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Quantum computational advantage using photons (2012.01625v1)

Published 3 Dec 2020 in quant-ph, cond-mat.other, and physics.optics

Abstract: Gaussian boson sampling exploits squeezed states to provide a highly efficient way to demonstrate quantum computational advantage. We perform experiments with 50 input single-mode squeezed states with high indistinguishability and squeezing parameters, which are fed into a 100-mode ultralow-loss interferometer with full connectivity and random transformation, and sampled using 100 high-efficiency single-photon detectors. The whole optical set-up is phase-locked to maintain a high coherence between the superposition of all photon number states. We observe up to 76 output photon-clicks, which yield an output state space dimension of $10{30}$ and a sampling rate that is $10{14}$ faster than using the state-of-the-art simulation strategy and supercomputers. The obtained samples are validated against various hypotheses including using thermal states, distinguishable photons, and uniform distribution.

Citations (1,787)
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Summary

  • The paper demonstrates a quantum computational advantage using Gaussian Boson Sampling with a sophisticated photonic setup.
  • It employs 50 single-mode squeezed states in a 100-mode ultralow-loss interferometer, achieving up to 76 photon-clicks and a state-space near 10^30.
  • Results challenge classical simulation limits and the extended Church-Turing thesis, paving the way for applications in quantum chemistry, optimization, and machine learning.

Quantum Computational Advantage Using Photons

In the paper of quantum computational advantage, Gaussian Boson Sampling (GBS) provides a notable experimental framework, elucidating the intrinsic computational complexity aspects of quantum mechanics. The paper under investigation rigorously explores GBS using photons as a means of demonstrating this advantage, solidifying its place as a key alternative to classical computation methods. The research presents an intricate experimental setup and validation process, highlighting the ways GBS can surpass classical computation constraints.

Experimentation and Methodology

The authors employ an elaborate setup utilizing 50 single-mode squeezed states (SMSS) as inputs into a 100-mode ultra-low-loss interferometer—which is fully connected and perturbed randomly—followed by Gaussian sampling through 100 high-efficiency single-photon detectors. The configuration harnesses the Gaussian nature of parametric down-conversion sources. The experimental results are promising: up to 76 photon-clicks were observed, leading to a state-space dimension of approximately 103010^{30} and a sampling rate exponentially faster than advanced classical strategies, challenging the efficacy of classical supercomputers.

Results

In this experiment, Gaussian Boson Sampling did not only outperform classical simulation methods in terms of operational speed but also asserted its computational authenticity through rigorous validation techniques. The results demonstrated a significant disparity in outcomes when compared to hypotheses including thermal states and distinguishable photon distribution, reinforcing the genuine quantum interference underpinning the phenomenon.

Implications

This paper has vast implications for the extended Church-Turing thesis, presenting formidable evidence challenging classical assumptions concerning computational efficiency. Noteworthy is the validation effort, which relied on digital simulations and hypothesis testing to confirm the integrity of the results. The breadth of the experiment demonstrates potential practical applications in real-world problems such as quantum chemistry, graph optimization, and machine learning, laying groundwork for specialized quantum computational platforms.

Future Directions

Future endeavors might focus on enhancing detector efficiency, expanding the interferometer's scale, and improving parametric down-conversion efficiency. Moreover, the continual development of algorithms optimized for adapting to experimental parameters in GBS could further increase classical simulation efficiency, challenging the quantum advantage poised by this research. Additionally, exploring the application of GBS to graph-structured and molecular problems can further entrench its place in practical quantum information processing.

The contribution of this research is substantial, shedding light on the burgeoning domain of quantum computation through photonic implementation, thereby marking a pivotal advancement in experimental quantum advantage paradigms.

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