Recycling qubits in near-term quantum computers

TL;DR

This paper introduces a protocol for recycling qubits in near-term quantum computers, significantly reducing spatial costs during tensor network contractions by unitarily resetting qubits, with proven noise resilience.

Contribution

The paper proposes a novel qubit recycling protocol that unitarily resets qubits in convolutional circuits, reducing resource costs for quantum tensor network contractions.

Findings

Protocol effectively resets qubits to |0> state with exponentially small error in noise-free case.

Numerical evidence shows protocol's robustness in noisy environments.

Provides a condition for rigorous noise-resilience of the protocol.

Abstract

Quantum computers are capable of efficiently contracting unitary tensor networks, a task that is likely to remain difficult for classical computers. For instance, networks based on matrix product states or the multi-scale entanglement renormalization ansatz (MERA) can be contracted on a small quantum computer to aid the simulation of a large quantum system. However, without the ability to selectively reset qubits, the associated spatial cost can be exorbitant. In this paper, we propose a protocol that can unitarily reset qubits when the circuit has a common convolutional form, thus dramatically reducing the spatial cost for implementing the contraction algorithm on general near-term quantum computers. This protocol generates fresh qubits from used ones by partially applying the time-reversed quantum circuit over qubits that are no longer in use. In the absence of noise, we prove that the state of a subset of these qubits becomes $|0\ldots 0\rangle$, up to an error exponentially small in the number of gates applied. We also provide a numerical evidence that the protocol works in the presence of noise. We also provide a numerical evidence that the protocol works in the presence of noise, and formulate a condition under which the noise-resilience follows rigorously.