85 citations · 101 across the 6 of their papers we have counts for
6 papers
Hardware Efficient Quantum Kernels Using Multimode Bulk Acoustic Resonators
Collin C. D. Frink, Chaoyang Ti, Stephen K. Gray +2
The kernel trick is a widely applicable technique in machine learning domains that maps datasets that are difficult to classify into a computationally friendly feature space. As th…
A Perspective on Quantum Computing Applications in Quantum Chemistry using 25--100 Logical Qubits
Yuri Alexeev, Victor S. Batista, Nicholas Bauman +27
The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owin…
Non-unitary Variational Quantum Eigensolver with the Localized Active Space Method and Cost Mitigation
Qiaohong Wang, Ruhee D'Cunha, Abhishek Mitra +4
Accurately describing strongly correlated systems with affordable quantum resources remains a central challenge for quantum chemistry applications on near and intermediate-term qua…
QREChem: Quantum Resource Estimation Software for Chemistry Applications
Matthew Otten, Byeol Kang, Dmitry Fedorov +4
As quantum hardware continues to improve, more and more application scientists have entered the field of quantum computing. However, even with the rapid improvements in the last fe…
The Localized Active Space Method with Unitary Selective Coupled Cluster
Abhishek Mitra, Ruhee D'Cunha, Qiaohong Wang +5
We introduce a hybrid quantum-classical algorithm, the localized active space unitary selective coupled cluster singles and doubles (LAS-USCCSD) method. Derived from the localized…
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…