Interactive Protocols for Classically-Verifiable Quantum Advantage

Zhu, Daiwei; Kahanamoku–Meyer, Gregory D.; Lewis, L. H.; Noel, Crystal; Katz, Or; Harraz, Bahaa; Wang, Qingfeng; Risinger, Andrew; Feng, Lei; Biswas, Debopriyo; Egan, Laird; Gheorghiu, Alexandru; Nam, Yoonsu; Vidick, Thomas; Vazirani, Umesh; Yao, Norman Y.; Cetina, Marko; Monroe, Christopher

doi:10.48550/arxiv.2112.05156

Cited by 6 publications

(13 citation statements)

References 49 publications

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“…This reveals some information about x and x that is not accessible to a classical device. Such protocols were recently improved to much simpler functions (Kahanamoku-Meyer et al, 2021) and low-depth implementations (Hirahara and Gall, 2021;Liu and Gheorghiu, 2021), bringing their experimental demonstration within closer reach (Zhu et al, 2021).…”

Section: Cryptographic Testsmentioning

confidence: 99%

“…What we do not discuss in this review are ways to demonstrate a quantum advantage by other means. Particularly prominent examples are the discovery of verifiable proofs of quantumness (Brakerski et al, 2018(Brakerski et al, , 2020Kahanamoku-Meyer et al, 2021) for which there are recent proof-ofprinciple demonstrations (Zhu et al, 2021). These schemes demonstrate access and control over a single qubit via a cryptographic encoding.…”

Section: Introductionmentioning

confidence: 99%

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Computational advantage of quantum random sampling

Hangleiter¹,

Eisert²

2022

Preprint

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Quantum random sampling is the leading proposal for demonstrating a computational advantage of quantum computers over classical computers. Recently, first large-scale implementations of quantum random sampling have arguably surpassed the boundary of what can be simulated on existing classical hardware. In this article, we comprehensively review the theoretical underpinning of quantum random sampling in terms of computational complexity and verifiability, as well as the practical aspects of its experimental implementation using superconducting and photonic devices and its classical simulation. We discuss in detail open questions in the field and provide perspectives for the road ahead, including potential applications of quantum random sampling.

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Section: Cryptographic Testsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computational advantage of quantum random sampling

Hangleiter¹,

Eisert²

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…It is desirable to Ruge Lin: ruge.lin@tii.ae Weiqiang Wen: weiqiang.wen@telecom-paris.fr have a performance test on quantum hardware, proving to a verifier and unable to falsify. Recent works [5,6,7,8] demands a classical verifier. In particular, they rely on the hardness of the learning with errors problem and needs thousands of qubits, which is not applicable to present quantum hardware.…”

Section: Introductionmentioning

confidence: 99%

Quantum computation capability verification protocol for NISQ devices with dihedral coset problem

Lin,

Wen

2022

Preprint

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In this article, we propose a protocol for one party (the verifier) holding a quantum computer to verify the quantum computation power of another party's (the prover) device via a one-way quantum channel. To achieve this, we use the dihedral coset problem (DCP), which is a puzzle hypothesized to be only solvable by a quantum computer (the best-known classical solving algorithm is a random guess over the solutions). We name this protocol the DCP challenge. The verifier needs to prepare quantum states encoding secrets (DCP samples) and send them to the prover. The prover is then asked to recover those secrets with a certain accuracy. Numerical simulation shows that this accuracy is sensitive to errors in quantum hardware. The DCP challenge is aimed to be performed on current quantum resources. The smallest instance only needs 2 qubits from the verifier and 4 qubits from the prover.

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“…Existing techniques for verifying the output of quantum computers [15][16][17][18][19][20][21][22][23] have complementary properties to ours. These methods can be divided into those that, like ours, quantify the accuracy with which a quantum circuit can be executed on a quantum computer that is noisy and error-prone but otherwise trusted, and methods for verifying the correct operation of a potentially malicious quantum computing server.…”

mentioning

confidence: 99%

“…In particular, direct fidelity estimation [18] is a technique for measuring the execution fidelity of any circuit, but it is only efficient for circuits that can be efficiently simulated classically [24]. The existing techniques for verifying the output of a potentially malicious quantum computer-using interactive proofs, blind quantum computing, and cryptographic methods-require resource-intensive implementations of algorithms that are experimentally challenging [20][21][22][23]25]. It is unlikely that they can be used to establish trust in the first practically important quantum com-…”

mentioning

confidence: 99%