806 citations · 5.4k across the 44 of their papers we have counts for
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Analyzing the quantum approximate optimization algorithm: ansätze, symmetries, and Lie algebras
Sujay Kazi, Martín Larocca, Marco Farinati +3
The Quantum Approximate Optimization Algorithm (QAOA) has been proposed as a method to obtain approximate solutions for combinatorial optimization tasks. In this work, we study the…
More buck-per-shot: Why learning trumps mitigation in noisy quantum sensing
Aroosa Ijaz, C. Huerta Alderete, Frédéric Sauvage +3
Quantum sensing is one of the most promising applications for quantum technologies. However, reaching the ultimate sensitivities enabled by the laws of quantum mechanics can be a c…
Quantum Convolutional Neural Networks are Effectively Classically Simulable
Pablo Bermejo, Paolo Braccia, Manuel S. Rudolph +3
Quantum Convolutional Neural Networks (QCNNs) are widely regarded as a promising model for Quantum Machine Learning (QML). In this work we tie their heuristic success to two facts.…
Exact spectral gaps of random one-dimensional quantum circuits
Andrew E. Deneris, Pablo Bermejo, Paolo Braccia +2
The spectral gap of local random quantum circuits is a fundamental property that determines how close the moments of the circuit's unitaries match those of a Haar random distributi…
Barren Plateaus in Variational Quantum Computing
Martin Larocca, Supanut Thanasilp, Samson Wang +7
Variational quantum computing offers a flexible computational paradigm with applications in diverse areas. However, a key obstacle to realizing their potential is the Barren Platea…
Computing exact moments of local random quantum circuits via tensor networks
Paolo Braccia, Pablo Bermejo, Lukasz Cincio +1
A basic primitive in quantum information is the computation of the moments . These describe the distribution of expectation values obtained…