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We propose a fault-tolerant quantum error correction architecture consisting of a linear array of emitters and delay lines. In our scheme, a resource state for fault-tolerant quantum computation is generated by letting the emitters interact…

Quantum Physics · Physics 2025-04-02 Jintae Kim , Jung Hoon Han , Isaac H. Kim

Quantum error correction is necessary to perform large-scale quantum computations in the presence of noise and decoherence. As a result, several aspects of quantum error correction have already been explored. These have been primarily…

Quantum Physics · Physics 2021-08-05 Ariel Shlosberg , Anthony M. Polloreno , Graeme Smith

Adversarial attacks represent a substantial challenge in Natural Language Processing (NLP). This study undertakes a systematic exploration of this challenge in two distinct phases: vulnerability evaluation and resilience enhancement of…

Computation and Language · Computer Science 2024-02-16 Álvaro Huertas-García , Alejandro Martín , Javier Huertas-Tato , David Camacho

We present a general framework for applying linear quantum error mitigation (QEM) techniques directly to physical qubits within a logical qubit to suppress logical errors. By exploiting the linearity of quantum error correction (QEC), we…

Quantum Physics · Physics 2026-01-27 Minjun Jeon , Zhenyu Cai

Quantum computers have the possibility of a much reduced calculation load compared with classical computers in specific problems. Quantum error correction (QEC) is vital for handling qubits, which are vulnerable to external noise. In QEC,…

Machine Learning · Computer Science 2025-12-15 Hideo Mukai , Hoshitaro Ohnishi

Quantum error correction is an essential technique for constructing a scalable quantum computer. In order to implement quantum error correction with near-term quantum devices, a fast and near-optimal decoding method is demanded. A decoder…

Quantum Physics · Physics 2020-09-16 Amarsanaa Davaasuren , Yasunari Suzuki , Keisuke Fujii , Masato Koashi

Recent studies reveal that well-performing reinforcement learning (RL) agents in training often lack resilience against adversarial perturbations during deployment. This highlights the importance of building a robust agent before deploying…

Machine Learning · Computer Science 2024-10-07 Tung M. Luu , Thanh Nguyen , Tee Joshua Tian Jin , Sungwoon Kim , Chang D. Yoo

Quantum error correction is a critical component for scaling up quantum computing. Given a quantum code, an optimal decoder maps the measured code violations to the most likely error that occurred, but its cost scales exponentially with the…

Quantum Physics · Physics 2023-04-18 Evgenii Egorov , Roberto Bondesan , Max Welling

Noise in quantum computing is countered with quantum error correction. Achieving optimal performance will require tailoring codes and decoding algorithms to account for features of realistic noise, such as the common situation where the…

Quantum Physics · Physics 2020-04-02 David K. Tuckett , Stephen D. Bartlett , Steven T. Flammia , Benjamin J. Brown

This work addresses the open question of implementing fault-tolerant QRLCs with feasible computational overhead. We present a new decoder for quantum random linear codes (QRLCs) capable of dealing with imperfect decoding operations. A first…

Quantum Physics · Physics 2024-07-08 Diogo Cruz , Francisco A. Monteiro , André Roque , Bruno C. Coutinho

We demonstrate that the performance of quantum error correction can be improved with noise-aware decoders that are calibrated to the likelihood of physical error configurations in a device. We show that noise-aware decoding increases the…

Quantum Physics · Physics 2025-04-02 Evan T. Hockings , Andrew C. Doherty , Robin Harper

Active quantum error correction using qubit stabilizer codes has emerged as a promising, but experimentally challenging, engineering program for building a universal quantum computer. In this review we consider the formalism of qubit…

Quantum Physics · Physics 2015-04-13 Barbara M. Terhal

Error correction code is a major part of the communication physical layer, ensuring the reliable transfer of data over noisy channels. Recently, neural decoders were shown to outperform classical decoding techniques. However, the existing…

Machine Learning · Computer Science 2022-03-30 Yoni Choukroun , Lior Wolf

The remarkable discovery of Quantum Error Correction (QEC), which can overcome the errors experienced by a bit of quantum information (qubit), was a critical advance that gives hope for eventually realizing practical quantum computers. In…

According to recent studies, the vulnerability of state-of-the-art Neural Networks to adversarial input samples has increased drastically. A neural network is an intermediate path or technique by which a computer learns to perform tasks…

Computer Vision and Pattern Recognition · Computer Science 2022-03-22 Anirudh Yadav , Ashutosh Upadhyay , S. Sharanya

Studies of quantum error correction (QEC) typically focus on stochastic Pauli errors because the existence of a threshold error rate below which stochastic Pauli errors can be corrected implies that there exists a threshold below which…

Quantum Physics · Physics 2023-06-27 Stefanie J. Beale , Joel J. Wallman

Quantum key distribution (QKD) allows two distant parties to share encryption keys with security based on laws of quantum mechanics. In order to share the keys, the quantum bits have to be transmitted from the sender to the receiver over a…

Information Theory · Computer Science 2019-09-09 Sathwik Chadaga , Mridul Agarwal , Vaneet Aggarwal

We instantiate the quantum reservoir autoencoder (QRA) with a noise-induced reservoir employing reset noise channels and address two open problems: noise-resilient reversibility and blind decryption. For a single-ciphertext protocol with 10…

Quantum Physics · Physics 2026-03-16 Hikaru Wakaura , Taiki Tanimae

Quantum error correction (QEC) is essential for reliable quantum information processing. Targeting a particular error channel, both the encoding and the recovery channel can be optimized through a biconvex optimization to give a…

Quantum Physics · Physics 2025-05-20 Xuanhui Mao , Qian Xu , Liang Jiang

Recent work has shown the impact of adversarial machine learning on deep neural networks (DNNs) developed for Radio Frequency Machine Learning (RFML) applications. While these attacks have been shown to be successful in disrupting the…

Signal Processing · Electrical Eng. & Systems 2021-01-05 Matthew DelVecchio , Bryse Flowers , William C. Headley