Efficient and Effective Quantum Compiling for Entanglement-based Machine Learning on IBM Q Devices
January 08, 2018 Β· Declared Dead Β· π International Journal of Quantum Information
"No code URL or promise found in abstract"
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Authors
Davide Ferrari, Michele Amoretti
arXiv ID
1801.02363
Category
quant-ph: Quantum Computing
Cross-listed
cs.DS,
cs.LG,
cs.SE
Citations
13
Venue
International Journal of Quantum Information
Last Checked
5 months ago
Abstract
Quantum compiling means fast, device-aware implementation of quantum algorithms (i.e., quantum circuits, in the quantum circuit model of computation). In this paper, we present a strategy for compiling IBM Q -aware, low-depth quantum circuits that generate Greenberger-Horne-Zeilinger (GHZ) entangled states. The resulting compiler can replace the QISKit compiler for the specific purpose of obtaining improved GHZ circuits. It is well known that GHZ states have several practical applications, including quantum machine learning. We illustrate our experience in implementing and querying a uniform quantum example oracle based on the GHZ circuit, for solving the classically hard problem of learning parity with noise.
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