Quantum Defragmentation Algorithm

TL;DR

This paper introduces a quantum defragmentation algorithm demonstrating that ancillary memory size can be finite during quantum control transformations, enabling efficient simulation of noisy quantum systems with limited resources.

Contribution

It presents the first quantum analog of classical defragmentation algorithms, showing finite memory suffices for control and simulation tasks in quantum systems.

Findings

Ancillary memory can be kept finite during quantum control transformations.

Quantum defragmentation algorithms reorganize quantum information efficiently.

Reduced dynamics in noisy systems can be simulated with finite resources.

Abstract

In this addendum of our paper [D. Burgarth and V. Giovannetti, Phys. Rev. Lett. 99, 100501 (2007)] we prove that during the transformation that allows one to enforce control by relaxation on a quantum system, the ancillary memory can be kept at a finite size, independently from the fidelity one wants to achieve. The result is obtained by introducing the quantum analog of defragmentation algorithms which are employed for efficiently reorganizing classical information in conventional hard-disks. Our result also implies that the reduced dynamics in any noisy system can be simulated with finitely many resources.