Exact NMR simulation of protein-size spin systems using tensor train formalism
Exact NMR simulation of protein-size spin systems using tensor train formalism
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 N15 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.
Savostyanov, D.V.
e96cbd06-e7b0-4712-8cb6-d786e34bf796
Dolgov, S.V.
11937919-7cb7-47d9-a845-8e7f8f911431
Werner, J.M.
1b02513a-8310-4f4f-adac-dc2a466bd115
Kuprov, Ilya
bb07f28a-5038-4524-8146-e3fc8344c065
25 August 2014
Savostyanov, D.V.
e96cbd06-e7b0-4712-8cb6-d786e34bf796
Dolgov, S.V.
11937919-7cb7-47d9-a845-8e7f8f911431
Werner, J.M.
1b02513a-8310-4f4f-adac-dc2a466bd115
Kuprov, Ilya
bb07f28a-5038-4524-8146-e3fc8344c065
Savostyanov, D.V., Dolgov, S.V., Werner, J.M. and Kuprov, Ilya
(2014)
Exact NMR simulation of protein-size spin systems using tensor train formalism.
Physical Review B, 90 (8), [085139].
(doi:10.1103/PhysRevB.90.085139).
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 N15 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.
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PhysRevB.90.085139
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Available under License Other.
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Published date: 25 August 2014
Organisations:
Computational Systems Chemistry
Identifiers
Local EPrints ID: 369176
URI: http://eprints.soton.ac.uk/id/eprint/369176
ISSN: 1550-235X
PURE UUID: 8001f22c-fc50-47a7-a179-fce785af2049
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Date deposited: 29 Sep 2014 11:18
Last modified: 15 Mar 2024 03:43
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Author:
D.V. Savostyanov
Author:
S.V. Dolgov
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