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At least 163 records · Page 9

First Measurement of 𝐴 = 4 Hypernuclei and Antihypernuclei at the LHC

In this Letter, the first evidence of the $^4_{\bar{Λ}}$$\overline{He}$ antihypernucleus is presented, along with the first measurement at the LHC of the production of (anti)hypernuclei with mass number 𝐴 = 4, specifically (anti)⁢$^4_Λ$H and (anti)⁢$^4_Λ$He. In addition, the antiparticle-to-particle ratios for both hypernuclei ($^4_{\bar{Λ}}$$\bar{H}$⁡/$^4_Λ$H and $^4_{\bar{Λ}}$$\overline{He}$/$^4_Λ$He) are shown, which are sensitive to the baryochemical potential of the strongly interacting matter created in heavy-ion collisions. The results are obtained from a data sample of central Pb-Pb collisions, collected during the 2018 LHC data taking at a center-of-mass energy per nucleon pair of $\sqrt{𝑠_{NN}}$ = 5.02 TeV. The yields measured for the average of the charge-conjugated states are found to be [0.78 ± 0.19⁢(stat) ± 0.17⁢(syst)] × 10 −6 for the (anti)⁢$^4_Λ$H and [1.08 ± 0.34⁢(stat)± 0.20⁢(syst)] × 10 −6 for the (anti)⁢$^4_Λ$He, and the measured antiparticle-to-particle ratios are in agreement with unity. The presence of (anti)⁢$^4_Λ$H and (anti)⁢$^4_Λ$He excited states is expected to strongly enhance the production yield of these hypernuclei. The yield values exhibit a combined deviation of 3.3⁢𝜎 from the theoretical ground-state-only expectation, while the inclusion of the excited states in the calculations leads to an agreement within 0.6⁢𝜎 with the present measurements. Additionally, the measured (anti)$^4_Λ$H and (anti)⁢$^4_Λ$He masses are compatible with the world-average values within the uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sign Problem in Tensor-Network Contraction

We investigate how the computational difficulty of contracting tensor networks depends on the sign structure of the tensor entries. Using results from computational complexity, we observe that the approximate contraction of tensor networks with only positive entries has lower computational complexity as compared to tensor networks with general real or complex entries. This raises the question of how this transition in computational complexity manifests itself in the hardness of different tensor-network-contraction schemes. We pursue this question by studying random tensor networks with varying bias toward positive entries. First, we consider contraction via Monte Carlo sampling and find that the transition from hard to easy occurs when the tensor entries become predominantly positive; this can be understood as a tensor-network manifestation of the well-known negative-sign problem in quantum Monte Carlo. Second, we analyze the commonly used contraction based on boundary tensor networks. The performance of this scheme is governed by the number of correlations in contiguous parts of the tensor network (which by analogy can be thought of as entanglement). Remarkably, we find that the transition from hard to easy—i.e., from a volume-law to a boundary-law scaling of entanglement—already occurs for a slight bias of the tensor entries toward a positive mean, scaling inversely with the bond dimension D , and thus the problem becomes easy the earlier the larger D occurs. This is in contrast both to expectations and to the behavior found in Monte Carlo contraction, where the hardness at fixed bias increases with the bond dimension. To provide insight into this early breakdown of computational hardness and the accompanying entanglement transition, we construct an effective classical statistical-mechanical model that predicts a transition at a bias of the tensor entries of 1 / D , confirming our observations. We conclude by investigating the computational difficulty of computing expectation values of tensor-network wave functions (projected entangled-pair states, PEPSs) and find that in this setting, the complexity of entanglement-based contraction always remains low. We explain this by providing a local transformation that maps PEPS expectation values to a positive-valued tensor network. This not only provides insight into the origin of the observed boundary-law entanglement scaling but also suggests new approaches toward PEPS contraction based on positive decompositions. Published by the American Physical Society 2025

Chen, Jielun (ORCID:0000000178411545)↗

Perturbative Stability and Error-Correction Thresholds of Quantum Codes

Topologically ordered phases are stable to local perturbations, and topological quantum error-correcting codes enjoy thresholds to local errors. We connect the two notions of stability by constructing classical statistical mechanics models for decoding general Calderbank-Shor-Steane codes and classical linear codes. Our construction encodes correction success probabilities under uncorrelated bit-flip and phase-flip errors, and simultaneously describes a generalized ℤ 2 lattice-gauge theory with quenched disorder. We observe that the clean limit of the latter is precisely the discretized imaginary-time path integral of the corresponding quantum code Hamiltonian when the errors are turned into a perturbative 𝑋 or 𝑍 magnetic field. Motivated by error-correction considerations, we define general order parameters for all such generalized ℤ 2 lattice-gauge theories, and show that they are generally lower bounded by success probabilities of error correction. For CSS codes satisfying the low-density parity-check condition and with a sufficiently large code distance, we prove the existence of a low-temperature ordered phase of the corresponding lattice-gauge theories, particularly for those lacking Euclidean spatial locality and/or when there is a nonzero code rate. We further argue that these results provide evidence for stable phases in the corresponding perturbed quantum Hamiltonians, obtained in the limit of continuous imaginary time. To do so, we distinguish space- and timelike defects in the lattice-gauge theory. A high free-energy cost of spacelike defects corresponds to a successful “memory experiment” and suppresses the energy splitting among the ground states, while a high free-energy cost of timelike defects corresponds to a successful “stability experiment” and points to a nonzero gap to local excitations.

quantum error correction↗

Observation of the Ω⁡(2012) baryon at the LHC

A signal consistent with the Ω⁡(2012) baryon has been observed with a significance of 15⁢𝜎 in pp collisions at $\sqrt{𝑠}$ = 13 TeV at the LHC. In this paper, the analysis technique is described and measurements of the mass and width of the Ω⁡(2012) are reported, along with the first measurement of its transverse-momentum spectrum and yield. This paper corroborates the observation by the Belle Collaboration of this excited Ω state and the observation that the Ω⁡(2012) has a rather narrow width for a strongly decaying resonance. The yield measurement is combined with a statistical thermal model calculation of strange baryon yield ratios to obtain estimates of the Ω⁢(2012) − → $Ξ⁢\bar{\textrm{K}}$ branching ratios. These results will improve our understanding of the internal structure and mass spectrum of excited baryon states and serve as a baseline for searches regarding modifications of these properties in high-temperature media.

Acharya, S. [INFN] (ORCID:0000000292135329)↗

Visual Analytics of Crosstalk in Quantum Hardware

Crosstalk remains a major obstacle to building scalable and fault-tolerant quantum computers. Conventional diagnostic techniques-often based on numerical simulation or statistical modeling-struggle to scale with hardware complexity and offer limited interpretability. In this work, we present a visual analytics framework for diagnosing qubit crosstalk using lightweight, circuit-based models integrated with an interactive user interface. Our approach quantifies correlations between active and idle qubits under parameterized single- and twoqubit operations, enabling detection of both spatial and gateinduced crosstalk. The system incorporates qubit topology and gate performance data to support sector-based exploration and correlation mapping. This tool assists users in identifying correlated error sources, informing qubit placement strategies, and guiding noise-aware circuit design.

Chae, Junghoon [ORNL] (ORCID:0000000206016746)↗

$\Sigma ^{+}$ production in pp collisions at $\sqrt{\textit{s}}=13$ TeV

The measurement of $\Sigma ^{+}$ production in pp collisions at $\sqrt{s}=13$ TeV is presented. The measurement is performed at midrapidity in both minimum-bias and high-multiplicity pp collisions at $\sqrt{s}=13$ TeV. The $\Sigma ^{+}$ is reconstructed via its weak-decay topology in the decay channel $\Sigma ^{+} \rightarrow \mathrm{{p}} + \pi ^{0}$ with $\pi ^{0} \rightarrow \gamma + \gamma$. In a novel approach, the neutral pion is reconstructed by combining photons that convert in the detector material with photons measured in the calorimeters. The transverse-momentum $(p_{\textrm{T}})$ distributions of the $\Sigma ^{+}$ and its rapidity densities dN/dy in both event classes are reported. The $p_{\textrm{T}}$ spectrum in minimum-bias collisions is compared to QCD-inspired event generators. The ratio of $\Sigma ^{+}$ to previously measured Λ baryons is in good agreement with calculations from the Statistical Hadronization Model. The high efficiency and purity of the novel reconstruction method for $\Sigma ^{+}$ presented here will enable future studies of the interaction of $\Sigma ^{+}$ with protons in the context of femtoscopic measurements, which could be crucial for understanding the equation of state of neutron stars.

Abualrob, I. J. [University of Houston] (ORCID:000↗

Multiplicity dependence of f 0 (980) production in pp collisions at $\mathbf{\sqrt{s}}$ = 13 TeV

The dependence of f 0 (980) production on the final-state charged-particle multiplicity is reported for proton–proton (pp) collisions at the centre-of-mass energy, $\mathbf{\sqrt{s}}$ = 13 TeV. The production of (980) is measured with the ALICE detector via the decay channel in a midrapidity region of |y| < 0.5. The evolution of the integrated yields and mean transverse momentum of f 0 (980) as a function of charged-particle multiplicity measured in pp at $\mathbf{\sqrt{s}}$ = 13 TeV follows the trends observed in pp at $\mathbf{\sqrt{s}}$ = 5.02 TeV and in proton–lead (p–Pb) collisions at$\mathbf{\sqrt{s_{NN}}}$ = 5.02 TeV. Particle yield ratios of f 0 (980) to π ± and K* (892) are found to decrease with increasing charged-particle multiplicity. These particle ratios are compared with calculations from the canonical statistical thermal model as a function of charged-particle multiplicity. The thermal model calculations provide a better description of the decreasing trend of particle ratios when no strange or antistrange quark composition for f 0 (980) is assumed, which suggests that the data do not support significant hidden strangeness in the f 0 (980).

Abualrob, I. J. [University of Houston] (ORCID:000↗

Design Methods, Tools, and Data for Ceramic Solar Receivers

This report presents the development of tools and methods for evaluating the reliability and performance of ceramic materials in high temperature solar receivers. As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat requirements, current high temperature metallic materials face challenges in maintaining structural integrity. This report explores advanced ceramics as a promising alternative, given their superior high temperature strength and lower thermal expansion, compared to metals. To address the need for effective ceramic receiver design tools, this report integrates statistical failure models of ceramics into the existing srlife tool: an open-source software package designed to estimate the life of high temperature CSP components. These failure models account for the inherent variability and flaw distribution in ceramics, as well as the impact of subcritical crack growth under high temperature cyclic loads. The report also presents experimental data collected for a commercially available ceramic material, SiC, and details the process of estimating reliability model parameters from these data. A comparative design analysis is then performed between ceramic (SiC) and metallic (current nickel-based superalloys A740H and A282) receiver. This comparison demonstrates that SiC receivers can achieve service life exceeding 30 years under high incident heat flux conditions, compared to just a few years for metallic receivers.

14 SOLAR ENERGY↗

Robust Dark Energy Constraints with the Dark Energy Spectroscopic Survey (Final Technical Report)

This project developed and applied advanced theoretical, computational, and data-analysis methodologies to extract robust and precise cosmological constraints from the Dark Energy Spectroscopic Instrument (DESI). The work focused on maximizing the scientific return of DESI through optimized survey strategy, novel higher-order clustering statistics, improved modeling of small-scale structure, and rigorous mitigation of observational systematics. Over the award period, the project made substantial contributions to DESI science planning, produced new methods for bispectrum and three-point correlation function analyses, advanced constraints on primordial non-Gaussianity, and delivered widely used software tools. The project also played a major role in training graduate students and a postdoctoral researcher who contributed directly to DESI key projects. The results have significantly enhanced the cosmological reach of DESI and provide a strong foundation for future surveys such as DESI-II and Stage-V experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

XRISM Spectroscopy of the Fe Kα Emission Line in the Seyfert Active Galactic Nucleus NGC 4151 Reveals the Disk, Broad-line Region, and Torus

Abstract We present an analysis of the first two XRISM/Resolve spectra of the well-known Seyfert-1.5 active galactic nucleus (AGN) in NGC 4151, obtained in 2023 December. Our work focuses on the nature of the narrow Fe K α emission line at 6.4 keV, the strongest and most common X-ray line observed in AGN. The total line is found to consist of three components. Even the narrowest component of the line is resolved with evident Fe K α ,1 (6.404 keV) and K α ,2 (6.391 keV) contributions in a 2:1 flux ratio, fully consistent with neutral gas with negligible bulk velocity. Subject to the limitations of our models, the narrowest and intermediate-width components are consistent with emission from optically thin gas, suggesting that they arise in a disk atmosphere and/or wind. Modeling the three line components in terms of Keplerian broadening, they are readily associated with (1) the inner wall of the “torus,” (2) the innermost optical “broad-line region” (or “X-ray BLR”), and (3) a region with a radius of r ≃ 100 GM / c 2 that may signal a warp in the accretion disk. Viable alternative explanations of the broadest component include a fast-wind component and/or scattering; however, we find evidence of variability in the narrow Fe K α line complex on timescales consistent with small radii. The best-fit models are statistically superior to simple Voigt functions, but when fit with Voigt profiles the time-averaged lines are consistent with a projected velocity broadening of FWHM = 1600 − 200 + 400 km s − 1 . Overall, the resolution and sensitivity of XRISM show that the narrow Fe K line in AGN is an effective probe of all key parts of the accretion flow, as it is currently understood. We discuss the implications of these findings for our understanding of AGN accretion, future studies with XRISM, and X-ray-based black hole mass measurements.

Audard, Marc (ORCID:000000034721034X)↗

First results from the search of $ν_μ$ disappearance with ICARUS

his work presents a search for muon neutrino disappearance signal using the ICARUS detector. ICARUS is currently working as the far detector of the Short-Baseline Neutrino (SBN) program. Its main goal is to investigate the possible oscillation of a sterile neutrino state ($\Delta m^2 \sim \text{eV}^2$), that would drive short baseline oscillations at the scale of L/E $\sim$ km/GeV. Neutrino interactions from the Booster Neutrino Beam (BNB) are investigated, looking for simple final state topology with a single muon and at least one proton (1$\mu$Np). This analysis tests the 3+1 model using the two flavor neutrino approximation, where careful consideration has been given to the systematic uncertainties arising from flux, neutrino interaction, and detector models. No statistically significant $\nu_\mu$ disappearance is observed, hence 90\% C.L. exclusion contours are reported in the $\Delta m^2_{41} - \sin^22\theta_{\mu\mu}$ parameter space.

Artero Pons, Maria [INFN, Padua; U. Padua (main)]↗

Probing the limits of statistical neutron capture for the r process: Experimental constraints on 141 Cs nuclear level densities

The r-process abundance peaks, particularly near mass number A ∼ 130, reflect underlying nuclear structure effects such as closed neutron shells, yet modeling the nucleosynthesis in this region remains hindered by uncertain neutron-capture rates. These rates are especially sensitive to nuclear level densities (NLDs) and γ-ray strength functions of neutron-rich nuclei, where experimental data are scarce. We present the first experimental constraint on the NLD of 141 Cs using the β-Oslo method, extending sensitivity to the neutron-rich regime near the N = 82 closed shell. Our data allow for critical calibration of microscopic NLD models and reveal that 141 Cs lies near the limit of statistical model applicability. Using this experimental input, we evaluate radiative neutron-capture rates across neighboring isotones using both Hauser–Feshbach (HF) and High Fidelity Resonance (HFR) models. Our results show order-of-magnitude rate increases for nuclei along the N = 86 line, signaling a transition to resonance-dominated capture in this region. These findings underscore the importance of constraining NLDs to improve r-process reaction network predictions, particularly in environments where the validity of statistical models breaks down.

Nuclear level density↗

Stokes-dependent droplet collection efficiency on a NACA 0012 airfoil from droplet-informed simulations with statistical overloading

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60 ≤ U ≤ 240 m s −1 and the chord length of the airfoil in the range 0.5 ≤ c ≤ 2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision are also neglected. To reduce the computational cost, we employ statistical overloading of droplets, allowing us to simulate millions of impinging droplets in a time span on the order of milliseconds. Our results show that the droplet collection efficiency, which measures the likelihood of droplet impingement on the airfoil surface, increases with droplet size and free-stream velocity but decreases with airfoil size. We demonstrate that collection efficiency, impingement velocity and impingement angle are primarily dictated by a single non-dimensional parameter, the droplet Stokes number. We also identify a critical stagnation-streamline Stokes number below which impingements do not occur and use it to estimate the minimum droplet size for impingement. In addition, we observe droplet behaviour to become Stokes number independent at large values of the Stokes number. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics↗

Challenges in integrating dissolved organic matter chemodiversity into kinetic models of soil respiration

The chemodiversity of dissolved organic matter (DOM) in soil has been proposed to influence the microbial metabolism and fate of belowground organic carbon (C). However, integrating DOM chemistry into soil C cycle models to improve predictions of C stocks and fluxes—beyond simply considering DOM pool size—remains a challenge. While recent research suggests that incorporating DOM chemodiversity into models can improve predictions of microbial respiration, there is still a lack of mechanistic understanding describing how DOM chemodiversity affects microbial metabolism and soil respiration. Here, we evaluated whether DOM chemodiversity was a determinant of soil respiration using paired measurements of high-resolution DOM chemistry, obtained from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), and potential soil respiration rates from across the United States (U.S.), all data provided by the Molecular Observation Network. Our objectives were to (1) assess statistical relationships between DOM chemodiversity and microbial respiration, and (2) evaluate the ability of kinetic models to leverage DOM chemistry to explain empirical relationships found in statistical models. Statistical regressions revealed that DOM chemodiversity (alpha diversity) was nonlinearly related to potential soil respiration rates, both independently and through its interactions with DOM and total C concentrations. In soils with relatively high DOM but low total C concentrations, potential soil respiration rates were negatively correlated with DOM alpha diversity, whereas in soils with relatively low DOM and high total C concentrations showed the opposite trend. However, when metabolic transition theory kinetic models were modified to include chemodiversity, their performance was comparable to traditional Monod kinetics approaches, which simulate respiration rates as a function of DOM concentration. The inability to account for nonlinearities in DOM chemodiversity–respiration relationships highlight an opportunity to advance substrate uptake kinetics by establishing causal links between DOM chemodiversity, microbial metabolism trade-offs, and potential interactions under varied environmental conditions.

Bioenergetic model↗

Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations

People commonly utilize visualizations not only to examine a given dataset, but also to draw generalizable conclusions about the underlying models or phenomena. Prior research has compared human visual inference to that of an optimal Bayesian agent, with deviations from rational analysis viewed as problematic. However, human reliance on non-normative heuristics may prove advantageous in certain circumstances. We investigate scenarios where human intuition might surpass idealized statistical rationality. In two experiments, we examine individuals’ accuracy in characterizing the parameters of known data-generating models from bivariate visualizations. Our findings indicate that, although participants generally exhibited lower accuracy compared to statistical models, they frequently outperformed Bayesian agents, particularly when faced with extreme samples. Participants appeared to rely on their internal models to filter out noisy visualizations, thus improving their resilience against spurious data. However, participants displayed overconfidence and struggled with uncertainty estimation. They also exhibited higher variance than statistical machines. Our findings suggest that analyst gut reactions to visualizations may provide an advantage, even when departing from rationality. These results carry implications for designing visual analytics tools, offering new perspectives on how to integrate statistical models and analyst intuition for improved inference and decision-making. The data and materials for this paper are available at https://osf.io/qmfv6

human-machine collaboration↗

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul [National Renewable Energy Lab. (NREL↗

Capturing the fractocohesive length scale in elastomers through a statistical mechanics-based gradient enhanced damage model

Here, this study aims to examine modeling flaw sensitivity in elastomers. The direct incorporation of polymer chain statistical mechanics considerations into a continuum stretch-based gradient-enhanced damage formulation, in turn, allows a representation of diffuse chain damage and fracture events that align with known micromechanical mechanisms. Through a series of numerical experiments, we simulate crack propagation and extract the fracture energy as an output of the model, while keeping track of the micromechanical signatures of diffuse chain damage that accommodate fracture propagation and eventually influence flaw sensitivity. Finally, by combining the fracture toughness and the work to rupture, we identify a fractocohesive length of the material, corresponding to the full width of the damage process zone. As the damage-to-fracture cascade in the proposed GED model is influenced by the introduction of a length scale associated with network imperfection and long-range load transfer, the emerging relationship of the two length scales is discussed, providing a potential link between microscopic damage mechanisms and the observed macroscopic fracture response.

36 MATERIALS SCIENCE↗

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

Here, this work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace reduced-order model for the canonical (NVT) and isobaric (NPT) ensembles. The symplectic reduced-order basis is randomized on the tangent space of the Stiefel manifold to provide topological relationships and capture model-form uncertainty. Using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), we assess the relevance of these stochastic reduced-order atomistic models on canonical problems involving a Lennard-Jones fluid and an argon crystal melt.

42 ENGINEERING↗