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arXiv:2408.12433 · Työväentutkimus Vuosikirja

Technology and Performance Benchmarks of IQM's 20-Qubit Quantum Computer

Leonid Victorovich Abdurakhimov, Adam, Janos, Ahmad, Hasnain, Olli Ahonen, Manuel G. Algaba, Guillermo Alonso, Ville Bergholm, Rohit Beriwal, Matthias Beuerle, Clinton Bockstiegel, Alessio Calzona, Chan, Chun Fai, Daniele Cucurachi, Saga Dahl, Rakhim Davletkaliyev, Olexiy Fedorets, Alejandro Gomez Frieiro, Gao, Zheming, Johan Guldmyr, Andrew Guthrie, Juha Hassel, Hermanni Heimonen, Johannes Heinsoo, Tuukka Hiltunen, Holland, Keiran, Juho Hotari, Hao Hsu, Antti Huhtala, Eric Hyyppä, Aleksi Hämäläinen, Joni Ikonen, Sinan Inel, David Janzso, Teemu Jaakkola, Máté Jenei, Shan W. Jolin, Kristinn Júlíusson, Jaakko Jussila, Sana Khalid, S. Kim, Miikka Koistinen, Roope Kokkoniemi, Anton Komlev, Caspar F. Ockeloen-Korppi, Otto Koskinen, Janne Kotilahti, Toivo Kuisma, Kukushkin, Vladimir, Kumpulainen, Kari, Ilari Kuronen, Joonas Kylmälä, Niclas Lamponen, Julia Lamprich, Alessandro Landra, Martin Leib, Tianyi Li, Per Liebermann, Aleksi Lintunen, Wei Liu, Jürgen Luus, Fabian Marxer, Arianne Meijer-van de Griend, Mitra, Kunal, Jalil Khatibi Moqadam, Jakub Mrożek, Henrikki Mäkynen, Janne Mäntylä, T. Naaranoja, Francesco Nappi, Niemi, Janne, Lucas Ortega, Mario Palma, Miha Papič, Matti Partanen, Jari S Penttilä, Alexander Plyushch, Wei Qiu, Aniket Rath, Kari Repo, Tomi Riipinen, Jussi Ritvas, Pedro Figueroa Romero, Jarkko Ruoho, Jukka Räbinä, Saarinen, Sampo, Indrajeet Sagar, Hayk Sargsyan, Matthew Sarsby, Niko Savola, Mykhailo Savytskyi, Ville Selinmaa, Smirnov, Pavel, Marco Marín Suárez, Linus Sundström, Sandra Słupińska, Eelis Takala, Ivan Takmakov, Brian Tarasinski, Manish Thapa, Jukka Tiainen

Published Aug 22, 2024• 3 citations
arXivHTMLPDF

Abstract

Quantum computing has tremendous potential to overcome some of the fundamental limitations present in classical information processing. Yet, today's technological limitations in the quality and scaling prevent exploiting its full potential. Quantum computing based on superconducting quantum processing units (QPUs) is among the most promising approaches towards practical quantum advantage. In this article the basic technological approach of IQM Quantum Computers is described covering both the QPU and the rest of the full-stack quantum computer. In particular, the focus is on a 20-qubit quantum computer featuring the Garnet QPU and its architecture, which we will scale up to 150 qubits. We also present QPU and system-level benchmarks, including a median 2-qubit gate fidelity of 99.5% and genuinely entangling all 20 qubits in a Greenberger-Horne-Zeilinger (GHZ) state.

DOI
10.48550/arxiv.2408.12433

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Quantum computing has tremendous potential to overcome some of the fundamental limitations present in classical information processing. Yet, today's technological limitations in the quality and scaling prevent exploiting its full potential. Quantum computing based on superconducting quantum processing units (QPUs) is among the most promising approaches towards practical quantum advantage. In this article the basic technological approach of IQM Quantum Computers is described covering both the QPU and the rest of the full-stack quantum computer. In particular, the focus is on a 20-qubit quantum computer featuring the Garnet QPU and its architecture, which we will scale up to 150 qubits. We also present QPU and system-level benchmarks, including a median 2-qubit gate fidelity of 99.5% and genuinely entangling all 20 qubits in a Greenberger-Horne-Zeilinger (GHZ) state.
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Quantum computing is an emerging computational paradigm that uses the principles of quantum mechanics, including superposition, entanglement, and quantum interference, to process information in fundamentally different ways from classical computers. During the last decade, quantum computing has progressed from theoretical research toward experimental and cloud-accessible systems. Recent developments have focused on increasing the number and quality of qubits, reducing gate errors, developing quantum error correction, improving quantum software, and integrating quantum processors with classical high-performance computing systems. Despite significant progress, practical large-scale quantum computing remains challenging because quantum states are extremely sensitive to environmental disturbances, resulting in decoherence and computational errors. Other challenges include limited qubit coherence time, gate fidelity, scalability, cryogenic requirements, quantum error correction overhead, hardware connectivity, programming complexity, and the difficulty of demonstrating useful quantum advantage for real-world applications. Recent developments from major research organizations indicate a shift from simply increasing physical qubit counts toward building reliable logical qubits and fault-tolerant quantum systems. Google has reported progress toward error-corrected logical qubits, while IBM\\\'s roadmap focuses on increasingly complex processors, modular architectures, quantum-classical integration, and fault-tolerant systems. Microsoft is pursuing a topological-qubit approach aimed at scalable quantum computing. This paper reviews the current state of quantum computing, examines major technological and scientific challenges, analyzes current research directions, and identifies future opportunities in drug discovery, materials science, optimization, cryptography, artificial intelligence, finance, and scientific simulation. The study concludes that the most realistic future is likely to involve quantum-centric computing, in which quantum processors work together with classical CPUs, GPUs, high-performance computing systems, and quantum networks rather than completely replacing classical computers.
This paper proposes a novel quantum computing architecture designed based on fundamental physical laws. The architecture addresses limitations inherent in current quantum computing approaches, primarily those utilizing superconducting qubits. The core of the design leverages emerging quantum bit technologies, specifically topological qubits and photonic qubits, to achieve enhanced fidelity and scalability. We argue that by moving beyond the established paradigm of superconducting qubits, and embracing physically grounded approaches, we can significantly advance the performance and practicality of quantum computation. This document details the architectural components, outlines the key technological considerations, and presents a theoretical framework for a fundamentally robust quantum computing system. The focus is on building a system that aligns with known physical constraints, offering a more reliable path toward realizing the full potential of quantum computation. ---
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