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For many quantum systems of interest, the classical computational cost of simulating their time evolution scales exponentially in the system size. At the same time, quantum computers have been shown to allow for simulations of some of these…

Quantum Physics · Physics 2023-01-25 Dorota M. Grabowska , Christopher Kane , Benjamin Nachman , Christian W. Bauer

Noncollinear (NC) magnetism and spin-orbit coupling (SOC) are indispensable for predictive ab initio materials simulations with pronounced relativistic effects and magnetic frustration, yet they significantly increase the cost of…

We study the entanglement entropy between (possibly distinct) topological phases across an interface using an Abelian Chern-Simons description with topological boundary conditions (TBCs) at the interface. From a microscopic point of view,…

Strongly Correlated Electrons · Physics 2017-11-09 Jackson R. Fliss , Xueda Wen , Onkar Parrikar , Chang-Tse Hsieh , Bo Han , Taylor L. Hughes , Robert G. Leigh

The Configuration Interaction (CI) method using orbitals centered on the nucleus has recently been applied to calculate the interactions of positrons interacting with atoms. Computational investigations of the convergence properties of…

Atomic Physics · Physics 2007-05-23 J. Mitroy , M. W. J. Bromley

An electrodynamical coupled cluster (CC) methodology starting from a covariant formalism and an equal time approximation, and finally based on the Dirac-Fock picture of the electron and positron fields and Coulomb gauge, is given here. The…

Atomic Physics · Physics 2019-04-30 Sambhu N. Datta

We study the low-energy physics of topological insulator (TI) nanoribbons proximity-coupled to s-wave superconductors (SCs) by explicitly incorporating the proximity effects that emerge at the TI-SC interface. We construct a low-energy…

Superconductivity · Physics 2014-07-24 Piyapong Sitthison , Tudor D. Stanescu

Nonlinear balanced truncation is a model order reduction technique that reduces the dimension of nonlinear systems in a manner that accounts for either open- or closed-loop observability and controllability aspects of the system. A…

Optimization and Control · Mathematics 2024-04-23 Boris Kramer , Serkan Gugercin , Jeff Borggaard , Linus Balicki

By using event-driven molecular dynamics simulation, we investigate effects of varying the area fraction of the smaller component on structure, compressibility factor and dynamics of the highly size-asymmetric binary hard-disk liquids. We…

Soft Condensed Matter · Physics 2015-06-05 Wen-Sheng Xu , Zhao-Yan Sun , Li-Jia An

Semi-local approximations to the density functional for the exchange-correlation energy of a many-electron system necessarily fail for lobed one-electron densities, including not only the familiar stretched densities but also the less…

In this paper, we improved the performance of the contrast source inversion (CSI) method by incorporating a so-called cross-correlated cost functional, which interrelates the state error and the data error in the measurement domain. The…

Signal Processing · Electrical Eng. & Systems 2019-06-27 Shilong Sun , Bert Jan Kooij , Tian Jin , Alexander G. Yarovoy

We develop a cubic scaling approach to excited-state-specific second order perturbation theory in which the completeness of a local correlation treatment is carefully matched between the ground and excited state. With this matching, the…

Chemical Physics · Physics 2025-05-14 Rachel Clune , Eric Neuscamman

We investigate the decay of spatial correlations of $\mathcal{PT}$-symmetric non-Hermitian one-dimensional models that host higher-order exceptional points. Beyond a certain correlation length, they develop anomalous power-law behavior that…

Mesoscale and Nanoscale Physics · Physics 2023-08-16 Doru Sticlet , Cătălin Paşcu Moca , Balázs Dóra

We study the convergence of a linear atomic cluster expansion (ACE) potential with respect to its basis functions, in terms of the effective two-body interactions of elemental Carbon and Silicon systems. We build ACE potentials with…

Computational Physics · Physics 2025-07-30 Apolinario Miguel Tan , Franco Pellegrini , Stefano de Gironcoli

Bipartite entanglement entropy of a segment with the length $l$ in $1+1$ dimensional conformal field theories (CFT) follows the formula $S=\frac{c}{3}\ln l+\gamma$, where $c$ is the central charge of the CFT and $\gamma$ is a cut-off…

High Energy Physics - Theory · Physics 2017-12-20 M. A. Rajabpour

Understanding the influence of dark energy on the formation of structures is currently a major challenge in Cosmology, since it can distinguish otherwise degenerated viable models. In this work we consider the Top-Hat Spherical-Collapse…

Cosmology and Nongalactic Astrophysics · Physics 2019-06-19 D. Herrera , I. Waga , S. E. Jorás

By performing a stochastic dynamic in a space of Slater determinants, the Full Configuration Interaction Quantum Monte Carlo (FCIQMC) method has been able to obtain energies which are essentially free from systematic error to the basis set…

Computational Physics · Physics 2014-10-10 George H. Booth , Deidre Cleland , Ali Alavi , David P. Tew

We extend our recently-developed heat-bath configuration interaction (HCI) algorithm, and our semistochastic algorithm for performing multireference perturbation theory, to the calculation of excited-state wavefunctions and energies. We…

Strongly Correlated Electrons · Physics 2017-11-22 Adam A. Holmes , C. J. Umrigar , Sandeep Sharma

The investigation of spatio-temporal couplings (STCs) of broadband light beams is becoming a key topic for the optimization as well as applications of ultrashort laser systems. This calls for accurate measurements of STCs. Yet, it is only…

Size extensivity, defined as the correct scaling of energy with system size, is a desirable property for any many-body method. Traditional CI methods are not size extensive hence the error increases as the system gets larger. Coupled…

Chemical Physics · Physics 2022-07-27 Vibin Abraham , Nicholas J. Mayhall

Compressive learning (CL) is an emerging framework that integrates signal acquisition via compressed sensing (CS) and machine learning for inference tasks directly on a small number of measurements. It can be a promising alternative to…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Chong Mou , Jian Zhang
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