Efficient and effective quantum compiling for entanglement-based machine learning on IBM Q devices

DOI10.1142/S0219749918400063zbMath1407.81061arXiv1801.02363OpenAlexW2901060757WikidataQ128882651 ScholiaQ128882651MaRDI QIDQ4620294

Michele Amoretti, Davide Ferrari

Publication date: 8 February 2019

Published in: International Journal of Quantum Information (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1801.02363

zbMATH Keywords

quantum compilingIBM Qparity learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Quantum computation (81P68) Analytic circuit theory (94C05) Quantum coherence, entanglement, quantum correlations (81P40)

Related Items (1)

Deterministic algorithms for compiling quantum circuits with recurrent patterns

Uses Software

• GitHub
• QISKit

Cites Work

• Unnamed Item
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• Model checking at IBM
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• On Learning Ring-Sum-Expansions
• Learning Integer Lattices
• On the inherent intractability of certain coding problems (Corresp.)
• Learning DNF over the Uniform Distribution Using a Quantum Example Oracle
• Some optimal inapproximability results
• On lattices, learning with errors, random linear codes, and cryptography

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