Search arXivSearch

arXiv · 2503.10335

A Scalable Diagonalization Framework for Tensor-Product Bitstring Selected Configuration Interaction

Abstract

Selected configuration interaction (SCI) methods are effective for treating strongly correlated electronic systems, yet their scalability has long been limited by implementations that replicate the configuration interaction (CI) vector across processes, leading to severe memory bottlenecks. Here, we present a fully distributed diagonalization framework tailored for extremely large selected determinant spaces, directly addressing this major scalability bottleneck of modern SCI methods. The method is grounded in a tensor-product bitstring (TPB) representation, in which determinants are organized through a TPB structure constructed from selected alpha- and beta-bitstrings, and is referred to as tensor-product bitstring SCI (TBSCI). An efficient TBSCI eigensolver is developed based on a novel bitstring-based Hamiltonian evaluation algorithm together with a suite of MPI communication strategies designed to improve parallel efficiency. Large-scale full configuration interaction (FCI) benchmarks, employed as communication-intensive stress tests, demonstrate that the implemented TBSCI eigensolver continues to reduce the wall time for distributed diagonalization of 2.6 trillion determinants, reaching 54,000 nodes (more than 2.5 million cores) on supercomputer Fugaku. Beyond scalability, we investigate the structural compactness of the TPB representation and show that selecting alpha- and beta-bitstrings according to their collective weights in a reference SCI wavefunction yields TPB-based wavefunctions approaching the FCI limit while using only a small fraction of determinants. These results establish TBSCI as a scalable SCI methodology and provide evidence for the intrinsic compactness of the TPB representation.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Enhua Xu, William Dawson, Himadri Pathak, Takahito Nakajima. 2026-04-29. A Scalable Diagonalization Framework for Tensor-Product Bitstring Selected Configuration Interaction. https://doi.org/10.1063/5.0332736

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Intrinsic Matching Frustration in Fluctuating Finite Systems

We formulate intrinsic matching frustration (IMF), a fluctuation-induced, kinetics-independent reduction in the mean capacity permitted by a prescribed matching rule. For complementary one-to-one matching, the instantaneous capacity is set by the minority population, so fluctuations produce a nonzero mean deficit even when the two populations are balanced on average. At finite size, this deficit depends on the full distribution of the population difference and is determined by its variance alone only in the Gaussian limit. Compartmentalization hides matching capacity by preventing cancellation between local imbalances of opposite sign. Fusion releases this hidden capacity monotonically under coarse graining, producing a measurable recovery of product yield following local reaction to completion.

physics.chem-ph

Phonon chirality as an additive control of CISS: a symmetry-protected law

Chirality-induced spin selectivity (CISS) is usually associated with molecular handedness. The possible contribution of chiral phonons is less established. We study a helical tight-binding model in which local phonon angular momentum modulates spin-dependent nearest-neighbor hopping. Fewest-switches surface hopping calculations give the transmitted spin polarization $\mathrm{SP}=aC+b\mathrm{PH}$. Here $C$ is the molecular chirality and $\mathrm{PH}$ is the phonon chirality. A mirror symmetry reverses $C$, $\mathrm{PH}$, and $\mathrm{SP}$ simultaneously. This symmetry excludes both a chirality-independent offset and a $C\cdot\mathrm{PH}$ term. The phonon contribution can therefore enhance, cancel, or reverse the molecular CISS signal.

physics.chem-ph

A fast physics-based matrix model for the impedance of a PEM fuel cell: Incorporating functionally graded catalyst layer and channel impedances

We extend a recent physics-based matrix model for calculating PEM fuel cell impedance (doi:10.1149/2754-2734/ad6ce8) to cases of low air flow stoichiometry and functionally graded cathode catalyst layers (CCLs). We demonstrate that the matrix model produces accurate spectra and is almost three orders of magnitude faster than a model based on the standard boundary-value problem solver. The physics-based matrix model can compete with equivalent circuit models for fitting experimental EIS spectra, particularly those measured from cells with functionally graded CCL.

physics.chem-ph