Wave Matrix Lindbladization II: General Lindbladians, Linear
Combinations, and Polynomials
- URL: http://arxiv.org/abs/2309.14453v1
- Date: Mon, 25 Sep 2023 18:20:00 GMT
- Title: Wave Matrix Lindbladization II: General Lindbladians, Linear
Combinations, and Polynomials
- Authors: Dhrumil Patel and Mark M. Wilde
- Abstract summary: We investigate the problem of simulating open system dynamics governed by the well-known Lindblad master equation.
We introduce an input model in which Lindblad operators are encoded into pure quantum states, called program states.
We also introduce a method, called wave matrix Lindbladization, for simulating Lindbladian evolution by means of interacting the system of interest with these program states.
- Score: 4.62316736194615
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we investigate the problem of simulating open system dynamics
governed by the well-known Lindblad master equation. In our prequel paper, we
introduced an input model in which Lindblad operators are encoded into pure
quantum states, called program states, and we also introduced a method, called
wave matrix Lindbladization, for simulating Lindbladian evolution by means of
interacting the system of interest with these program states. Therein, we
focused on a simple case in which the Lindbladian consists of only one Lindblad
operator and a Hamiltonian. Here, we extend the method to simulating general
Lindbladians and other cases in which a Lindblad operator is expressed as a
linear combination or a polynomial of the operators encoded into the program
states. We propose quantum algorithms for all these cases and also investigate
their sample complexity, i.e., the number of program states needed to simulate
a given Lindbladian evolution approximately. Finally, we demonstrate that our
quantum algorithms provide an efficient route for simulating Lindbladian
evolution relative to full tomography of encoded operators, by proving that the
sample complexity for tomography is dependent on the dimension of the system,
whereas the sample complexity of wave matrix Lindbladization is dimension
independent.
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