On the sampling complexity of open quantum systems
Isobel A. Aloisio, Gregory A. L. White, Charles D. Hill, Kavan Modi

TL;DR
This paper investigates the computational complexity of simulating open quantum systems, demonstrating that multi-time sampling tasks are classically hard and exploring how quantum computers could potentially address this challenge.
Contribution
It introduces a complexity-theoretic framework linking multi-time sampling in open quantum systems to the difficulty of simulating many-body states, highlighting quantum computers' potential.
Findings
Multi-time sampling complexity can be as hard as sampling from classically intractable many-body states.
The complexity of open quantum system dynamics relates directly to the complexity of associated master equations.
Quantum computers may offer advantages in simulating complex open quantum systems.
Abstract
Open quantum systems are ubiquitous in the physical sciences, with widespread applications in the areas of chemistry, condensed matter physics, material science, optics, and many more. Not surprisingly, there is significant interest in their efficient simulation. However, direct classical simulation quickly becomes intractable with coupling to an environment whose effective dimension grows exponentially. This raises the question: can quantum computers help model these complex dynamics? A first step in answering this question requires understanding the computational complexity of this task. Here, we map the temporal complexity of a process to the spatial complexity of a many-body state using a computational model known as the process tensor framework. With this, we are able to explore the simulation complexity of an open quantum system as a dynamic sampling problem: a system coupled to…
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Taxonomy
TopicsQuantum many-body systems · Tensor decomposition and applications · Advanced Thermodynamics and Statistical Mechanics
