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Virginia Tech

Automated Implementation of Advanced Electronic Structure Methods

Abstract

dc:description.abstract

The continuous demand for higher accuracy in computational chemistry necessitates the development of advanced many-body electronic structure methods. However, the derivation and efficient implementation of these theories constitute a significant bottleneck. As the rank of the associated tensors increases, the governing equations explode in complexity, rendering manual implementation labor-intensive, error-prone, and difficult to optimize for modern hardware. To address this challenge, this dissertation presents SeQuant, a comprehensive framework for the automated derivation and parallel implementation of many-body quantum chemistry methods. Built upon a robust symbolic algebra engine, SeQuant allows for the expression of theories in the natural language of second quantization. It automates the transformation of high-level theoretical ansatzes into explicit tensor contraction expressions and subsequently generates optimized, high-performance C++ code. A central innovation of this work is the extension of automated implementation to reduced-scaling methods, which exploit the sparsity inherent in electronic correlation. We introduce a novel "tensor-of-tensors" data structure designed to manage the irregular sparsity patterns of Pair Natural Orbital (PNO) formulations. This development enables the first fully automated implementation of PNO-Coupled Cluster (PNO-CC) methods, bridging the gap between symbolic abstraction and the runtime requirements of sparse tensor algebra. The results demonstrate that SeQuant not only reproduces established dense methods (such as CCSD and CCSDT) with high fidelity but also effectively handles the complexity of sparse, local correlation approaches. By decoupling the complexity of the physics from the details of the implementation, this framework establishes a new paradigm for method development, dramatically accelerating the translation of theoretical insights into computational reality.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Chemistry
Department dc:contributor.department
Chemistry
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2026

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gaudel, Bimal
Chair dc:contributor.committeechair
  • Valeyev, Eduard Faritovich
Committee members dc:contributor.committeemember
  • Troya, Diego
  • Mayhall, Nicholas
  • Crawford, Thomas Daniel

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:45611
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/141157

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Gaudel, Bimal. Automated Implementation of Advanced Electronic Structure Methods. doctoral thesis, Virginia Tech, 2026. https://hdl.handle.net/10919/141157