D. Bucher
YOU?
Author Swipe
View article: Penalty-free approach to accelerating constrained quantum optimization
Penalty-free approach to accelerating constrained quantum optimization Open
Traditional methods for handling (inequality) constraints in the quantum approximate optimization (QAOA) typically rely on penalty terms and slack variables, which increase problem complexity and expand the search space. More sophisticated…
View article: Efficient QAOA Architecture for Solving Multi-Constrained Optimization Problems
Efficient QAOA Architecture for Solving Multi-Constrained Optimization Problems Open
This paper proposes a novel combination of constraint encoding methods for the Quantum Approximate Optimization Ansatz (QAOA). Real-world optimization problems typically consist of multiple types of constraints. To solve these optimization…
View article: IF-QAOA: A Penalty-Free Approach to Accelerating Constrained Quantum Optimization
IF-QAOA: A Penalty-Free Approach to Accelerating Constrained Quantum Optimization Open
Traditional methods for handling (inequality) constraints in the Quantum Approximate Optimization Ansatz (QAOA) typically rely on penalty terms and slack variables, which increase problem complexity and expand the search space. More sophis…
View article: Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches
Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches Open
This paper presents a novel optimization approach for allocating grid operation costs in Peer-to-Peer (P2P) electricity markets using Quantum Computing (QC). We develop a Quadratic Unconstrained Binary Optimization (QUBO) model that matche…
View article: Towards Less Greedy Quantum Coalition Structure Generation in Induced Subgraph Games
Towards Less Greedy Quantum Coalition Structure Generation in Induced Subgraph Games Open
The transition to 100% renewable energy requires new techniques for managing energy networks, such as dividing them into sensible subsets of prosumers called micro-grids. Doing so in an optimal manner is a difficult optimization problem, a…
View article: CUAOA: A Novel CUDA-Accelerated Simulation Framework for the QAOA
CUAOA: A Novel CUDA-Accelerated Simulation Framework for the QAOA Open
The Quantum Approximate Optimization Algorithm (QAOA) is a prominent quantum algorithm designed to find approximate solutions to combinatorial optimization problems, which are challenging for classical computers. In the current era, where …
View article: Solving the Turbine Balancing Problem using Quantum Annealing
Solving the Turbine Balancing Problem using Quantum Annealing Open
Quantum computing has the potential for disruptive change in many sectors of\nindustry, especially in materials science and optimization. In this paper, we\ndescribe how the Turbine Balancing Problem can be solved with quantum\ncomputing, …
View article: Evaluating Quantum Optimization for Dynamic Self-Reliant Community Detection
Evaluating Quantum Optimization for Dynamic Self-Reliant Community Detection Open
Power grid partitioning is an important requirement for resilient distribution grids. Since electricity production is progressively shifted to the distribution side, dynamic identification of self-reliant grid subsets becomes crucial for o…
View article: Demonstrating Quantum Scaling Advantage in Approximate Optimization for Energy Coalition Formation with 100+ Agents
Demonstrating Quantum Scaling Advantage in Approximate Optimization for Energy Coalition Formation with 100+ Agents Open
The formation of energy communities is pivotal for advancing decentralized and sustainable energy management. Within this context, Coalition Structure Generation (CSG) emerges as a promising framework. The complexity of CSG grows rapidly w…
View article: Towards Robust Benchmarking of Quantum Optimization Algorithms
Towards Robust Benchmarking of Quantum Optimization Algorithms Open
Benchmarking the performance of quantum optimization algorithms is crucial for identifying utility for industry-relevant use cases. Benchmarking processes vary between optimization applications and depend on user-specified goals. The heuri…
View article: Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects
Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects Open
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 aims to assess potential quantum utility optimization applicat…
View article: Incentivizing Demand-Side Response Through Discount Scheduling Using Hybrid Quantum Optimization
Incentivizing Demand-Side Response Through Discount Scheduling Using Hybrid Quantum Optimization Open
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 and promote a more balanced and efficient use of (renewable)…
View article: Introducing Reduced-Width QNNs, an AI-Inspired Ansatz Design Pattern
Introducing Reduced-Width QNNs, an AI-Inspired Ansatz Design Pattern Open
Variational Quantum Algorithms are one of the most promising candidates to yield the first industrially relevant quantum advantage.Being capable of arbitrary function approximation, they are often referred to as Quantum Neural Networks (QN…
View article: Approximative Lookup-Tables and Arbitrary Function Rotations for Facilitating NISQ-Implementations of the HHL and Beyond
Approximative Lookup-Tables and Arbitrary Function Rotations for Facilitating NISQ-Implementations of the HHL and Beyond Open
Many promising applications of quantum computing with a provable speedup\ncenter around the HHL algorithm. Due to restrictions on the hardware and its\nsignificant demand on qubits and gates in known implementations, its execution\nis proh…
View article: Sampling problems on a Quantum Computer
Sampling problems on a Quantum Computer Open
Due to the advances in the manufacturing of quantum hardware in the recent years, significant research efforts have been directed towards employing quantum methods to solving problems in various areas of interest. Thus a plethora of novel …
View article: Incentivising Demand Side Response through Discount Scheduling using Hybrid Quantum Optimization
Incentivising Demand Side Response through Discount Scheduling using Hybrid Quantum Optimization Open
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 and promote a more balanced and efficient use of (renewable)…
View article: NISQ-Ready Community Detection Based on Separation-Node Identification
NISQ-Ready Community Detection Based on Separation-Node Identification Open
The analysis of network structure is essential to many scientific areas ranging from biology to sociology. As the computational task of clustering these networks into partitions, i.e., solving the community detection problem, is generally …
View article: NISQ-Ready Community Detection Based on Separation-Node Identification
NISQ-Ready Community Detection Based on Separation-Node Identification Open
The analysis of network structure is essential to many scientific areas, ranging from biology to sociology. As the computational task of clustering these networks into partitions, i.e., solving the community detection problem, is generally…
View article: Introducing Reduced-Width QNNs, an AI-inspired Ansatz Design Pattern
Introducing Reduced-Width QNNs, an AI-inspired Ansatz Design Pattern Open
Variational Quantum Algorithms are one of the most promising candidates to yield the first industrially relevant quantum advantage. Being capable of arbitrary function approximation, they are often referred to as Quantum Neural Networks (Q…
View article: Exponential Quantum Speedup for Simulation-Based Optimization Applications
Exponential Quantum Speedup for Simulation-Based Optimization Applications Open
The simulation of many industrially relevant physical processes can be executed up to exponentially faster using quantum algorithms. However, this speedup can only be leveraged if the data input and output of the simulation can be implemen…
View article: Disentangling Intertwined Quantum States in a Prototypical Cuprate Superconductor
Disentangling Intertwined Quantum States in a Prototypical Cuprate Superconductor Open
Spontaneous symmetry breaking constitutes a paradigmatic classification scheme of matter. However, broken symmetry also entails domain degeneracy that often impedes identification of novel low symmetry states. In quantum matter, this is ad…
View article: Common Data Environment within the AEC Ecosystem: moving collaborative platforms beyond the open versus closed dichotomy
Common Data Environment within the AEC Ecosystem: moving collaborative platforms beyond the open versus closed dichotomy Open
The Common Data Environment (CDE) is seen as an opportunity to increase collaboration and efficiency during project handling and act as a basis for Industry 4.0 in the construction industry. CDE developments in industry and research use va…
View article: Beam Energy and Centrality Dependence of Direct-Photon Emission from Ultrarelativistic Heavy-Ion Collisions
Beam Energy and Centrality Dependence of Direct-Photon Emission from Ultrarelativistic Heavy-Ion Collisions Open
The PHENIX collaboration presents first measurements of low-momentum (0.45 GeV/c), but when results from different collision energies are compared, an additional sqrt[s_{NN}]-dependent multiplicative factor is needed to describe the integr…
View article: Qiskit: An Open-source Framework for Quantum Computing
Qiskit: An Open-source Framework for Quantum Computing Open
Qiskit is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. https://qiskit.org