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At least 649 records · Page 36

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no systematic evaluation exists of how well vision-language models (VLMs) interpret them. We introduce QCalEval, the first VLM benchmark for quantum calibration plots: 243 samples across 87 scenario types from 22 experiment families, spanning superconducting qubits and neutral atoms, evaluated on six question types in both zero-shot and in-context learning settings. The best general-purpose zero-shot model reaches a mean score of 72.3, and many open-weight models degrade under multi-image in-context learning, whereas frontier closed models improve substantially. A supervised fine-tuning ablation at the 9-billion-parameter scale shows that SFT improves zero-shot performance but cannot close the multimodal in-context learning gap. As a reference case study, we release NVIDIA Ising Calibration 1, an open-weight model based on Qwen3.5-35B-A3B that reaches 74.7 zero-shot average score.

Cao, Shuxiang↗

Optical calibration of the SNO+ detector in the water phase with deployed sources

SNO+ is a large-scale liquid scintillator experiment with the primary goal of searching for neutrinoless double beta decay, and is located approximately 2 km underground in SNOLAB, Sudbury, Canada. The detector acquired data for two years as a pure water Cherenkov detector, starting in May 2017. During this period, the optical properties of the detector were measured in situ using a deployed light diffusing sphere, with the goal of improving the detector model and the energy response systematic uncertainties. The measured parameters included the water attenuation coefficients, effective attenuation coefficients for the acrylic vessel, and the angular response of the photomultiplier tubes and their surrounding light concentrators, all across different wavelengths. Finally, the calibrated detector model was validated using a deployed tagged gamma source, which showed a 0.6% variation in energy scale across the primary target volume.

47 OTHER INSTRUMENTATION↗

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗

Two-dimensional plasma density evolution local to the inversion layer during sawtooth crash events using Beam Emission Spectroscopy

Here, we present methods for analyzing Beam Emission Spectroscopy (BES) data to obtain the plasma density evolution associated with rapid sawtooth crash events at the DIII-D tokamak. BES allows coverage over a 2D spatial plane, inherently local measurements, with fast time responses, and, therefore, provides a valuable new channel for data during sawtooth events. A method is developed to remove sawtooth-induced edge-light pulses contained in the BES data. The edge light pulses appear to be from the D α emission produced by edge recycling during sawtooth events, and are large enough that traditional spectroscopic filtering and data analysis techniques are insufficient to deduce physically meaningful quantities. A cross-calibration of 64 BES channels is performed by using a novel method to ensure accurate measurements. For the large-amplitude density oscillations observed, we discuss and use the non-linear relationship between the BES signal δI/ I 0 and the plasma density variation δn e / n e0 . The 2D BES images cover an 8 × 20 cm 2 region around the sawtooth inversion layer and show large-amplitude density oscillations, with additional significant spatial variations across the inversion layer that grows and peaks near the time of the temperature crash. The edge light removal technique and method of converting large-amplitude δI/ I 0 to δn e / n e0 presented here may help analyze other impulsive MHD phenomena in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Unified differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or produce insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate a unified start-to-end differentiable digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes, the development of generic interfaces between device models and surrogate or physics-based sections, and the export of the parameters through either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to support larger proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗

Effect of Anoxic Iron Corrosion on WIPP Brine Geochemistry FY23 Final Report (U)

A 280-day study was completed to evaluate the effect of zero-valent iron (Fe 0 ) on the Waste Isolation Pilot Plant (WIPP) brine geochemistry under anticipated reducing conditions. Hydrogen (H 2 ) gas is expected to be present in the repository after closure due to the anoxic corrosion of a vast quantity of iron contained in the waste forms disposed at WIPP; therefore, a background argon atmosphere containing H 2 was chosen for this study. WIPP groundwater brine pH and E h will impact the mobility and fate of plutonium within the repository. Modeling and laboratory results for Castile WIPP brine indicate that equilibrium fa values relative to the standard hydrogen electrode (SHE) are 40 mV more reducing (i.e., more negative) than those for Salado WIPP brine (-480 mV vs. -440 mV, respectively) because of the higher pH of the Castile brine (pH 9 .3 for Castile vs. pH 8.8 for Salado). The E h and pH data were corrected for the effects of high ionic strength. The experimental results for both brines are consistent with thermodynamic predictions using OLI Systems' Mixed Solvent Electrolyte chemical equilibrium model. The measured and corrected pH and E h data from this study are provided in Table ES-I and Table ES-2, respectively. The experimental study, with four test conditions in triplicate, was performed in a dual glovebox with a nominally 3 vol.% H 2 in argon atmosphere (target H 2 range: 3 ± I vol.%). Simulants containing MgO only ( experimental control) and MgO+Fe 0 (WIPP base case) were prepared for both the Salado and Castile brines. MgO was included in all simulants to account for the use of bulk magnesium oxide in the WIPP repository. Fe 0 was included in some simulants to incorporate the effects of the anoxic corrosion of iron and in-situ hydrogen generation in the study. The brine compositions were developed by Sandia National Laboratory (SNL; Xiong, 2008) and have been used in previous WIPP evaluations. The test method (agitation, etc.) is partially based on ASTM D3987-12. Twelve rounds of periodic measurements of pH and E h were performed over the course of the study. Chemical analysis results for liquids and solids (ICP-MS, ICP-ES, IC Anion, TIC, SEM-EDX) are consistent with the pH, E h , and thermodynamic modeling results. This study included the following conditions that deviate from anticipated post-closure conditions following brine intrusion, but were selected to facilitate bench-scale testing to validate modeling of pH and E h for the post-closure WIP P repository: an anoxic glove box atmosphere containing ≤ 4 vol. % H 2 vs. substantially higher H 2 gas concentrations assumed in the WIPP Performance Assessment (PA); a significantly higher liquid-to-solid test ratio compared to the much lower phase ratio anticipated in the WIP P repository; agitation of the simulant bottles to maximize mass transfer; and finally the use of Fe 0 reagents having a much greater surface area than expected in the WIP P repository. Non-representative conditions were chosen for various reasons such as: to provide bounding conservative results, to provide a margin of safety for testing, or to facilitate simulant sub-sampling and analysis. In a parallel effort, aqueous electrolyte thermodynamic models were developed for the synthetic Salado and Castile brines to inform the experimental design, facilitate laboratory data interpretation, and allow extension of evaluations beyond the parameters tested. Thermodynamic modeling simulations including the MgO and Fe 0 additives that are directly relevant to the experimental measurements (e.g., pH calibration curve, ORP corrections) are included in this report. The measured fa of the simulants was close to the OLI model predictions for both brines and was largely controlled by the background H 2 partial pressure in the vapor phase as well as H 2 generated in situ in the aqueous phase by the Fe 0 corrosion. The H 2 gas-phase concentration tested and thermodynamically evaluated was much lower than is assumed in the WIPP PA; however, H 2 (g) concentrations significantly below this level are still predicted to result in very reducing conditions. In conclusion: • The experimental results are consistent with thermodynamic model predictions for fa, pH, and the effects of high ionic strength. • Evidence to date suggests that the H2 concentration in the glovebox atmosphere ultimately determined the final E h values of the simulants and resulted in highly reducing conditions. As a result, little difference was observed between the control simulants containing only MgO and the WIPP base-case simulants that contained MgO and Fe 0 . • This test methodology is recommended for future studies evaluating WIPP repository conditions. The methodology includes: (1) background H 2 in argon with agitation ( or could alternatively include in-situ-generated H 2 in sealed bottles); (2) carefully measured and corrected ORP data ( with much effort focused on allowing the probes to fully stabilize); and (3) ionic-strength-corrected pH data. Other best practices, such as simulant sparging/handling, ORP probe replacement, etc., should also be considered. • The coupling of experimental studies and thermodynamic modeling is also highly recommended because these methods inform and direct one another leading to greater confidence in and understanding of the results.

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One Galaxy Sample to Rule Them All: Halo Occupation Distribution Modeling of DES Year 3 Source Galaxies

Abstract For the joint analysis of second-order weak-lensing and galaxy clustering statistics, so-called 3 × 2 analyses, the selection and characterization of optimal galaxy samples is a major area of research. One promising choice is to use the same galaxy sample as lenses and sources, which reduces the systematics parameter space that describes the uncertainties related to galaxy samples. Such a “lens-equal-source” analysis significantly improves the self-calibration of photo- z systematics, leading to improved cosmological constraints. With the aim of enabling a lens-equal-source analysis on small scales, we investigate the halo–galaxy connection of DES Year 3 source galaxies. We develop a technique to construct mock source galaxy populations by matching COSMOS/UltraVISTA photometry to U niverse M achine galaxies. These mocks predict a source halo occupation distribution (HOD) that exhibits significant redshift evolution, nontrivial central incompleteness, and galaxy assembly bias. We produce multiple realizations of mock source galaxies drawn from the U niverse M achine posterior, with added uncertainties in the measured Dark Energy Survey photometry and galaxy shapes. We fit a modified HOD formalism to these realizations to produce priors on the galaxy–halo connection for cosmological analyses. We additionally train an emulator that predicts this HOD to ∼2% accuracy from redshift z = 0.1−1.3 that models the dependence of this HOD on (1) observational uncertainties in galaxy size and photometry and (2) uncertainties in the U niverse M achine predictions.

Salcedo, Andrés N. (ORCID:000000031420527X)↗

Determining the Solubility Behavior of Kogarkoite in Simulated Nuclear Waste

Kogarkoite (Na 3 FSO 4 ) is a sparingly soluble fluoride–sulfate double salt that has been identified in high level nuclear waste sludge at the Hanford Site and, more recently, in sludge batch compilation samples at the Savannah River Site (SRS). Due to its complex dissolution behavior, which exhibits an inverse dependence on sodium ion activity, the presence of this mineral poses significant challenges to waste retrieval and processing. Incomplete dissolution during sludge washing can lead to the retention of fluoride and sulfate in the high-level waste feed, potentially causing the formation of corrosive, immiscible molten salt layers, known as "glass gall,” in vitrification melters. Current efforts to optimize flowsheet parameters and wash-water volumes are hindered by the absence of a commercially available, certified reference material, which prevents the accurate calibration of analytical methods and the verification of dissolution kinetics. To address this critical gap, this research focuses on the laboratory synthesis of pure Kogarkoite to serve as a standard for comprehensive solubility and washing performance testing. A coupled synthesis and simulant campaign was executed using an evaporative crystallization protocol designed to replicate the dynamic concentration effects observed in tank farm operations. Thirteen simulant matrices were prepared by dissolving systematically varied ratios of sodium fluoride (NaF) and sodium sulfate (Na 2 SO 4 ) in deionized water under three distinct caustic regimes: 0.0 g (control), 4.0 g (~1 M), and 12.0 g (~3 M) sodium hydroxide (NaOH). While thermodynamic equilibrium models suggest that high-caustic environments should favor the stability of the double salt7, results from this evaporative study at 25 0 C revealed a distinct kinetic divergence. Simulants with high hydroxide loading predominantly yielded large, blocky crystals of sodium sulfate decahydrate (Na 2 SO 4 .10H 2 O). Successful synthesis of pure Kogarkoite was achieved exclusively in specific NaOH-free compositional windows, where the precipitate manifested as fine, opaque granular aggregates. Ion chromatography (IC) analysis confirmed phase purity through the simultaneous stoichiometric depletion of both fluoride and sulfate from the supernatant. This successful synthesis establishes a reproducible route to generate bulk Kogarkoite, enabling the subsequent phase of quantitative dissolution testing using inhibited water to optimize sludge-batch assembly.

Sarker, Md Sharif [Florida International Univ. (FI↗

DESI peculiar velocity survey – Fundamental Plane

The Dark Energy Spectroscopic Instrument (DESI) peculiar velocity survey aims to measure the peculiar velocities of early- and late-type galaxies within the DESI footprint using both the Fundamental Plane and optical Tully–Fisher relations. Direct measurements of peculiar velocities can significantly improve constraints on the growth rate of structure, reducing uncertainty by a factor of approximately 2.5 at redshift 0.1 compared to the DESI Bright Galaxy Survey’s redshift space distortion measurements alone. We assess the quality of stellar velocity dispersion measurements from DESI spectroscopic data. These measurements, along with photometric data from the Legacy Survey, establish the Fundamental Plane relation and determine distances and peculiar velocities of early-type galaxies. During survey validation, we obtain spectra for 6698 unique early-type galaxies, up to a photometric redshift of 0.15. 64 per cent of observed galaxies (4267) have relative velocity dispersion errors below 10 per cent. This percentage increases to 75 per cent if we restrict our sample to galaxies with spectroscopic redshifts below 0.1. We use the measured central velocity dispersion, along with photometry from the DESI Legacy Imaging Surveys, to fit the Fundamental Plane parameters using a 3D Gaussian maximum likelihood algorithm that accounts for measurement uncertainties and selection cuts. In addition, we conduct zero-point calibration using the absolute distance measurements to the Coma cluster, leading to a value of the Hubble constant, H 0 = 76.05 ± 0.35 (statistical) ±0.49 (systematic Fundamental Plane) ±4.86 (statistical due to calibration) km s –1 Mpc –1 ⁠. This H 0 value is within 2σ of Planck cosmic microwave background results and within 1σ of other low-redshift distance indicator-based measurements.

cosmological parameters↗

Measurement of the photometric baryon acoustic oscillations with self-calibrated redshift distribution

ABSTRACT We use a galaxy sample derived from the Dark Energy Camera Legacy Survey Data Release 9 to measure the baryonic acoustic oscillations (BAO). The magnitude-limited sample consists of 10.6 million galaxies in an area of 4974 deg2 over the redshift range of [0.6, 1]. A key novelty of this work is that the true redshift distribution of the photo-z sample is derived from the self-calibration method, which determines the true redshift distribution using the clustering information of the photometric data alone. Through the angular correlation function in four tomographic bins, we constrain the BAO scale dilation parameter α to be 1.025 ± 0.033, consistent with the fiducial Planck cosmology. Alternatively, the ratio between the comoving angular diameter distance and the sound horizon, DM/rs, is constrained to be 18.94 ± 0.61 at the effective redshift of 0.749. We corroborate our results with the true redshift distribution obtained from a weighted spectroscopic sample, finding very good agreement. We have conducted a series of tests to demonstrate the robustness of the measurement. Our work demonstrates that the self-calibration method can effectively constrain the true redshift distribution in cosmological applications, especially in the context of photometric BAO measurement.

Astronomy & Astrophysics↗

Polyconvex neural network models of thermoelasticity

Machine-learning function representations such as neural networks have proven to be excellent constructs for constitutive modeling due to their flexibility to represent highly nonlinear data and their ability to incorporate constitutive constraints, which also allows them to generalize well to unseen data. Here, in this work, we extend a polyconvex hyperelastic neural network framework to (isotropic) thermo-hyperelasticity by specifying the thermodynamic and material theoretic requirements for an expansion of the Helmholtz free energy expressed in terms of deformation invariants and temperature. Different formulations which a priori ensure polyconvexity with respect to deformation and concavity with respect to temperature are proposed and discussed. The physics-augmented neural networks are furthermore calibrated with a recently proposed sparsification algorithm that not only aims to fit the training data but also penalizes the number of active parameters, which prevents overfitting in the low data regime and promotes generalization. The performance of the proposed framework is demonstrated on synthetic data, which illustrate the expected thermomechanical phenomena, and existing temperature-dependent uniaxial tension and tension-torsion experimental datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cosmology from clustering, cosmic shear, CMB lensing, and cross correlations: combining Rubin observatory and Simons Observatory

ABSTRACT In the near future, the overlap of the Rubin Observatory Legacy Survey of Space and Time (LSST) and the Simons Observatory (SO) will present an ideal opportunity for joint cosmological data set analyses. In this paper, we simulate the joint likelihood analysis of these two experiments using six two-point functions derived from galaxy position, galaxy shear, and CMB lensing convergence fields. Our analysis focuses on realistic noise and systematics models and we find that the dark energy Figure of merit (FoM) increases by 53 per cent (92 per cent) from LSST-only to LSST+SO in Year 1 (Year 6). We also investigate the benefits of using the same galaxy sample for both clustering and lensing analyses, and find the choice improves the overall signal to noise by ${\sim}30{-}40{{\ \rm per\ cent}}$, which significantly improves the photo-z calibration and mildly improves the cosmological constraints. Finally, we explore the effects of catastrophic photo-z outliers finding that they cause significant parameter biases when ignored. We develop a new mitigation approach termed ‘island model’, which corrects a large fraction of the biases with only a few parameters while preserving the constraining power.

79 ASTRONOMY AND ASTROPHYSICS↗

Uncertainty-quantified phenomenological optical potentials for single-nucleon scattering

Optical-model potentials (OMPs) continue to play a key role in nuclear reaction calculations. However, the uncertainty of phenomenological OMPs in widespread use—inherent to any parametric model trained on data—has not been fully characterized, and its impact on downstream users of OMPs remains unclear. Here we assign well-calibrated uncertainties for two representative global OMPs, those of Koning-Delaroche and Chapel Hill '89, using Markov-chain Monte Carlo for parameter inference. By comparing the canonical versions of these OMPs against the experimental data originally used to constrain them, we show how a lack of outlier rejection and a systematic underestimation of experimental uncertainties contributes to bias of, and overconfidence in, best-fit parameter values. Our updated, uncertainty-quantified versions of these OMPs address these issues and yield complete covariance information for potential parameters. Scattering predictions generated from our ensembles show improved performance both against the original training corpora of experimental data and against a new “test” corpus comprising many of the experimental single-nucleon scattering data collected over the last twenty years. Finally, we apply our uncertainty-quantified OMPs to two case studies of application-relevant cross sections. We conclude that, for many common applications of OMPs, including OMP uncertainty should become standard practice. Furthermore, to facilitate their immediate use, digital versions of our updated OMPs and related tools for forward uncertainty propagation are included as Supplemental Material.

150 ≤ A ≤ 189↗

Control-Oriented Modeling of Cycle-to-Cycle Combustion Variability at the Misfire Limit in SI Engines

A control-oriented model is presented that can capture the prior-cycle correlation of combustion cycles during conditions with high levels of exhaust gas recirculation (EGR). Combustion events are modeled in discrete time and the dynamic evolution is captured by the residual air, fuel, and inert gas trapped in the combustion chamber. The mathematical formulation of the model is presented together with the calibration procedure to emulate a particular engine operating condition. A cycle-to-cycle system identification methodology is described which allows regressing model parameters from experimental data. Simulations are presented and compared to real engine measurements to show the modeling potential for analysis and control of combustion events.

Maldonado Puente, Bryan↗

DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.14

Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O

Adams, BrianM.↗

DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.16

Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O

Adams, BrianM.↗

Mechanistic within-host mathematical model of inhalational anthrax

We present a mathematical model of the dynamics of Bacillus anthracis bacteria within the lymph nodes and blood of a host, following inhalation of an initial dose of spores. We also incorporate the dynamics of protective antigen, which is the binding component of the anthrax toxin produced by the bacteria. The model offers a mechanistic description of the early infection dynamics of inhalational anthrax, while its stochastic nature allows us to study the probabilities of different outcomes (for example, how likely it is that the infection will be cleared for a given inhaled dose of spores) in order to explain dose-response data for inhalational anthrax. The model is calibrated via a Bayesian approach, using in vivo data from New Zealand white rabbit and guinea pig infection studies, enabling within-host parameters to be estimated. We also leverage incubation-period data from the Sverdlovsk 1979 anthrax outbreak to show that the model can accurately describe human time-to-symptoms data under reasonable parameter regimes. Finally, we derive a simple approximate formula for the probability of symptom onset before time t, assuming that the number of inhaled spores has a Poisson distribution.

59 BASIC BIOLOGICAL SCIENCES↗

AWCC Simulations

Neutron well counters provide a means to measure fissile mass by detecting coincident neutrons, which is a unique signature to fission. For coincidence counting, mass is determined using a calibration curve established with items that have the same material characteristics. Multiplicity analysis solves the point model equations for mass using known detector parameters. In both cases, mass measurements may exhibit a bias due to item characteristics and should be corrected for. Experiments can be done to estimate bias and material effects, but they require having both the well counter and the material well defined. In pursuit of estimating measurement bias and uncertainty in a High Efficiency Neutron Counter (HENC), an MCNP simulation was matched to measurements performed with an Active Well Coincidence Counter (AWCC) to de ne a neutron source term. The neutron source term will be used to predict measurement performance of similar material types in a HENC.

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