3.3k citations · 11.2k across the 86 of their papers we have counts for
88 papers
Multivariate quantum state preparation with optimized tensor networks
Matthew L. Sims-Goh, Lukasz Cincio, Annina Z. Lieberherr +2
Quantics tensor trains are attracting intense interest for quantum-inspired computing and quantum state preparation. These methods, which approximate continuum functions by represe…
Exponentially many initializations to avoid barren plateaus
Ankit Kulshrestha, Ricard Puig, Diego García-Martín +4
Barren plateaus are stated as an average-case phenomenon: pick an ansatz, initialize it naively, and concentration follows. This has led to the common view that a potential cure fo…
Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
Elijah Pelofske, Marek Rams, Andreas Bärtschi +4
The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One…
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…
Resilience-Runtime Tradeoff Relations for Quantum Algorithms
Luis Pedro García-Pintos, Tom O'Leary, Tanmoy Biswas +4
A leading approach to algorithm design aims to minimize the number of operations in an algorithm's compilation. One intuitively expects that reducing the number of operations may d…
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.…