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The tailored coupled cluster (TCC) approach is a promising ansatz that preserves the simplicity of single-reference coupled cluster theory, while incorporating a multi-reference wave function through amplitudes obtained from a preceding…

Chemical Physics · Physics 2021-01-07 Maximilian Mörchen , Leon Freitag , Markus Reiher

Causal discovery with time series data remains a challenging yet increasingly important task across many scientific domains. Convergent cross mapping (CCM) and related methods have been proposed to study time series that are generated by…

Machine Learning · Computer Science 2025-06-25 Kurt Butler , Daniel Waxman , Petar M. Djurić

Quantum-selected configuration interaction (QSCI) has emerged as a feasible approach for approximating electronic ground states on noisy quantum devices toward large-system demonstrations. In QSCI, Slater determinants are sampled from a…

Quantum Physics · Physics 2026-04-14 Ryota Kemmoku , Qi Gao , Shu Kanno , Kimberlee Keithley , Ikko Hamamura , Naoki Yamamoto , Kouhei Nakaji

The configuration interaction (CI) is a versatile wavefunction theory for interacting fermions but it involves an extremely long CI series. Using a symmetric tensor decomposition (STD) method, we convert the CI series into a compact and…

Chemical Physics · Physics 2013-05-30 Wataru Uemura , Osamu Sugino

Finding the ground-state energy of molecules is an important and challenging computational problem for which quantum computing can potentially find efficient solutions. The variational quantum eigensolver (VQE) is a quantum algorithm that…

Quantum Physics · Physics 2023-02-15 Daniel Yoffe , Amir Natan , Adi Makmal

Addressing both dynamic and static correlation accurately is a primary goal in electronic structure theory. Non-orthogonal configuration interaction (NOCI) is a versatile tool for treating static correlation, offering chemical insights by…

Chemical Physics · Physics 2025-06-27 Chong Sun , Fei Gao , Gustavo E. Scuseria

A deep-learning approach to optimize the selection of Slater determinants in configuration interaction calculations for condensed-matter quantum many-body systems is developed. We exemplify our algorithm on the discrete version of the…

Strongly Correlated Electrons · Physics 2025-02-11 Pavlo Bilous , Louis Thirion , Henri Menke , Maurits W. Haverkort , Adriana Pálffy , Philipp Hansmann

Finding statistically significant high-order interaction features in predictive modeling is important but challenging task. The difficulty lies in the fact that, for a recent applications with high-dimensional covariates, the number of…

Machine Learning · Statistics 2015-06-29 S. Suzumura , K. Nakagawa , K. Tsuda , I. Takeuchi

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has…

Materials Science · Physics 2026-04-01 Jacob Jeffries , Bochuan Sun , Enrique Martinez

We investigate the performance of a class of compact and systematically improvable Jastrow-Slater wave functions for the efficient and accurate computation of structural properties, where the determinantal component is expanded with a…

Chemical Physics · Physics 2019-01-17 Monika Dash , Saverio Moroni , Anthony Scemama , Claudia Filippi

An accurate description of electron correlation is one of the most challenging problems in quantum chemistry. The exact electron correlation can be obtained by means of full configuration interaction (FCI). A simple strategy for…

Chemical Physics · Physics 2021-05-14 Jae Woo Park

The efficiency of the recently proposed iCIPT2 [iterative configuration interaction (iCI) with selection and second-order perturbation theory (PT2); J. Chem. Theory Comput. 16, 2296 (2020)] for strongly correlated electrons is further…

Chemical Physics · Physics 2020-11-19 Ning Zhang , Wenjian Liu , Mark R. Hoffmann

We propose Selective Multiple Power Iterations (SMPI), a new algorithm to address the important Tensor PCA problem that consists in recovering a spike $\bf{v_0}^{\otimes k}$ corrupted by a Gaussian noise tensor $\bf{Z} \in…

Machine Learning · Computer Science 2021-12-24 Mohamed Ouerfelli , Mohamed Tamaazousti , Vincent Rivasseau

Incremental full configuration interaction (iFCI) closely approximates the FCI limit with polynomial cost through a many-body expansion of the correlation energy, providing highly accurate total energies within a given basis set. To extend…

Chemical Physics · Physics 2025-02-26 Jeffrey Hatch , Paul M. Zimmerman

In this work we propose a novel approach to solve the Schr\"{o}dinger equation which combines projection onto the ground state with a path-filtering truncation scheme. The resulting projector configuration interaction (PCI) approach…

Chemical Physics · Physics 2016-06-29 Tianyuan Zhang , Francesco A. Evangelista

We propose a novel partitioning of the Hilbert space, hierarchy configuration interaction (hCI), where the excitation degree (with respect to a given reference determinant) and the seniority number (i.e., the number of unpaired electrons)…

Chemical Physics · Physics 2022-05-12 Fábris Kossoski , Yann Damour , Pierre-François Loos

We present an approach to combining selected configuration interaction (SCI) and initiator full configuration interaction quantum Monte Carlo (i-FCIQMC). In the current i-FCIQMC scheme, the space of initiators is chosen dynamically by a…

Chemical Physics · Physics 2019-11-15 Nick S. Blunt

We present a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian by proposing an adaptive construction of a quantum state for the quantum-selected configuration interaction…

Quantum Physics · Physics 2024-12-12 Yuya O. Nakagawa , Masahiko Kamoshita , Wataru Mizukami , Shotaro Sudo , Yu-ya Ohnishi

Variable selection for optimal treatment regime in a clinical trial or an observational study is getting more attention. Most existing variable selection techniques focused on selecting variables that are important for prediction, therefore…

Methodology · Statistics 2014-05-22 Ailin Fan , Wenbin Lu , Rui Song

Conventional clustering methods based on pairwise affinity usually suffer from the concentration effect while processing huge dimensional features yet low sample sizes data, resulting in inaccuracy to encode the sample proximity and…

Machine Learning · Computer Science 2023-02-06 Hongmin Cai , Fei Qi , Junyu Li , Yu Hu , Yue Zhang , Yiu-ming Cheung , Bin Hu