Heisenberg picture tensor network formalism for optical circuits

TL;DR

This paper introduces a novel tensor network formalism in the Heisenberg picture for optical circuits, enabling efficient simulation of photon-counting probabilities, including effects like distinguishability and loss.

Contribution

It presents an alternative tensor network framework that computes photon probabilities with classical complexity and extends to practical imperfections in optical quantum computing.

Findings

Efficient computation of the permanent using tensor networks.

Extension of the formalism to include photon loss and partial distinguishability.

Bridging the complexity gap in simulating optical quantum circuits.

Abstract

Tensor network formalisms have emerged as powerful tools for simulating quantum state evolution. While widely applied in the study of optical quantum circuits, such as Boson Sampling, existing tensor network approaches fail to address the complexity mismatch between tensor contractions and the calculation of photon-counting probability amplitudes. Here, we present an alternative tensor network framework that exploits the input-output relations of quantum optical circuits encoded in the unitary interferometer matrix. Our approach bridges the complexity gap by enabling the computation of the permanent -- central to Boson Sampling -- with the same computational complexity as the best known classical algorithm based on a graphical representation of the operator-basis MPS that we introduce. Furthermore, we exploit the flexibility of tensor networks to extend our formalism to incorporate partial distinguishability and photon loss, two key imperfections in practical interferometry experiments. This work offers a significant step forward in the simulation of large-scale quantum optical systems and the understanding of their computational complexity.