86 citations · 408 across the 11 of their papers we have counts for
11 papers
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…
A Model for Circuit Execution Runtime And Its Implications for Quantum Kernels At Practical Data Set Sizes
Travis L. Scholten, Derrick Perry, Joseph Washington +2
Quantum machine learning (QML) is a fast-growing discipline within quantum computing. One popular QML algorithm, quantum kernel estimation, uses quantum circuits to estimate a simi…
Representation Learning via Quantum Neural Tangent Kernels
Junyu Liu, Francesco Tacchino, Jennifer R. Glick +2
Variational quantum circuits are used in quantum machine learning and variational quantum simulation tasks. Designing good variational circuits or predicting how well they perform…
Approximate Solutions of Combinatorial Problems via Quantum Relaxations
Bryce Fuller, Charles Hadfield, Jennifer R. Glick +8
Combinatorial problems are formulated to find optimal designs within a fixed set of constraints. They are commonly found across diverse engineering and scientific domains. Understa…
Covariant quantum kernels for data with group structure
Jennifer R. Glick, Tanvi P. Gujarati, Antonio D. Corcoles +4
The use of kernel functions is a common technique to extract important features from data sets. A quantum computer can be used to estimate kernel entries as transition amplitudes o…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…
Quantum Algorithms for Mixed Binary Optimization applied to Transaction Settlement
Lee Braine, Daniel J. Egger, Jennifer Glick +1
We extend variational quantum optimization algorithms for Quadratic Unconstrained Binary Optimization problems to the class of Mixed Binary Optimization problems. This allows us to…
Generating remote entanglement via disentangling operations
Jennifer R. Glick, Christoph Adami
Shared entanglement between spatially separated systems is an essential resource for quantum information processing including long-distance quantum cryptography and teleportation.…
Markovian and non-Markovian quantum measurements
Jennifer R. Glick, Christoph Adami
Consecutive measurements performed on the same quantum system can reveal fundamental insights into quantum theory's causal structure, and probe different aspects of the quantum mea…
Quantum information theory of the Bell-state quantum eraser
Jennifer R. Glick, Christoph Adami
Quantum systems can display particle- or wave-like properties, depending on the type of measurement that is performed on them. The Bell-state quantum eraser is an experiment that b…
Quantum Mechanics of Consecutive Measurements
Jennifer R. Glick, Christoph Adami
Consecutive quantum measurements performed on the same system can reveal fundamental insights into quantum theory's causal structure, and probe different aspects of the quantum mea…