Neurocomputing approach to matrix product state using quantum dynamics

DOI10.1007/S11128-018-2053-0zbMath1400.81068OpenAlexW2890371450WikidataQ129273153 ScholiaQ129273153MaRDI QIDQ1994719

Ajay Kumar, Amandeep Singh Bhatia

Publication date: 1 November 2018

Published in: Quantum Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11128-018-2053-0

zbMATH Keywords

quantum dynamicsmatrix product statequantum probabilistic logic nodequantum RAM-based nodequantum weightless neural networks

Mathematics Subject Classification ID

Searching and sorting (68P10) Learning and adaptive systems in artificial intelligence (68T05) Quantum computation (81P68) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Quantum coherence, entanglement, quantum correlations (81P40)

Related Items (2)

Quantum \(\omega\)-automata over infinite words and their relationships ⋮ Matrix Product State–Based Quantum Classifier

Cites Work

• Unnamed Item
• A practical introduction to tensor networks: Matrix product states and projected entangled pair states
• The quest for a quantum neural network
• Quantifying matrix product state
• Neural networks with quantum architecture and quantum learning
• Quantum Computation and Quantum Information
• Handbook of Finite State Based Models and Applications
• MEASUREMENT-BASED QUANTUM COMPUTATION WITH CLUSTER STATES

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