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FQXi BLOGS
October 1, 2022

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Quantum information pioneers win US$3-million Breakthrough Prize
By ZEEYA MERALI • Sep. 22, 2022 @ 16:21 GMT

Charles Bennett, Breakthrough Prizes
Congratulations to Charles Bennett of IBM, Gilles Brassard of the University of Montreal, David Deutsch of Oxford University and Peter Shor at MIT for sharing this year’s Breakthrough Prize in Fundamental Physics. I’ve written more about the win for Nature, as well as the awards in the Life Sciences and in Maths.

The physicists were recognised as founders of the field of quantum information, laying the groundwork for many of today’s advances in quantum communication, cryptography and quantum computing. In 1984, Bennett and Brassard developed the BB84 protocol for exploiting quantum effects for secure communication. In 1985, Deutsch published a paper outlining the first ‘universal quantum computer.’ And then in the 90s, Shor developed an algorithm enabling a quantum computer to factorise large numbers—the first quantum algorithm to describe a practically useful process. It also has potentially troubling consequences, because much of today’s Internet traffic is encoded using a system based on the fact that classical computers cannot factorise large numbers quickly.

In our interview, Shor recalled being reluctant to tell people what he was working on until he had the algorithm; he did mention it to one colleague who “poo pooed” it. But once published, he had assumed that many more would follow, which hasn’t really transpired.

I contacted quantum physicist Sabrina Maniscalco at the University of Helsinki for her reaction to the win, but in the end her quote got cut because the article is quite long. However, I want to share her thoughts on the importance of supporting foundational research. “This prize recognises the importance of purely intellectual-curiosity driven research,” Maniscalco told me. “It shows us how unveiling the fundamental laws of our Universe gives us the fruits of new empowering technologies that will help us face the challenges our society is facing, from climate change to health care and sustainable development.”

Gilles Brassard, Breakthrough Prizes
Quantum computing has also been in the news in recent weeks thanks to a provocative article by Nikita Gourianov, a quantum physicist at Oxford University, who wrote a piece in The Financial Times about “The Quantum Computing Bubble.” There have been numerous announcements in recent years of small-scale quantum computers performing specific tasks faster than a classical supercomputer could. IBM's Eagle quantum computer is the biggest of the current crop, I believe, with 127 quantum bits. Nonetheless Gourianov is concerned that large-scale quantum computers are significantly harder to build because of the difficult challenge of dealing with errors.

David Deutsch, Breakthrough Prizes
Gourianov’s piece caused a bit of a stir. Scott Aaronson gave a brief response, on his blog, noting that there are known strategies for addressing errors, even if it may take a while to develop the technological capabilities to deal with them. Given this discussion, I also contacted Gourianov for comment on the physics prize. Part of his comment has been included in the Nature article, but anyone who has read the FT piece can probably guess that his positive quote was tempered by a big “but” that followed, which has been cut to save space.

Here is Guarinov’s full quote, with a bit of extra context:

“This massive result proved that quantum computers were more than just another academic curiosity,” says quantum physicist Nikita Gourianov, also at Oxford. However, Gourianov has been urging against overhyping progress. He notes that building a large-scale quantum computer is no easy feat. "Whenever quantum computers become larger, the noise and errors explode," he says.

I also spoke to Shor about this concern. He agreed that building a large-scale quantum computer remains an “immense engineering job” adding that error-correction will require gates that are 10 to 100 times more accurate than we have now. He was not pariticularly surprised by any backlash to quantum computing. “The media hype has really accelerated over the past few years,” giving the wrongful impression that a large-scale quantum computer lies around the corner, he told me. “It’s probably going to take 20, 30 or even 40 years,” he added.

Peter Shor, Breakthrough Prizes
This, of course, shouldn’t detract from the well-deserved wins by the physics winners—and indeed the life sciences winners and the maths winner. You can read more about them all in the Nature piece. And for a fun proposal for dealing with errors in quantum computing by harnessing a portal to an extra time dimension (of sorts), check out this article I wrote for Scientific AmericanNew Phase of Matter Opens Portal to Extra Time Dimension,” in July.

I’ll finish with more words from Maniscalco, who was speaking in the context of the Fundamental Physics award, but whose words are probably relevant for all the winners, and indeed beyond:

“History teaches us that…we need resources, focus, and hard work,” she says. “But most of all we need to believe in the impossible and make it happen.”
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Machine Learning Based Control of Quantum Devices I Quantum Technology User Meeting 2022 by Natalia Ares
By NATALIA ARES • Sep. 19, 2022 @ 15:39 GMT

At the Quantum Technology User Meeting 2022 Natalia Ares from the University of Oxford shared her work on using machine learning to tune up semiconductor quantum devices. In her experiments, fast and high-fidelity readout of the state of the quantum devices is a crucial ingredient to generating the large datasets needed to train the AI agents. Already now, machine learning improves the speed and reliability of tuning up semiconductor quantum dots, and it enables faster and more reliable qubit experiments on this platform



Keywords: #IAF #Information_As_Fuel #Ares #Quantum_Information #Quantum_Technology
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AI4SD2022: Cross-architecture tuning of quantum devices faster than human experts – Dr Natalia Ares by Natalia Ares
By NATALIA ARES • Sep. 19, 2022 @ 15:38 GMT

This video is the tenth talk that was given for the AI4SD2022 Conference.



Cross-architecture tuning of quantum devices faster than human experts – Dr Natalia Ares (University of Oxford)



Abstract: A concerning consequence of quantum device variability is that the tuning of each qubit in a quantum circuit constitutes a time-consuming non-trivial process that has to be independently performed for each device, requiring a deep understanding of the particular device to be tuned and “muscle memory”. I will show a machine-learning based approach that can tune quantum devices completely automatically, regard less of the device architecture and being agnostic to the material realisation. Our algorithm was able to tune double quantum dot devices defined in a Si FinFET, a Ge/Sicore/shell nanowire, and both SiGe and AlGaAs/GaAs heterostructures, successfully accommodating the different modes of gate operation and noise characteristics. We report tuning times as fast as 10 minutes starting from scratch – well over an order of magnitude faster than what would be achievable by a dedicated expert human operator. Just as AlphaZero showed that the achievements of AlphaGo could be extended to learning to win at different board games without needing to be reprogrammed for each, so our result shows that cross-architecture tuning of quantum devices can be achieved using machine learning.



Bio: Natalia Ares is an Associate Professor at the Department of Engineering Science, a Tutorial Fellow in New College and a Royal Society University Research Fellow. Her research focuses on quantum device control. She develops machine learning algorithms for the automation of quantum device measurement and optimisation. She also harnesses the capabilities of nanoscale devices to explore thermodynamics in the quantum realm. She completed her PhD thesis at Université Grenoble Alpes, France, and her undergraduates’ studies at Universidad de Buenos Aires, Argentina.



Keywords: #IAF #Information_As_Fuel #Ares #Quantum_Information
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Marcus Huber: Thermodynamic limits to measurements by Marcus Huber
By JOSH HOFFMAN • Sep. 19, 2022 @ 15:34 GMT

Workshop on Quantum Research and Education in Europe and in Ukraine

(QREdU 2022) https://kau.org.ua/qredu

27‑28 July 2022, Kyiv, Ukraine



Keywords: #IAF #Information_As_Fuel #Huber #Quantum #Thermodynamics
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Lab based tests of gravitational decoherence by Prof. Gerard Milburn (Queensland U.) by Gerard Milburn
By JOSH HOFFMAN • Sep. 19, 2022 @ 15:24 GMT

Physics Colloquium (16/06/2022).



Abstract: The enduring challenge of reconciling quantum mechanics and general relativity is not helped by a lack of experimental guidance. Theoretical reconciliations, such as loop quantum gravity and string theory, seem to require unachievable experimental domains, and, while astrophysical data may one day provide guidance, the possibility of lab based experiments seems remote. Recently there have been suggestions for lab based tests of one aspect of the problem: gravitational decoherence. In this talk, I will review the concept of gravitational decoherence form Karolyhazy to Penrose and Diosi. I will discuss opto-mechanical proposals for constraining the decoherence rate by experiment. I will conclude with a discussion of a new approach based on single photonics that avoid many of the challenges that arise from tests involving particles with large rest mass.



Keywords: #IAF #Information_As_Fuel #Milburn #Gravity #Decoherence #Quantum_Information
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