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AMARETTO: Enabling Efficient Quantum Algorithm Emulation on Low-Tier FPGAs

Authors: Conti, Christian; Volpe, Deborah; Graziano, Mariagrazia; Zamboni, Maurizio; Turvani, Giovanna;

AMARETTO: Enabling Efficient Quantum Algorithm Emulation on Low-Tier FPGAs

Abstract

Researchers and industries are increasingly drawn to quantum computing for its computational potential. However, validating new quantum algorithms is challenging due to the limitations of current quantum devices. Software simulators are time and memory-consuming, making hardware emulators an attractive alternative. This article introduces AMARETTO (quAntuM ARchitecture EmulaTion TechnOlogy), designed for quantum computing emulation on low-tier Field-Programmable gate arrays (FPGAs), supporting Clifford+T and rotational gate sets. It simplifies and accelerates the verification of quantum algorithms using a Reduced-Instruction-Set-Computer (RISC)-like structure and efficient handling of sparse quantum gates. A dedicated compiler translates OpenQASM 2.0 into RISC-like instructions. AMARETTO is validated against the Qiskit simulators. Our results show successful emulation of sixteen qubits on a AMD Kria KV260 SoM. This approach rivals other works in emulated qubit capacity on a smaller, more affordable FPGA

paper accepted at the IEEE International Conference on Electronics Circuits and Systems 2024 conference, 4 pages, 6 figures

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Keywords

Quantum Physics, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Physical sciences, Quantum Computing Emulation; Field Programmable Gate Array; Quantum Algorithm Verification; Quantum Computing Simulation, Systems and Control (eess.SY), Quantum Physics (quant-ph), Systems and Control

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green