Approximating dynamical correlation functions with constant depth quantum circuits
One of the most important quantities characterizing the microscopic properties of quantum systems are dynamical correlation functions. These correlations are obtained by time-evolving a perturbation of an eigenstate of the system, typically the ground state. In this work, we study approximations of...
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Main Authors | , |
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Format | Journal Article |
Language | English |
Published |
05.06.2024
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Subjects | |
Online Access | Get full text |
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Summary: | One of the most important quantities characterizing the microscopic
properties of quantum systems are dynamical correlation functions. These
correlations are obtained by time-evolving a perturbation of an eigenstate of
the system, typically the ground state. In this work, we study approximations
of these correlation functions that do not require time dynamics. We show that
having access to a circuit that prepares an eigenstate of the Hamiltonian, it
is possible to approximate the dynamical correlation functions up to
exponential accuracy in the complex frequency domain
$\omega=\Re(\omega)+i\Im(\omega)$, on a strip above the real line
$\Im(\omega)=0$. We achieve this by exploiting the continued fraction
representation of the dynamical correlation functions as functions of frequency
$\omega$, where the level $k$ approximant can be obtained by measuring a weight
$O(k)$ operator on the eigenstate of interest. In the complex $\omega$ plane,
we show how this approach allows to determine approximations to correlation
functions with accuracy that increases exponentially with $k$.
We analyse two algorithms to generate the continuous fraction representation
in scalar or matrix form, starting from either one or many initial operators.
We prove that these algorithms generate an exponentially accurate approximation
of the dynamical correlation functions on a region sufficiently far away from
the real frequency axis. We present numerical evidence of these theoretical
results through simulations of small lattice systems. We comment on the
stability of these algorithms with respect to sampling noise in the context of
quantum simulation using quantum computers. |
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DOI: | 10.48550/arxiv.2406.03204 |