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At least 73 records · Page 4

SDA: a symbolic differential algebra package in C++

Truncated Power Series Algebra (TPSA), or Differential Algebra (DA), is a well-established tool in accelerator physics, commonly used for generating high-order maps of dynamic systems, as well as in symplectic tracking, normal form analysis, verified integration, optimization, and fast multipole methods. This package is the first to perform symbolic DA computations, enabling traceability of initial condition contributions and runtime reduction for repeated DA calculations, potentially expanding DA’s applications.

97 MATHEMATICS AND COMPUTING↗

Electronic Excitation‐Driven β‐Ga 2 O 3 Metastability Transformation and Self‐Organization Mechanism: β→κ/γ/δ Phases

Here, irradiation-driven multiphase self-organization presents emergent opportunities for the customization of nanoscale engineering properties, dynamically tuning strain-field distributions and interfacial electronic structures. Responding to intense electronic excitation-induced energy deposition, the dominant phase transformations, with varying Gibbs free energy $Δ,G^o_f$ are confirmed as β → κ → γ → δ that are located in specific microregions for Gallium (III) oxide (Ga 2 O 3 ), as follows: (i) Surface-localized interstitial accumulation under compressive stress triggers β → δ via semi-coherent interface formation. (ii) Tensile stress within latent tracks drives vacancy-mediated oxygen layer truncation (4/12 periodicity along ⟨0001⟩), stabilizing coherent 4H (ABCB) κ and 3C (ABC) β (ABC) interfaces through strain-compensated octahedral distortion. (iii) Screw dislocation-mediated lattice relaxation induces β → γ via cation disordering (Ga 3+ occupancy at β-interstitial sites), forming metastable spinel γ with mixed occupancy across 16d/8a Wyckoff sites. Irradiation-driven β-Ga 2 O 3 →κ/γ/δ transitions, as mechanistically revealed via inelastic thermal spike (i-TS) calculations and molecular dynamics simulations, induce defect-mediated nonlinear photoresponse, critical for optoelectronic engineering.

Han, Xinqing [Shandong Univ., Jinan (China)]↗

Crystal structures of Salmonella enterica FraB deglycase reveal a conformational heterodimer with remarkable structural plasticity at the active site

Abstract Thefralocus ofSalmonella entericaencodes five genes for metabolism of fructose‐asparagine, an Amadori product formed by condensation of asparagine with glucose. In the last step of this pathway, the FraB deglycase cleaves 6‐phospho‐fructose‐aspartate into glucose‐6‐phosphate and aspartate. In homology models, FraB forms a homodimer with two equivalent active sites located at the dimer interface. E214 and H230, two invariant residues essential for catalysis, project into each active site cleft from opposing subunits of the dimer. Here, we have determined six crystal structures of FraB, three of a variant containing an N‐terminal His 6 tag and two mutations needed for crystallization (hereafter referred to as WT′), two with additional mutations to active site residues (E214A and P232A), and one of a variant with C‐terminal residues 313–325 deleted. Surprisingly, in the WT′ FraB structure, the two catalytic residues, E214 (general base) and H230 (general acid), are positioned ~22 Å apart. In the E214A and C‐terminus‐truncated FraB variants, however, a conformational change in the E214‐residing helix brings E214 and H230* to ~7 Å (* indicates residue from the second protomer that creates the inter‐subunit catalytic center). The loop bearing H230 also exhibits significant variation, ranging from being completely disordered to adopting open or closed states, with the nearby P232* residue being eithercisortrans. The C‐terminal residues 313–325 form a flexible “C‐tail” that can be fully disordered, bind in the active site to block access of substrate, or angle across the active site to wrap across the other subunit of the dimer and potentially close over substrate. Collectively, these structures reveal that FraB is a conformational heterodimer with two chemically identical subunits that are constrained to adopt different structures as they come together for catalysis. This plasticity likely involves correlated opening and closure of the two active sites for their respective binding and release of substrates and ligands.

Biochemistry & Molecular Biology↗

Monolayer TiS 2 Nanosheets on Au(111)–Structural Characterization and Effect of Edge Stability for Shape Control

Transition metal dichalcogenides are promising alternatives to noble metal catalysts, e.g., for (photo-)activation of greenhouse gases or hydrogenations. Herein, a direct synthetic route for 2D TiS 2 nanosheets on Au(111) by titanium deposition in the presence of a mild, organic, non-oxidizing sulfur source is presented. High-resolution scanning tunneling microscopy (STM) is used to gain atomic-level insights into the TiS 2 nanosheet morphology. In contrast to the literature, this protocol gains mostly hexagonal and truncated triangular nanosheets with an increased edge contrast in STM, analog to metallic edge states in MoS 2 . Synchrotron-based photoelectron spectroscopy allows insights into compositional details, specifically to distinguish different S sites on the TiS 2 sheets and other S species on the sample. Further, a minimum size is identified (9 S atoms side length), which underlines the importance of moiré reconstructions for stress relief. The TiS 2 sheets coexist with [Au]Ti 1 S 3 clusters, in which a single gold atom is alloyed into the surface and capped by three S atoms. Together with the finding of a critical sheet size, this points toward on-surface Ostwald ripening as a relevant process in the sheet formation. Ab-initio calculations (density functional theory) underscore that the chemical potential of S is an essential descriptor to maintain shape control.

2D nanomaterials↗

Tensor network representation of non-abelian gauge theory coupled to reduced staggered fermions

We show how to construct a tensor network representation of the path integral for reduced staggered fermions coupled to a non-abelian gauge field in two dimensions. The resulting formulation is both memory and computation efficient because reduced staggered fermions can be represented in terms of a minimal number of tensor indices while the gauge sector can be approximated using Gaussian quadrature with a truncation. Numerical results obtained using the Grassmann TRG algorithm are shown for the case of SU(2) lattice gauge theory and compared to Monte Carlo results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improving the five-point bootstrap

We present a new algorithm for the numerical evaluation of five-point conformal blocks in d-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the 〈σσϵσσ〉 correlator in the 3d critical Ising model by truncating the operator product expansion (OPE) and only including operators with conformal dimension below a cutoff ∆ ⩽ ∆cutoff. We approximate the contributions of the operators above the cutoff by the corresponding contributions in a suitable disconnected five-point correlator. Using this approach, we compute a number of OPE coefficients with greater accuracy than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fuzzy spheres in stringy matrix models: quantifying chaos in a mixed phase space

We consider a truncation of the BMN matrix model to a configuration of two fuzzy spheres, described by two coupled non-linear oscillators dependent on the mass parameter μ. The classical phase diagram of the system generically (μ ≠ 0) contains three equilibrium points: two centers and a center-saddle; as μ → 0 the system exhibits a pitchfork bifurcation. We demonstrate that the system is exactly integrable in quadratures for μ = 0, while for very large values of μ, it approaches another integrable point characterized by two harmonic oscillators. The classical phase space is mixed, containing both integrable islands and chaotic regions, as evidenced by the classical Lyapunov spectrum. At the quantum level, we explore indicators of early and late time chaos. The eigenvalue spacing is best described by a Brody distribution, which interpolates between Poisson and Wigner distributions; it dovetails, at the quantum level, the classical results and reemphasizes the notion that the quantum system is mixed. We also study the spectral form factor and the quantum Lyapunov exponent, as defined by out-of-time-ordered correlators. These two indicators of quantum chaos exhibit weak correlations with the Brody distribution. We speculate that the behavior of the system as μ → 0 dominates the spectral form factor and the quantum Lyapunov exponent, making these indicators of quantum chaos less effective in the context of a mixed phase space.

AdS-CFT correspondence↗

Dynamics of heavy quarks in strongly coupled $\mathcal{N}$ = 4 SYM plasma

We calculate the probability distribution P(k) for a heavy quark with velocity v propagating through strongly coupled N = 4 SYM plasma in the ’t Hooft limit (N c → ∞, λ = g 2 N c → ∞) at a temperature T to acquire a momentum k due to interactions with the plasma. This distribution encodes the well-known drag coefficient η D and the transverse and longitudinal momentum diffusion coefficients κ T and κ L . The jet quenching parameter $\hat{q}$ can be extracted from P(k) for v = 1. Going beyond these known Gaussian characteristics of P(k), our calculation determines all of the higher order and mixed moments to leading order in 1/$\sqrt{λ}$ for the first time. These non-Gaussian features of P(k) include qualitatively novel correlations between longitudinal energy loss and transverse momentum broadening at nonzero v. We show that all higher moments scale characteristically with an effective temperature of the boosted plasma in the heavy quark rest frame, and we demonstrate that these non-Gaussian characteristics can be sizable in magnitude and even dominant in physically relevant situations. We use these results to derive a Kolmogorov equation for the evolution of the probability distribution for the total momentum of a heavy quark that propagates through strongly coupled plasma. This evolution equation accounts for all higher order correlations between transverse momentum broadening and longitudinal energy loss, which we have calculated from first principles. It reduces to a Fokker-Planck equation when truncated to only include the effects of η D , κ T and κ L . Remarkably, while heavy quarks do not reach kinetic equilibrium with the plasma if evolved with this Fokker-Planck equation, by showing that the Boltzmann distribution is a static solution of the all-order Kolmogorov equation that we have derived we demonstrate that heavy quarks do reach kinetic equilibrium if evolved with this equation. Our results thus provide a dynamically complete framework for understanding the thermalization of a heavy quark that may be initially far from equilibrium in the strongly coupled N = 4 SYM plasma — as well as new insight into heavy quark transport and equilibration in quark-gluon plasma.

Holography and Hydrodynamics↗

A supersymmetric SYK model with a curious low energy behavior

We consider N = 2,4 supersymmetric SYK models that have a peculiar low energy behavior, with the entropy going like S = S 0 + (constant)T a , where a ≠ 1. The large N equations for these models are a generalization of equations that have been previously studied as an unjustified truncation of the planar diagrams describing the BFSS matrix quantum mechanics or other related matrix models. Here we reanalyze these equations in order to better understand the low energy physics of these models. We find that the scalar fields develop large expectation values which explore the low energy valleys in the potential. The low energy physics is dominated by quadratic fluctuations around these values. These models were previously conjectured to have a spin glass phase. We did not find any evidence for this phase by using the usual diagnostics, such as searching for replica symmetry breaking solutions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Accidental suppression of Wilson coefficients in Higgs coupling

Higgs couplings are essential probes for physics beyond the Standard Model (BSM) since they can be modified by new physics, such as through the Higgs portal interaction |H| 2 Ο. These modifications influence Higgs interactions via dimension-6 operators of the form (∂|H| 2 ) 2 and |H| 6 , which are generally expected to be of comparable size. This paper discusses a phenomenon of accidental suppression, where the |H| 6 coupling is significantly smaller than (∂|H| 2 ) 2 . This suppression, arising from the truncation of the tree-level effective potential, lacks a clear symmetry explanation but persists in portal models. This paper aims to inspire further studies on additional instances of accidental suppression without symmetry explanations or a general framework to characterize such suppression. We also discuss constraints, at the HL-LHC and future colliders, on the Wilson coefficients of the two dimension-6 operators for various benchmark scenarios of the concrete model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive immersed isogeometric level-set topology optimization

Here, this paper presents for the first time an adaptive immersed approach for level-set topology optimization using higher-order truncated hierarchical B-spline discretizations for design and state variable fields. Boundaries and interfaces are represented implicitly by the iso-contour of one or multiple level-set functions. An immersed finite element method, the eXtended IsoGeometric Analysis, is used to predict the physical response. The proposed optimization framework affords different adaptively refined higher-order B-spline discretizations for individual design and state variable fields. The increased continuity of higher-order B-spline discretizations together with local refinement enables direct control over the accuracy of the representation of each field while simultaneously reducing computational cost compared to uniformly refined discretizations. A flexible mesh adaptation strategy enables local refinement based on geometric measures or physics-based error indicators. These adaptive discretization and analysis approaches are integrated into gradient-based optimization schemes, evaluating the design sensitivities using the adjoint method. Numerical studies illustrate the features of the proposed framework with static, linear elastic, multi-material, two- and three-dimensional problems. The examples provide insight into the effect of refining the design variable field on the optimization result and the convergence rate of the optimization process. Using coarse higher-order B-spline discretizations for level-set fields promotes the development of smooth designs and suppresses the emergence of small features. Moreover, adaptive mesh refinement for state variable fields results in a reduction of overall computational cost. Higher-order B-spline discretizations are especially interesting when evaluating gradients of state variable fields due to their higher inter-element continuity.

36 MATERIALS SCIENCE↗

Efficient proximal subproblem solvers for a nonsmooth trust-region method

In [R. J. Baraldi and D. P. Kouri, Mathematical Programming, (2022), pp. 1-40], we introduced an inexact trust-region algorithm for minimizing the sum of a smooth nonconvex and nonsmooth convex function. The principle expense of this method is in computing a trial iterate that satisfies the so-called fraction of Cauchy decrease condition—a bound that ensures the trial iterate produces sufficient decrease of the subproblem model. In this paper, we expound on various proximal trust-region subproblem solvers that generalize traditional trust-region methods for smooth unconstrained and convex-constrained problems. We introduce a simplified spectral proximal gradient solver, a truncated nonlinear conjugate gradient solver, and a dogleg method. Finally, we compare algorithm performance on examples from data science and PDE-constrained optimization.

97 MATHEMATICS AND COMPUTING↗

The atomic-level structure and stability of interfaces of Pt nanoparticles in alumina: An experimental and computational evaluation

The atomic-level structure of interfaces between Pt and a transition form of Al2O3 were studied using a combination of electron microscopy and first principles calculations. A model system of Pt nanoprecipitates in Al2O3 were formed in sapphire wafers via high-energy ion implantation of Pt followed by thermal annealing at 1000 °C in air. The Pt nanoparticles took the form of tetrahedra and truncated tetrahedra primarily bound by {111}Pt facets. The high prevalence of these facets motivated the development of density functional theory (DFT) based models of (111)Pt interfaces with six different chemical terminations of ( 2 ¯ 01 ) θ-alumina. The atomic-level structure of the Pt/Al2O3 interfaces was characterized with aberration-corrected scanning transmission electron microscopy (STEM) and the experimental images were compared to STEM image simulations of the DFT models. The model interface with Pt bonded to oxygen-terminated θ-Al2O3, with the Pt located on top of the O and with an underlying layer of octahedral Al, provided the best match to the experimental images. This interfacial termination is also the most stable for the thermal annealing conditions used based on thermodynamic calculations of the interfacial energy as a function of temperature and oxygen partial pressure. This experimentally verified model provides a basis for improving models of Pt/γ-alumina interfaces.

Clauser, A L↗

Physics-coupled data-driven design of high-temperature alloys

We present a materials design loop, which streamlines physics-coupled machine learning (ML) surrogate models to discover new alloy chemistries with improved properties. The efficacy is demonstrated by discovering a high-temperature alumina-forming austenitic (AFA) stainless steel with enhanced creep, followed by experimental validation. The ML models have been trained using a well-curated, highly consistent experimental dataset augmented with synthetic microstructural features from a computational thermodynamic approach. We have populated a large number of hypothetical AFA alloys to explore the high-dimensional composition space and have predicted their creep properties by providing the same synthetic input features obtained from the trained ML models. Uncertainties from the ML training were taken as thresholds for truncating predicted results to identify alloys with improved or deteriorated creep. Individual elemental compositions have been determined via probability density distribution analysis from the group of alloys at the top and bottom of the predicted creep values for further virtual and experimental validations. In conclusion, we anticipate that this workflow can be applied to screen desired conditions, such as chemistry and processing parameters, in high-dimensional space through physics-guided data analytics.

Alloy design↗

Bayesian modeling of traffic-related air pollutants: A case study of urban transportation and air quality dynamics in Columbia, South Carolina

Traffic emissions significantly impact near-road air quality and public health. This research applies a Bayesian modeling framework to investigate these impacts using high-resolution traffic and air pollutant data from an urban corridor in Columbia, South Carolina. Despite a data collection period truncated by the COVID-19 lockdown, the Bayesian approach successfully identified significant predictors and quantified model uncertainty. Employing Bayesian Model Selection and Averaging enhanced prediction accuracy and evaluated model uncertainty. Findings indicate that higher temperatures and increased moisture levels elevate particulate matter (PM 1.0 , PM 2.5 , PM 10 ) concentrations, while traffic speed significantly affects nitrogen dioxide (NO 2 ) levels. Specifically, higher average traffic speeds (indicative of smoother flow) correspond to lower NO 2 concentrations, suggesting that less congested conditions reduce NO 2 emissions. This study highlights the robustness of Bayesian methods for generating reliable air quality insights even under data-constrained conditions. The findings underscore the importance of traffic flow management (e.g., reducing congestion) for mitigating near-road NO 2 exposure and provide a basis for developing targeted public health strategies.

54 ENVIRONMENTAL SCIENCES↗

Metal oxide-promoted calcium cuprate catalysts for diol oxidative dehydrocyclization to lactones

Here, this work investigates structure-function relationships in electronically tunable, redox-active, basic Cu-Ca mixed metal oxide catalysts for oxidative dehydrocyclization of liquid diols to lactones. Compositional screening identified Ni 2+ and Zn 2+ as effective promoters that increase the surface Cu 2+ population by ∼1.7× and Cu-normalized activity for liquid 1,4-butanediol conversion to γ-butyrolactone by ∼3–4×. In situ Raman spectroscopy, in situ X-ray absorption spectroscopy (XAS), in situ diffuse-reflectance Fourier transform infrared spectroscopy (DRIFTS), ex situ X-ray diffraction (XRD), and H 2 -temperature-programmed reduction (H 2 -TPR) show that Ni 2+ or Zn 2+ incorporation promotes the formation of Ca 0.82 Cu 1.00 O 2 nanoparticles under mild calcination conditions. This cuprate phase features stronger and shorter Cu–O bonds (1.90 Å) than inactive bulk CuO (1.95 Å) and square-planar Cu 2+ O 4 sites with enhanced d z2 electrophilicity, strengthening alkoxy adsorption. Pyridine-DRIFTS confirms the purely basic nature of the catalyst surface, while methanol-DRIFTS indicates Cu 2+ surface enrichment with Ni or Zn promotion, where Cu–O(Ca)–Cu sites can exist as amorphous domains or a truncation layer on crystalline nanoparticles.

09 BIOMASS FUELS↗

High order interpolation of magnetic fields with vector potential reconstruction for particle simulations

We propose a method for interpolating divergence-free continuous magnetic fields via vector potential reconstruction using Hermite interpolation, which ensures high-order continuity for applications requiring adaptive, high-order ordinary differential equation (ODE) integrators, such as the Dormand-Prince method. The method provides C(m) continuity and achieves high-order accuracy, making it particularly suited for particle trajectory integration and Poincaré section analysis under optimal integration order and timestep adjustments. Through numerical experiments, we demonstrate that the Hermite interpolation method preserves volume and continuity, which are critical for conserving toroidal canonical momentum and magnetic moment in guiding center simulations, especially over long-term trajectory integration. Furthermore, we analyze the impact of insufficient derivative continuity on Runge-Kutta schemes and show how it degrades accuracy at low error tolerances, introducing discontinuity-induced truncation errors. Lastly, we demonstrate performant Poincaré section analysis in two relevant settings of field data collocated from finite element meshes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerating eigenvalue computation for nuclear structure calculations via perturbative corrections

Subspace projection methods utilizing perturbative corrections have been proposed for computing the lowest few eigenvalues and corresponding eigenvectors of large Hamiltonian matrices. In this paper, we build upon these methods and introduce the term Subspace Projection with Perturbative Corrections (SPPC) method to refer to this approach. We tailor the SPPC for nuclear many-body Hamiltonians represented in a truncated configuration interaction subspace, i.e., the no-core shell model (NCSM). We use the hierarchical structure of the NCSM Hamiltonian to partition the Hamiltonian as the sum of two matrices. The first matrix corresponds to the Hamiltonian represented in a small configuration space, whereas the second is viewed as the perturbation to the first matrix. Eigenvalues and eigenvectors of the first matrix can be computed efficiently. Because of the split, perturbative corrections to the eigenvectors of the first matrix can be obtained efficiently from the solutions of a sequence of linear systems of equations defined in the small configuration space. These correction vectors can be combined with the approximate eigenvectors of the first matrix to construct a subspace from which more accurate approximations of the desired eigenpairs can be obtained. We show by numerical examples that the SPPC method can be more efficient than conventional iterative methods for solving large-scale eigenvalue problems such as the Lanczos, block Lanczos and the locally optimal block preconditioned conjugate gradient (LOBPCG) method. The method can also be combined with other methods to avoid convergence stagnation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗