Accelerating quantum computer developments

Alberts, Garrelt; Rol, Michiel Adriaan; Broer, Benno W.; Bultink, Cornelis Christiaan; Rijlaarsdam, Matthijs; Hauwermeiren, Amber E. Van

doi:10.1140/epjqt/s40507-021-00107-w

Cited by 18 publications

(9 citation statements)

References 31 publications

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“…Other important and recent works can be seen in Singh et al ( 2021a ), Wang et al ( 2021 ), Yunakovsky et al ( 2021 ), Gao et al ( 2021 ), Huber et al ( 2021 ), Kulkarni et al ( 2021 ), Ajagekar and You ( 2021 ), Alberts et al ( 2021 ), Medvidović and Carleo ( 2021 ), Singh et al ( 2021b ), Im et al ( 2021 ) Liu et al ( 2021 ).…”

Section: Literature Reviewmentioning

confidence: 96%

A review on quantum computing and deep learning algorithms and their applications

Valdez

Melín

2022

Soft Comput

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In this paper, we describe a review concerning the Quantum Computing (QC) and Deep Learning (DL) areas and their applications in Computational Intelligence (CI). Quantum algorithms (QAs), engage the rules of quantum mechanics to solve problems using quantum information, where the quantum information is concerning the state of a quantum system, which can be manipulated using quantum information algorithms and other processing techniques. Nowadays, many QAs have been proposed, whose general conclusion is that using the effects of quantum mechanics results in a significant speedup (exponential, polynomial, super polynomial) over the traditional algorithms. This implies that some complex problems currently intractable with traditional algorithms can be solved with QA. On the other hand, DL algorithms offer what is known as machine learning techniques. DL is concerned with teaching a computer to filter inputs through layers to learn how to predict and classify information. Observations can be in the form of plain text, images, or sound. The inspiration for deep learning is the way that the human brain filters information. Therefore, in this research, we analyzed these two areas to observe the most relevant works and applications developed by the researchers in the world.

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Section: Literature Reviewmentioning

confidence: 96%

A review on quantum computing and deep learning algorithms and their applications

Valdez

Melín

2022

Soft Comput

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“…Although sufficiently powerful quantum computers are not fully developed yet today, this evolving research area is drawing a growing attention. Generally, the forecasts are optimistic for having the quantum computer as a commercial product in the coming years [22]. Therefore, encryption in current communications systems needs further improvement to face the forthcoming risk of developing a full-scale quantum computer, hence, breaking the current encryption algorithms exponentially faster than the best non-quantum machines.…”

Section: Quantum Communicationsmentioning

confidence: 99%

Characterizing and Utilizing the Interplay between Quantum Technologies and Non-Terrestrial Networks

Al-Hraishawi¹,

Rehman²,

Razavi³

et al. 2022

Preprint

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Quantum technologies have been widely recognized as one of the milestones towards the ongoing digital transformation, which will also trigger new disruptive innovations. Quantum technologies encompassing quantum computing, communications, and sensing offer an interesting set of advantages such as unconditional security and ultra-fast computing capabilities. However, deploying quantum services at a global scale requires circumventing the limitations due to the geographical boundaries and terrestrial obstacles, which can be adequately addressed by considering non-terrestrial networks (NTNs). In the recent few years, establishing multi-layer NTNs has been extensively studied to integrate space-airborne-terrestrial communications systems, particularly by the international standardization organizations such as the third-generation partnership project (3GPP) and the international telecommunication union (ITU), in order to support future wireless ecosystems. Indeed, amalgamating quantum technologies and NTNs will scale up the quantum communications ranges and provide unprecedented levels of security and processing solutions that are safer and faster than the traditional offerings. This paper provides some insights into the interplay between the evolving NTN architectures and quantum technologies with a particular focus on the integration challenges and their potential solutions for enhancing the quantum-NTN interoperability among various space-air-ground communications nodes. The emphasis is on how the quantum technologies can benefit from satellites and aerial platforms as an integrated network and vice versa. Moreover, a set of future research directions and new opportunities are identified.

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“…Therefore, a continuous engineering cycle is needed to iteratively approach the desired parameters for this target application. In [9,11] a more in-depth discussion on the development of superconducting quantum chips is given.…”

Section: Motivation and Introductionmentioning

confidence: 99%

Key ingredients for manufacturing superconducting quantum processors at scale

Last¹,

Mongillo²,

Ivanov³

et al. 2023

Novel Patterning Technologies 2023

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Computational ecosystems in which classical supercomputers and general-purpose quantum computers provide a steady increase in value-creating computation capabilities have shown immense progress in recent years. Superconducting qubit technology, in particular, has emerged as a leading candidate for realizing a scalable quantum computing platform ready for paving the way to commercial quantum advantage. However, current academic approaches in fabrication and testing of quantum devices are not scalable and have already started to limit the rapid development of the field. Novel solutions are required to tackle the combined challenge of increasing the qubit count on a quantum processor and the need to further reduce the qubit’s error rates. This, in turn, will lead to a renewed acceleration in qubit manufacturing, test and diagnostics. Here we present aspects of how to move superconducting qubit manufacturing and testing from small-scale laboratory to large-scale fabrication facility environments. To enable this transfer, two key ingredients are demonstrated: (i) A foundry-compatible fabrication process of superconducting qubits that can benefit from the advanced process control in industry-scale CMOS fabrication facilities, and (ii) an acceleration of testing and cryogenic measurement throughput by using a milli-Kelvin cryo-CMOS signal multiplexer operating in near proximity to quantum devices and integrated qubit diagnostic and benchmarking tools with end-to-end data analytics. Although some of these elements have been explored independently, co-development is crucial to enable an efficient scalable development cycle for quantum computing technology. A full development cycle consisting of scalable manufacturing, testing, and benchmarking will enable the large-scale fabrication and control of quantum computing devices and thus pave the way to commercial quantum advantage.

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Accelerating quantum computer developments

Cited by 18 publications

References 31 publications

A review on quantum computing and deep learning algorithms and their applications

A review on quantum computing and deep learning algorithms and their applications

Characterizing and Utilizing the Interplay between Quantum Technologies and Non-Terrestrial Networks

Key ingredients for manufacturing superconducting quantum processors at scale

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