Quantum Advantage with Timestamp Membosonsampling

TL;DR

This paper introduces timestamp membosonsampling, a scalable quantum sampling method leveraging photon timestamp information, demonstrated on a photonic chip with unprecedented multi-photon registration and Hilbert space size, advancing quantum advantage prospects.

Contribution

It proposes a novel, scalable variant of boson sampling using timestamp information, verified experimentally on a large-scale photonic chip, surpassing previous limitations.

Findings

Achieved 56-fold multi-photon registrations in 750,000 modes

Demonstrated a Hilbert space size up to 10^254

Provided a scalable platform for quantum information processing

Abstract

Quantum computer, harnessing quantum superposition to boost a parallel computational power, promises to outperform its classical counterparts and offer an exponentially increased scaling. The term "quantum advantage" was proposed to mark the key point when people can solve a classically intractable problem by artificially controlling a quantum system in an unprecedented scale, even without error correction or known practical applications. Boson sampling, a problem about quantum evolutions of multi-photons on multimode photonic networks, as well as its variants, has been considered as a promising candidate to reach this milestone. However, the current photonic platforms suffer from the scaling problems, both in photon numbers and circuit modes. Here, we propose a new variant of the problem, timestamp membosonsampling, exploiting the timestamp information of single photons as free resources, and the scaling of the problem can be in principle extended to infinitely large. We experimentally verify the scheme on a self-looped photonic chip inspired by memristor, and obtain multi-photon registrations up to 56-fold in 750,000 modes with a Hilbert space up to $10^{254}$. Our work exhibits an integrated and cost-efficient shortcut stepping into the "quantum advantage" regime in a photonic system far beyond previous scenarios, and provide a scalable and controllable platform for quantum information processing.