Authors: Junyu Zhou, Yuhao Liu, Yunong Shi, Ali Javadi-Abhari, Gushu Li

Published on: February 03, 2024

Impact Score: 8.22

Arxiv code: Arxiv:2402.02279

Summary

• What is new: Introduces Bosehedral, a compiler optimization framework for Bosonic quantum computing, focusing on handling infinite-dimensional qumodes efficiently.
• Why this is important: Lack of compiler optimizations in Bosonic quantum computing has limited its potential for practical applications.
• What the research proposes: Bosehedral uses a compact unitary matrix representation for program analysis and optimizations, optimizing qumode gate decomposition and mapping, and a probabilistic gate dropout method.
• Results: Significant improvement in performance by reducing the program size while maintaining high approximation fidelity, leading to better end-to-end application performance.

Technical Details

Technological frameworks used: Bosehedral

Models used: Gaussian Boson sampling models

Data used: Unitary matrix representation for infinite-dimensional qumode gates

Potential Impact

Quantum computing market, particularly companies developing quantum computing hardware and applications that rely on Bosonic quantum computing

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