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Performing experiments on small-scale quantum computers is certainly a challenging endeavor. Many parameters need to be optimized to achieve high-fidelity operations. This can be done efficiently for operations acting on single qubits as…

Quantum Physics · Physics 2016-08-31 M. Müller , A. Rivas , E. A. Martínez , D. Nigg , P. Schindler , T. Monz , R. Blatt , M. A. Martin-Delgado

We introduce a quantum error mitigation technique based on probabilistic error cancellation to eliminate errors which have accumulated during the application of a quantum circuit. Our approach is based on applying an optimal "denoiser"…

Quantum Physics · Physics 2024-05-21 Maurits S. J. Tepaske , David J. Luitz

We introduce an error mitigation framework that mitigates errors in a quantum circuit using circuit cutting. Our framework can be implemented in polynomial time for a wide variety of quantum circuits. Our technique involves cutting the…

Quantum Physics · Physics 2022-12-15 Ji Liu , Alvin Gonzales , Zain H. Saleem

Quantum Approximation Optimization Algorithm (QAOA) is a highly advocated variational algorithm for solving the combinatorial optimization problem. One critical feature in the quantum circuit of QAOA algorithm is that it consists of…

Quantum Physics · Physics 2022-07-21 Yuwei Jin , Jason Luo , Lucent Fong , Yanhao Chen , Ari B. Hayes , Chi Zhang , Fei Hua , Eddy Z. Zhang

The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising variational quantum algorithm that aims to solve combinatorial optimization problems that are classically intractable. This comprehensive review offers an overview…

Practical implementation of quantum error correction is currently limited by near-term quantum hardware. In contrast, quantum error mitigation has demonstrated strong promise for improving the performance of noisy quantum circuits without…

Quantum Physics · Physics 2025-10-02 Dawei Zhong , William Munizzi , Huo Chen , Wibe Albert de Jong

The Quantum Approximate Optimization Algorithm (QAOA) represents a significant opportunity for practical quantum computing applications, particularly in the era before error correction is fully realized. This algorithm is especially…

Quantum Physics · Physics 2024-10-08 Yiwen Liu , Qingyue Jiao , Yidong Zhou , Zhiding Liang , Yiyu Shi , Ke Wan , Shangjie Guo

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most promising Noisy Intermediate Quantum Algorithms (NISQ) in solving combinatorial optimizations and displays potential over classical heuristic techniques.…

Quantum Physics · Physics 2024-01-18 Arul Rhik Mazumder , Anuvab Sen , Udayon Sen

If NISQ-era quantum computers are to perform useful tasks, they will need to employ powerful error mitigation techniques. Quasi-probability methods can permit perfect error compensation at the cost of additional circuit executions, provided…

Quantum Physics · Physics 2022-02-14 Armands Strikis , Dayue Qin , Yanzhu Chen , Simon C. Benjamin , Ying Li

The Quantum Approximate Optimization Algorithm (QAOA) is a promising quantum approach for tackling combinatorial optimization problems. However, hardware constraints such as limited scaling and susceptibility to noise pose significant…

Quantum Physics · Physics 2025-05-19 Bao G Bach , Filip B. Maciejewski , Ilya Safro

Near-term quantum computers have been built as intermediate-scale quantum devices and are fragile against quantum noise effects, namely, NISQ devices. Traditional quantum-error-correcting codes are not implemented on such devices and to…

Quantum Physics · Physics 2024-03-18 Yusuke Hama , Hirofumi Nishi

This paper proposes a novel combination of constraint encoding methods for the Quantum Approximate Optimization Ansatz (QAOA). Real-world optimization problems typically consist of multiple types of constraints. To solve these optimization…

Developing quantum algorithms adaptive to specific constraints of near-term devices is an essential step towards practical quantum advantage. In a recent work [Phys. Rev. Lett. 131, 103601(2023)], we show cold atoms in an optical cavity can…

Quantum Physics · Physics 2024-06-12 Yuchen Luo , Xiaopeng Li , Jian Lin

Designing noisy-resilience quantum algorithms is indispensable for practical applications on Noisy Intermediate-Scale Quantum~(NISQ) devices. Here we propose a quantum approximate optimization algorithm~(QAOA) with a very shallow circuit,…

Quantum Physics · Physics 2021-09-27 Fang-Gang Duan , Dan-Bo Zhang

Running quantum circuits on quantum computers does not always generate "clean" results, unlike on a simulator, as noise plays a significant role in any quantum device. To explore this, we experimented with the Quantum Approximate…

Quantum Physics · Physics 2025-10-09 Abyan Khabir Irfan , Chansu Yu

Unwanted interaction between a quantum system and its fluctuating environment leads to decoherence and is the primary obstacle to establishing a scalable quantum information processing architecture. Strategies such as environmental and…

Variational quantum algorithms are believed to be promising for solving computationally hard problems and are often comprised of repeated layers of quantum gates. An example thereof is the quantum approximate optimization algorithm (QAOA),…

Quantum circuit optimization - the process of transforming a quantum circuit into an equivalent one with reduced time and space requirements - is crucial for maximizing the utility of current and near-future quantum devices. While most…

Quantum Physics · Physics 2026-01-23 Marcin Szyniszewski , Aleks Kissinger , Noah Linden , Paul Skrzypczyk

Quantum systems have potential to demonstrate significant computational advantage, but current quantum devices suffer from the rapid accumulation of error that prevents the storage of quantum information over extended periods. The…

By taking into account the physical nature of quantum errors it is possible to improve the efficiency of quantum error correction. Here we consider an optimisation to conventional quantum error correction which involves exploiting…

Quantum Physics · Physics 2007-09-26 Z. W. E. Evans , A. M. Stephens , J. H. Cole , L. C. L. Hollenberg
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