Spacetime Quantum Circuit Complexity via Measurements

TL;DR

This paper introduces the concept of embedded complexity in quantum circuits, analyzing how measurements and auxiliary systems influence complexity growth, with implications for quantum information processing and physics.

Contribution

It defines embedded complexity for measurement-assisted states and shows it is lower-bounded by circuit volume, extending complexity growth theorems and applications.

Findings

Embedded complexity is lower-bounded by circuit volume.

Measurement-assisted methods do not significantly reduce state preparation cost.

Spacetime conversion concentrates circuit volume for specific models.

Abstract

Quantum circuit complexity is a fundamental concept whose importance permeates quantum information, computation, many-body physics and high-energy physics. While extensively studied in closed systems, its characterization and behaviors in the widely important setting where the system is embedded within a larger one -- encompassing measurement-assisted state preparation -- lack systematic understanding. We introduce the notion of embedded complexity that characterizes the complexity of projected states and measurement operators in this general setting incorporating auxiliary systems and measurements. For random circuits and certain strongly interacting time-independent Hamiltonian dynamics, we show that the embedded complexity is lower-bounded by the circuit volume -- the total number of gates acting on both the subsystem and its complement. This strengthens the complexity linear growth theorems, enriches the understanding of deep thermalization, and indicates that measurement-assisted methods generically cannot yield significant advantages in state preparation cost, contrary to expectations. We further demonstrate a spacetime conversion of certain circuit models that concentrates circuit volume onto a subsystem, and showcase applications for random circuit sampling and shadow tomography. Our theory establishes a unified framework for space and time aspects of quantum circuit complexity, yielding profound new insights and applications across quantum information and physics.