40 citations · 57 across the 17 of their papers we have counts for
15 papers · 1 filter
Quantum Boltzmann Machines using Parallel Annealing for Medical Image Classification
Daniëlle Schuman, Mark V. Seebode, Tobias Rohe +5
Exploiting the fact that samples drawn from a quantum annealer inherently follow a Boltzmann-like distribution, annealing-based Quantum Boltzmann Machines (QBMs) have gained increa…
Clique detection using symmetry-restricted quantum circuits
Maximilian Balthasar Mansky, Tobias Rohe, Dmytro Bondarenko +2
We show the application of permutation-invariant quantum circuits to the clique problem. The experiment asks to label a clique through identification of the nodes in a larger subgr…
Analysis of quantum neural network performance via edge cases
Maximilian Balthasar Mansky, Tobias Rohe, Linus Menzel +2
We evaluate the particular performance of different quantum machine learning networks on a graph classification task. Quantum circuits with varying internal symmetry that completel…
Solving graph problems using permutation-invariant quantum machine learning
Maximilian Balthasar Mansky, Tobias Rohe, Gerhard Stenzel +7
Many computational problems are unchanged under some symmetry operation. In classical machine learning, this can be reflected with the layer structure of the neural network. In qua…
Quality Diversity for Variational Quantum Circuit Optimization
Maximilian Zorn, Jonas Stein, Maximilian Balthasar Mansky +3
Optimizing the architecture of variational quantum circuits (VQCs) is crucial for advancing quantum computing (QC) towards practical applications. Current methods range from static…
Accelerated VQE: Parameter Recycling for Similar Recurring Problem Instances
Tobias Rohe, Maximilian Balthasar Mansky, Michael Kölle +3
Training the Variational Quantum Eigensolver (VQE) is a task that requires substantial compute. We propose the use of concepts from transfer learning to considerably reduce the tra…
A Constant Measurement Quantum Algorithm for Graph Connectivity
Maximilian Balthasar Mansky, Chonfai Kam, Claudia Linnhoff-Popien
We introduce a novel quantum algorithm for determining graph connectedness using a constant number of measurements. The algorithm can be extended to find connected components with…
Scaling of symmetry-restricted quantum circuits
Maximilian Balthasar Mansky, Miguel Armayor Martinez, Alejandro Bravo de la Serna +6
The intrinsic symmetries of physical systems have been employed to reduce the number of degrees of freedom of systems, thereby simplifying computations. In this work, we investigat…
Sampling Problems on a Quantum Computer
Maximilian Balthasar Mansky, Jonas Nüßlein, David Bucher +3
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 probl…
Symmetry-restricted quantum circuits are still well-behaved
Maximilian Balthasar Mansky, Santiago Londoño Castillo, Miguel Armayor-Martínez +5
We show that quantum circuits restricted by a symmetry inherit the properties of the whole special unitary group , in particular composition, algebraic and topological clo…
Permutation-invariant quantum circuits
Maximilian Balthasar Mansky, Santiago Londoño Castillo, Victor Ramos Puigvert +1
The implementation of physical symmetries into problem descriptions allows for the reduction of parameters and computational complexity. We show the integration of the permutation…
Weight Re-Mapping for Variational Quantum Algorithms
Michael Kölle, Alessandro Giovagnoli, Jonas Stein +5
Inspired by the remarkable success of artificial neural networks across a broad spectrum of AI tasks, variational quantum circuits (VQCs) have recently seen an upsurge in quantum m…
Decomposition Algorithm of an Arbitrary Pauli Exponential through a Quantum Circuit
Maximilian Balthasar Mansky, Victor Ramos Puigvert, Santiago Londoño Castillo +1
We review the staircase algorithm to decompose the exponential of a generalized Pauli matrix and we propose two alternative recursive methods which offer more efficient quantum cir…
Improving Convergence for Quantum Variational Classifiers using Weight Re-Mapping
Michael Kölle, Alessandro Giovagnoli, Jonas Stein +3
In recent years, quantum machine learning has seen a substantial increase in the use of variational quantum circuits (VQCs). VQCs are inspired by artificial neural networks, which…
Near-optimal quantum circuit construction via Cartan decomposition
Maximilian Balthasar Mansky, Santiago Londoño Castillo, Victor Ramos Puigvert +1
We show the applicability of the Cartan decomposition of Lie algebras to quantum circuits. This approach can be used to synthesize circuits that can efficiently implement any desir…