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At least 397 records · Page 22

Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis

The generalized singular value decomposition (GSVD) is a valuable tool that has many applications in computational science. However, computing the GSVD for large-scale problems is challenging. Motivated by applications in hyper-differential sensitivity analysis (HDSA), in this work we propose new randomized algorithms for computing the GSVD which use randomized subspace iteration and weighted QR factorization. Detailed error analysis is given which provides insight into the accuracy of the algorithms and the choice of the algorithmic parameters. We demonstrate the performance of our algorithms on test matrices and a large-scale model problem where HDSA is used to study subsurface flow.

97 MATHEMATICS AND COMPUTING↗

Smoothed aggregation for difficult stretched mesh and coefficient variation problems

Abstract Four adaptations of the smoothed aggregation algebraic multigrid (SA‐AMG) method are proposed with an eye toward improving the convergence and robustness of the solver in situations when the discretization matrix contains many weak connections. These weak connections can cause higher than expected levels of fill‐in within the coarse discretization matrices and can also give rise to suboptimal smoothing within the prolongator smoothing phase. These smoothing drawbacks are due to the relatively small size of some diagonal entries within the filtered matrix that one obtains after dropping the weak connections. The new algorithms consider modifications to the Jacobi‐like step that defines the prolongator smoother, modifications to the filtered matrix, and also direct modifications to the resulting grid transfer operators. Numerical results are given illustrating the potential benefits of the proposed adaptations.

Hu, Jonathan J.↗

Anderson acceleration with approximate calculations: Applications to scientific computing

Here we provide rigorous theoretical bounds for Anderson acceleration (AA) that allow for approximate calculations when applied to solve linear problems. We show that, when the approximate calculations satisfy the provided error bounds, the convergence of AA is maintained while the computational time could be reduced. We also provide computable heuristic quantities, guided by the theoretical error bounds, which can be used to automate the tuning of accuracy while performing approximate calculations. For linear problems, the use of heuristics to monitor the error introduced by approximate calculations, combined with the check on monotonicity of the residual, ensures the convergence of the numerical scheme within a prescribed residual tolerance. Motivated by the theoretical studies, we propose a reduced variant of AA, which consists in projecting the least-squares used to compute the Anderson mixing onto a subspace of reduced dimension. The dimensionality of this subspace adapts dynamically at each iteration as prescribed by the computable heuristic quantities. We numerically show and assess the performance of AA with approximate calculations on: (i) linear deterministic fixed-point iterations arising from the Richardson's scheme to solve linear systems with open-source benchmark matrices with various preconditioners and (ii) non-linear deterministic fixed-point iterations arising from non-linear time-dependent Boltzmann equations.

97 MATHEMATICS AND COMPUTING↗

A matrix-free approach for finite-strain hyperelastic problems using geometric multigrid

This paper investigates matrix-free algorithms for problems in quasi-static finite-strain hyperelasticity. Iterative solvers with matrix-free operator evaluation have emerged as an attractive alternative to sparse matrices in the fluid dynamics and wave propagation communities because they significantly reduce the memory traffic, the limiting factor in classical finite element solvers. Specifically, we study different matrix-free realizations of the finite element tangent operator and determine whether generalized methods of incorporating complex constitutive behavior might be feasible. Furthermore, in order to improve the convergence behavior of iterative solvers, we also propose a method by which to construct level tangent operators and employ them to define a geometric multigrid preconditioner. Additionally, the performance of the matrix-free operator and the geometric multigrid preconditioner is compared to the matrix-based implementation with an algebraic multigrid (AMG) preconditioner on a single node for a representative numerical example of a heterogeneous hyperelastic material in two and three dimensions. We find that matrix-free methods for finite-strain solid mechanics are very promising, outperforming linear matrix-based schemes by two to five times, and that it is possible to develop numerically efficient implementations that are independent of the hyperelastic constitutive law.

42 ENGINEERING↗

Latent variable Gaussian process models: A rank‐based analysis and an alternative approach

Abstract Gaussian process (GP) models have been extended to emulate expensive computer simulations with both qualitative/categorical and quantitative/continuous variables. Latent variable (LV) GP models, which have been recently developed to map each qualitative variable to some underlying numerical LVs, have strong physics‐based justification and have achieved promising performance. Two versions use LVs in Cartesian (LV‐Car) space and hyperspherical (LV‐sph) space, respectively. Despite their success, the effects of these different LV structures are still poorly understood. This article illuminates this issue with two contributions. First, we develop a theorem on the effect of the ranks of the qualitative factor correlation matrices of mixed‐variable GP models, from which we conclude that the LV‐sph model restricts the interactions between the input variables and thus restricts the types of response surface data with which the model can be consistent. Second, following a rank‐based perspective like in the theorem, we propose a new alternative model named LV‐mix that combines the LV‐based correlation structures from both LV‐Car and LV‐sph models to achieve better model flexibility than them. Through extensive case studies, we show that LV‐mix achieves higher average accuracy compared with the existing two.

Tao, Siyu↗

Mapping Thermal Conductivity at the Atomic Scale: A Step toward the Thermal Design of Materials

We describe a spatial decomposition of the thermal conductivity, termed site-projected thermal conductivity, which quantifies the thermal conduction activity at each atomic site—a critical parameter for the thermal design of materials. The method is based on the Green–Kubo formula and the harmonic approximation and requires the force-constant and dynamical matrices, as well as a relaxed structural model. Throughout the study, it uses high quality models previously tested and compared to many experiments. It discusses the method and underlying approximations for amorphous silicon, carries the detailed analysis for amorphous silicon, and then examines an amorphous-crystal silicon interface and representative carbon materials. This study identifies the sites and local structures that reduce heat transport, and quantify these (estimate the spatial range) over which these “thermal defects” are effective. It identifies filamentary structures in the amorphous silicon network which impact heat transport and electronic structure (the Urbach edge) and electronic transport.

36 MATERIALS SCIENCE↗

Depth profiling and standardization from the back side of a sample for accurate analyses: Emphasis on quantifying low‐fluence, shallow implants in diamond‐like carbon

Rationale Back‐side thinning of wafers is used to eliminate issues with transient sputtering when analyzing near‐surface element distributions. Precise and accurate calibrated implants are created by including a standard reference material during the implantation. Combining these methods allows accurate analysis of low‐fluence, shallow features even if matrix effects are a concern. Methods Implanted Na (<2.0 × 10 11 ions/cm 2 , peaking <50 nm) in diamond‐like carbon (DLC) film on silicon (solar wind returned by NASA's Genesis mission) was prepared for measurement as follows. Implanted surfaces of samples were epoxied to wafers and back‐side‐thinned using physical or chemical methods. Thinned samples were then implanted with reference ions for accurate quantification of the solar wind implant. Analyses used a CAMECA IMS 7f‐GEO SIMS in depth‐profiling mode. Results Back‐side‐implanted reference ions reduced the need to change sample mounts or stage position and could be spatially separated from the solar wind implant even when measuring monoisotopic ions. Matrix effects in DLC were mitigated and the need to find an identical piece of DLC for a reference implant was eliminated. Accuracy was only limited by the back‐side technique itself. Conclusions Combining back‐side depth profiling with back‐side‐implanted internal standards aides quantification of shallow mono‐ and polyisotopic implants. This technique helps mitigate matrix effects and keeps measurement conditions consistent. Depth profile acquisition times are longer, but if sample matrices are homogeneous, procedural changes can decrease measurement times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single-Filament Imaging Mass Spectrometry Lipidomics in Arthrospira platensis

Elucidating intra-organismal biochemical and lipid organization in photosynthetic biological cell factories of filamentous cyanobacteria, i.e., Arthrospira platensis (Spirulina), is important to track physiological response mechanisms during growth. Little is known about the filaments' biochemical organization and cellular structure and no label-free imaging techniques exist that provide molecular mapping. We applied ultra-high resolution mass spectrometry (7T FT-ICR-MS) matrix-assisted laser desorption ionization (MALDI) imaging to immobilized Spirulina filaments to investigate the localization of lipids across distinct physiological regions. We optimized matrix selection and deposition methods with the goal of facilitating high spatial, and intra-filament, resolution using untargeted multivariate statistical spectral deconvolution across MS pixels. Our results demonstrate an improved two step application with an optimized procedure for intra-organismal lipid profiling to improve analyte sensitivity and achieve higher spatial resolution, whereby we evaluate three conventional matrices 2,5-dihydroxybenzoic acid (DHB), a 9:1 ratio of DHB:superDHB (sDHB), 1,5- diaminonaphthalene (DAN) and a 50:50 mix of DHB:sDHB and compare delineation and pixel-based elucidation of intra-filament lipidomics. We identified a total of 1,626 features that could be putatively assigned a lipid-like formula based on database query and 46 unique features, with associated lipid assignments that were significantly distinct in their intra-filament location. MALDI- imaging MS with untargeted statistical spectral deconvolution was used to visualize intra-filament lipidomics organization in Spirulina filaments. Improvements in matrix deposition, including sequential sublimation and pneumatic spraying, increased signal abundance at high spatial resolution and allowed for identification of distinct lipid composition regions. Here in this work outlines a methodology that may be used for micro-ecological untargeted molecular phenotyping.

09 BIOMASS FUELS↗

Toward a standardization of cryostructure and cryogenic soil structure terminology for the field description of permafrost‐affected soils

This paper establishes standardized terminology and field documentation protocols for cryostructures and cryogenic soil structures in permafrost‐affected soils and provides brief guidance on descriptions of ground ice morphology and ice volume estimates. We consolidate permafrost terminology from Russian and North American literature, clarify long‐standing ambiguities, and provide explicit guidelines that align with US Department of Agriculture‐Natural Resources Conservation Service soil description standards. Our scheme makes critical distinctions between cryostructure, the distribution of ice within soil, and cryogenic soil structure, the morphological structure of soil resulting from ice formation. The scheme organizes cryostructures into three main categories: non‐segregated ice, visible segregated ice, and ice matrices. We introduce standardized codes and parameters for field descriptions of ice and soil that enable machine‐readable data collection compatible with existing soil information systems. This standardization will significantly enhance the integration of field observations into landscape‐scale assessments of permafrost stability, infrastructure vulnerability, and ecosystem response to permafrost thaw, addressing an urgent need for quantitative data to inform modeling and decision‐making in rapidly changing Arctic and subarctic environments.

Andersen, Megan L. [University of Minnesota, Saint↗

An Adsorptive Membrane Platform for Precision Ion Separation: Membrane Design and First‐Principles Studies

One of the key challenges in separation science is the lack of precise ion separation methods and mechanistic understanding crucial for efficiently recovering critical materials from complex aqueous matrices. Herein, first-principles electronic structure calculations and in situ Raman spectroscopy are studied to elucidate the factors governing ion discrimination in an adsorptive membrane specifically designed for transition metal ion separation. Density functional theory calculations and in situ Raman data jointly reveal the thermodynamically favorable binding preferences and detailed adsorption mechanisms for competing ions. How membrane binding preferences correlate with the electronic properties of ligands is explored, such as orbital hybridization and electron localization. The findings underscore the importance of the phenolate group in oxime ligands for achieving high selectivity among competing transition metal ions. In-depth understanding on which specific atomistic site within the microenvironment of metal-ligand binding pockets governs the ion discrimination behaviors of the host will build a solid foundation to guide the rational design of next-generation materials for precision separation essential for energy technologies and environment remediation. In tandem, synthetic controllability is demonstrated to transform 3D micrometer-scale crystals to a 2D crystalline selective layer in membranes, paving the way for more precise and sustainable advances in separation science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗

libwfa: Wavefunction analysis tools for excited and open‐shell electronic states

Abstract An open‐source software library for wavefunction analysis, libwfa, provides a comprehensive and flexible toolbox for post‐processing excited‐state calculations, featuring a hierarchy of interconnected visual and quantitative analysis methods. These tools afford compact graphical representations of various excited‐state processes, provide detailed insight into electronic structure, and are suitable for automated processing of large data sets. The analysis is based on reduced quantities, such as state and transition density matrices (DMs), and allows one to distill simple molecular orbital pictures of physical phenomena from intricate correlated wavefunctions. The implemented descriptors provide a rigorous link between many‐body wavefunctions and intuitive physical and chemical models, for example, exciton binding, double excitations, orbital relaxation, and polyradical character. A broad range of quantum‐chemical methods is interfaced with libwfa via a uniform interface layer in the form of DMs. This contribution reviews the structure of libwfa and highlights its capabilities by several representative use cases. This article is categorized under: Software > Quantum Chemistry Theoretical and Physical Chemistry > Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Kokkos OpenMPTarget Backend: Implementation and Lessons Learned

As the supercomputing landscape diversifies, solutions such as Kokkos to write vendor agnostic applications and libraries have risen in popularity. Kokkos provides a programming model designed for performance portability, which allows developers to write a single source implementation that can run efficiently on various architectures. At its heart, Kokkos maps parallel algorithms to architecture and vendor specific backends written in lower level programming models such as CUDA and HIP. Another approach to writing vendor agnostic parallel code is using OpenMP’s directives based approach, which lets developers annotate code to express parallelism. It is implemented at the compiler level and is supported by all major high performance computing vendors, as well as the primary Open Source toolchains GNU and LLVM. Since its inception, Kokkos has used OpenMP to parallelize on CPU architectures. In this paper, we explore leveraging OpenMP for a GPU backend and discuss the challenges we encountered when mapping the Kokkos APIs and semantics to OpenMP target constructs. As an exemplar workload we chose a simple conjugate gradient solver for sparse matrices. We find that performance on NVIDIA and AMD GPUs varies widely based on details of the implementation strategy and the chosen compiler. Furthermore, the performance of the OpenMP implementations decreases with increasing complexity of the investigated algorithms.

Gayatri, Rahulkumar↗

Randomized Algorithms for Low-Rank Matrix and Tensor Decompositions

This paper surveys randomized algorithms in numerical linear algebra for low-rank decompositions of matrices and tensors. The survey begins with a review of classical matrix algorithms that can be accelerated by randomized dimensionality reduction, such as the singular value decomposition (SVD) or interpolative (ID) and CUR decompositions. Recent advances in randomized dimensionality reduction are discussed, including new methods of fast matrix sketching and sampling techniques, which are incorporated into classical matrix algorithms for fast low-rank matrix approximations. The extension of randomized matrix algorithms to tensors is then explored for several low-rank tensor decompositions in the CP and Tucker formats, including the higher-order SVD, ID, and CUR decomposition.

Pearce, Katherine J. [The University of Texas at A↗

$\mathrm{Z}$ero-jettiness resummation for top-quark pair production at the $\mathrm{LHC}$

We study the resummation of the 0-jettiness resolution variable $\mathcal{T}_o$ for the top-quark pair production process in hadronic collisions. Starting from an effective theory framework we derive a factorisation formula for this observable which allows its resummation at any logarithmic order in the $\mathcal{T}_o$→ o limit. We then calculate the $\mathcal{O}(a_s)$ corrections to the soft function matrices and, by employing renormalisation group equation methods, we obtain the ingredients for the resummation formula up to next-to-next-to-leading logarithmic (NNLL) accuracy. We study the impact of these corrections to the 0-jettiness distribution by comparing predictions at different accuracy orders: NLL, NLL', NNLL and Approximate NNLL' (NNLL$^{'}_{a}$). We match these results to the corresponding fixed order calculations both at leading order and next-to-leading order for the $t\bar{t}$+jet production process, obtaining the most accurate prediction of the 0-jettiness distribution for the top-quark pair production process at NNLL$^{'}_{a}$+NLO accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Complex eigenvalue instantons and the Fredholm determinant expansion in the Gross-Witten-Wadia model

We study the leading nonperturbative corrections to the strong-coupling (ungapped) phase of the Gross-Witten-Wadia (GWW) integral over unitary matrices, to one-loop order. We compute these corrections directly in terms of eigenvalue tunneling in a holomorphic presentation of the integral over eigenvalues. The leading nonperturbative contribution to the partition function comes from a pair of complex eigenvalue instantons. We show that these are in fact “ghost instantons”, which are extrema of the one-eigenvalue effective potential on the “unphysical sheet” of the spectral curve and have been discussed in detail recently by Mariño, Schiappa, and Schwick. Further, we discuss the relationship of these instantons to the Fredholm determinant expansion of the unitary matrix integral, which has recently become an object of interest in the computations of BPS indices of supersymmetric gauge theories and black holes. We find that, after taking the ’t Hooft limit, the first correction given by the Fredholm determinant expansion of the GWW integral agrees precisely with the leading nonperturbative correction, to one-loop order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integrable field theories and their CCFT duals

We compute the Mellin transforms of various two-dimensional integrable S-matrices, providing the first explicit, non-perturbative realizations of celestial CFT. In two dimensions, the Mellin transform is simply the Fourier transform in rapidity space, and the “celestial correlator” has no position dependence. The simplified setting allows us to study the analytic properties of CCFT correlators exactly as a function of the conformal dimensions. We find that the correlators exist as real distributions of the conformal weights, with asymptotics controlled by the mass spectrum and three-point couplings of the model. Coupling these models to a flat space limit of JT gravity preserves integrability and dresses the amplitudes by a rapidly varying gravitational phase. We find that the coupling to gravity smooths out certain singular aspects of the Mellin-transformed correlators.

2D Gravity↗

The geometry of the modular bootstrap

Abstract We explore the geometry behind the modular bootstrap and its image in the space of Taylor coefficients of the torus partition function. In the first part, we identify the geometry as an intersection of planes with the convex hull of moment curves onR + ⊗ℤ, with boundaries characterized by the total positivity of generalized Hankel matrices. We phrase the Hankel constraints as a semi-definite program, which has several advantages, such as the validity of bounds irrespective of spin truncation. We derive bounds on the gap, twist-gap, and the space of Taylor coefficients themselves. We find that if the gap is above$$ {\Delta }_{\textrm{gap}}^{\ast } $$ ∆ gap ∗ , where$$ \frac{c-1}{12}<{\Delta}_{\textrm{gap}}^{\ast }<\frac{c}{12} $$ c − 1 12 < Δ gap ∗ < c 12 , all coefficients become bounded on both sides and kinks develop in the space. In the second part, we propose an analytic method of imposing the integrality condition for the degeneracy number in the spinless bootstrap, which leads to a non-convex geometry. We find that even at very low derivative order this condition rules out regions otherwise allowed by bootstraps at high derivative order.

Physics↗