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The adaptive derivative-assembled pseudo-trotter variational quantum eigensolver (ADAPT-VQE) is a promising hybrid quantum-classical algorithm for molecular ground state energy calculation, yet its practical scalability is hampered by…

Quantum Physics · Physics 2026-02-05 Runhong He , Xin Hong , Qiaozhen Chai , Ji Guan , Junyuan Zhou , Arapat Ablimit , Guolong Cui , Shenggang Ying

Approximate Bayesian computation (ABC) using a sequential Monte Carlo method provides a comprehensive platform for parameter estimation, model selection and sensitivity analysis in differential equations. However, this method, like other…

Machine Learning · Statistics 2015-07-21 Sanmitra Ghosh , Srinandan Dasmahapatra , Koushik Maharatna

We introduce a novel extrapolation algorithm inspired by quantum mechanics and evaluate its performance against linear prediction. Our method involves mapping function values onto a quantum state and estimating future function values by…

Quantum Physics · Physics 2023-10-13 Lambert Lin , Steven R White

The ability of quantum computers to overcome the exponential memory scaling of many-body problems is expected to transform quantum chemistry. Quantum algorithms require accurate representations of electronic states on a quantum device, but…

Chemical Physics · Physics 2024-04-26 Hugh G. A. Burton

Basis set convergence of the Hartree-Fock and the correlation energy is examined for the hydrogen bonded infinite bent chains (HF)_infinity and (HCl)_infinity. We employ series of correlation consistent basis sets up to quintuple zeta…

Other Condensed Matter · Physics 2007-05-23 Christian Buth , Beate Paulus

This paper proposes an alternative algorithm for multichannel variational autoencoder (MVAE), a recently proposed multichannel source separation approach. While MVAE is notable in its impressive source separation performance, the…

Machine Learning · Computer Science 2019-02-14 Li Li , Hirokazu Kameoka , Shoji Makino

Quantum correlations that typically develop between a quantum battery and its charger reduce the amount of work extractable from the battery. We show that by coupling the system with an additional environment that can be continuously…

Quantum Physics · Physics 2025-12-08 Gabriele Cenedese , Giuliano Benenti , Dario Ferraro , Marco G. Genoni

Gaussian process regression has recently emerged as a powerful, system-agnostic tool for building global potential energy surfaces (PES) of polyatomic molecules. While the accuracy of GP models of PES increases with the number of potential…

Chemical Physics · Physics 2019-07-23 Jun Dai , Roman V. Krems

The random-phase approximation (RPA) formulated within the adiabatic connection fluctuation-dissipation framework is a powerful approach to compute the ground-state energies and properties of molecules and materials. Its overall…

Chemical Physics · Physics 2025-05-13 Muhammad N. Tahir , Honghui Shang , Xinguo Ren

We report a new implementation of multireference algebraic diagrammatic construction theory (MR-ADC) for simulations of electron attachment and ionization in strongly correlated molecular systems (EA/IP-MR-ADC). Following our recent work on…

Chemical Physics · Physics 2021-01-19 Koushik Chatterjee , Alexander Yu. Sokolov

In 2009, our group pioneered a novel method CBTOPE for predicting conformational B-cell epitopes in a protein from its amino acid sequence, which received extensive citations from the scientific community. In a recent study, Cia et al.…

Biomolecules · Quantitative Biology 2025-06-17 Anupma Pandey , Megha , Nishant Kumar , Ruchir Sahni , Gajendra P. S. Raghava

In order to leverage the information embedded in the background state and observations, covariance matrices modelling is a pivotal point in data assimilation algorithms. These matrices are often estimated from an ensemble of observations or…

Methodology · Statistics 2019-10-22 Sibo Cheng , Jean-Philippe Argaud , Bertrand Iooss , Didier Lucor , Angélique Ponçot

We investigate the use of orbital-optimized references in conjunction with single-reference coupled-cluster theory with single and double substitutions (CCSD) for the study of core excitations and ionizations of 18 small organic molecules,…

Precise theoretical calculations of open-shell atomic systems are critical for extracting fundamental physics parameters from precision experiments. Here we present proof-of-principle calculations illustrating the effectiveness of the…

Atomic Physics · Physics 2022-12-19 G. Tenkila , V. Chand , T. Miyagi , H. Patel , S. R. Stroberg , R. F. Garcia Ruiz , J. D. Holt

Extrapolation from a source to a target, e.g., from adults to children, is a promising approach to utilizing external information when data are sparse. In the context of meta-analysis, one is commonly faced with a small number of studies,…

Methodology · Statistics 2019-01-21 Christian Röver , Simon Wandel , Tim Friede

We describe CPMC-Lab, a Matlab program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to…

Strongly Correlated Electrons · Physics 2014-10-14 Huy Nguyen , Hao Shi , Jie Xu , Shiwei Zhang

We present a practical workflow to compute the potential energy curve of the hydrogen molecule on near intermediate-scale quantum (NISQ) devices. The proposed approach uses an extrapolation scheme to deliver, with only few qubits, full…

Chemical Physics · Physics 2022-09-23 Ryan Ward , David M. Benoit , Francesco Benfenati

The direct random-phase approximation (dRPA) is used to calculate and compare atomization energies for the HEAT set and 10 selected molecules of the G2-1 set using both plane waves and Gaussian-type orbitals. We describe detailed procedures…

Meaningful predictions for electric quadrupole (E2) observables from ab initio nuclear theory are necessary, if the ab initio description of collective correlations is to be confronted with experiment, as well as to provide predictive power…

Nuclear Theory · Physics 2022-06-23 Mark A. Caprio , Patrick J. Fasano , Pieter Maris

The Bethe-Salpeter Equation (BSE) is the workhorse method to study excitons in materials. The BSE Hamiltonian size, which depends on how many valence-to-conduction band transitions are considered, needs to be chosen to be sufficiently large…

Materials Science · Physics 2025-10-20 Rafael R. Del Grande , David A. Strubbe