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Test Environment for Verifying Quantum Algorithms and Controlling SINARA Real-time Modules

Michał P. WYROSTKIEWICZ, Tomasz Kuczerski, D. Gibalski

Published Mar 26, 2024• 0 citations
Publisher

Abstract

This paper describes the process of creating and using a quantum computing environment. It also discusses the manner in which first quantum experiments using mathematical models, simulators or commercially available quantum computers may be conducted. In addition, it explains how the available quantum algorithms may be understood and applied. Finally, the role of real-time systems and their control in the architecture of a quantum computer is described.

DOI
10.5604/01.3001.0054.4488

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This paper describes the process of creating and using a quantum computing environment. It also discusses the manner in which first quantum experiments using mathematical models, simulators or commercially available quantum computers may be conducted. In addition, it explains how the available quantum algorithms may be understood and applied. Finally, the role of real-time systems and their control in the architecture of a quantum computer is described.
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This paper discusses the basic components that are required to build a quantum computing environment. Quantum computers have a distinctive advantage over classical computers due to its ability to solve problems with large number of computations faster. To utilize these capabilities to its best, we should ensure that the computers are on par with the quantum computing requirements to float a working environment. The whole thrust on this is to ensure that the quantum computing environment is chained by the laws of quantum mechanics. The issue becomes more complicated when it is to be executed on a classical platform. This paper surveys the basics of Quantum Computing and the existing Quantum Computing simulators. Further, it also points out the basic rules to ensure a proper translation of each capabilities from a classical system to a quantum system and vice versa.
For the first time, we enable the execution of hybrid machine learning methods on real quantum computers with 100 data samples and real-device-based simulations with 5,000 data samples, thereby outperforming the current state of research of Suryotrisongko and Musashi from 2022 who were dealing with 1,000 data samples and quantum simulators (pure software-based emulators) only. Additionally, we beat their reported accuracy of 76.8%76.8\%76.8% by an average accuracy of 91.2%91.2\%91.2%, all within a total execution time of 1,687 seconds. We achieve this significant progress through two-step strategy: Firstly, we establish a stable quantum architecture that enables us to execute HQML algorithms on real quantum devices. Secondly, we introduce new hybrid quantum binary classification algorithms based on Hoeffding decision tree algorithms. These algorithms speed up the process via batch-wise execution, reducing the number of shots required on real quantum devices compared to conventional loop-based optimizers. Their incremental nature serves the purpose of online large-scale data streaming for DGA botnet detection, and allows us to apply hybrid quantum machine learning to the field of cybersecurity analytics. We conduct our experiments using the Qiskit library with the Aer quantum simulator, and on three different real quantum devices from Azure Quantum: IonQ, Rigetti, and Quantinuum. This is the first time these tools are combined in this manner.
Ion trap quantum computers are complex optoelectronic systems that require several electronic subsystems orchestrated to sub-1ns precision, both low-noise and high speed. WUT developed a modular control system in EEM/DIOT form factor called SINARA (Standardised Instrumentation Architecture for Research Applications) [1]. SINARA became the de facto standard in atomic and Molecular laboratories worldwide; a few leading quantum computer manufacturers also use it. Its success, which can be attributed to the open-source, open-hardware licensing model, has significantly advanced the field of quantum computing by providing a reliable and adaptable control system. SINARA was primarily developed for lab applications but recently has been transformed into an industrial form factor (DIOT [5]) because many lab projects have turned into spin-offs and startups.The scaling of quantum computers creates several technological issues. Most topologies are enclosed in a vacuum and use cryogenic temperatures. Future quantum computer architectures need to implement electronic control systems capable of steering hundreds of thousands of electrodes with high precision and relatively high voltage of a few dozen V. Within the framework of the Quantera SIQCI [3] project, a collaborative effort aimed at advancing the field of quantum computing, we are building a demonstrator of such a scalable control system. An essential step of the design process is characterising a standard 180nm high voltage process at temperatures below 10 K. The next step is updating the process PDK and designing the test structures using updated models. This paper presents the requirements for such a control system, the first results of the measurements and the design methodology.Furthermore, this talk will unveil the first coherent operations results performed on ions trapped in the WUT labs using the SINARA system, marking a significant milestone in our system’s practical applications.