From the 1 of 9 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
9 papers
A framework of partial error correction for intermediate-scale quantum computers
Nikolaos Koukoulekidis, Samson Wang, Tom O'Leary +3
The paper proposes a framework for using error correction on only a subset of qubits in intermediate‑scale quantum computers, showing that mixing error‑corrected and noisy qubits c…
Robust design under uncertainty in quantum error mitigation
Maksym Prodius, Piotr Czarnik, Michael McKerns +2
Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical post-processing of quantum computation outcomes is a popular approach for error mitigati…
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…
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…
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…