469 citations · 922 across the 30 of their papers we have counts for
17 papers · 1 filter
Tensor networks for quantum computing
Aleksandr Berezutskii, Minzhao Liu, Atithi Acharya +25
In the rapidly evolving field of quantum computing, tensor networks serve as an important tool due to their multifaceted utility. In this paper, we review the diverse applications…
Comparison between Tensor Networks and Variational Quantum Classifier
Georgios Laskaris, Artem A. Melnikov, Michael R. Perelshtein +3
The primary objective of this paper is to conduct a comparative analysis between two Machine Learning approaches: Tensor Networks (TN) and Variational Quantum Classifiers (VQC). Wh…
Do we live in a [quantum] simulation? Constraints, observations, and experiments on the simulation hypothesis
Florian Neukart, Anders Indset, Markus Pflitsch +1
The question "What is real?" can be traced back to the shadows in Plato's cave. Two thousand years later, Rene Descartes lacked knowledge about arguing against an evil deceiver fee…
Quantum-Enhanced Selection Operators for Evolutionary Algorithms
David Von Dollen, Sheir Yarkoni, Daniel Weimer +2
Genetic algorithms have unique properties which are useful when applied to black box optimization. Using selection, crossover, and mutation operators, candidate solutions may be ob…
Practical application-specific advantage through hybrid quantum computing
Michael Perelshtein, Asel Sagingalieva, Karan Pinto +7
Quantum computing promises to tackle technological and industrial problems insurmountable for classical computers. However, today's quantum computers still have limited demonstrabl…
Multi-car paint shop optimization with quantum annealing
Sheir Yarkoni, Alex Alekseyenko, Michael Streif +3
We present a generalization of the binary paint shop problem (BPSP) to tackle an automotive industry application, the multi-car paint shop (MCPS) problem. The objective of the opti…
Beating classical heuristics for the binary paint shop problem with the quantum approximate optimization algorithm
Michael Streif, Sheir Yarkoni, Andrea Skolik +2
The binary paint shop problem (BPSP) is an APX-hard optimization problem of the automotive industry. In this work, we show how to use the Quantum Approximate Optimization Algorithm…
Quantum Shuttle: Traffic Navigation with Quantum Computing
Sheir Yarkoni, Florian Neukart, Eliane Moreno Gomez Tagle +5
The Web Summit conference in Lisbon, Portugal, is one of the biggest technology conferences in Europe, attended by tens of thousands of people every year. The high influx of people…
Semi-supervised time series classification method for quantum computing
Sheir Yarkoni, Andrii Kleshchonok, Yury Dzerin +2
In this paper we develop methods to solve two problems related to time series (TS) analysis using quantum computing: reconstruction and classification. We formulate the task of rec…
Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor
Matthew P. Harrigan, Kevin J. Sung, Matthew Neeley +83
We demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algor…
Quantum-assisted finite-element design optimization
Dyon van Vreumingen, Florian Neukart, David Von Dollen +4
Quantum annealing devices such as the ones produced by D-Wave systems are typically used for solving optimization and sampling tasks, and in both academia and industry the characte…
A Hybrid Solution Method for the Capacitated Vehicle Routing Problem Using a Quantum Annealer
Sebastian Feld, Christoph Roch, Thomas Gabor +5
The Capacitated Vehicle Routing Problem (CVRP) is an NP-optimization problem (NPO) that has been of great interest for decades for both, science and industry. The CVRP is a variant…
Solving Quantum Chemistry Problems with a D-Wave Quantum Annealer
Michael Streif, Florian Neukart, Martin Leib
Quantum annealing devices have been subject to various analyses in order to classify their usefulness for practical applications. While it has been successfully proven that such sy…
Quantum annealing with anneal path control: application to 2-SAT problems with known energy landscapes
Ting-Jui Hsu, Fengping Jin, Christian Seidel +3
We study the effect of the anneal path control per qubit, a new user control feature offered on the D-Wave 2000Q quantum annealer, on the performance of quantum annealing for solvi…
Quantum-assisted cluster analysis
Florian Neukart, David Von Dollen, Christian Seidel
We present an algorithm for quantum-assisted cluster analysis (QACA) that makes use of the topological properties of a D-Wave 2000Q quantum processing unit (QPU). Clustering is a f…
Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces
Florian Neukart, David Von Dollen, Christian Seidel +1
Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as…
Traffic flow optimization using a quantum annealer
Florian Neukart, Gabriele Compostella, Christian Seidel +3
Quantum annealing algorithms belong to the class of meta-heuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such a…