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Dynamical decoupling (DD) is a widely-used quantum control technique that takes advantage of temporal symmetries in order to partially suppress quantum errors without the need resource-intensive error detection and correction protocols.…

A quantum computer -- i.e., a computer capable of manipulating data in quantum superposition -- would find applications including factoring, quantum simulation and tests of basic quantum theory. Since quantum superpositions are fragile, the…

Quantum Physics · Physics 2007-05-23 Ben W. Reichardt

Realizing practical quantum computing requires overcoming a number of computation errors and the limitation of device size, which have intensively been tackled by quantum error mitigation (QEM) these days. As a unified approach of…

Extending the context window support of large language models (LLMs) is crucial for tasks with long-distance dependencies. RoPE-based interpolation and extrapolation methods, such as linear scaling and frequency-aware schemes, enable longer…

Machine Learning · Computer Science 2025-10-02 Ye Qiao , Haocheng Xu , Xiaofan Zhang , Sitao Huang

Physics-informed extreme learning machine (PIELM) has recently received significant attention as a rapid version of physics-informed neural network (PINN) for solving partial differential equations (PDEs). The key characteristic is to fix…

Machine Learning · Computer Science 2024-09-30 Xu Liu , Wen Yao , Wei Peng , Weien Zhou

Noise in pre-fault-tolerant quantum computers can result in biased estimates of physical observables. Accurate bias-free estimates can be obtained using probabilistic error cancellation (PEC), which is an error-mitigation technique that…

Quantum Physics · Physics 2023-10-25 Ewout van den Berg , Zlatko K. Minev , Abhinav Kandala , Kristan Temme

Variational quantum algorithms (VQAs) offer the most promising path to obtaining quantum advantages via noisy intermediate-scale quantum (NISQ) processors. Such systems leverage classical optimization to tune the parameters of a…

Quantum Physics · Physics 2022-09-26 Sharu Theresa Jose , Osvaldo Simeone

Near term quantum computers suffer from the presence of different noise sources. In order to mitigate for this effect and acquire results with significantly better accuracy, there is the urge of designing efficient error correction or error…

Quantum phase estimation (QPE) is the key subroutine of several quantum computing algorithms as well as a central ingredient in quantum computational chemistry and quantum simulation. While QPE strategies have focused on the estimation of a…

Quantum Physics · Physics 2021-07-26 Valentin Gebhart , Augusto Smerzi , Luca Pezzè

The variational quantum eigensolver (VQE) is generally regarded as a promising quantum algorithm for near-term noisy quantum computers. However, when implemented with the deep circuits that are in principle required for achieving a…

Quantum Physics · Physics 2025-06-05 Simone Cantori , Andrea Mari , David Vitali , Sebastiano Pilati

Recently, a lot of effort has been devoted towards designing erasure qubits in which dominant physical noise excites leakage states whose population can be detected and returned to the qubit subspace. Interest in these erasure qubits has…

Quantum Physics · Physics 2024-08-05 Kathleen Chang , Shraddha Singh , Jahan Claes , Kaavya Sahay , James Teoh , Shruti Puri

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

Quantum Parameter Estimation (QPE) is important from the perspective of both fundamental quantum research and various practical applications of quantum technologies such as for developing optimal quantum control strategies. Standard and…

Quantum Physics · Physics 2024-07-18 Bijita Sarma , Junxin Chen , Sangkha Borah

Logical qubits can be protected from decoherence by performing QEC cycles repeatedly. Algorithms for fault-tolerant QEC must be compiled to the specific hardware platform under consideration in order to practically realize a quantum memory…

Quantum Physics · Physics 2025-05-13 Sascha Heußen , David F. Locher , Markus Müller

Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors on quantum information. Here, we present such a quantum…

Quantum error mitigation is regarded as a possible path to near-term quantum utility. The methods under the quantum error mitigation umbrella term, such as probabilistic error cancellation (PEC), zero-noise extrapolation (ZNE) or Clifford…

Quantum Physics · Physics 2025-09-03 Timon Scheiber , Paul Haubenwallner , Matthias Heller

Quantum embedding is a fundamental prerequisite for applying quantum machine learning techniques to classical data, and has substantial impacts on performance outcomes. In this study, we present Neural Quantum Embedding (NQE), a method that…

Quantum Physics · Physics 2024-08-12 Tak Hur , Israel F. Araujo , Daniel K. Park

Quantum computing requires a universal set of gate operations; regarding gates as rotations, any rotation angle must be possible. However a real device may only be capable of $B$ bits of resolution, i.e. it might support only $2^B$ possible…

Quantum Physics · Physics 2024-03-28 Bálint Koczor , John Morton , Simon Benjamin

Quantum computing technology has the potential to revolutionize the simulation of materials and molecules in the near future. A primary challenge in achieving near-term quantum advantage is effectively mitigating the noise effects inherent…

Quantum Physics · Physics 2024-01-17 Tao Jiang , John Rogers , Marius S. Frank , Ove Christiansen , Yong-Xin Yao , Nicola Lanatà

The minimum error entropy (MEE) criterion has been verified as a powerful approach for non-Gaussian signal processing and robust machine learning. However, the implementation of MEE on robust classification is rather a vacancy in the…

Machine Learning · Computer Science 2025-08-07 Yuanhao Li , Badong Chen , Natsue Yoshimura , Yasuharu Koike
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