643 citations
- Ludwig-Maximilians-Universität MünchenDE217 papers
- Centre National de la Recherche ScientifiqueFR67 papers
- Instituto de Astrofísica de CanariasES67 papers
- University of BonnDE61 papers
- University College LondonGB60 papers
- California Institute of TechnologyUS59 papers
- Centro de Investigaciones Energéticas, Medioambientales y TecnológicasES59 papers
- Institute for High Energy PhysicsES59 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR59 papers
- Jet Propulsion LaboratoryUS59 papers
- Trieste Astronomical ObservatoryIT59 papers
- Institució Catalana de Recerca i Estudis AvançatsES58 papers
9 papers · 1 filter
Constrained Quantum Optimization via Iterative Warm-Start XY-Mixers
David Bucher, Maximilian Janetschek, Michael Poppel +3
The Quantum Approximate Optimization Algorithm (QAOA) is a leading hybrid heuristic for combinatorial optimization, but efficiently handling hard constraints remains a significant…
Circuit Partitioning for the Quantum Internet
Leo Sünkel, Thomas Gabor, Claudia Linnhoff-Popien
In a quantum internet, quantum processing units (QPUs) with varying architectures and capabilities may be connected through quantum communication channels, enabling new application…
Evaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing
Leo Sünkel, Jonas Stein, Jonas Nüßlein +2
Scaling quantum computers, i.e., quantum processing units (QPUs) to enable the execution of large quantum circuits is a major challenge, especially for applications that should pro…
Evolutionary-Based Circuit Optimization for Distributed Quantum Computing
Leo Sünkel, Jonas Stein, Gerhard Stenzel +3
In this work, we evaluate an evolutionary algorithm (EA) to optimize a given circuit in such a way that it reduces the required communication when executed in the Distributed Quant…
From Classical Data to Quantum Advantage -- Quantum Policy Evaluation on Quantum Hardware
Daniel Hein, Simon Wiedemann, Markus Baumann +7
Quantum policy evaluation (QPE) is a reinforcement learning (RL) algorithm which is quadratically more efficient than an analogous classical Monte Carlo estimation. It makes use of…
Time-Aware Qubit Assignment and Circuit Optimization for Distributed Quantum Computing
Leo Sünkel, Jonas Stein, Maximilian Zorn +2
The emerging paradigm of distributed quantum computing promises a potential solution to scaling quantum computing to currently unfeasible dimensions. While this approach itself is…