first by increasing both the computational domain and the Kolmogorov microscale and second by using super-droplets instead of real droplets. To ensure proper dissipation of TKE and scalar variance at small scales, molecular transport coefficients are appropriately scaled up with the grid length. For the scaled-up domains, say, meters and tens of meters, one needs to follow billions of real droplets. This is not computationally feasible, and so-called super-droplets are applied in scaled-up DNS simulations. Each super-droplet represents an ensemble of identical real droplets, and the number of real droplets represented by a super-droplet is referred to as the multiplicity attribute. After simple tests showing the validity of the methodology, scaled-up DNS simulations are conducted for five domains, the largest of 64 3 m 3 volume using a DNS of 256 3 grid points and various multiplicities. All simulations are carried out with vanishing mean vertical velocity and with no mean supersaturation, similarly to past DNS studies. As expected, the supersaturation fluctuations as well as the spread in droplet size distribution increase with the domain size, with the droplet radius variance increasing in time t as t 1∕2 as identified in previous DNS studies. Scaled-up simulations with different multiplicities document numerical convergence of the scaled-up solutions. Finally, we compare the scaled-up DNS results with a simple stochastic model that calculates supersaturation fluctuations based on the vertical velocity fluctuations updated using the Langevin equation. Overall, the results document similar scaling to previous small-domain DNS simulations and support the notion that the stochastic subgrid-scale model is a valuable tool for the multi-scale simulation of droplet spectral evolution applying a large-eddy simulation model.

54 ENVIRONMENTAL SCIENCES↗

Developing a complete AI-accelerated workflow for superconductor discovery

The quest to identify new superconducting materials with enhanced properties is hindered by the prohibitive cost of computing electron-phonon spectral functions, severely limiting the materials space that can be explored. Here, we introduce a Bootstrapped Ensemble of Equivariant Graph Neural Networks (BEE-NET), a machine-learning model trained to predict the Eliashberg spectral function and superconducting critical temperature with a mean-absolute-error of 0.87 K relative to DFT-based Allen-Dynes calculations. Intriguingly, BEE-NET achieves a true-negative-rate of 99.4%, enabling highly efficient screening for the rare property of superconductivity. Integrated into a multi-stage, AI-accelerated discovery pipeline that incorporates elemental-substitution strategies and machine-learned interatomic potentials, our workflow reduced over 1.3 million candidate structures to 741 dynamically and thermodynamically stable compounds with DFT-confirmed T c > 5 K. We report the successful synthesis and experimental confirmation of superconductivity in two of these previously unreported compounds. This study establishes a data-driven framework that integrates machine learning, quantum calculations, and experiments to systematically accelerate superconductor discovery.

Gibson, Jason B. [Quantum Formatics, Cambridge, MA↗

Out of distribution evaluation for neural image compression

Official code for the NeurIPS 2023 paper "Neural Image Compression: Generalization, Robustness, and Spectral Biases". This code can be used to: - Computing spectral distortion errors of images compressed with traditional codes or neural image compression models (as proposed in the aformentioned paper) - Visualize power spectral densities and fourier heatmaps (as proposed in the aformentioned paper) - Train and test a variety of neural image compression models

Lieberman, KelseyA↗

Pulsed contact glow discharge electrification for online material quantification

Real-time elemental analysis of liquids in extreme environments remains a significant challenge for sensor development, particularly in applications such as advanced nuclear reactors. Plasma-based optical emission spectroscopy offers a promising solution. In this study, we investigate pulsed contact glow discharge electrolysis (CGDE) as an alternative plasma generation method for emission-based material quantification. Using aqueous NaCl solutions, we examine the role of discharge polarity on plasma behavior, emission characteristics, and spectral output. Our results demonstrate that cathodic discharges generate more energetic plasmas, enabling the detection of ionic species such as cerium, while anodic discharges favor atomic emission. These findings reveal a potential dual-mode sensing capability controlled by circuit configuration rather than hardware changes. Through synchronized measurements of emission, current, bubble, and spectral dynamics, we present a model in which electron emission and ohmic heating drive plasma formation. This model enhances our understanding of pulsed-CGDE and supports its potential as a versatile, adaptable platform for future deployment in high-temperature liquids such as molten salts.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

Influence of Polymorphs and Local Defect Structures on NMR Parameters of Graphite Fluorides

In this study, the role of local molecular structure on calculated 13 C and 19 F NMR chemical shifts for graphite fluoride materials was explored by using gauge-including projector augmented wave (GIPAW) computational methods for different periodic crystal polymorphs and density functional theory (DFT) gauge-including atomic orbital (GIAO) computational methods for individual graphite fluoride platelets, i.e., fluorinated graphene (FG). The impact of stacking sequences, d -spacing, and ring conformations on fully fluorinated graphite fluoride structures was investigated. A range of different defects including Stone–Wales, F and C vacancies, void formation, and F inversion were also evaluated using FG structures. These calculations show that distinct chemical shift signatures exist for many of these polymorphs and defects, therefore providing a basis for spectral assignment and development of models describing the mean local CF structure in disordered graphite fluoride materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Moment expansion of polarized dust SED: A new path towards capturing the CMB B -modes with LiteBIRD

Accurate characterization of the polarized dust emission from our Galaxy will be decisive in the quest for the cosmic microwave background (CMB) primordial B-modes. An incomplete modeling of its potentially complex spectral properties could lead to biases in the CMB polarization analyses and to a spurious measurement of the tensor-to-scalar ratio r. It is particularly crucial for future surveys like the LiteBIRD satellite, the goal of which is to constrain the faint primordial signal leftover by inflation with an accuracy on the tensor-to-scalar ratio r of the order of 10 –3 . Variations of the dust properties along and between lines of sight lead to unavoidable distortions of the spectral energy distribution (SED) that cannot be easily anticipated by standard component-separation methods. This issue can be tackled using a moment expansion of the dust SED, an innovative parametrization method imposing minimal assumptions on the sky complexity. In the present paper, we apply this formalism to the B-mode cross-angular power spectra computed from simulated LiteBIRD polarization data at frequencies between 100 and 402 GHz that contain CMB, dust, and instrumental noise. The spatial variation of the dust spectral parameters (spectral index β and temperature T) in our simulations lead to significant biases on r (~21 σ r ) if not properly taken into account. Performing the moment expansion in β, as in previous studies, reduces the bias but does not lead to sufficiently reliable estimates of r. We introduce, for the first time, the expansion of the cross-angular power spectra SED in both β and T, showing that, at the sensitivity of LiteBIRD, the SED complexity due to temperature variations needs to be taken into account in order to prevent analysis biases on r. Thanks to this expansion, and despite the existing correlations between some of the dust moments and the CMB signal responsible for a rise in the error on r, we can measure an unbiased value of the tensor-to-scalar ratio with a dispersion as low as σ r = 8.8 × 10 –4 .

79 ASTRONOMY AND ASTROPHYSICS↗

AFM-IR and s-SNOM-IR measurements of chemically addressable monolayers on Au nanoparticles

The performance of catalysts depends on their nanoscale properties, and local variations in structure and composition can have a dramatic impact on the catalytic reactivity. Therefore, probing the localized reactivity of catalytic surfaces using high spatial resolution vibrational spectroscopy, such as infrared (IR) nanospectroscopy and tip-enhanced Raman spectroscopy, is essential for mapping their reactivity pattern. Two fundamentally different scanning probe IR nanospectroscopy techniques, namely, scattering-type scanning near-field optical microscopy (sSNOM) and atomic force microscopy-infrared spectroscopy (AFM-IR), provide the capabilities for mapping the reactivity pattern of catalytic surfaces with a spatial resolution of ~20 nm. Herein, we compare these two techniques with regard to their applicability for probing the vibrational signature of reactive molecules on catalytic nanoparticles. For this purpose, we use chemically addressable self-assembled molecules on Au nanoparticles as model systems. We identified significant spectral differences depending on the measurement technique, which originate from the fundamentally different working principles of the applied methods. While AFM-IR spectra provided information from all the molecules that were positioned underneath the tip, the s-SNOM spectra were more orientation-sensitive. Due to its field-enhancement factor, the s-SNOM spectra showed higher vibrational signals for dipoles that were perpendicularly oriented to the surface. The s-SNOM sensitivity to the molecular orientation influenced the amplitude, position, and signal-to-noise ratio of the collected spectra. Ensemble-based IR measurements verified that differences in the localized IR spectra stem from the enhanced sensitivity of s-SNOM measurements to the adsorption geometry of the probed molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hyperspectral radiance mapping and chromatic correction for temperature measurement in laser-heated diamond anvil cells

In laser-heated diamond anvil cell (DAC) experiments, the effective heated region typically decreases in size with increasing pressure, leading to steeper thermal gradients. Under these conditions, chromatic aberration in the optical path from sample to detector can significantly create bias in spectro-radiometric temperature measurement. We present a radiance-mapping approach using a hyperspectral camera that records 25 spectral channels spanning 605–875 nm at each pixel in a single exposure, providing spatially and spectrally resolved radiance in each frame. This enables chromatic effects to be recorded and corrected in data processing. We developed a procedure for hyperspectral mapping, involving per-camera calibration, crosstalk removal, measured spectral throughput functions, and optional sub-pixel co-registration to minimize chromatic distortion. The calibrated radiance maps are then used to derive temperature maps of the laser-heated hotspots. For smaller heating spots, the radiance mapping approach reveals chromatic shifts that conventional spectro-radiometric methods cannot quantify. Ambient-pressure heating experiments confirm accurate temperature retrieval. At high pressure, application of the hyperspectral system to a platinum-heating experiment at 12 GPa demonstrates stable temperature reconstruction under steep thermal gradients. Beyond mitigating chromatic aberrations, the ability to diagnose optical artifacts separately from emissivity variations during controlled test experiments or in situ suggests a path toward more rigorous spectral emissivity analysis and improved modeling of thermal transport in laser-heated DAC experiments.

47 OTHER INSTRUMENTATION↗

Resolving turbulent magnetohydrodynamics: a hybrid operator-diffusion framework

We present a hybrid machine learning framework that combines physics-informed neural operators (PINOs) with score-based generative diffusion models to simulate the full spatio-temporal evolution of two-dimensional, incompressible, resistive magnetohydrodynamic turbulence across a broad range of Reynolds numbers (Re). The framework leverages the equation-constrained generalization capabilities of PINOs to predict coherent, low-frequency dynamics, while a conditional diffusion model stochastically corrects high-frequency residuals, enabling accurate modeling of fully developed turbulence. Trained on a comprehensive ensemble of high-fidelity simulations with Re ϵ {100, 250, 500, 750, 1000, 3000, 10000}, the approach achieves state-of-the-art accuracy in regimes previously inaccessible to deterministic surrogates. At Re = 1000 and 3000, the model faithfully reconstructs the full spectral energy distributions of both velocity and magnetic fields late into the simulation, capturing non-Gaussian statistics, intermittent structures, and cross-field correlations with high fidelity. At extreme turbulence levels (Re = 10 000), it remains the first surrogate capable of recovering the high-wavenumber evolution of the magnetic field, preserving large-scale morphology and enabling statistically meaningful predictions.

Diffusion-Integrated Neural Operators↗

A spectrophotometric analysis of cool white dwarfs in the Gaia and pan-STARRS footprint

We present a spectrophotometric analysis of 2880 cool white dwarfs within 100 pc of the Sun and cooler than T eff ∼ 10 000 K, with grizy Pan-STARRS photometry and Gaia trigonometric parallaxes available. We also supplement our data sets with near-infrared JHK photometry, when available, which is shown to be essential for interpreting the coolest white dwarfs in our sample. We perform a detailed analysis of each individual object using state-of-the-art model atmospheres appropriate for each spectral type, including DA, DC, DQ, DZ, He-rich DA, and the so-called IR-faint white dwarfs. We discuss the temperature and mass distributions of each subsample, as well as revisit the spectral evolution of cool white dwarfs. We find little evidence in our sample for the transformation of a significant fraction of DA stars into He-atmosphere white dwarfs through the process of convective mixing between T eff = 10 000 and ∼6500 K, although the situation changes drastically in the range T eff = 6500–5500 K where the fraction of He-atmosphere white dwarfs reaches ∼45 per cent. However, we also provide strong evidence that at even cooler temperatures (T eff ≲ 5200 K), most DC white dwarfs have H atmospheres. We discuss a possible mechanism to account for this sudden transformation from He- to H-atmosphere white dwarfs involving the onset of crystallization and the occurrence of magnetism. Finally, we also argue that DQ, DZ, and DC white dwarfs may form a more homogeneous population than previously believed.

79 ASTRONOMY AND ASTROPHYSICS↗

Lattice B -field correlators for heavy quarks

We analyze the color-magnetic (or “ B ”) field two-point function that encodes the finite-mass correction to the heavy-quark momentum-diffusion coefficient. The simulations are done on fine isotropic lattices in the quenched approximation at 1.5 T c , using a range of gradient flow times for noise suppression and operator renormalization. The continuum extrapolation is performed at fixed flow time followed by a second extrapolation to zero flow time. Perturbative calculations to next-to-leading order of this correlation function, matching gradient-flowed correlators to MS ¯ , are used to resolve nontrivial renormalization issues. We perform a spectral reconstruction based on perturbative model fits to estimate the coefficient κ B of the finite-mass correction to the heavy-quark momentum-diffusion coefficient. The approach we present here yields high-precision data for the correlator with all renormalization issues incorporated at next-to-leading order and is also applicable for actions with dynamical fermions. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Reconstructing f ( T ) gravity and exploring the torsion driven warm inflationary cosmology

The current paper reports an investigation of a warm inflationary scenario in the context of f(T) gravity for a spatially flat FLRW universe. In our model, inflation is driven purely by the torsional sector of f(T) gravity, without introducing any additional scalar fields. We focus on the high dissipative regime (R >> 1), reconstruct the Hubble parameter as a function of the e-folding number N, and derive the slow-roll parameters ε 1 (N) and ε 2 (N). The study has encapsulated the dynamics of inflation and its duration under strong dissipation. The dissipative coefficient Γ is modeled with a temperature-dependent power-law form, linking the inflationary dynamics to thermal corrections and the particle content of the early universe. The analysis has affirmed that the torsion-induced energy density ρ T successfully transitions to radiation energy density ρ rad , facilitating a graceful exit from inflation. Finally, we have validated our model by comparing the scalar spectral index and tensor-to-scalar ratio with Planck 2018 results, demonstrating consistency within observational bounds. Additionally, it is verified that the thermal domination condition T * /H > 1 and the torsion dominance condition ρ T /ρ rad > 1 are satisfied.

Ghosh, Moli [Amity University, Kolkata (India); Mr↗

Integrated and dynamic multi-spectroscopic in situ imaging of plant metabolism at the level of subcellular compartments. Final Report

The goals of this project was to develop integrated multi-spectral molecular imaging technologies (Raman, fluorescence, and mass spectrometry), that can assess, and image metabolic processes at the cellular and subcellular levels of plant organs. These imaging technologies were developed in the context of computational capabilities that integrated multi-spectral images with genome scale models of metabolism. The integrated molecular imaging technologies were developed in the biological context of autophagy that remodels membrane lipid topologies, which control spatially defined subcellular regions within plant cells and optimizes plant biomass productivity during environmental stresses that can limit biomass productivity.

09 BIOMASS FUELS↗

NuSTAR broad-band X-ray observation campaign of energetic pulsar wind nebulae in synergy with VERITAS, HAWC and Fermi gamma-ray telescopes

We report recent progress on the on-going NuSTAR observation campaign of 8 TeV-detected middle-aged pulsar wind nebulae (PWNe). This campaign constitutes a major part of our NuSTAR study of some of the most energetic TeV sources in our Galaxy detected by VERITAS and HAWC. NuSTAR is the first focusing X-ray telescope operating above 10 keV in space with sub-arcminute angular resolution. Broad-band X-ray imaging and spectroscopy data, obtained by NuSTAR, allow us to probe sub-PeV electron populations through detecting synchrotron X-ray radiation. Our targets include PeVatron candidates detected by HAWC, the Boomerang nebula, PWNe crushed by supernova remnant shocks (or relic PWNe) and G0.9‚0.1 in the Galactic Center. Combined with Fermi-LAT data and available TeV data, we aim to provide a complete, multi-wavelength view of a diverse class of middle-aged (~10–100 kyrs old) PWNe. Our NuSTAR analysis detected hard X-ray emission from the Eel and Boomerang PWNe and characterized their broad-band X-ray spectra most accurately. We plan to apply both time-evolution and multi-zone PWNe models to multi-wavelength spectral energy distribution (SED) data over the radio, X-ray, GeV and TeV bands. In this proceeding, we will review our observation campaign and discuss the preliminary results for some PWNe.

79 ASTRONOMY AND ASTROPHYSICS↗

Study of Anharmonicity in Zirconium Hydrides Using Inelastic Neutron Scattering and Ab-Initio Computer Modeling

The anharmonic phonon behavior in zirconium hydrides and deuterides, including ϵ-ZrH 2 , γ-ZrH, and γ-ZrD, has been investigated from aspects of inelastic neutron scattering (INS) and lattice dynamics calculations within the framework of density functional theory (DFT). The harmonic model failed to reproduce the spectral features observed in the experimental data, indicating the existence of anharmonicity in those materials and the necessity of further explanations. Here, we present a detailed study on the anharmonicity in zirconium hydrides/deuterides by exploring the 2D potential energy surface of hydrogen/deuterium atoms and solving the corresponding 2D single-particle Schrödinger equation to obtain the eigenfrequencies, which are then convoluted with the instrument resolution. The convoluted INS spectra qualitatively describe the anharmonic peaks in the experimental INS spectra and demonstrate that the anharmonicity originates from the deviations of hydrogen potentials from quadratic behavior in certain directions; the effects are apparent for the higher-order excited vibrational states, but small for the ground and first excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗