Cover Image

Discovering highly efficient low-weight quantum error-correcting codes with reinforcement learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Austin Yubo, Liu, Zi-Wen
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics Artificial Intelligence Information Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Discovering highly efficient low-weight quantum error-correcting codes with reinforcement learning
by: He, Austin Yubo, et al.
Published: (2025)

Discovering autonomous quantum error correction via deep reinforcement learning
by: Yin, Yue, et al.
Published: (2025)

Universal scaling laws in quantum-probabilistic machine learning by tensor network towards interpreting representation and generalization powers
by: Bai, Sheng-Chen, et al.
Published: (2024)

Curriculum reinforcement learning for quantum architecture search under hardware errors
by: Patel, Yash J., et al.
Published: (2024)

Sample-efficient quantum error mitigation via classical learning surrogates
by: Liao, Wei-You, et al.
Published: (2025)

Quantum-secure multiparty deep learning
by: Sulimany, Kfir, et al.
Published: (2024)

Deflating quantum error-correcting codes
by: Gundersen, Jaron Skovsted, et al.
Published: (2025)

Theory of low-weight quantum codes
by: Wei, Fuchuan, et al.
Published: (2026)

Exponential quantum advantage in processing massive classical data
by: Zhao, Haimeng, et al.
Published: (2026)

Transition Role of Entangled Data in Quantum Machine Learning
by: Wang, Xinbiao, et al.
Published: (2023)

Neural Minimum Weight Perfect Matching for Quantum Error Codes
by: Peled, Yotam, et al.
Published: (2026)

Training-efficient density quantum machine learning
by: Coyle, Brian, et al.
Published: (2024)

Enhancing variational quantum state diagonalization using reinforcement learning techniques
by: Kundu, Akash, et al.
Published: (2023)

A quantum-classical reinforcement learning model to play Atari games
by: Freinberger, Dominik, et al.
Published: (2024)

Prior-dependent analysis of posterior sampling reinforcement learning with function approximation
by: Li, Yingru, et al.
Published: (2024)

Existence of Pauli-like stabilizers for every quantum error-correcting code
by: Kao, Jhih-Yuan, et al.
Published: (2023)

Improving thermal state preparation of Sachdev-Ye-Kitaev model with reinforcement learning on quantum hardware
by: Kundu, Akash
Published: (2025)

BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
by: Ikhtiarudin, Azhar, et al.
Published: (2025)

Discovering emergent connections in quantum physics research via dynamic word embeddings
by: Frohnert, Felix, et al.
Published: (2024)

Towards sample-optimal learning of bosonic Gaussian quantum states
by: Chen, Senrui, et al.
Published: (2026)

Transversal non-Clifford gates on almost-good quantum LDPC and quantum locally testable codes
by: Li, Yiming, et al.
Published: (2026)

Complexity and order in approximate quantum error-correcting codes
by: Yi, Jinmin, et al.
Published: (2023)

Shadows of quantum machine learning
by: Jerbi, Sofiene, et al.
Published: (2023)

Learning shallow quantum circuits
by: Huang, Hsin-Yuan, et al.
Published: (2024)

Reinforcement learning for quantum processes with memory
by: Lumbreras, Josep, et al.
Published: (2026)

Reinforcement learning-assisted quantum architecture search for variational quantum algorithms
by: Kundu, Akash
Published: (2024)

Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware
by: Kundu, Akash, et al.
Published: (2024)

The power and limitations of learning quantum dynamics incoherently
by: Jerbi, Sofiene, et al.
Published: (2023)

Information-theoretic generalization bounds for learning from quantum data
by: Caro, Matthias, et al.
Published: (2023)

Parameterized quantum comb and simpler circuits for reversing unknown qubit-unitary operations
by: Mo, Yin, et al.
Published: (2024)

A Scalable Quantum Non-local Neural Network for Image Classification
by: Gupta, Sparsh, et al.
Published: (2024)

Khovanov homology and quantum error-correcting codes
by: Akhmechet, Rostislav, et al.
Published: (2024)

An invitation to the sample complexity of quantum hypothesis testing
by: Cheng, Hao-Chung, et al.
Published: (2024)

Training quantum machine learning models on cloud without uploading the data
by: He, Guang Ping
Published: (2024)

Tight bounds on Pauli channel learning without entanglement
by: Chen, Senrui, et al.
Published: (2023)

Ansatz-free Hamiltonian learning with Heisenberg-limited scaling
by: Hu, Hong-Ye, et al.
Published: (2025)

A learning theory for quantum photonic processors and beyond
by: Rosati, Matteo
Published: (2022)

Generative quantum machine learning via denoising diffusion probabilistic models
by: Zhang, Bingzhi, et al.
Published: (2023)

Certifying almost all quantum states with few single-qubit measurements
by: Huang, Hsin-Yuan, et al.
Published: (2024)

Instance-optimal high-precision shadow tomography with few-copy measurements: A metrological approach
by: Chen, Senrui, et al.
Published: (2026)