181 citations · 333 across the 18 of their papers we have counts for
16 papers · 1 filter
Efficient Circuit Transpilation of Commuting Gates on 2D Grids
Sabina Drăgoi, Daniel J. Egger
Combinatorial optimization problems are central to many applications but can be challenging to solve. Quantum approaches such as the Quantum Approximate Optimization Algorithm (QAO…
Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting
Filip B. Maciejewski, Stuart Hadfield, Oscar Wallis +5
Progress towards a quantum advantage using known heuristic methods for combinatorial optimization is impeded by hardware noise and limited qubit count. Here, we propose a noise-awa…
Optimizing Symmetry Informed Probabilistic Error Cancellation
Tom O'Leary, Daniel J. Egger, Dieter Jaksch
We show that combining quantum error detection (QED) with probabilistic error cancellation (PEC) gives more accurate and lower-variance estimates than PEC alone, provided that the…
Setting angles in quantum approximate optimization at utility-scale
Maosheng Guo, Joel Jurado Diaz, Anurag Ramesh +16
The quantum approximate optimization algorithm (QAOA) is a powerful heuristic that seeks to solve combinatorial optimization problems using quantum hardware and classical optimizat…
Efficient Fourier-Based Linear Combination of Unitaries and Applications in Quantum Optimization
Almudena Carrera Vazquez, Daniel J. Egger, Stefan Woerner
We investigate ancilla-free linear combination of unitaries (LCU) as a framework for approximating complex quantum circuits. This is particularly effective for quantum optimization…
Quantum-enhanced Markov Chain Monte Carlo for Combinatorial Optimization
Kate V. Marshall, Daniel J. Egger, Michael Garn +4
Quantum computing offers an alternative paradigm for addressing combinatorial optimization problems compared to classical computing. Despite recent hardware improvements, the execu…
Mitigating errors in state preparation and measurement with noncomputational states
Conrad J. Haupt, Almudena Carrera Vazquez, Laurin E. Fischer +2
Error mitigation has enabled quantum computing applications with over one hundred qubits and deep circuits. Many error mitigation methods are noise-aware, relying on a faithful cha…
Approximate Quadratization of High-Order Hamiltonians for Combinatorial Quantum Optimization
Sabina Drăgoi, Alberto Baiardi, Daniel J. Egger
Combinatorial optimization problems have wide-ranging applications in industry and academia. Quantum computers may help solve them by sampling from carefully prepared Ansatz quantu…
Quantum Optimization Benchmarking Library - The Intractable Decathlon
Thorsten Koch, David E. Bernal Neira, Ying Chen +24
Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particu…
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…
Genuine Multipartite Entanglement in Quantum Optimization
Gopal Chandra Santra, Sudipto Singha Roy, Daniel J. Egger +1
The ability to generate bipartite entanglement in quantum computing technologies is widely regarded as pivotal. However, the role of genuinely multipartite entanglement is much les…
Learning How to Dynamically Decouple
Arefur Rahman, Daniel J. Egger, Christian Arenz
Current quantum computers suffer from noise that stems from interactions between the quantum system that constitutes the quantum device and its environment. These interactions can…
Benchmarking digital quantum simulations above hundreds of qubits using quantum critical dynamics
Alexander Miessen, Daniel J. Egger, Ivano Tavernelli +1
The real-time simulation of large many-body quantum systems is a formidable task, that may only be achievable with a genuine quantum computational platform. Currently, quantum hard…
Combining quantum processors with real-time classical communication
Almudena Carrera Vazquez, Caroline Tornow, Diego Riste +3
Quantum computers process information with the laws of quantum mechanics. Current quantum hardware is noisy, can only store information for a short time, and is limited to a few qu…
Challenges and Opportunities in Quantum Optimization
Amira Abbas, Andris Ambainis, Brandon Augustino +43
Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum a…
Provable bounds for noise-free expectation values computed from noisy samples
Samantha V. Barron, Daniel J. Egger, Elijah Pelofske +4
In this paper, we explore the impact of noise on quantum computing, particularly focusing on the challenges when sampling bit strings from noisy quantum computers as well as the im…