Tensor product methods and entanglement optimization for ab initio quantum chemistry
Szil\'ard Szalay, Max Pfeffer, Valentin Murg, Gergely Barcza, Frank, Verstraete, Reinhold Schneider, \"Ors Legeza

TL;DR
This paper introduces tensor product and entanglement-based methods for high-dimensional quantum chemistry problems, demonstrating their theoretical foundations and numerical benefits in optimizing wavefunctions and tackling complex quantum systems.
Contribution
It provides a pedagogical overview of entanglement optimization techniques and their application to quantum chemistry, integrating concepts from many-body physics and tensor approximations.
Findings
Entanglement-based methods improve high-dimensional quantum problem solving.
Numerical examples demonstrate the effectiveness of the approaches.
Theoretical background supports future developments in quantum chemistry algorithms.
Abstract
The treatment of high-dimensional problems such as the Schr\"odinger equation can be approached by concepts of tensor product approximation. We present general techniques that can be used for the treatment of high-dimensional optimization tasks and time-dependent equations, and connect them to concepts already used in many-body quantum physics. Based on achievements from the past decade, entanglement-based methods, -- developed from different perspectives for different purposes in distinct communities already matured to provide a variety of tools -- can be combined to attack highly challenging problems in quantum chemistry. The aim of the present paper is to give a pedagogical introduction to the theoretical background of this novel field and demonstrate the underlying benefits through numerical applications on a text book example. Among the various optimization tasks we will discuss…
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