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QED as a many-body theory of worldlines: General formalism and infrared structure
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QED as a many-body theory of worldlines. II. All-order S -matrix formalism
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Convolution formalism for defining densities of hadrons
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One loop reduced QED for massive fermions within an innovative formalism
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Constraining cosmological parameters with needlet internal linear combination maps. I. Analytic power spectrum formalism
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High-throughput determination of Hubbard $U$ and Hund $J$ values for transition metal oxides via the linear response formalism
DFT+U provides a convenient, cost-effective correction for the self-interaction error (SIE) that arises when describing correlated electronic states using conventional approximate density functional theory (DFT). The success of a DFT+U(+J) calculation hinges on the accurate determination of its Hubbard U and Hund J parameters, and the linear response (LR) methodology has proven to be computationally effective and accurate for calculating these parameters. This study provides a high-throughput computational analysis of the U and J values for transition metal d-electron states in a representative set of over 1000 magnetic transition metal oxides (TMOs), providing a frame of reference for researchers who use DFT+U to study transition metal oxides. In order to perform this high-throughput study, an ATOMATE workflow is developed for calculating U and J values automatically on massively parallel supercomputing architectures. Here, to demonstrate an application of this workflow, the spin-canting magnetic structure and unit cell parameters of the multiferroic olivine LiNiPO4 are calculated using the computed Hubbard U and Hund J values for Ni-d and O-p states, and are compared with experiment. Both the Ni-d U and J corrections have a strong effect on the Ni-moment canting angle. Additionally, including a O-pU value results in a significantly improved agreement between the computed lattice parameters and experiment
Crystallographic map: A general lattice and basis formalism enabling efficient and discretized exploration of crystallographic phase space
Three-dimensional lattices are fundamental to solid-state physics. The description of a lattice with an atomic basis constitutes the necessary information to predict solid phase properties and evolution. Here, we present an algorithm for systematically exploring crystallographic phase space. Further, coupled with ab initio techniques, such as density functional theory, this algorithm offers an approach for exploring and tuning materials behavior, with a broad range of potential applications: particularly martensitic phase transformations and materials stability.
Qubit-Oscillator Concatenated Codes: Decoding Formalism and Code Comparison
Concatenating bosonic error-correcting codes with qubit codes can substantially boost the errorcorrecting power of the original qubit codes. It is not clear how to concatenate optimally, given that there are several bosonic codes and concatenation schemes to choose from, including the recently discovered Gottesman-Kitaev-Preskill (GKP) – stabilizer codes [Phys. Rev. Lett. 125, 080503 (2020)] that allow protection of a logical bosonic mode from fluctuations of the conjugate variables of the mode. We develop efficient maximum-likelihood decoders for and analyze the performance of three different concatenations of codes taken from the following set: qubit stabilizer codes, analog or Gaussian stabilizer codes, GKP codes, and GKP-stabilizer codes. We benchmark decoder performance against additive Gaussian white noise, corroborating our numerics with analytical calculations. We observe that the concatenation involving GKP-stabilizer codes outperforms the more conventional concatenation of a qubit stabilizer code with a GKP code in some cases. We also propose a GKP-stabilizer code that suppresses fluctuations in both conjugate variables without extra quadrature squeezing and formulate qudit versions of GKP-stabilizer codes.
Dispersive and nondispersive 𝐾-matrix formalisms
The modeling of coupled-channel effects has become increasingly important due to the availability of highly precise data for a large variety of hadronic (re)scattering processes. The 𝐾-matrix is a powerful, yet comparatively simple, method to describe scattering amplitudes, including coupled-channel effects, with the aim of interpreting experimental data. Throughout the literature, a range of dispersive and nondispersive 𝐾-matrix methods are employed. Here, we compare the dispersive and nondispersive formulations in the context of the N/D method. It is shown that the methods are equivalent in the physical region under 𝐾-matrix reparametrization. Differences away from the physical region are examined. Applications to synthetic data are used to illustrate the effects of model choices concerning form factors and the application of dispersion relations, with the goal of clarifying best practices. We find no clear preference with regard to dispersive modeling. In contrast, we find that interpretational ambiguity of the bare model parameters—and even of the form of the bare model—is endemic, and recommend a thorough sampling of data and model spaces to assess conclusion robustness.
Illustrated formalisms for total scattering data: a guide for new practitioners
The total scattering method is the simultaneous study of both the real- and reciprocal-space representations of diffraction data. While conventional Bragg-scattering analysis (employing methods such as Rietveld refinement) provides insight into the average structure of the material, pair distribution function (PDF) analysis allows for a more focused study of the local atomic arrangement of a material. Generically speaking, a PDF is generated by Fourier transforming the total measured reciprocal-space diffraction data (Bragg and diffuse) into a real-space representation. However, the details of the transformation employed and, by consequence, the resultant appearance and weighting of the real-space representation of the system can vary between different research communities. As the worldwide total scattering community continues to grow, these subtle differences in nomenclature and data representation have led to conflicting and confusing descriptions of how the PDF is defined and calculated. This paper provides a consistent derivation of many of these different forms of the PDF and the transformations required to bridge between them. Some general considerations and advice for total scattering practitioners in selecting and defining the appropriate choice of PDF in their own research are presented. This contribution aims to benefit people starting in the field or trying to compare their results with those of other researchers.
Illustrated formalisms for total scattering data: a guide for new practitioners. Corrigendum and addendum
Errors and ambiguities in the article by Peterson, Olds, McDonnell & Page [ J. Appl. Cryst. (2021), 54 , 317–332] are corrected and clarified, respectively.
SYCL for Performance Portability: Application Experience with Coupled Cluster Formalism in Quantum Chemistry on Exascale Systems
The exascale computing has brought unprecedented heterogeneity in node architectures, with systems such as Frontier and Aurora featuring diverse GPU accelerators, network connectivity among others. Ensuring performance portability across these platforms is a key challenge. To address this, we employ the SYCL programming model to develop portable, high-performance quantum chemistry workloads. As a representative application, we focus on the non-iterative Triples component of the coupled-cluster CCSD(T) method, a key driver in quantum chemistry. In this work, we report on our experience deploying SYCL-based implementations using both DPC++ and AdaptiveCPP across two flagship exascale platforms: OLCF Frontier with AMD MI250X GPUs and ALCF Aurora with Intel GPUs. Our results demonstrate that SYCL enables efficient, single-source implementations that scale to thousands of nodes, delivering performance on par with vendor-optimized HIP solutions. We highlight key insights into runtime behavior, kernel portability, and scaling characteristics, showing that SYCL offers a viable path for performance-portable computing.
Formal methods approach to the charging facility location problem for battery electric vehicles
Battery electric vehicles (BEVs) are becoming more prevalent as improvements in battery technology and energy management continue to be made. As the number of electric vehicles grows, the demand for fast-charging stations is expected to increase dramatically. Thus, building new charging station infrastructure efficiently will be key to reducing upfront costs while meeting consumer demands. In this work, we propose a method for choosing a set of charging station locations that are optimized based on a set of given common vehicle demand points. As part of this solution, we also offer a novel abstraction of the road network on which energy-efficient paths that account for charge-time delays may be found. The current algorithm chooses the optimal charging locations for a single agent which has a route objective specified using temporal logic. To demonstrate the proposed method, the running example shows how a charging station could be chosen for an electric delivery vehicle. Simulations were run on sample road networks with a given set of demand points to service and potential charging station locations to compare. The method is shown to successfully rank potential charging stations in terms of their expected average charging time cost.
A Case Study in the Formal Modeling of Safe and Secure Manufacturing Automation
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A systematic decision-making methodology to formalize the selection of degree of realism in screening analysis of probabilistic risk assessment
In the nuclear power domain, Probabilistic Risk Assessment (PRA) is used to inform decision-making for Nuclear Power Plants (NPPs). Recently, there has been an increase in the utilization of modeling and simulation (M&S) to support the estimation of PRA inputs. Risk analysts should carefully select the PRA items that require M&S and their degree of realism (DoR) with consideration of the required resources. To support this selection, this article formulates a systematic decision-making approach for the DoR selection. The DoR selection is made based on two predictive decision-making attributes: the predicted differences in safety risk estimate (ΔSaRi) and the cost of analysis (ΔCAN). This research also develops and quantifies causal models to estimate ΔSaRi and ΔCAN. The causal model-based prediction of ΔSaRi and ΔCAN helps reduce the trial-and-error nature of the DoR selection in the PRA screening analysis and provides insights for DoR selection and the gradual refinements of PRA realism. This approach is demonstrated for a case study on fire PRA of NPPs, where an adequate DoR is selected from two fire models: an engineering correlation and a zone model.
Ensuring completeness of formal verification with Gap Free Verification.
Abstract not provided.
Tackling DIS Region Using Spectral Function Formalism
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