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Classification of Hybrid quantum-Classical Computing 1

23rd International Conference on Computational Science, ICCS 2023

作者： Phillipson, Frank Neumann, Niels Wezeman, Robert Department Applied Cryptography and Quantum Algorithms TNO The Hague Netherlands School of Business and Economics Maastricht University Maastricht Netherlands

ISBN: (数字)9783031360305

ISBN: (纸本)9783031360299

As quantum computers mature, the applicability in practice becomes more important. quantum computers will often be used in a hybrid setting, where classical computers still play an important role in operating and using the quantum computer. However the term hybrid is diffuse and multi-interpretable. In this work we define two classes of hybrid quantum-classical computing: vertical and horizontal hybrid quantum-classical computing. The first is application-agnostic and concerns using and operating quantum computers. The second is application-specific and concerns running an algorithm. For both, we give a further subdivision in different types of hybrid quantum-classical computing and we introduce terms for them. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： quantum theory

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Translating Constraints into QUBOs for the Quadratic Knapsack Problem 1

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23rd International Conference on Computational Science, ICCS 2023

作者： Bontekoe, Tariq Phillipson, Frank Schoot, Ward van der TNO Department Applied Cryptography and Quantum Algorithms The Hague Netherlands School of Business and Economics Maastricht University Maastricht Netherlands

ISBN: (数字)9783031360305

ISBN: (纸本)9783031360299

One of the first fields where quantum computing will likely show its use is optimisation. Many optimisation problems naturally arise in a quadratic manner, such as the quadratic knapsack problem. The current state of quantum computers requires these problems to be formulated as a quadratic unconstrained binary optimisation problem, or QUBO. Constrained quadratic binary optimisation can be translated into QUBOs by translating the constraint. However, this translation can be made in several ways, which can have a large impact on the performance when solving the QUBO. We show six different formulations for the quadratic knapsack problem and compare their performance using simulated annealing. The best performance is obtained by a formulation that uses no auxiliary variables for modelling the inequality constraint. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Simulated annealing

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quantum computing for partial differential equations in practice

Quantum computing for partial differential equations in prac...

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quantum Technologies for Defence and Security 2024

作者： Neumann, Niels Verbree, Jasper Hoek, Carmen Department of Applied Cryptography and Quantum Applications TNO Anna van Buerenplein 1 The Hague2595 DA Netherlands

ISBN: (数字)9781510681132

ISBN: (纸本)9781510681125

quantum computers have the potential to solve some complex problems much faster than classical equivalents. Significant research efforts are aimed at determining which algorithms give which advantages for different use-cases. An application where quantum computers can possibly bring great advantages is solving (partial) differential equations, which has a broad set of applications, for instance in wave-propagation models. Few differential equations admit an analytical solution. For most heuristic methods are required to approximate a solution. Well-known heuristic techniques include the finite element and finite difference method, where the considered space is partitioned and systems of linear equations resulting from this partitioning need to be solved. quantum computing puts forward new methods to solve these systems of linear equations and hence these differential equations. First, the HHL algorithm gives an efficient way to solve a linear system of equations. The HHL algorithm comes with drawbacks, but in this specific use-case some of these objections might be circumvented. quantum computers furthermore offer the variational approach: an optimization-based path to solving differential equations. With this approach, the devices might even 'learn' the noise patterns emerging in present day quantum computers and compensate for it. In this work we revisit quantum methods for solving partial differential equations and consider how well they work in solving differential equations in practice. We also discuss possible caveats and bottlenecks of the approaches. © 2024 SPIE.

关键词： Heuristic methods

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QuAS: quantum Application Score for Benchmarking the Utility of quantum Computers

QuAS: Quantum Application Score for Benchmarking the Utility...

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quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Koen J. Mesman Ward van der Schoot Matthias Möller Niels M. P. Neumann QAIMS Delft University of Technology Delft Netherlands Applied Cryptography and Quantum Algorithms TNO The Hague Netherlands Applied Mathematics Delft University of Technology Delft Netherlands

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Benchmarking quantum computers helps to quantify them and bringing the technology to the market. Various application-level metrics exist to benchmark a quantum device at an application level. This paper presents a revised holistic scoring method called the quantum Application Score (QuAS) incorporating strong points of previous metrics, such as QPack and the Q-score. We discuss how to integrate both and thereby obtain an application-level metric that better quantifies the practical utility of quantum computers. We evaluate the new metric on different hardware platforms such as D- Wave and IBM as well as quantum simulators of quantum Inspire and Rigetti.

关键词： Measurement Computers quantum computing Benchmark testing Hardware

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QuAS: quantum Application Score for benchmarking the utility of quantum computers

arXiv

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arXiv 2024年

作者： Mesman, Koen J. van der Schoot, Ward Möller, Matthias Neumann, Niels M.P. QAIMS Delft University of Technology Delft Netherlands Applied Cryptography and Quantum Algorithms TNO The Hague Netherlands Delft University of Technology Delft Netherlands

Benchmarking quantum computers helps to quantify them and bringing the technology to the market. Various application-level metrics exist to benchmark a quantum device at an application level. This paper presents a revised holistic scoring method called the quantum Application Score (QuAS) incorporating strong points of previous metrics, such as QPack and the Q-score. We discuss how to integrate both and thereby obtain an application-level metric that better quantifies the practical utility of quantum computers. We evaluate the new metric on different hardware platforms such as D-Wave and IBM as well as quantum simulators of quantum Inspire and Rigetti. © 2024, CC BY.

关键词： Benchmarking

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qgym: A Gym for Training and Benchmarking RL-Based quantum Compilation

qgym: A Gym for Training and Benchmarking RL-Based Quantum C...

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quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Stan van der Linde Willem de Kok Tariq Bontekoe Sebastian Feld Applied Cryptography & Quantum Algorithms The Netherlands Organisation for Applied Scientific Research (TNO) The Hague The Netherlands Faculty of Science and Engineering Bernoulli Institute University of Groningen Groningen The Netherlands Quantum & Computer Engineering QuTech Delft University of Technology Delft The Netherlands

Compiling a quantum circuit for specific quantum hardware is a challenging task. Moreover, current quantum computers have severe hardware limitations. To make the most use of the limited resources, the compilation process should be optimized. To improve currents methods, Reinforcement Learning (RL), a technique in which an agent interacts with an environment to learn complex policies to attain a specific goal, can be used. In this work, we present qgym, a software framework derived from the OpenAI gym, together with environments that are specifically tailored towards quantum compilation. The goal of qgym is to connect the research fields of Artificial Intelligence (AI) with quantum compilation by abstracting parts of the process that are irrelevant to either domain. It can be used to train and benchmark RL agents and algorithms in highly customizable environments.

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Classification of Hybrid quantum-Classical Computing

arXiv

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arXiv 2022年

作者： Phillipson, Frank Neumann, Niels Wezeman, Robert TNO Dpt. Applied Cryptography & Quantum Algorithms The Hague Netherlands Maastricht University School of Business and Economics Maastricht Netherlands

As quantum computers mature, the applicability in practice becomes more important. Many uses of quantum computers will be hybrid, with classical computers still playing an important role in operating and using the quantum computer. The term hybrid is however diffuse and multi-interpretable. In this work we define two classes of hybrid quantum-classical computing: vertical and horizontal. The first is application-agnostic and concerns using quantum computers. The second is application-specific and concerns running an algorithm. For both, we give a further subdivision in different types of hybrid quantum-classical computing and we coin terms for them. © 2022, CC BY.

关键词： quantum theory

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Finding Debt Cycles: Qubo Formulations for the Maximum Weighted Cycle Problem Solved Using quantum Annealing

SSRN

引用

SSRN 2022年

作者： Künnemann, Hendrik Phillipson, Frank Maastricht University School of Business and Economics Maastricht Netherlands TNO Dept. Applied Cryptography & Quantum Algorithms The Hague Netherlands

The problem of finding the maximum weighted cycle in a directed graph maps to optimization problems in NP, implying that approaches in classical computing are inefficient. Here, quantum computing might be a promising alternative. Many current approaches on the quantum computer are based on a Quadratic Unconstrained Binary Optimization (QUBO) problem formulation. This paper develops four different QUBO approaches to this problem. The first two take the starting vertex and the number of vertices used in the cycle as given, while the latter two loosen the second assumption of knowing the size of the cycle. A QUBO formulation is derived for each approach. Further, the number of binary variables required to encode the maximum weighted cycle problem with one or both assumptions for the respective approach is made explicit. The problem is motivated by finding the maximum weighted debt cycle in a debt graph. This paper compares classical computing versus currently avaiable (hybrid) quantum computing approaches for various debt graphs. For the classical part, it investigated the Depth-First-Search (DFS) method and Simulated Annealing. For the (hybrid) quantum approaches, we utilized direct embedding on the quantum annealer and two types of quantum hybrid solvers. Simulated Annealing and the usage of the hybrid CQM (Constrained Quadratic Model) machine functioned promising. The DFS method, direct QPU, and hybrid BQM (Binary Quadratic Model), on the other hand, performed less, due to memory issues, surpassing the limit of decision variables, and finding the right penalty values, respectively. © 2022, The Authors. All rights reserved.

关键词： Simulated annealing

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