85 citations · 105 across the 26 of their papers we have counts for
7 papers · 2 filters
Quantum Homotopy Algorithm for Solving Nonlinear PDEs and Flow Problems
Sachin S. Bharadwaj, Balasubramanya Nadiga, Stephan Eidenbenz +1
Quantum algorithms to integrate nonlinear PDEs governing flow problems are challenging to discover but critical to enhancing the practical usefulness of quantum computing. We prese…
Quantum Data Learning of Topological-to-Ferromagnetic Phase Transitions in the 2+1D Toric Code Loop Gas Model
Shamminuj Aktar, Rishabh Bhardwaj, Andreas Bärtschi +2
Quantum data learning (QDL) provides a framework for extracting physical insights directly from quantum states, bypassing the need for any identification of the classical observabl…
Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
Elijah Pelofske, Marek Rams, Andreas Bärtschi +4
The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One…
MPS-JuliQAOA: User-friendly, Scalable MPS-based Simulation for Quantum Optimization
Sean Feeney, Reuben Tate, John Golden +1
We present the MPS-JuliQAOA simulator, a user-friendly, open-source tool to simulate the Quantum Approximate Optimization Algorithm (QAOA) of any optimization problem that can be e…
Variational Quantum Simulations of a Two-Dimensional Frustrated Transverse-Field Ising Model on a Trapped-Ion Quantum Computer
Ammar Kirmani, Elijah Pelofske, Andreas Bärtschi +2
Quantum computers are an ideal platform to study the ground state properties of strongly correlated systems due to the limitation of classical computing techniques particularly for…
Quantum Approximate Multi-Objective Optimization
Ayse Kotil, Elijah Pelofske, Stephanie Riedmüller +4
The goal of multi-objective optimization is to understand optimal trade-offs between competing objective functions by finding the Pareto front, i.e., the set of all Pareto optimal…
Enhancing Quantum Expectation Values via Exponential Error Suppression and CVaR Optimization
Touheed Anwar Atif, Reuben Blake Tate, Stephan Eidenbenz
Precise quantum expectation values are crucial for quantum algorithm development, but noise in real-world systems can degrade these estimations. While quantum error correction is r…