Gradient Analysis of Barren Plateau in Parameterized Quantum Circuits with multi-qubit gates

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Hauptverfasser: Yao, Yuhan, Hasegawa, Yoshihiko
Format: Preprint
Veröffentlicht: 2026
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author Yao, Yuhan
Hasegawa, Yoshihiko
author_facet Yao, Yuhan
Hasegawa, Yoshihiko
contents The emergence of the Barren Plateau phenomenon poses a significant challenge to quantum machine learning. While most Barren Plateau analyses focus on single-qubit rotation gates, the gradient behavior of Parameterized Quantum Circuits built from multi-qubit gates remains largely unexplored. In this work, we present a general theoretical framework for analyzing the gradient properties of Parameterized Quantum Circuits with multi-qubit gates. Our method generalizes the direct computation framework, bypassing the Haar random assumption on parameters and enabling the calculation of the gradient expectation and variance. We apply this framework to single-layer and deep-layer circuits, deriving analytical results that quantify how gradient variance is co-determined by the size of the multi-qubit gate and the number of qubits, layers, and effective parameters. Numerical simulations validate our findings. Our study provides a refined framework for analyzing and optimizing Parameterized Quantum Circuits with complex multi-qubit gates.
format Preprint
id arxiv_https___arxiv_org_abs_2602_05288
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Gradient Analysis of Barren Plateau in Parameterized Quantum Circuits with multi-qubit gates
Yao, Yuhan
Hasegawa, Yoshihiko
Quantum Physics
The emergence of the Barren Plateau phenomenon poses a significant challenge to quantum machine learning. While most Barren Plateau analyses focus on single-qubit rotation gates, the gradient behavior of Parameterized Quantum Circuits built from multi-qubit gates remains largely unexplored. In this work, we present a general theoretical framework for analyzing the gradient properties of Parameterized Quantum Circuits with multi-qubit gates. Our method generalizes the direct computation framework, bypassing the Haar random assumption on parameters and enabling the calculation of the gradient expectation and variance. We apply this framework to single-layer and deep-layer circuits, deriving analytical results that quantify how gradient variance is co-determined by the size of the multi-qubit gate and the number of qubits, layers, and effective parameters. Numerical simulations validate our findings. Our study provides a refined framework for analyzing and optimizing Parameterized Quantum Circuits with complex multi-qubit gates.
title Gradient Analysis of Barren Plateau in Parameterized Quantum Circuits with multi-qubit gates
topic Quantum Physics
url https://arxiv.org/abs/2602.05288