Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

The overheads of classical decoding for quantum error correction in cryogenic quantum
systems grow rapidly with the number of logical qubits and their correction code distance …

In this work, we migrate the quantum error mitigation technique of Zero-Noise Extrapolation
(ZNE) to fault-tolerant quantum computing. We employ ZNE on logically encoded qubits …

Quantum computing technology has grown rapidly in recent years, with new technologies
being explored, error rates being reduced, and quantum processors' qubit capacity growing …

Designing performant and noise-robust circuits for Quantum Machine Learning (QML) is
challenging---the design space scales exponentially with circuit size, and there are few well …

With the increasing maturity and scale of quantum hardware and its integration into HPC
systems, there is a need to develop robust techniques for developing, characterizing, and …

The field of quantum computing has experienced a rapid expansion in recent years, with
ongoing exploration of new technologies, a decrease in error rates, and a growth in the …

This work presents a novel quantum system characterization and error mitigation framework
that applies Pauli check sandwiching (PCS). We motivate our work with prior art in software …

Employing quantum mechanical resources in computing and networking opens the door to
new computation and communication models and potential disruptive advantages over …