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The Multilevel Monte Carlo (MLMC) method has proven to be an effective variance-reduction statistical method for Uncertainty Quantification (UQ) in Partial Differential Equation (PDE) models, combining model computations at different levels…

Mathematical Software · Computer Science 2023-05-24 Santiago Badia , Jerrad Hampton , Javier Principe

Realizing large-scale quantum advantage is expected to require quantum error correction (QEC), making the compilation and optimization of logical operations a critical area of research. Logical computation imposes distinct constraints and…

Similarity transformation of the Hubbard Hamiltonian using a Gutzwiller correlator leads to a non-Hermitian effective Hamiltonian, which can be expressed exactly in momentum-space representation, and contains three-body interactions. We…

Strongly Correlated Electrons · Physics 2019-08-12 Werner Dobrautz , Hongjun Luo , Ali Alavi

Quantum Monte Carlo (QMC) is a stochastic method which has been particularly successful for ground-state electronic structure calculations but mostly unexplored for the computation of excited-state energies. Here, we show that, within a…

Chemical Physics · Physics 2018-08-09 Anthony Scemama , Anouar Benali , Denis Jacquemin , Michel Caffarel , Pierre-François Loos

Quantum computers are special purpose machines that are expected to be particularly useful in simulating strongly correlated chemical systems. The quantum computer excels at treating a moderate number of orbitals within an active space in a…

In this study, we evaluate multi-configurational trial wave function protocols for phaseless auxiliary field quantum Monte Carlo (ph-AFQMC) on transition metal containing systems. First, we benchmark vertical ionization potentials for 22 3d…

Certain point defects in solids can efficiently be used as qubits for applications in quantum technology. They have spin states that are initializable, readable, robust, and can be manipulated optically. New theoretical methods are needed…

Computational Physics · Physics 2023-09-20 Kristoffer Simula , Ilja Makkonen

We consider the problem of improving the efficiency of randomized Fourier feature maps to accelerate training and testing speed of kernel methods on large datasets. These approximate feature maps arise as Monte Carlo approximations to…

Machine Learning · Statistics 2015-08-11 Haim Avron , Vikas Sindhwani , Jiyan Yang , Michael Mahoney

The nuclear-electronic orbital (NEO) approach incorporates nuclear quantum effects into quantum chemistry calculations by treating specified nuclei quantum mechanically, equivalently to the electrons. Within the NEO framework, excited…

Chemical Physics · Physics 2025-03-19 Christopher L. Malbon , Sharon Hammes-Schiffer

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and…

Computational Physics · Physics 2016-03-23 Hao Shi , Shiwei Zhang

We present efficient algorithms for using selected configuration interaction (sCI) trial wave functions in phaseless auxiliary field quantum Monte Carlo (ph-AFQMC). These advancements, geared towards optimizing computational performance for…

Chemical Physics · Physics 2022-05-18 Ankit Mahajan , Joonho Lee , Sandeep Sharma

Inspired by our earlier semi-stochastic work aimed at converging high-level coupled-cluster (CC) energetics [J. E. Deustua, J. Shen, and P. Piecuch, Phys. Rev. Lett. 119, 223003 (2017); J. Chem. Phys. 154, 124103 (2021)], we propose a novel…

Chemical Physics · Physics 2022-10-06 Karthik Gururangan , J. Emiliano Deustua , Jun Shen , Piotr Piecuch

We present a technique for optimizing hundreds of thousands of variational parameters in variational quantum Monte Carlo. By introducing iterative Krylov subspace solvers and by multiplying by the Hamiltonian and overlap matrices as they…

Strongly Correlated Electrons · Physics 2013-05-30 Eric Neuscamman , C. J. Umrigar , Garnet Kin-Lic Chan

One of the primary challenges in quantum chemistry is the accurate modeling of strong electron correlation. While multireference methods effectively capture such correlation, their steep scaling with system size prohibits their application…

Accurate computation of non-covalent, intermolecular interaction energies is important to understand various chemical phenomena, and quantum computers are anticipated to accelerate it. Although the state-of-the-art quantum computers are…

Quantum Physics · Physics 2025-12-29 Yuhei Tachi , Akihiko Arakawa , Taisei Osawa , Masayoshi Terabe , Kenji Sugisaki

Variational Quantum Circuits (VQC) are promising models for quantum machine learning, but standard monolithic architectures face an expressivity--trainability dilemma: small circuits can be under-parameterized, while larger circuits are…

Quantum Physics · Physics 2026-05-12 Howard Su , Chen-Yu Liu , Samuel Yen-Chi Chen , Kuan-Cheng Chen , Huan-Hsin Tseng

We show that the quasiparticle effective mass $M^*$ diverges as a function of the system's density $x$, $M^*\propto 1/(x-x_{FC})$, when a system approaches the critical point $x_{FC}$ at which the fermion condensation quantum phase…

Strongly Correlated Electrons · Physics 2007-05-23 V. R. Shaginyan

We propose a measurement-based FTQC (MB-FTQC) architecture for high-connectivity platforms such as trapped ions and neutral atoms. The key idea is to use verified logical ancillas combined with Knill's error-correcting teleportation,…

Quantum Physics · Physics 2025-12-10 Yohei Ibe , Yutaka Hirano , Yasuo Ozu , Toru Kawakubo , Keisuke Fujii

The combinatorial scaling of configuration interaction (CI) has long restricted its applicability to only the simplest molecular systems. Here, we report the first numerically exact CI calculation exceeding one quadrillion ($10^{15}$)…

Chemical Physics · Physics 2025-12-16 Agam Shayit , Can Liao , Shiv Upadhyay , Hang Hu , Tianyuan Zhang , Eugene DePrince , Chao Yang , Xiaosong Li

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation…