37 citations
- Google (United States)US2 papers
- Imperial College LondonGB2 papers
- Initial Teaching Alphabet FoundationUS2 papers
- Turing InstituteGB2 papers
- Duke UniversityUS1 paper
- Helmholtz-Zentrum Dresden-RossendorfDE1 paper
- Royal Holloway University of LondonGB1 paper
- Stanford UniversityUS1 paper
- The Alan Turing InstituteGB1 paper
- University of California, IrvineUS1 paper
- University of EdinburghGB1 paper
5 papers
Iterative Quantum Optimization with Adaptive Problem Hamiltonian
Yifeng Rocky Zhu, David Joseph, Cong Ling +1
Quantum optimization algorithms hold the promise of solving classically hard, discrete optimization problems in practice. The requirement of encoding such problems in a Hamiltonian…
Density Matrix Renormalization Group with Tensor Processing Units
Martin Ganahl, Jackson Beall, Markus Hauru +4
Google's Tensor Processing Units (TPUs) are integrated circuits specifically built to accelerate and scale up machine learning workloads. They can perform fast distributed matrix m…
Variational quantum solutions to the Shortest Vector Problem
Martin R. Albrecht, Miloš Prokop, Yixin Shen +1
A fundamental computational problem is to find a shortest non-zero vector in Euclidean lattices, a problem known as the Shortest Vector Problem (SVP). This problem is believed to b…
Large scale quantum chemistry with Tensor Processing Units
Ryan Pederson, John Kozlowski, Ruyi Song +8
We demonstrate the use of Google's cloud-based Tensor Processing Units (TPUs) to accelerate and scale up conventional (cubic-scaling) density functional theory (DFT) calculations.…
Quantum mean value approximator for hard integer value problems
David Joseph, Antonio J. Martinez, Cong Ling +1
Evaluating the expectation of a quantum circuit is a classically difficult problem known as the quantum mean value problem (QMV). It is used to optimize the quantum approximate opt…