2 citations · 2 across the 5 of their papers we have counts for
10 papers · 1 filter
Realizing Quantum Kernel Models at Scale with Matrix Product State Simulation
Mekena Metcalf, Pablo Andrés-Martínez, Nathan Fitzpatrick
Data representation in quantum state space offers an alternative function space for machine learning tasks. However, benchmarking these algorithms at a practical scale has been lim…
Quantum Multiple Kernel Learning in Financial Classification Tasks
Shungo Miyabe, Brian Quanz, Noriaki Shimada +11
Financial services is a prospect industry where unlocked near-term quantum utility could yield profitable potential, and, in particular, quantum machine learning algorithms could p…
Reinforcement learning pulses for transmon qubit entangling gates
Ho Nam Nguyen, Felix Motzoi, Mekena Metcalf +3
The utility of a quantum computer depends heavily on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular i…
Emergent Order in Classical Data Representations on Ising Spin Models
Jorja J. Kirk, Matthew D. Jackson, Daniel J. M. King +2
Encoding classical data on quantum spin Hamiltonians yields ordered spin ground states which are used to discriminate data types for binary classification. The Ising Hamiltonian is…
Compact Molecular Simulation on Quantum Computers via Combinatorial Mapping and Variational State Preparation
Diana Chamaki, Mekena Metcalf, Wibe A. de Jong
Compact representations of fermionic Hamiltonians are necessary to perform calculations on quantum computers that lack error-correction. A fermionic system is typically defined wit…
Quantum Markov Chain Monte Carlo with Digital Dissipative Dynamics on Quantum Computers
Mekena Metcalf, Emma Stone, Katherine Klymko +3
Modeling the dynamics of a quantum system connected to the environment is critical for advancing our understanding of complex quantum processes, as most quantum processes in nature…