From the 1 of 7 linked papers with an AI index.
1 citations · 1 across the 3 of their papers we have counts for
7 papers
Quantum Gaussian processes for prediction of channel observations
Jonas Jäger, Yaroslav Khmelnitskiy, Paolo Braccia +4
Given a set of input states, we consider the task of predicting the expectation value of a Pauli observable at the output of an unknown quantum evolution, using only a limited numb…
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…
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…
Improving the efficiency of learning-based error mitigation
Piotr Czarnik, Michael McKerns, Andrew T. Sornborger +1
Error mitigation will play an important role in practical applications of near-term noisy quantum computers. Current error mitigation methods typically concentrate on correction qu…
Efficient Online Quantum Circuit Learning with No Upfront Training
Tom O'Leary, Piotr Czarnik, Elijah Pelofske +3
We propose a surrogate-based method for optimizing parameterized quantum circuits which is designed to operate with few calls to a quantum computer. We employ a computationally ine…