Saved in:
Bibliographic Details
Main Authors: Araújo, Mateus, Garner, Andrew J. P., Navascues, Miguel
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2408.02572
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916853269397504
author Araújo, Mateus
Garner, Andrew J. P.
Navascues, Miguel
author_facet Araújo, Mateus
Garner, Andrew J. P.
Navascues, Miguel
contents Non-commutative polynomial optimization (NPO) problems seek to minimize the state average of a polynomial of some operator variables, subject to polynomial constraints, over all states and operators, as well as the Hilbert spaces where those might be defined. Many of these problems are known to admit a complete hierarchy of semidefinite programming (SDP) relaxations. In this work, we consider a variant of NPO problems where a subset of the operator variables satisfies a system of ordinary differential equations. We find that, under mild conditions of operator boundedness, for every such problem one can construct a standard NPO problem with the same solution. This allows us to define a complete hierarchy of SDPs to tackle the original differential problem. We apply this method to bound averages of local observables in quantum spin systems subject to a Hamiltonian evolution (i.e., a quench). We find that, even in the thermodynamic limit of infinitely many sites, low levels of the hierarchy provide very good approximations for reasonably long evolution times.
format Preprint
id arxiv_https___arxiv_org_abs_2408_02572
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Non-commutative optimization problems with differential constraints
Araújo, Mateus
Garner, Andrew J. P.
Navascues, Miguel
Quantum Physics
Optimization and Control
Non-commutative polynomial optimization (NPO) problems seek to minimize the state average of a polynomial of some operator variables, subject to polynomial constraints, over all states and operators, as well as the Hilbert spaces where those might be defined. Many of these problems are known to admit a complete hierarchy of semidefinite programming (SDP) relaxations. In this work, we consider a variant of NPO problems where a subset of the operator variables satisfies a system of ordinary differential equations. We find that, under mild conditions of operator boundedness, for every such problem one can construct a standard NPO problem with the same solution. This allows us to define a complete hierarchy of SDPs to tackle the original differential problem. We apply this method to bound averages of local observables in quantum spin systems subject to a Hamiltonian evolution (i.e., a quench). We find that, even in the thermodynamic limit of infinitely many sites, low levels of the hierarchy provide very good approximations for reasonably long evolution times.
title Non-commutative optimization problems with differential constraints
topic Quantum Physics
Optimization and Control
url https://arxiv.org/abs/2408.02572