Variational optimization of continuous matrix product states
- URL: http://arxiv.org/abs/2006.01801v2
- Date: Thu, 3 Jun 2021 07:59:01 GMT
- Title: Variational optimization of continuous matrix product states
- Authors: Beno\^it Tuybens and Jacopo De Nardis and Jutho Haegeman and Frank
Verstraete
- Abstract summary: We show how to optimize continuous matrix product states for systems with inhomogeneous external potentials.
We show how both the energy and its backwards derivative can be calculated exactly and at a cost that scales as the cube of the bond dimension.
We illustrate this by finding ground states of interacting bosons in external potentials, and by calculating boundary or Casimir energy corrections of continuous many-body systems.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Just as matrix product states represent ground states of one-dimensional
quantum spin systems faithfully, continuous matrix product states (cMPS)
provide faithful representations of the vacuum of interacting field theories in
one spatial dimension. Unlike the quantum spin case however, for which the
density matrix renormalization group and related matrix product state
algorithms provide robust algorithms for optimizing the variational states, the
optimization of cMPS for systems with inhomogeneous external potentials has
been problematic. We resolve this problem by constructing a piecewise linear
parameterization of the underlying matrix-valued functions, which enables the
calculation of the exact reduced density matrices everywhere in the system by
high-order Taylor expansions. This turns the variational cMPS problem into a
variational algorithm from which both the energy and its backwards derivative
can be calculated exactly and at a cost that scales as the cube of the bond
dimension. We illustrate this by finding ground states of interacting bosons in
external potentials, and by calculating boundary or Casimir energy corrections
of continuous many-body systems with open boundary conditions.
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