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20222025
most citedMapping quantum circuits to modular architectures with QUBO

34 citations · 94 across the 21 of their papers we have counts for

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14 papers · 1 filter

quant-ph2025★ 3 cited

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…

quant-ph2024

Reducing QUBO Density by Factoring Out Semi-Symmetries

Jonas Nüßlein, Leo Sünkel, Jonas Stein +6

Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are prominent approaches for solving combinatorial optimization problems, such as those formulated as Quadra…

quant-ph2024

Reducing QAOA Circuit Depth by Factoring out Semi-Symmetries

Jonas Nüßlein, Leo Sünkel, Jonas Stein +4

QAOA is a quantum algorithm for solving combinatorial optimization problems. It is capable of searching for the minimizing solution vector of a QUBO problem . The number…

quant-ph2024★ 1 cited

Solving Max-3SAT Using QUBO Approximation

Sebastian Zielinski, Jonas Nüßlein, Michael Kölle +3

As contemporary quantum computers do not possess error correction, any calculation performed by these devices can be considered an involuntary approximation. To solve a problem on…

quant-ph2024

Architectural Influence on Variational Quantum Circuits in Multi-Agent Reinforcement Learning: Evolutionary Strategies for Optimization

Michael Kölle, Karola Schneider, Sabrina Egger +5

In recent years, Multi-Agent Reinforcement Learning (MARL) has found application in numerous areas of science and industry, such as autonomous driving, telecommunications, and glob…

quant-ph2024★ 1 cited

The Questionable Influence of Entanglement in Quantum Optimisation Algorithms

Tobias Rohe, Daniëlle Schuman, Jonas Nüßlein +3

The performance of the Variational Quantum Eigensolver (VQE) is promising compared to other quantum algorithms, but also depends significantly on the appropriate design of the unde…

quant-ph2024

Demonstrating Quantum Scaling Advantage in Approximate Optimization for Energy Coalition Formation with 100+ Agents

Naeimeh Mohseni, Thomas Morstyn, Corey O'Meara +3

The formation of energy communities is pivotal for advancing decentralized and sustainable energy management. Within this context, Coalition Structure Generation (CSG) emerges as a…

quant-ph2024★ 1 cited

Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects

Jonas Blenninger, David Bucher, Giorgio Cortiana +6

In this project summary paper, we summarize the key results and use-cases explored in the German Federal Ministry of Education and Research (BMBF) funded project "Q-GRID" which aim…

quant-ph2023★ 6 cited

Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization

Michael Kölle, Felix Topp, Thomy Phan +3

Multi-Agent Reinforcement Learning is becoming increasingly more important in times of autonomous driving and other smart industrial applications. Simultaneously a promising new ap…

quant-ph2023★ 6 cited

Incentivising Demand Side Response through Discount Scheduling using Hybrid Quantum Optimization

David Bucher, Jonas Nüßlein, Corey O'Meara +5

Demand Side Response (DSR) is a strategy that enables consumers to actively participate in managing electricity demand. It aims to alleviate strain on the grid during high demand a…

quant-ph2023★ 34 cited

Mapping quantum circuits to modular architectures with QUBO

Medina Bandic, Luise Prielinger, Jonas Nüßlein +8

Modular quantum computing architectures are a promising alternative to monolithic QPU (Quantum Processing Unit) designs for scaling up quantum devices. They refer to a set of inter…

quant-ph2023★ 10 cited

Pattern QUBOs: Algorithmic construction of 3SAT-to-QUBO transformations

Sebastian Zielinski, Jonas Nüßlein, Jonas Stein +3

3SAT instances need to be transformed into instances of Quadratic Unconstrained Binary Optimization (QUBO) to be solved on a quantum annealer. Although it has been shown that the c…

quant-ph2023★ 7 cited

Influence of Different 3SAT-to-QUBO Transformations on the Solution Quality of Quantum Annealing: A Benchmark Study

Sebastian Zielinski, Jonas Nüßlein, Jonas Stein +3

To solve 3SAT instances on quantum annealers they need to be transformed to an instance of Quadratic Unconstrained Binary Optimization (QUBO). When there are multiple transformatio…

quant-ph2023★ 1 cited

Solving (Max) 3-SAT via Quadratic Unconstrained Binary Optimization

Jonas Nüßlein, Sebastian Zielinski, Thomas Gabor +2

We introduce a novel approach to translate arbitrary 3-SAT instances to Quadratic Unconstrained Binary Optimization (QUBO) as they are used by quantum annealing (QA) or the quantum…