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Robert Wezeman

Publications and source records attributed to Robert Wezeman.

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Distributed Quantum Computing: Applications and Challenges

Quantum computing is presently undergoing rapid development to achieve a significant speedup promised in certain applications. Nonetheless, scaling quantum computers remains a formidable engineering challenge, prompting exploration of alternative methods to achieve the promised quantum advantage. An example is given by the concept of distributed quantum computing, which aims to scale quantum computers through the linking of different individual quantum computers. Additionally, distributed quantum computing opens the way to new applications on the longer term. This study seeks to give an overview of this technology on an application-level, considering both use cases and implementation considerations. In this way, this work aims to push forward the field of distributed quantum computing, aiming for real-world distributed quantum systems in the near future.

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Noise robustness of a multiparty quantum summation protocol

Connecting quantum computers to a quantum network opens a wide array of new applications, such as securely performing computations on distributed data sets. Near-term quantum networks are noisy, however, and hence correctness and security of protocols are not guaranteed. To study the impact of noise, we consider a multiparty summation protocol with imperfect shared entangled states. We study analytically the impact of both depolarising and dephasing noise on this protocol and the noise patterns arising in the probability distributions. We conclude by eliminating the need for a trusted third party in the protocol using Shamir's secret sharing.

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Evaluating Three Levels of Quantum Metrics on Quantum-Inspire Hardware

With the rise of quantum computing, many quantum devices have been developed and many more devices are being developed as we speak. This begs the question of which device excels at which tasks and how to compare these different quantum devices with one another. The answer is given by quantum metrics, of which many exist today already. Different metrics focus on different aspects of (quantum) devices and choosing the right metric to benchmark one device against another is a difficult choice. In this paper we aim to give an overview of this zoo of metrics by grouping established metrics in three levels: component level, system level and application level. With this characterisation we also mention what the merits and uses are for each of the different levels. In addition, we evaluate these metrics on the Starmon-5 device of Quantum-Inspire through the cloud access, giving the most complete benchmark of a quantum device from an user experience to date.

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Extending the Q-score to an Application-level Quantum Metric Framework

Evaluating the performance of quantum devices is an important step towards scaling quantum devices and eventually using them in practice. The great number of available quantum metrics and the different hardware technologies used to develop quantum computers complicate this evaluation. In addition, different computational paradigms implement quantum operations in different ways. A prominent quantum metric is given by the Q-score metric of Atos. This metric was originally introduced as a standalone way to benchmark devices using the Max-Cut problem. In this work, we show that the Q-score defines a framework of quantum metrics, which allows benchmarking using different problems, user settings and solvers. To showcase the applicability of the framework, we showcase a second Q-score in this framework, called the Q-score Max-Clique. This yields, to our knowledge, the first application-level metric capable of natively comparing three different paradigms of quantum computing. This metric is evaluated on these computational quantum paradigms -- quantum annealing, gate-based quantum computing, and photonic quantum computing -- and the results are compared to those obtained by classical solvers.

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Classification of Hybrid Quantum-Classical Computing

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.

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Evaluating the Q-score of Quantum Annealers

We report the Atos Q-score for D-Wave's quantum devices, classical algorithms and hybrid quantum-classical solver. Computing the Q-score entails solving the Max-Cut problem for increasingly large graphs. This work presents the first computation of the Q-score on a quantum device and shows how these quantum devices compare to classical devices at solving optimisation problems. We use D-Wave's standard methods out of the box with a time limit of 60 seconds. The Q-score for D-Wave's 2000Q and Advantage devices are 70 and 140, respectively. The Q-score for two of D-Wave's classical algorithms, based on tabu search and simulated annealing respectively, are 2,300 and 5,800. Finally, we report the out-of-the-box hybrid approach to have a Q-score of 12,500.

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