Copertina

Certifying almost all quantum states with few single-qubit measurements

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Huang, Hsin-Yuan, Preskill, John, Soleimanifar, Mehdi
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Quantum Physics Information Theory Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

When can classical neural networks represent quantum states?
di: Yang, Tai-Hsuan, et al.
Pubblicazione: (2024)

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

Learning to erase quantum states: thermodynamic implications of quantum learning theory
di: Zhao, Haimeng, et al.
Pubblicazione: (2025)

Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes
di: Gu, Shouzhen, et al.
Pubblicazione: (2025)

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

The vast world of quantum advantage
di: Huang, Hsin-Yuan, et al.
Pubblicazione: (2025)

Predicting adaptively chosen observables in quantum systems
di: Huang, Jerry, et al.
Pubblicazione: (2024)

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

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

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

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

Improved machine learning algorithm for predicting ground state properties
di: Lewis, Laura, et al.
Pubblicazione: (2023)

Sample-optimal classical shadows for pure states
di: Grier, Daniel, et al.
Pubblicazione: (2022)

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

Estimating quantum relative entropies on quantum computers
di: Lu, Yuchen, et al.
Pubblicazione: (2025)

Boosted linear-optical measurements on single-rail qubits with unentangled ancillas
di: Sajjad, Aqil, et al.
Pubblicazione: (2026)

Quantum-Enhanced Neural Contextual Bandit Algorithms
di: Huang, Yuqi, et al.
Pubblicazione: (2026)

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

Mixing time of quantum Gibbs sampling for random sparse Hamiltonians
di: Ramkumar, Akshar, et al.
Pubblicazione: (2024)

Efficient Pauli channel estimation with logarithmic quantum memory
di: Chen, Sitan, et al.
Pubblicazione: (2023)

Shor's algorithm is possible with as few as 10,000 reconfigurable atomic qubits
di: Cain, Madelyn, et al.
Pubblicazione: (2026)

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

Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries
di: Heidari, Mohsen, et al.
Pubblicazione: (2024)

Decoding Quantum LDPC Codes Using Graph Neural Networks
di: Ninkovic, Vukan, et al.
Pubblicazione: (2024)

New Bounds on Quantum Sample Complexity of Measurement Classes
di: Heidari, Mohsen, et al.
Pubblicazione: (2024)

Adaptivity can help exponentially for shadow tomography
di: Chen, Sitan, et al.
Pubblicazione: (2024)

Principal eigenstate classical shadows
di: Grier, Daniel, et al.
Pubblicazione: (2024)

Quantization of Ricci Curvature in Information Geometry
di: Rodriguez, Carlos C.
Pubblicazione: (2026)

Toward Practical Quantum Machine Learning: A Novel Hybrid Quantum LSTM for Fraud Detection
di: Ubale, Rushikesh, et al.
Pubblicazione: (2025)

Lower Bounds on Learning Pauli Channels with Individual Measurements
di: Fawzi, Omar, et al.
Pubblicazione: (2023)

Generalization Bounds for Quantum Learning via Rényi Divergences
di: Warsi, Naqueeb Ahmad, et al.
Pubblicazione: (2025)

Performance Guarantees for Quantum Neural Estimation of Entropies
di: Sreekumar, Sreejith, et al.
Pubblicazione: (2025)

Quantum Doeblin Coefficients: Interpretations and Applications
di: George, Ian, et al.
Pubblicazione: (2025)

Equivalence of Privacy and Stability with Generalization Guarantees in Quantum Learning
di: Dasgupta, Ayanava, et al.
Pubblicazione: (2026)

A Mixture of Experts Vision Transformer for High-Fidelity Surface Code Decoding
di: Nguyen, Hoang Viet, et al.
Pubblicazione: (2026)

HyperNQ: A Hypergraph Neural Network Decoder for Quantum LDPC Codes
di: Bhave, Ameya S., et al.
Pubblicazione: (2025)

Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes
di: Mi, Xiangjun, et al.
Pubblicazione: (2025)

Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings
di: Sreekumar, Sreejith, et al.
Pubblicazione: (2026)

Vehicle Routing Problems via Quantum Graph Attention Network Deep Reinforcement Learning
di: Giang, Le Tung, et al.
Pubblicazione: (2025)

Quantum Information Ordering and Differential Privacy
di: Warsi, Naqueeb Ahmad, et al.
Pubblicazione: (2025)