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Quantum error correction can reduce the effects of noise in quantum systems, e.g. in metrology or most notably in quantum computing. Typically, this requires making measurements that provide information about the errors that have occurred…

Quantum Physics · Physics 2024-12-12 Christian Wimmer , Jochen Szangolies , Michael Epping

The promise of quantum computing is closer to reality today than ever before, thanks to rapid progress in the development of quantum hardware. Even as qubit lifetimes and gate fidelities continue to improve, realizing robust, fault-tolerant…

Quantum Physics · Physics 2026-04-02 Vismay Joshi , Anubhab Rudra , Sourav Dutta , Siddharth Dhomkar , Prabha Mandayam

Present-day quantum computers suffer from various noises or errors such as gate error, relaxation, dephasing, readout error, and crosstalk. Besides, they offer a limited number of qubits with restrictive connectivity. Therefore, quantum…

Quantum simulation is a promising way toward practical quantum advantage, but noise in current quantum hardware poses a significant obstacle. We prove that not only the physical error but also the algorithmic error in a single Trotter step…

Quantum Physics · Physics 2025-10-29 Jue Xu , Chu Zhao , Junyu Fan , Qi Zhao

Mutation analysis is a well-established technique for assessing test quality in the traditional software development paradigm by injecting artificial faults into programs. Its application to deep learning (DL) has expanded beyond classical…

Software Engineering · Computer Science 2025-12-19 Zaheed Ahmed , Philip Makedonski , Jens Grabowski

We propose a novel dark matter detection scheme by leveraging quantum coherence across a network of multiple quantum sensors. This method effectively eliminates incoherent background noise, thereby significantly enhancing detection…

High Energy Physics - Phenomenology · Physics 2024-10-31 Jing Shu , Bin Xu , Yuan Xu

Quantum machine learning is a discipline that holds the promise of revolutionizing data processing and problem-solving. However, dissipation and noise arising from the coupling with the environment are commonly perceived as major obstacles…

Quantum Physics · Physics 2023-12-18 María Laura Olivera-Atencio , Lucas Lamata , Jesús Casado-Pascual

The speed-up provided by quantum algorithms with respect to their classical counterparts is at the origin of scientific interest in quantum computation. However, the fundamental reasons for such a speed-up are not yet completely understood…

Quantum Physics · Physics 2007-05-23 C. Di Franco , M. Paternostro , M. S. Kim

Quantum error mitigation (QEM) is vital for noisy intermediate-scale quantum (NISQ) devices. While most conventional QEM schemes assume discrete gate-based circuits with noise appearing either before or after each gate, the assumptions are…

Quantum Physics · Physics 2021-03-12 Jinzhao Sun , Xiao Yuan , Takahiro Tsunoda , Vlatko Vedral , Simon C. Bejamin , Suguru Endo

Current noisy intermediate-scale quantum devices suffer from various sources of intrinsic quantum noise. Overcoming the effects of noise is a major challenge, for which different error mitigation and error correction techniques have been…

Noise robustness remains a critical challenge for deploying neural speech codecs in real-world acoustic scenarios where background noise is often inevitable. A key observation we make is that even slight input noise perturbations can cause…

Audio and Speech Processing · Electrical Eng. & Systems 2025-10-14 Rui-Chen Zheng , Yang Ai , Hui-Peng Du , Li-Rong Dai

The dynamics of quantum systems are unavoidably influenced by their environment and in turn observing a quantum system (probe) can allow one to measure its environment: Measurements and controlled manipulation of the probe such as dynamical…

Quantum Physics · Physics 2019-07-16 Matthias M. Müller , Stefano Gherardini , Filippo Caruso

In this paper, we propose a scheme to eliminate the influence of noises on system dynamics, by means of a sequential unsharp measurements and unitary feedback operations. The unsharp measurements are carried out periodically during system…

Quantum Physics · Physics 2018-09-19 Du Ran , Ye-Hong Chen , Zhi-Cheng Shi , Zhen-Biao Yang , Jie Song , Yan Xia

Quantum reservoir computing offers a promising approach to the utilization of complex quantum dynamics in machine learning. Statistical noise inevitably arises in real settings of quantum reservoir computing (QRC) due to the practical…

Quantum Physics · Physics 2026-04-23 Youssef Kora , Christoph Simon

Quantization has become a predominant approach for model compression, enabling deployment of large models trained on GPUs onto smaller form-factor devices for inference. Quantization-aware training (QAT) optimizes model parameters with…

Machine Learning · Computer Science 2022-12-13 Zheng Wang , Juncheng B Li , Shuhui Qu , Florian Metze , Emma Strubell

Measurement based quantum computation (MBQC) is an effective paradigm for universal quantum computation. In this scheme, the universal set of quantum gates are realized by only local measurements on the prior prepared cluster states. The…

Quantum Physics · Physics 2013-11-26 Ding Zhong , Jian Wang , Ning Dai , Liang-Zhu Mu , Heng Fan

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…

How to effectively construct robust quantum gates for time-varying noise is a very important but still outstanding problem. Here we develop a systematic method to find pulses for quantum gate operations robust against both low- and…

Quantum Physics · Physics 2017-08-22 Chia-Hsien Huang , Hsi-Sheng Goan

Advancements in quantum computing have spurred significant interest in harnessing its potential for speedups over classical systems. However, noise remains a major obstacle to achieving reliable quantum algorithms. In this work, we present…

Quantum Physics · Physics 2025-05-29 Lucas Tecot , Di Luo , Cho-Jui Hsieh

Transformers (Vaswani et al., 2017) have brought a remarkable improvement in the performance of neural machine translation (NMT) systems but they could be surprisingly vulnerable to noise. In this work, we try to investigate how noise…

Computation and Language · Computer Science 2021-09-13 Peyman Passban , Puneeth S. M. Saladi , Qun Liu