20 citations · 24 across the 18 of their papers we have counts for
19 papers
Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization
Lukas Theißinger, Thore Gerlach, Christian Bauckhage
Differentiable quantum architecture search (DQAS) is a promising framework for the automated design of quantum circuits, particularly for variational quantum optimization algorithm…
Hardware-Aware QUBO Reformulation of Constrained Binary Optimization via the Walsh-Fourier Transform
Loong Kuan Lee, Harsha Nagarajan, Thore Gerlach +3
We present a novel slack-free, penalty-based framework for reformulating constrained binary optimization as Quadratic Unconstrained Binary Optimization (QUBO) on near-term quantum…
Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesis
Lukas Theißinger, Thore Gerlach, David Berghaus +1
Quantum unitary synthesis addresses the problem of translating abstract quantum algorithms into sequences of hardware-executable quantum gates. Solving this task exactly is infeasi…
Quadratic Continuous Quantum Optimization
Sascha Mücke, Thore Gerlach, Nico Piatkowski
Quantum annealers can solve QUBO problems efficiently but struggle with continuous optimization tasks like regression due to their discrete nature. We introduce Quadratic Continuou…
Quantum Adiabatic Generation of Human-Like Passwords
Sascha Mücke, Raoul Heese, Thore Gerlach +3
Generative Artificial Intelligence (GenAI) for Natural Language Processing (NLP) is the predominant AI technology to date. An important perspective for Quantum Computing (QC) is th…
Kernel -Medoids as General Vector Quantization
Thore Gerlach, Sascha Mücke, Christian Bauckhage
Vector Quantization (VQ) is a widely used technique in machine learning and data compression, valued for its simplicity and interpretability. Among hard VQ methods, -medoids clu…
Standardization of Multi-Objective QUBOs
Loong Kuan Lee, Thore Gerlach, Nico Piatkowski
Multi-objective optimization involving Quadratic Unconstrained Binary Optimization (QUBO) problems arises in various domains. A fundamental challenge in this context is the effecti…
Hybrid Quantum-Classical Multi-Agent Pathfinding
Thore Gerlach, Loong Kuan Lee, Frédéric Barbaresco +1
Multi-Agent Path Finding (MAPF) focuses on determining conflict-free paths for multiple agents navigating through a shared space to reach specified goal locations. This problem bec…
Dynamic Range Reduction via Branch-and-Bound
Thore Gerlach, Nico Piatkowski
The demand for high-performance computing in machine learning and artificial intelligence has led to the development of specialized hardware accelerators like Tensor Processing Uni…
Multi-Objective Quantum Power System Redispatch
Loong Kuan Lee, Johannes Knaute, Florian Gerhardt +4
The rising energy production costs and the increasing reliance on volatile renewable sources have driven the need for more efficient power system redispatch strategies. In this wor…
Investigating the Relation Between Problem Hardness and QUBO Properties
Thore Gerlach, Sascha Mücke
Combinatorial optimization problems, integral to various scientific and industrial applications, often vary significantly in their complexity and computational difficulty. Transfor…
FPGA-Placement via Quantum Annealing
Thore Gerlach, Stefan Knipp, David Biesner +3
Field-Programmable Gate Arrays (FPGAs) have asserted themselves as vital assets in contemporary computing by offering adaptable, reconfigurable hardware platforms. FPGA-based accel…
Efficient Light Source Placement using Quantum Computing
Sascha Mücke, Thore Gerlach
NP-hard problems regularly come up in video games, with interesting connections to real-world problems. In the game Minecraft, players place torches on the ground to light up dark…
Optimum-Preserving QUBO Parameter Compression
Sascha Mücke, Thore Gerlach, Nico Piatkowski
Quadratic unconstrained binary optimization (QUBO) problems are well-studied, not least because they can be approached using contemporary quantum annealing or classical hardware ac…
Shapley Values with Uncertain Value Functions
Raoul Heese, Sascha Mücke, Matthias Jakobs +2
We propose a novel definition of Shapley values with uncertain value functions based on first principles using probability theory. Such uncertain value functions can arise in the c…
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning
Raoul Heese, Thore Gerlach, Sascha Mücke +3
Methods of artificial intelligence (AI) and especially machine learning (ML) have been growing ever more complex, and at the same time have more and more impact on people's lives.…
Solving Subset Sum Problems using Quantum Inspired Optimization Algorithms with Applications in Auditing and Financial Data Analysis
David Biesner, Thore Gerlach, Christian Bauckhage +2
Many applications in automated auditing and the analysis and consistency check of financial documents can be formulated in part as the subset sum problem: Given a set of numbers an…
Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning
Nico Piatkowski, Thore Gerlach, Romain Hugues +3
Given is a set of images, where all images show views of the same area at different points in time and from different viewpoints. The task is the alignment of all images such that…
QUBOs for Sorting Lists and Building Trees
Christian Bauckhage, Thore Gerlach, Nico Piatkowski
We show that the fundamental tasks of sorting lists and building search trees or heaps can be modeled as quadratic unconstrained binary optimization problems (QUBOs). The idea is t…