Efficient classical simulation of the Gisin-Massar quantum cloning machine

TL;DR

This paper details a tensor-network based classical simulation method for the Gisin-Massar quantum cloning machine, enabling efficient generation of optimal clones with controllable resources using matrix-product states.

Contribution

It introduces a novel tensor-network protocol that efficiently simulates the Gisin-Massar quantum cloner on classical computers, leveraging matrix-product states and parity features.

Findings

Efficient classical simulation of the Gisin-Massar quantum cloning machine.

Use of matrix-product states to represent the output state.

Controlled numerical resource management for clone generation.

Abstract

We provide here the technical details of the recently proposed tensor-network protocol for classical simulation of the Gisin-Massar quantum cloner by the authors [Phys. Rev. A, 85, 052323 (2012)]. The protocol essentially instructs how to efficiently simulate an optimal quantum cloning machine of Gisin-Massar on a classical computer. A viable computational platform for generation on demand of arbitrary number of optimal clones with controllable numerical resources is realized by rephrasing the Gisin-Massar output state in terms of the hierarchy of the so-called matrix-product states (MPS) and invoking parity features peculiar to such an output.