65 citations · 105 across the 10 of their papers we have counts for
6 papers · 2 filters
Measuring error rates of mid-circuit measurements
Daniel Hothem, Jordan Hines, Charles Baldwin +3
High-fidelity mid-circuit measurements, which read out the state of specific qubits in a multiqubit processor without destroying them or disrupting their neighbors, are a critical…
A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations
Avimita Chatterjee, Sonny Rappaport, Anish Giri +5
Quantum Hamiltonian simulation is one of the most promising applications of quantum computing and forms the basis for many quantum algorithms. Benchmarking them is an important gau…
A Practical Introduction to Benchmarking and Characterization of Quantum Computers
Akel Hashim, Long B. Nguyen, Noah Goss +16
Rapid progress in quantum technology has transformed quantum computing and quantum information science from theoretical possibilities into tangible engineering challenges. Breakthr…
Benchmarking quantum computers
Timothy Proctor, Kevin Young, Andrew D. Baczewski +1
The rapid pace of development in quantum computing technology has sparked a proliferation of benchmarks for assessing the performance of quantum computing hardware and software. Go…
Pauli Noise Learning for Mid-Circuit Measurements
Jordan Hines, Timothy Proctor
Current benchmarks for mid-circuit measurements (MCMs) are limited in scalability or the types of error they can quantify, necessitating new techniques for quantifying their perfor…
What is my quantum computer good for? Quantum capability learning with physics-aware neural networks
Daniel Hothem, Ashe Miller, Timothy Proctor
Quantum computers have the potential to revolutionize diverse fields, including quantum chemistry, materials science, and machine learning. However, contemporary quantum computers…