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Quantum Machine Learning Quantum Simulation

Demonstrating Quantum Homomorphic Encryption Through Simulation

arXiv

Authors: Sohrab Ganjian, Connor Paddock, Anne Broadbent

Year

2024

Paper ID

66187

Status

Preprint

Abstract Read

~2 min

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Abstract

Quantum homomorphic encryption (QHE), allows a quantum cloud server to compute on private data as uploaded by a client. We provide a proof-of-concept software simulation for QHE, according to the "EPR" scheme of Broadbent and Jeffery, for universal quantum circuits. We demonstrate the near-term viability of this scheme and provide verification that the additional cost of homomorphic circuit evaluation is minor when compared to the simulation cost of the quantum operations. Our simulation toolkit is an open-source Python implementation, that serves as a step towards further hardware applications of quantum homomorphic encryption between networked quantum devices.

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This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
It adds a 2024 reference point for readers tracking recent quantum research.
Quantum homomorphic encryption (QHE), allows a quantum cloud server to compute on private data as uploaded by a client.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2406.16247 [2] arXiv https://arxiv.org/abs/2406.16247 [3] Publisher https://arxiv.org/abs/2406.16247

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