53 citations · 186 across the 25 of their papers we have counts for
6 papers · 1 filter
Classical Combinatorial Optimization Scaling for Random Ising Models on 2D Heavy-Hex Graphs
Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz
Motivated by near term quantum computing hardware limitations, combinatorial optimization problems that can be addressed by current quantum algorithms and noisy hardware with littl…
Generative Discrete Event Process Simulation for Hidden Markov Models to Predict Competitor Time-to-Market
Nandakishore Santhi, Stephan Eidenbenz, Brian Key +1
We study the challenge of predicting the time at which a competitor product, such as a novel high-capacity EV battery or a new car model, will be available to customers; as new inf…
Quantum Approximate Optimization: A Computational Intelligence Perspective
Christo Meriwether Keller, Satyajayant Misra, Andreas Bärtschi +1
Quantum computing is an emerging field on the multidisciplinary interface between physics, engineering, and computer science with the potential to make a large impact on computatio…
Potential Applications of Quantum Computing at Los Alamos National Laboratory
Andreas Bärtschi, Francesco Caravelli, Carleton Coffrin +16
The emergence of quantum computing technology over the last decade indicates the potential for a transformational impact in the study of quantum mechanical systems. It is natural t…
Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation
Shamminuj Aktar, Andreas Bärtschi, Diane Oyen +2
Parameterized quantum circuits (PQCs) are fundamental to quantum machine learning (QML), quantum optimization, and variational quantum algorithms (VQAs). The expressibility of PQCs…
Trainability Barriers in Low-Depth QAOA Landscapes
Joel Rajakumar, John Golden, Andreas Bärtschi +1
The Quantum Alternating Operator Ansatz (QAOA) is a prominent variational quantum algorithm for solving combinatorial optimization problems. Its effectiveness depends on identifyin…