6 papers · 1 filter
Revisiting the Quantum-Guided Cluster Algorithm: Improvements and Numerical Experiments
Peter J. Eder, Sarah Braun
We study correlation-guided cluster algorithms for solving the Max-Cut problem that iteratively try to improve solutions by updating clusters of nodes. Building on the recently pro…
Open-System Adiabatic Quantum Search under Dephasing
Afaf El Kalai, Peter J. Eder, Christian B. Mendl
Adiabatic quantum algorithms must evolve slowly enough to suppress non-adiabatic transitions while remaining fast enough to be practical. In open systems, this trade-off is reshape…
Grover Adaptive Search with Problem-Specific State Preparation
Maximilian Hess, Lilly Palackal, Abhishek Awasthi +5
Grover's search algorithm is one of the basic building block in the world of quantum algorithms. Successfully applying it to combinatorial optimization problems is a subtle challen…
Quantum Computing -- Strategic Recommendations for the Industry
Marvin Erdmann, Lukas Karch, Abhishek Awasthi +9
This whitepaper surveys the current landscape and short- to mid-term prospects for quantum-enabled optimization and machine learning use cases in industrial settings. Grounded in t…
Quantum-Guided Cluster Algorithms for Combinatorial Optimization
Peter J. Eder, Aron Kerschbaumer, Jernej Rudi Finžgar +5
Finding the ground state of Ising spin glasses is notoriously difficult due to disorder and frustration. Often, this challenge is framed as a combinatorial optimization problem, fo…
Quantum Dissipative Search via Lindbladians
Peter J. Eder, Jernej Rudi Finžgar, Sarah Braun +1
Closed quantum systems follow a unitary time evolution that can be simulated on quantum computers. By incorporating non-unitary effects via, e.g., measurements on ancilla qubits, t…