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Sampling from the output distributions of quantum computations comprising only commuting gates, known as instantaneous quantum polynomial (IQP) computations, is believed to be intractable for classical computers, and hence this task has…

量子物理 · 物理学 2025-03-07 Joel Rajakumar , James D. Watson , Yi-Kai Liu

We provide a polynomial-time classical algorithm for noisy quantum circuits. The algorithm computes the expectation value of any observable for any circuit, with a small average error over input states drawn from an ensemble (e.g. the…

量子物理 · 物理学 2024-10-15 Thomas Schuster , Chao Yin , Xun Gao , Norman Y. Yao

The class of commuting quantum circuits known as IQP (instantaneous quantum polynomial-time) has been shown to be hard to simulate classically, assuming certain complexity-theoretic conjectures. Here we study the power of IQP circuits in…

量子物理 · 物理学 2017-04-26 Michael J. Bremner , Ashley Montanaro , Dan J. Shepherd

We construct a polynomial-time classical algorithm that samples from the output distribution of noisy geometrically local Clifford circuits with any product-state input and single-qubit measurements in any basis. Our results apply to…

量子物理 · 物理学 2026-01-09 Jon Nelson , Joel Rajakumar , Dominik Hangleiter , Michael J. Gullans

Quantum Supremacy is a demonstration of a computation by a quantum computer that can not be performed by the best classical computer in a reasonable time. A well-studied approach to demonstrating this on near-term quantum computers is to…

量子物理 · 物理学 2025-09-22 Julien Codsi , John van de Wetering

Generative modeling is one of the most promising applications of quantum machine learning, yet training and deploying Quantum Generative Models (QGMs) on near-term hardware remains effectively intractable due to prohibitive gradient…

Establishing an advantage for (white-box) computations by a quantum computer against its classical counterpart is currently a key goal for the quantum computation community. A quantum advantage is achieved once a certain computational…

量子物理 · 物理学 2024-02-06 Dmitri Maslov , Sergey Bravyi , Felix Tripier , Andrii Maksymov , Joe Latone

We present a polynomial-time classical algorithm for estimating expectation values of arbitrary observables on typical quantum circuits under any incoherent local noise, including non-unital or dephasing. Although previous research…

量子物理 · 物理学 2026-04-23 Armando Angrisani , Antonio A. Mele , Manuel S. Rudolph , M. Cerezo , Zoë Holmes

While quantum computing can accomplish tasks that are classically intractable, the presence of noise may destroy this advantage in the absence of fault tolerance. In this work, we present a classical algorithm that runs in…

量子物理 · 物理学 2025-10-09 Yifan F. Zhang , Su-un Lee , Liang Jiang , Sarang Gopalakrishnan

Solving differential equations is one of the most promising applications of quantum computing. Recently we proposed an efficient quantum algorithm for solving one-dimensional Poisson equation avoiding the need to perform quantum arithmetic…

Simulating noisy quantum circuits is vital in designing and verifying quantum algorithms in the current NISQ (Noisy Intermediate-Scale Quantum) era, where quantum noise is unavoidable. However, it is much more inefficient than the classical…

量子物理 · 物理学 2023-11-27 Mingyu Huang , Ji Guan , Wang Fang , Mingsheng Ying

Between NISQ (noisy intermediate scale quantum) approaches without any proof of robust quantum advantage and fully fault-tolerant quantum computation, we propose a scheme to achieve a provable superpolynomial quantum advantage (under some…

Classical simulations of noisy quantum circuits are instrumental to our understanding of the behavior of real-world quantum systems and the identification of regimes where one expects quantum advantage. In this work, we present a highly…

量子物理 · 物理学 2026-02-17 Simon Cichy , Paul K. Faehrmann , Lennart Bittel , Jens Eisert , Hakop Pashayan

We introduce a distributed classical simulation algorithm for general quantum circuits, and present numerical results for calculating the output probabilities of universal random circuits. We find that we can simulate more qubits to greater…

量子物理 · 物理学 2018-05-08 Jianxin Chen , Fang Zhang , Cupjin Huang , Michael Newman , Yaoyun Shi

Large-scale variational quantum algorithms are widely recognized as a potential pathway to achieve practical quantum advantages. However, the presence of quantum noise might suppress and undermine these advantages, which blurs the…

量子物理 · 物理学 2024-09-20 Yuguo Shao , Fuchuan Wei , Song Cheng , Zhengwei Liu

We give a polynomial time classical algorithm for sampling from the output distribution of a noisy random quantum circuit in the regime of anti-concentration to within inverse polynomial total variation distance. This gives strong evidence…

量子物理 · 物理学 2023-06-06 Dorit Aharonov , Xun Gao , Zeph Landau , Yunchao Liu , Umesh Vazirani

For typical quantum subroutines in the gate-based model of quantum computing, explicit decompositions of circuits in terms of single-qubit and two-qubit entangling gates may exist. However, they often lead to large-depth circuits that are…

量子物理 · 物理学 2024-09-20 Dhruv Srinivasan , Kushal Chakrabarti , Nikhil Chopra , Avik Dutt

We consider quantum computations comprising only commuting gates, known as IQP computations, and provide compelling evidence that the task of sampling their output probability distributions is unlikely to be achievable by any efficient…

量子物理 · 物理学 2010-11-17 Michael J. Bremner , Richard Jozsa , Dan J. Shepherd

Understanding the computational power of noisy intermediate-scale quantum (NISQ) devices is of both fundamental and practical importance to quantum information science. Here, we address the question of whether error-uncorrected noisy…

量子物理 · 物理学 2020-09-16 Kyungjoo Noh , Liang Jiang , Bill Fefferman

In the current NISQ (Noisy Intermediate-Scale Quantum) era, simulating and verifying noisy quantum circuits is crucial but faces challenges such as quantum state explosion and complex noise representations, constraining simulation and…

量子物理 · 物理学 2025-12-12 Mingyu Huang , Ji Guan , Wang Fang , Mingsheng Ying
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