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New framework uses Lie symmetries for efficient quantum circuit gradient estimation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework for estimating gradients in parameterized quantum circuits (PQCs) that leverages Lie algebraic symmetries. This method uses the Hadamard test and analyzes the differential of the matrix exponential to express the gradient as a linear combination of expectation values. The approach significantly reduces measurement costs, requiring a logarithmic number of shots with respect to the parameters, and offers a polynomial speed-up in time compared to existing techniques. AI

IMPACT Introduces a novel method for optimizing quantum machine learning models, potentially accelerating research in quantum computing.

RANK_REASON The cluster contains an academic paper detailing a new method for gradient estimation in quantum circuits. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework uses Lie symmetries for efficient quantum circuit gradient estimation

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The cluster contains an academic paper detailing a new method for gradient estimation in quantum circuits. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mohsen Heidari, Masih Mozakka, Wojciech Szpankowski ·

    Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries

    arXiv:2404.05108v3 Announce Type: replace-cross Abstract: Gradient estimation is a central challenge in training parameterized quantum circuits (PQCs) for hybrid quantum-classical optimization and learning problems. This difficulty arises from several factors, including the expon…

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