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It is known that the estimating equations for quantile regression (QR) can be solved using an EM algorithm in which the M-step is computed via weighted least squares, with weights computed at the E-step as the expectation of independent…

Methodology · Statistics 2021-08-26 Haim Bar , James Booth , Martin T. Wells

Achieving near-term quantum advantage will require accurate estimation of quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigation method that applies to gate-based quantum…

Quantum Physics · Physics 2021-12-01 Piotr Czarnik , Andrew Arrasmith , Patrick J. Coles , Lukasz Cincio

Measurement error mitigation (MEM) techniques are postprocessing strategies to counteract systematic read-out errors on quantum computers (QC). Currently used MEM strategies face a tradeoff: methods that scale well with the number of qubits…

Quantum Physics · Physics 2022-10-25 Siddarth Srinivasan , Bibek Pokharel , Gregory Quiroz , Byron Boots

With sub-threshold quantum error correction on quantum hardware still out of reach, quantum error mitigation methods are currently deemed an attractive option for implementing certain applications on near-term noisy quantum devices. One…

Quantum Physics · Physics 2024-03-01 Wenbo Shi , Robert Malaney

Quantum error correcting codes have been shown to have the ability of making quantum information resilient against noise. Here we show that we can use quantum error correcting codes as diagnostics to characterise noise. The experiment is…

Quantum Physics · Physics 2009-11-13 M. Laforest , D. Simon , J. -C. Boileau , J. Baugh , M. Ditty , R. Laflamme

We propose a quantum error mitigation strategy for the variational quantum eigensolver (VQE) algorithm. We find, via numerical simulation, that very small amounts of coherent noise in VQE can cause substantially large errors that are…

All known qudit-based prepare-and-measure quantum key distribution (PM-QKD) schemes are more error resilient than their qubit-based counterparts. Their high error resiliency comes partly from the careful encoding of multiple bits of signals…

Quantum Physics · Physics 2015-12-16 H. F. Chau

Quantum error correction (QEC) is an essential concept for any quantum information processing device. Typically, QEC is designed with minimal assumptions about the noise process; this generic assumption exacts a high cost in efficiency and…

Quantum Physics · Physics 2007-06-26 Andrew S. Fletcher

Quantum annealers like those from D-Wave Systems implement adiabatic quantum computing to solve optimization problems, but their analog nature and limited control functionalities present challenges to correcting or mitigating errors. As…

Quantum Physics · Physics 2024-04-11 Hristo N. Djidjev

Quantum optimization algorithms offer a promising route to finding the ground states of target Hamiltonians on near-term quantum devices. None the less, it remains necessary to limit the evolution time and circuit depth as much as possible,…

Quantum Physics · Physics 2022-11-01 Chenfeng Cao , Yunlong Yu , Zipeng Wu , Nic Shannon , Bei Zeng , Robert Joynt

We propose a quantum error mitigation method termed self-mitigation, which is comparable with zero-noise extrapolation, to achieve quantum utility on near-term, noisy quantum computers. We investigate the effectiveness of several quantum…

Quantum Physics · Physics 2025-06-26 Seokwon Choi , Talal Ahmed Chowdhury , Kwangmin Yu

Due to the numerous limitations of current quantum devices, quantum error mitigation methods become potential solutions for realizing practical quantum applications in the near term. Zero-Noise Extrapolation (ZNE) and Clifford Data…

Quantum Physics · Physics 2025-03-26 Wenbo Shi , Neel Kanth Kundu , Robert Malaney

In this paper, we focus on distributed estimation and support recovery for high-dimensional linear quantile regression. Quantile regression is a popular alternative tool to the least squares regression for robustness against outliers and…

Machine Learning · Statistics 2024-06-04 Caixing Wang , Ziliang Shen

Superconducting quantum processor units (QPUs) are incapable of producing massive datasets for quantum error correction (QEC) because of hardware limitations. Thus, QEC decoders heavily depend on synthetic data from qubit error models.…

Quantum Physics · Physics 2026-04-27 Songhuan He , Yifei Cui , Bo Liu , Kai Guo , Cheng Wang

Error mitigation techniques, while instrumental in extending the capabilities of near-term quantum computers, often suffer from exponential resource scaling with noise levels. To address this limitation, we introduce a novel approach,…

Quantum Physics · Physics 2024-09-11 Gaurav Saxena , Thi Ha Kyaw

We describe a scheme for quantum error correction that employs feedback and weak measurement rather than the standard tools of projective measurement and fast controlled unitary gates. The advantage of this scheme over previous protocols…

Quantum Physics · Physics 2009-11-10 Mohan Sarovar , Charlene Ahn , Kurt Jacobs , Gerard J. Milburn

Numerous quantum error-mitigation protocols have been proposed, motivated by the critical need to suppress noise effects on intermediate-scale quantum devices. Yet, their general potential and limitations remain elusive. In particular, to…

Quantum Physics · Physics 2023-11-27 Ryuji Takagi , Hiroyasu Tajima , Mile Gu

An important measure of the development of quantum computing platforms has been the simulation of increasingly complex physical systems. Prior to fault-tolerant quantum computing, robust error mitigation strategies are necessary to continue…

Quantum Physics · Physics 2023-11-07 T. E. O'Brien , G. Anselmetti , F. Gkritsis , V. E. Elfving , S. Polla , W. J. Huggins , O. Oumarou , K. Kechedzhi , D. Abanin , R. Acharya , I. Aleiner , R. Allen , T. I. Andersen , K. Anderson , M. Ansmann , F. Arute , K. Arya , A. Asfaw , J. Atalaya , D. Bacon , J. C. Bardin , A. Bengtsson , S. Boixo , G. Bortoli , A. Bourassa , J. Bovaird , L. Brill , M. Broughton , B. Buckley , D. A. Buell , T. Burger , B. Burkett , N. Bushnell , J. Campero , Y. Chen , Z. Chen , B. Chiaro , D. Chik , J. Cogan , R. Collins , P. Conner , W. Courtney , A. L. Crook , B. Curtin , D. M. Debroy , S. Demura , I. Drozdov , A. Dunsworth , C. Erickson , L. Faoro , E. Farhi , R. Fatemi , V. S. Ferreira , L. Flores Burgos , E. Forati , A. G. Fowler , B. Foxen , W. Giang , C. Gidney , D. Gilboa , M. Giustina , R. Gosula , A. Grajales Dau , J. A. Gross , S. Habegger , M. C. Hamilton , M. Hansen , M. P. Harrigan , S. D. Harrington , P. Heu , J. Hilton , M. R. Hoffmann , S. Hong , T. Huang , A. Huff , L. B. Ioffe , S. V. Isakov , J. Iveland , E. Jeffrey , Z. Jiang , C. Jones , P. Juhas , D. Kafri , J. Kelly , T. Khattar , M. Khezri , M. Kieferová , S. Kim , P. V. Klimov , A. R. Klots , R. Kothari , A. N. Korotkov , F. Kostritsa , J. M. Kreikebaum , D. Landhuis , P. Laptev , K. Lau , L. Laws , J. Lee , K. Lee , B. J. Lester , A. T. Lill , W. Liu , W. P. Livingston , A. Locharla , E. Lucero , F. D. Malone , S. Mandra , O. Martin , S. Martin , J. R. McClean , T. McCourt , M. McEwen , A. Megrant , X. Mi , A. Mieszala , K. C. Miao , M. Mohseni , S. Montazeri , A. Morvan , R. Movassagh , W. Mruczkiewicz , O. Naaman , M. Neeley , C. Neill , A. Nersisyan , H. Neven , M. Newman , J. H. Ng , A. Nguyen , M. Nguyen , M. Y. Niu , S. Omonije , A. Opremcak , A. Petukhov , R. Potter , L. P. Pryadko , C. Quintana , C. Rocque , P. Roushan , N. Saei , D. Sank , K. Sankaragomathi , K. J. Satzinger , H. F. Schurkus , C. Schuster , M. J. Shearn , A. Shorter , N. Shutty , V. Shvarts , J. Skruzny , V. Smelyanskiy , W. C. Smith , R. Somma , G. Sterling , D. Strain , M. Szalay , D. Thor , A. Torres , G. Vidal , B. Villalonga , C. Vollgraff Heidweiller , T. White , B. W. K. Woo , C. Xing , Z. J. Yao , P. Yeh , J. Yoo , G. Young , A. Zalcman , Y. Zhang , N. Zhu , N. Zobrist , C. Gogolin , R. Babbush , N. C. Rubin

We present adaptive measurement techniques tailored for variational quantum algorithms on near-term small and noisy devices. In particular, we generalise earlier "learning to measure" strategies in two ways. First, by considering a class of…

Quantum error correction in general is experimentally challenging as it requires significant expansion of the size of quantum circuits and accurate performance of quantum gates to fulfill the error threshold requirement. Here we propose a…

Quantum Physics · Physics 2012-06-04 C. Shen , L. -M. Duan