Exact NMR simulation of protein-size spin systems using tensor train formalism

Dmitry Savostyanov, Sergey Dolgov, Joern Werner, Ilya Kuprov

Research output: Contribution to journalArticle

Abstract

We introduce a new method, based on alternating optimization, for compact representation of spin Hamiltonians and solution of linear systems of algebraic equations in the tensor train format. We demonstrate the method's utility by simulating, without approximations, a 15N NMR spectrum of ubiquitin—a protein containing several hundred interacting nuclear spins. Existing simulation algorithms for the spin system and the NMR experiment in question either require significant approximations or scale exponentially with the spin system size. We compare the proposed method to the Spinach package that uses heuristic restricted state space techniques to achieve polynomial complexity scaling. When the spin system topology is close to a linear chain (e.g., for the backbone of a protein), the tensor train representation is more compact and can be computed faster than the sparse representation using restricted state spaces.
Original languageEnglish
JournalPhysical Review B
Volume90
Issue number8
DOIs
Publication statusPublished - 15 Aug 2014

Bibliographical note

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

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