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At least 73 records · Page 4

Solving nuclear structure problems with the adaptive variational quantum algorithm

Here we use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model to examine the likely performance of variational quantum eigensolvers in nuclear-structure theory. The LMG model exhibits both a phase transition and spontaneous symmetry breaking at the mean-field level in one of the phases, features that characterize collective dynamics in medium-mass and heavy nuclei. We show that with appropriate modifications, the ADAPT-VQE algorithm, a particularly flexible and accurate variational approach, is not troubled by these complications. We treat up to 12 particles and show that the number of quantum operations needed to approach the ground-state energy scales linearly with the number of qubits. We find similar scaling when the algorithm is applied to the nuclear shell model with realistic interactions in the sd and pf shells. Although most of these simulations contain no noise, we use a noise model from real IBM hardware to show that for the LMG model with four particles, weak noise has no effect on the efficiency of the algorithm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Preliminary Feasibility Study on Multi-Cavity Cryomodule Integration for the Electron Ion Collider Energy Recover Linac Cooler

The Electron-Ion Collider (EIC) is a state-of-the-art accelerator designed for collisions between highly polarized electrons and ions. To achieve optimal luminosity, the ion beam is cooled using an electron beam sourced from an energy recovery linac (ERL). In the current ERL baseline design, one BNL type RF cavity is used per cryomodule, leading to spatial and cost challenges. This study examines the feasibility of using more compact PERLE (Powerful Energy Recovery Linac for Experiments) type cavities, which can house multiple cavities within a single cryomodule, by evaluating their Beam Breakup (BBU) instability performance. Higher Order Modes (HOM) parameters were obtained through frequency scaling, assuming constant quality factor Q_L, R/Q, and linearly scaling HOM frequencies. To predict the BBU threshold current and ensure accuracy, two different BBU tracking simulations are used for cross-verification. Although the reduced footprint of PERLE-type cavities is advantageous, maintaining sufficient damping of HOMs remains crucial. Finally, we compare the HOM damping efficiency of both cavity types and suggest a pathway forward.

Deitrick, K.↗

Nature and Scalings of Density Fluctuations of Compressible Magnetohydrodynamic Turbulence with Applications to the Solar Wind

Abstract The solar wind is a magnetized and turbulent plasma. Its turbulence is often dominated by Alfvénic fluctuations and often deemed as nearly incompressible far away from the Sun, as shown by in situ measurements near 1 au. However, for solar wind closer to the Sun, the plasma β decreases (often lower than unity) while the turbulent Mach number M t increases (can approach unity, e.g., transonic fluctuations). These conditions could produce significantly more compressible effects, characterized by enhanced density fluctuations, as seen by several space missions. In this paper, a series of 3D MHD simulations of turbulence are carried out to understand the properties of compressible turbulence, particularly the generation of density fluctuations. We find that, over a broad range of parameter space in plasma β , cross helicity, and polytropic index, the turbulent density fluctuations scale linearly as a function of M t , with the scaling coefficients showing weak dependence on parameters. Furthermore, through detailed spatiotemporal analysis, we show that the density fluctuations are dominated by low-frequency nonlinear structures, rather than compressible MHD eigenwaves. These results could be important for understanding how compressible turbulence contributes to solar wind heating near the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗

Prediction of Transition-State Scaling Relationships and Universal Transition-State Vibrational and Entropic Correlations for Dehydrogenations

Linear scaling relationships (LSRs) and Brønsted–Evans–Polanyi (BEP) or transition-state scaling (TSS) relations aid with the prediction of electronic energies. However, temperature effects and pre-exponentials are often taken as constants across metal surfaces or a homologous series. Vibrational scaling relationships (VSRs) offer a way to determine such parameters. Transition-state VSRs (TSVSRs) between local minima and transition states of AH X (A = C, N, O) surface diffusions correlate with BEP relations and broaden to thermochemical property scaling. Using density functional theory, we extend TSVSRs to AHX dehydrogenation reactions on transition-metal surfaces, relating vibrational modes of local minima to transition states. We first predict the slopes of the TSS relations by incorporating bond angles using the Slater–Koster structure factors and hybridization through crystal orbital overlap population analysis and energy overlap integrals between adsorbates and metal surfaces. Additionally, we uncover universal thermochemical property scaling, enabling the estimation of entropies and temperature corrections to enthalpies across a homologous series. Here, we demonstrate both significant vibrational corrections in reactions with low intrinsic electronic barriers and considerable variation in the pre-exponential of a simple dehydrogenation reaction across metals and AH X adsorbates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Frontal Slice Approaches for Tensor Linear Systems

Inspired by the row and column action methods for solving large-scale linear systems, in this work, we explore the use of frontal slices for solving tensor linear systems. In particular, this paper presents a novel approach for using frontal slices of a tensor $\mathcal{A}$ to solve tensor linear systems $\mathcal{A} ∗\mathcal{X} = \mathcal{B}$ where ∗ denotes the $t$-product. In addition, we consider variations of this method, including cyclic, block, and randomized approaches, each designed to optimize performance in different operational contexts. Our primary contribution lies in the development and convergence analysis of these methods. Experimental results on synthetically generated and real-world data, including applications such as image and video deblurring, demonstrate the efficacy of our proposed approaches and validate our theoretical findings.

Luo, Hengrui↗

Evidence for Nonlinear Gluon Effects in QCD and Their Mass Number Dependence at STAR

The STAR Collaboration reports measurements of back-to-back azimuthal correlations of di-π 0 s produced at forward pseudorapidities (2.6<η<4.0) in p+p, p+Al, and p+Au collisions at a center-of-mass energy of 200 GeV. We observe a clear suppression of the correlated yields of back-to-back π 0 pairs in p+Al and p+Au collisions compared to the p+p data. The observed suppression of back-to-back pairs as a function of transverse momentum suggests nonlinear gluon dynamics arising at high parton densities. Furthermore, the larger suppression found in p+Au relative to p+Al collisions exhibits a dependence of the saturation scale $Q^{2}_{s}$ on the mass number A . A linear scaling of the suppression with A 1/3 is observed with a slope of -0.09±0.01.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sparsity of the electron repulsion integral tensor using different localized virtual orbital representations in local second-order Møller–Plesset theory

Utilizing localized orbitals, local correlation theory can reduce the unphysically high system-size scaling of post-Hartree–Fock (post-HF) methods to linear scaling in insulating molecules. The sparsity of the four-index electron repulsion integral (ERI) tensor is central to achieving this reduction. For second-order Møller–Plesset theory (MP2), one of the simplest post-HF methods, only the (ia|jb) ERIs are needed, coupling occupied orbitals i, j and virtuals a, b. In this paper, we compare the numerical sparsity (called the “ragged list”) and two other approaches revealing the low-rank sparsity of the ERI. The ragged list requires only one set of (localized) virtual orbitals, and we find that the orthogonal valence virtual-hard virtual set of virtuals originally proposed by Subotnik et al. gives the sparsest ERI tensor. To further compress the ERI tensor, the pair natural orbital (PNO) type representation uses different sets of virtual orbitals for different occupied orbital pairs, while the occupied-specific virtual (OSV) approach uses different virtuals for each occupied orbital. Here, our results indicate that while the low-rank PNO representation achieves significant rank reduction, it also requires more memory than the ragged list. The OSV approach requires similar memory to that of the ragged list, but it involves greater algorithmic complexity. An approximation (called the “fixed sparsity pattern”) for solving the local MP2 equations using the numerically sparse ERI tensor is proposed and tested to be sufficiently accurate and to have highly controllable error. A low-scaling local MP2 algorithm based on the ragged list and the fixed sparsity pattern is therefore promising.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Discovery of Active and Selective Metal‐Nitrogen‐Graphene Catalysts for Electrooxidation of Water to H 2 O 2

A direct electrosynthesis of H 2 O 2 from either O 2 or H 2 O is an attractive strategy to replace the energy-intensive industrial anthraquinone process. Two-electron water oxidation reaction (2e-WOR) offers several advantages over the oxygen reduction reaction such as better mass transfer due to the absence of gas-phase reactants. However, 2e-WOR is a more challenging and less studied process with only a handful of metal oxides exhibiting reasonable activity/selectivity properties. Herein, we employ density-functional-theory calculations to screen a variety of metal-nitrogen-graphene structures for 2e-WOR. As a consequence of scaling between the adsorption energies of reaction intermediates, we determine a linear relation between selectivities for the first and second reaction steps of 2e-WOR, viz. that if selectivity toward adsorbed OH is improved, then selectivity toward H 2 O 2 at the subsequent step is decreased. We also find that selectivity and activity are linearly scaled in such a way that a higher activity (i.e., a lower overpotential) leads to a lower selectivity for the H 2 O 2 formation step. Based on the obtained results several chemistries, e.g., containing NiN x -C moieties, are predicted to rival the best-performing metal oxides such as ZnO and CaSnO 3 in terms of combination of their activity/selectivity characteristics for 2e-WOR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Block encoding of the three-dimensional heterogeneous Poisson equation with application to fracture flow

Quantum linear system (QLS) algorithms offer the potential to solve large-scale linear systems exponentially faster than classical methods. However, applying QLS algorithms to real-world problems remains challenging due to issues such as state preparation, data loading, and efficient information extraction. In this work, we study the feasibility of applying QLS algorithms to solve discretized three-dimensional (3D) heterogeneous Poisson equations, with specific examples relating to groundwater flow through geologic fracture networks. We explicitly construct a block encoding for the 3D heterogeneous Poisson matrix by leveraging the sparse local structure of the discretized operator. While classical solvers benefit from preconditioning, we show that block encoding the system matrix and preconditioner separately does not improve the effective condition number that dominates the QLS run-time. This differs from classical approaches where the preconditioner and the system matrix can often be implemented independently. Nevertheless, due to the structure of the problem in three dimensions, the quantum algorithm achieves a run-time of 𝑂⁡(𝑁 2/3 polylog 𝑁 ⋅log (1/𝜖)), outperforming the best classical methods (with run times of 𝑂⁡(𝑁⁢log 𝑁 ⋅log (1/𝜖))) and offering exponential memory savings. These results highlight both the promise and limitations of QLS algorithms for practical scientific computing, and point to effective condition-number reduction as a key barrier in achieving quantum advantages.

58 GEOSCIENCES↗

Gradient Coding With Iterative Block Leverage Score Sampling

Gradient coding is a method for mitigating straggling servers in a centralized computing network that uses erasure-coding techniques to distributively carry out first-order optimization methods. Randomized numerical linear algebra uses randomization to develop improved algorithms for large-scale linear algebra computations. In this study, we propose a method for distributed optimization that combines gradient coding and randomized numerical linear algebra. The proposed method uses a randomized ℓ 2 -subspace embedding and a gradient coding technique to distribute blocks of data to the computational nodes of a centralized network, and at each iteration the central server only requires a small number of computations to obtain the steepest descent update. The novelty of our approach is that the data is replicated according to importance scores, called block leverage scores, in contrast to most gradient coding approaches that uniformly replicate the data blocks. Furthermore, we do not require a decoding step at each iteration, avoiding a bottleneck in previous gradient coding schemes. We show that our approach results in a valid ℓ 2 -subspace embedding, and that our resulting approximation converges to the optimal solution.

97 MATHEMATICS AND COMPUTING↗

Quantum Ising model on (2+1)-dimensional anti–de Sitter space using tensor networks

We study the quantum Ising model on (2+1)-dimensional anti-de Sitter space using matrix product states (MPS) and matrix product operators (MPOs). We explore the bulk phase diagram of the theory on regular tessellations of hyperbolic space with coordination number seven and find disordered and ordered phases separated by a phase transition. We find that the boundary-boundary spin correlation function exhibits power law scaling deep in the disordered phase of the Ising model consistent with holography. At the critical point, we find the boundary entanglement entropy scales logarithmically with subsystem size but away from this, we see a linear scaling. In comparison, the full system exhibits a volume law scaling, which is expected in chaotic and/or highly connected systems. We also measure out of time ordered correlators (OTOCs) to explore the scrambling behavior of the theory.

Quantum spin models↗

Cumulative fidelity of large-momentum-transfer clock atom interferometers in the presence of laser noise

Clock atom interferometry is an emerging technique in precision measurements that is particularly well suited for sensitivity enhancement through large momentum transfer (LMT). While current systems have demonstrated momentum separations of several hundreds of photon momenta, next-generation quantum sensors are targeting an LMT enhancement factor beyond 10 4 . However, the viability of LMT clock interferometers has recently come into question due to the potential impact of laser frequency noise. Here, in this work, we resolve this concern by analyzing the cumulative fidelity of sequential state inversions in an LMT atom interferometer. We show that the population error from 𝑛 pulses applied from alternating directions scales linearly with 𝑛. This is a significant advantage over the 𝑛 2 scaling that occurs when probing a two-level system 𝑛 times from the same direction. We further show that contributions to the interferometer signal from parasitic paths generated by imperfect pulses are negligible, for any loss mechanism. These results establish that laser frequency noise is not a practical limitation for the development of high-fidelity LMT clock atom interferometers.

Mach-Zehnder atom interferometry↗

Transonic Turbulence and Density Fluctuations in the Near-Sun Solar Wind

We use in situ measurements from the first 19 encounters of Parker Solar Probe and the most recent five encounters of Solar Orbiter to study the evolution of the turbulent sonic Mach number M t (the ratio of the amplitude of velocity fluctuations to the sound speed) with radial distance and its relationship to density fluctuations. We focus on the near-Sun region with radial distances ranging from about 11 to 80 R ⊙ . Our results show that (1) the turbulent sonic Mach number M t gradually moves toward larger values as it approaches the Sun, until at least 11 R ⊙ , where M t is much larger than the previously observed value of 0.1 at and above 0.3 au; (2) transonic turbulence with M t ∼ 1 is observed in situ for the first time and is found mostly near the Alfvén critical surface; (3) Alfvén Mach number of the bulk flow M A shows a strong correlation with the plasma beta, indicating that most of the observed sub-Alfvénic intervals correspond to a low-beta plasma; (4) the scaling relation between density fluctuations and M t gradually changes from a linear scaling at larger radial distances to a quadratic scaling at smaller radial distances; and (5) transonic turbulence is more compressible than subsonic turbulence, with enhanced density fluctuations and slightly flatter spectra than subsonic turbulence. A systematic understanding of compressible turbulence near the Sun is necessary for future solar wind modeling efforts.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectroscopic Characterization of redMaPPer Galaxy Clusters with DESI

Optical galaxy cluster identification algorithms such as redMaPPer promise to enable an array of astrophysical and cosmological studies, but suffer from biases whereby galaxies in front of and behind a galaxy cluster are mistakenly associated with the primary cluster halo. These projection effects caused by irreducible photometric redshift uncertainty must be quantified to facilitate the use of optical cluster catalogues. We present measurements of galaxy cluster projection effects and velocity dispersion using spectroscopy from the Dark Energy Spectroscopic Instrument. Our findings are as follows: we confirm that the fraction of redMaPPer putative member galaxies mistakenly associated with cluster haloes is richness dependent, being more than twice as large at low richness than high richness; we present the first spectroscopic evidence of an increase in projection effects with increasing redshift, by as much as 25 per cent from $z\sim 0.1$ to $z\sim 0.2$; moreover, we find qualitative evidence for luminosity dependence in projection effects, with fainter galaxies being more commonly far behind clusters than their bright counterparts; finally, we fit the scaling relation between measured mean spectroscopic richness and velocity dispersion, finding an implied linear scaling between spectroscopic richness and halo mass. We discuss further directions for the application of spectroscopic data sets to improve use of optically selected clusters to test cosmological models.

clusters↗

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

97 MATHEMATICS AND COMPUTING↗

Quantum-Accurate Multiscale Modeling of Shock Hugoniots, Ramp Compression Paths, Structural and Magnetic Phase Transitions, and Transport Properties in Highly Compressed Metals

Fully characterizing high energy density (HED) phenomena using pulsed power facilities (Z machine) and coherent light sources is possible only with complementary numerical modeling for design, diagnostic development, and data interpretation. The exercise of creating numerical tests, that match experimental conditions, builds critical insight that is crucial for the development of a strong fundamental understanding of the physics behind HED phenomena and for the design of next generation pulsed power facilities. The persistence of electron correlation in HED materials arising from Coulomb interactions and the Pauli exclusion principle is one of the greatest challenges for accurate numerical modeling and has hitherto impeded our ability to model HED phenomena across multiple length and time scales at sufficient accuracy. An exemplar is a ferromagnetic material like iron, while familiar and widely used, we lack a simulation capability to characterize the interplay of structure and magnetic effects that govern material strength, kinetics of phase transitions and other transport properties. Herein we construct and demonstrate the Molecular-Spin Dynamics (MSD) simulation capability for iron from ambient to earth core conditions, all software advances are open source and presently available for broad usage. These methods are multi-scale in nature, direct comparisons between high fidelity density functional theory (DFT) and linear-scaling MSD simulations is done throughout this work, with advancements made to MSD allowing for electronic structure changes being reflected in classical dynamics. Main takeaways for the project include insight into the role of magnetic spins on mechanical properties and thermal conductivity, development of accurate interatomic potentials paired with spin Hamiltonians, and characterization of the high pressure melt boundary that is of critical importance to planetary modeling efforts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Constraints on S 8 from a full-scale and full-shape analysis of redshift-space clustering and galaxy–galaxy lensing in BOSS

ABSTRACT We present a novel simulation-based cosmological analysis of galaxy–galaxy lensing and galaxy redshift-space clustering. Compared to analysis methods based on perturbation theory, our simulation-based approach allows us to probe a much wider range of scales, $0.4 \, h^{-1} \, \mathrm{Mpc}$ to $63 \, h^{-1} \, \mathrm{Mpc}$, including highly non-linear scales, and marginalizes over astrophysical effects such as assembly bias. We apply this framework to data from the Baryon Oscillation Spectroscopic Survey LOWZ sample cross-correlated with state-of-the-art gravitational lensing catalogues from the Kilo Degree Survey and the Dark Energy Survey. We show that gravitational lensing and redshift-space clustering when analysed over a large range of scales place tight constraints on the growth-of-structure parameter $S_8 = \sigma _8 \sqrt{\Omega _{\rm m} / 0.3}$. Overall, we infer S8 = 0.792 ± 0.022 when analysing the combination of galaxy–galaxy lensing and projected galaxy clustering and S8 = 0.771 ± 0.027 for galaxy redshift-space clustering. These findings highlight the potential constraining power of full-scale studies over studies analysing only large scales and also showcase the benefits of analysing multiple large-scale structure surveys jointly. Our inferred values for S8 fall below the value inferred from the CMB, S8 = 0.834 ± 0.016. While this difference is not statistically significant by itself, our results mirror other findings in the literature whereby low-redshift large-scale structure probes infer lower values for S8 than the CMB, the so-called S8-tension.

79 ASTRONOMY AND ASTROPHYSICS↗