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Quantum chemistry calculations of large, strongly correlated systems are typically limited by the computation cost that scales exponentially with the size of the system. Quantum algorithms, designed specifically for quantum computers, can…

The molecular polarizability describes the tendency of a molecule to deform or polarize in response to an applied electric field. As such, this quantity governs key intra- and inter-molecular interactions such as induction and dispersion,…

Chemical Physics · Physics 2025-10-06 David M. Wilkins , Andrea Grisafi , Yang Yang , Ka Un Lao , Robert A. DiStasio , Michele Ceriotti

Non-unitary theories are commonly seen in the classical simulations of quantum systems. Among these theories, the method of moments of coupled-cluster equations (MMCCs) and the ensuing classes of the renormalized coupled-cluster (CC)…

Quantum Physics · Physics 2022-12-13 Bo Peng , Karol Kowalski

A size-extensive, converging, black-box, ab initio coupled-cluster ($\Delta$CC) ansatz is introduced that computes the energies and wave functions of stationary states from any degenerate or nondegenerate Slater-determinant references with…

Chemical Physics · Physics 2026-05-15 So Hirata

We extend our assessment of the potential of perturbative coupled cluster (CC) expansions for a test set of open-shell atoms and organic radicals to the description of quadruple excitations. Namely, the second- through sixth-order models of…

Chemical Physics · Physics 2016-05-17 Janus J. Eriksen , Devin A. Matthews , Poul Jørgensen , Jürgen Gauss

Simulating liquid water to an accuracy that matches its wealth of available experimental data requires both precise electronic structure methods and reliable sampling of nuclear (quantum) motion. This is challenging because applying the…

We use very large cosmological N--body simulations to obtain accurate predictions for the two-point correlations and power spectra of mass-limited samples of galaxy clusters. We consider two currently popular cold dark matter (CDM)…

In this tutorial-style review we discuss basic concepts of coupled cluster theory and recent developments that increase its computational efficiency for calculations of molecules, solids and materials in general. We will touch upon the…

Materials Science · Physics 2020-04-15 Igor Ying Zhang , Andreas Grüneis

The equation of motion coupled cluster singles and doubles model (EOM-CCSD) is an accurate, black-box correlated electronic structure approach to investigate electronically excited states and electron attachment or detachment processes. It…

Chemical Physics · Physics 2023-09-18 Loïc Halbert , Andre Severo Pereira Gomes

In truncated coupled-cluster (CC) theories, non-variational and/or generally complex ground-state energies can occur. This is due to the non-Hermitian nature of the similarity transformed Hamiltonian matrix in combination with CC…

Chemical Physics · Physics 2023-09-22 Tanner Culpitt , Erik I. Tellgren , Fabijan Pavosevic

In this work, we derive working equations for the Linear Response pair Coupled Cluster Doubles (LR-pCCD) ansatz and its extension to singles (S), LR-pCCD+S. These methods allow us to compute electronic excitation energies and transition…

Chemical Physics · Physics 2025-03-18 Somayeh Ahmadkhani , Katharina Boguslawsk , Paweł Tecmer

We recently proposed a novel approach to converging electronic energies equivalent to high-level coupled-cluster (CC) computations by combining the deterministic CC($P$;$Q$) formalism with the stochastic configuration interaction (CI) and…

Chemical Physics · Physics 2021-03-23 J. Emiliano Deustua , Jun Shen , Piotr Piecuch

We present an embedding approach to treat local electron correlation effects in periodic environments. In a single, consistent framework, our plane-wave based scheme embeds a local high-level correlation calculation (here Coupled Cluster…

Chemical Physics · Physics 2021-01-07 Tobias Schäfer , Florian Libisch , Georg Kresse , Andreas Grüneis

We present the data-driven coupled-cluster deep network (DDCCNet), a family of multitask, physics-enhanced deep learning architectures designed to predict coupled-cluster singles and doubles (CCSD) amplitudes and correlation energies from…

Chemical Physics · Physics 2026-02-03 P. D. Varuna S. Pathirage , Konstantinos D. Vogiatzis

Arguably the most widely used approaches for obtaining highly accurate molecular ground-state energies are coupled cluster methods. Despite introducing two layers of approximation, a linear and a nonlinear one, coupled cluster methods…

Numerical Analysis · Mathematics 2026-05-22 Jonas Beck , Benjamin Stamm

We investigate Machine-Learned Force Fields (MLFFs) trained on approximate Density Functional Theory (DFT) and Coupled Cluster (CC) level potential energy surfaces for the carbon diamond and lithium hydride solids. We assess the accuracy…

A novel approach to rapidly converging high-level coupled-cluster (CC) energetics in an automated fashion is proposed. The key idea is an adaptive selection of the excitation manifolds defining higher-than-two-body components of the cluster…

Chemical Physics · Physics 2023-08-25 Karthik Gururangan , Piotr Piecuch

Machine learning (ML) plays an important role in quantum chemistry, providing fast-to-evaluate predictive models for various properties of molecules. However, most existing ML models for molecular electronic properties use density…

Chemical Physics · Physics 2024-06-26 Hao Tang , Brian Xiao , Wenhao He , Pero Subasic , Avetik R. Harutyunyan , Yao Wang , Fang Liu , Haowei Xu , Ju Li

We present an implementation of equation of motion coupled-cluster singles and doubles (EOM-CCSD) theory using periodic boundary conditions and a plane wave basis set. Our implementation of EOM-CCSD theory is applied to study $F$-centers in…

Materials Science · Physics 2021-02-09 Alejandro Gallo , Felix Hummel , Andreas Irmler , Andreas Grüneis

The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel, and predictive structure-property…