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Related papers: Linear Response Selected Configuration Interaction

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This paper presents an ellipsoidal set-theoretic framework for robust safety filter synthesis in constrained linear systems subject to additive bounded disturbances and input constraints. We formulate the safety filter design as a convex…

Systems and Control · Electrical Eng. & Systems 2025-10-28 Reza Pordal , Alireza Sharifi , Ali Baniasad

Reinforcement learning (RL) with combinatorial action spaces remains challenging because feasible action sets are exponentially large and governed by complex feasibility constraints, making direct policy parameterization impractical.…

Machine Learning · Computer Science 2026-02-02 Lingkai Kong , Anagha Satish , Hezi Jiang , Akseli Kangaslahti , Andrew Ma , Wenbo Chen , Mingxiao Song , Lily Xu , Milind Tambe

Hierarchy configuration interaction (hCI) has been recently introduced as an alternative configuration interaction (CI) route combining excitation degree and seniority number, which showed to efficiently recover both dynamic and static…

Chemical Physics · Physics 2024-02-20 Fábris Kossoski , Pierre-François Loos

The most essential concept in concurrent multiscale methods involving atomistic-continuum coupling is how to define the relation between atomistic and continuum regions. A well-known coupling method that has been frequently employed in…

Mesoscale and Nanoscale Physics · Physics 2022-07-27 Pouya Towhidi , Manouchehr Salehi

We introduce SIRI, Scaling Iterative Reinforcement Learning with Interleaved Compression, a simple yet effective RL approach for Large Reasoning Models (LRMs) that enables more efficient and accurate reasoning. Existing studies have…

Machine Learning · Computer Science 2025-09-30 Haoming Wen , Yushi Bai , Juanzi Li , Jie Tang

To achieve higher throughput in next-generation Wi-Fi systems, a station (STA) needs to efficiently compress channel state information (CSI) and feed it back to an access point (AP). In this paper, we propose a novel deep learning…

Signal Processing · Electrical Eng. & Systems 2025-07-16 Junyong Shin , Eunsung Jeon , Inhyoung Kim , Yo-Seb Jeon

A power constrained sensor network that consists of multiple sensor nodes and a fusion center (FC) is considered, where the goal is to estimate a random parameter of interest. In contrast to the distributed framework, the sensor nodes may…

Information Theory · Computer Science 2012-07-03 Swarnendu Kar , Pramod K. Varshney

[Background] Single-reference density functional theory is very successful in reproducing bulk nuclear properties like binding energies, radii, or quadrupole moments throughout the entire periodic table. Its extension to the multi-reference…

Nuclear Theory · Physics 2017-01-30 W. Satula , P. Baczyk , J. Dobaczewski , M. Konieczka

We present a fully variational locally scaled self-interaction corrected (SIC) energy functional using complex optimal orbitals. This represents an important milestone for fully variational SIC energy functionals, which have been shown to…

The configuration interaction relativistic Hartree-Fock (CI-RHF) model is developed in this work. Compared to the conventional configuration interaction shell model (CISM), the CI-RHF model can be applied to study the structural properties…

Nuclear Theory · Physics 2025-04-14 Jia Liu , Yi Fei Niu , Wen Hui Long

Following our recent work on the benzene molecule [\href{https://doi.org/10.1063/5.0027617}{J.~Chem.~Phys.~\textbf{153}, 176101 (2020)}], itself motivated by the blind challenge of Eriksen \textit{et al.}…

\textsc{Quantum Package} is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods…

Neural networks are predominantly trained using gradient-based methods, yet in many applications their final predictions remain far from the accuracy attainable within the model's expressive capacity. We introduce Linearized Subspace…

Machine Learning · Computer Science 2026-01-21 Wenbo Cao , Weiwei Zhang

The computationally expensive evaluation and storage of high-rank reduced density matrices (RDMs) has been the bottleneck in the calculation of dynamic correlation for multireference wave functions in large active spaces. We present a…

Chemical Physics · Physics 2020-01-08 Ankit Mahajan , Nick S. Blunt , Iliya Sabzevari , Sandeep Sharma

A new method to calculate spectroscopic properties of deformed nuclei is proposed: configuration interaction on top of projected density functional theory (CI-PDFT). The general concept of this approach is discussed in the framework of…

Nuclear Theory · Physics 2016-10-12 P. W. Zhao , P. Ring , J. Meng

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

We present a data-driven method to synthesize robust control invariant (RCI) sets for linear parameter-varying (LPV) systems subject to unknown but bounded disturbances. A finite-length data set consisting of state, input, and scheduling…

Systems and Control · Electrical Eng. & Systems 2023-09-14 Manas Mejari , Sampath Kumar Mulagaleti , Alberto Bemporad

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

The recently developed semistochastic heat-bath configuration interaction (SHCI) method is a systematically improvable selected configuration interaction plus perturbation theory method capable of giving essentially exact energies for…

Chemical Physics · Physics 2020-10-01 Yuan Yao , Emmanuel Giner , Junhao Li , Julien Toulouse , C. J. Umrigar

Reliably characterizing the full conditional distribution of a multivariate response variable given a set of covariates is crucial for trustworthy decision-making. However, misspecified or miscalibrated multivariate models may yield a poor…

Machine Learning · Computer Science 2025-10-27 Victor Dheur , Souhaib Ben Taieb