Learning Spectral Properties of Boolean Functions: A Unifying Theme in Quantum Algorithms

Quantum computing algorithms are often presented with a notation and perspective inspired by physics. We instead relate a family of quantum algorithms to the classical problem of learning spectral properties of boolean functions.

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Published
2024-09-16
DOI
https://doi.org/10.1109/synasc65383.2024.00013
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
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article

Learning Spectral Properties of Boolean Functions: A Unifying Theme in Quantum Algorithms

Mohsen Heidari, Amr Sabry
Quantum Computing Algorithms and Architecture
article

Learning Spectral Properties of Boolean Functions: A Unifying Theme in Quantum Algorithms

Mohsen Heidari, Amr Sabry
article en

Abstract

Quantum computing algorithms are often presented with a notation and perspective inspired by physics. We instead relate a family of quantum algorithms to the classical problem of learning spectral properties of boolean functions.

Indiana University Bloomington (US)
Openalex Percentile: Top 75%
Quantum Computing Algorithms and Architecture
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Learning Spectral Properties of Boolean Functions: A Unifying Theme in Quantum Algorithms — Mohsen Heidari, Amr Sabry · (2024) | TGRS Research Map | TGRS