YAQQ: Yet Another Quantum Quantizer -- Design Space Exploration of Quantum Gate Sets using Novelty Search
Aritra Sarkar, Akash Kundu, Matthew Steinberg, Sibasish Mishra,, Sebastiaan Fauquenot, Tamal Acharya, Jaros{\l}aw A. Miszczak, Sebastian Feld

TL;DR
This paper introduces YAQQ, a software tool that explores quantum gate set design space using novelty search to optimize quantum circuit decomposition based on fidelity, depth, and novelty, aiding in quantum processor and algorithm design.
Contribution
The paper presents YAQQ, a novel software framework that employs novelty search and stochastic optimization to identify optimal quantum gate sets for various quantum computing tasks.
Findings
YAQQ effectively identifies advantageous quantum gate sets.
The tool improves quantum circuit fidelity and depth tradeoffs.
Practical applications include error correction and processor-specific compilation.
Abstract
In the standard circuit model of quantum computation, the number and quality of the quantum gates composing the circuit influence the runtime and fidelity of the computation. The fidelity of the decomposition of quantum algorithms, represented as unitary matrices, to bounded depth quantum circuits depends strongly on the set of gates available for the decomposition routine. To investigate this dependence, we explore the design space of discrete quantum gate sets and present a software tool for comparative analysis of quantum processing units and control protocols based on their native gates. The evaluation is conditioned on a set of unitary transformations representing target use cases on the quantum processors. The cost function considers three key factors: (i) the statistical distribution of the decomposed circuits' depth, (ii) the statistical distribution of process fidelities for…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Neural Networks and Reservoir Computing · Evolutionary Algorithms and Applications
