Willow in comparison – Google quantum chip

In scientific research, comparative analysis is an excellent way to objectively quantify two measurable entities. The recent Google quantum chip (named Willow) does that efficiently as it compares its capability with today’s fastest supercomputers. The comparison note on Google’s blog is worth reading.

In scientific analysis, such comparison teaches us three things:

a) how a scientific boundary is claimed to be pushed?

b) how a benchmark problem is used to achieve comparison?

c) what is the current state-of-the-art in that research area?

Some further observations on the work:

  • The theme of the Nature paper reporting this breakthrough is mainly on error correction. Technically, it shows how error tolerance is measured for a quantum device. This device is based on superconducting circuits, which were tested first on a 72-qubit processor and then on a 105-qubit processor.
  • Interestingly, as the authors mention in the paper, the origins of the errors are not understood well.
  • The paper is quite technical to read, and, to my limited understanding as an outsider, it makes a good case for the claim. The introduction and the outlook of the paper are written well, and give more technical information that can be appreciated by a general scientific audience.
  • There is more to come ! It looks like Google has further plans to expand on this work, and it will be interesting to see in which direction they will take the capability. The Google blog shows a roadmap and mentions their ambition as follows: “The next challenge for the field is to demonstrate a first “useful, beyond-classical” computation on today’s quantum chips that is relevant to a real-world application. We’re optimistic that the Willow generation of chips can help us achieve this goal.”
  • In the past 12 months or so, there has been a lot of buzz related to AI tools (thanks to GPTs, Nobels and perplexities :-), which are mainly in the realm of software theoretical development. This breakthrough in the realm of ‘hardware’ tells us how the physical world is still important!

More to learn and explore…interesting times ahead..

Gerhard Herzberg – scientific life


References:

Pavan Kumar, G. V. “Gerhard Herzberg (1904–1999): A Pioneer in Molecular Spectroscopy.” Resonance 29 (2024): 1339. https://www.ias.ac.in/describe/article/reso/029/10/1339-1345.

Stoicheff, Boris. Gerhard Herzberg: An Illustrious Life in Science. Ottawa : Montréal ; Ithaca N.Y.: Canadian Forest Service,Canada, 2002.

Stoicheff, Boris P. “Gerhard Herzberg PC CC. 25 December 1904 – 3 March 1999.” Biographical Memoirs of Fellows of the Royal Society 49 (December 2003): 179–95. https://doi.org/10.1098/rsbm.2003.0011.

Article on Gerhard Herzberg

The October 2024 issue of Resonance, Journal of Science Education

highlights the life and science of Gerhard Herzberg.

He was one of the greatest molecular spectroscopists who laid the foundation of atomic and molecular quantum mechanics and deeply impacted molecular astrophysics and astrochemistry.

He lived an extraordinary life, first in Europe learning quantum mechanics and then escaping 1930s Germany as his wife was of Jewish origin. Then, he settled in Canada to build and lead his lab, which was considered the ‘mecca of spectroscopy’ at NRC, Ottowa.

I wrote a sci-biography article about him in this issue

Link to full edition: https://www.ias.ac.in/listing/articles/reso/029/10

If you don’t know – Resonance is a pedagogical journal published by the Indian Academy of Sciences. It is a true open-access journal. Free to read and does not charge the authors to publish.

Do explore the past editions. There are some absolute gems. https://www.ias.ac.in/listing/issues/reso

Conversation with Chinmay Tumbe

Chinmay is an author, historian and associate professor at IIM Ahmedabad: https://sites.google.com/site/chinmaytumbe/home.

We explored his intellectual landscape of becoming a writer and a historian. We discuss his writing process and his experience of researching and teaching business history in a scientific & engaging way.

Many related strands…

Listen as we humanize science with history…

References:

  1. “Chinmay Tumbe.” Accessed October 15, 2024. https://sites.google.com/site/chinmaytumbe/home.
  2. “Chinmay Tumbe | IIMA.” Accessed October 15, 2024. https://www.iima.ac.in/faculty-research/faculty-directory/Chinmay-Tumbe.
  3. “‪Chinmay Tumbe – ‪Google Scholar.” Accessed October 15, 2024. https://scholar.google.com/citations?hl=en&btnA=1&user=MyvxhAUAAAAJ.
  4. “Chinmay Tumbe – History.” Accessed October 16, 2024. https://sites.google.com/site/chinmaytumbe/home/history.
  5. Diamond, Jared, and James A. Robinson. Natural Experiments of History. Reprint edition. Cambridge, Mass: Harvard University Press, 2011.
  6. Jha, Prabhat, Yashwant Deshmukh, Chinmay Tumbe, Wilson Suraweera, Aditi Bhowmick, Sankalp Sharma, Paul Novosad, et al. “COVID Mortality in India: National Survey Data and Health Facility Deaths.” Science 375, no. 6581 (February 11, 2022): 667–71. https://doi.org/10.1126/science.abm5154.
  7. “Literature Festivals: India’s Vibrant History Scene.” Accessed October 15, 2024. https://historylitfest.com/.
  8. Tumbe, Chinmay. Age Of Pandemics (1817-1920): How They Shaped India and the World, 2020.
  9. ———. India Moving: A History of Migration. Vintage Books, 2018.
  10. X (formerly Twitter). “(1) Chinmay Tumbe (@ChinmayTumbe) / X,” June 9, 2024. https://x.com/chinmaytumbe.
  11. X (formerly Twitter). “HITCH (@BizEconHist) / X,” September 15, 2022. https://x.com/bizeconhist.

Physics Nobel 2024 – anywhere to everywhere

The Nobel Prize in Physics 2024 was awarded to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks“. There has been much buzz surrounding this prize, especially in the context of whether these discoveries are indeed in the realm of mainstream physics. Many science commentators have questioned the choice and have provocatively dismissed it as ‘not part of mainstream physics’.

This has also brought into focus an important question: What is physics?

This question does not have a simple answer, given the rich history of the subject and its applicability over centuries. What we now call engineering is essentially an extrapolation of thinking in physics. New avenues have branched out from physics that cannot be readily identified as mainstream physics; a case in point is artificial intelligence and machine learning.

One of the aspects of mainstream physics is that the intellectual investment in the contemporary scenario is mainly driven by discoveries happening in the realm of quantum mechanics and general relativity. One of the mainstream problems in physics is to combine quantum mechanics and gravitation, which remains an unresolved task. Therefore, significant attention is paid to understanding these theories and verifying them through experimentation. Other areas and sub-disciplines in physics have become loosely connected to these two important theories.

There is another dimension to physics that is equally important and has vast applications: statistical physics. In statistical physics, the motivation comes from multi-particle systems and their applicability as models to understand our world, including biological systems. One utilizes knowledge from mathematics and statistics, combining them with physical laws to predict, invent and understand new forms and assemblies of matter. This thinking has been extrapolated to abstract assemblies and hence applied to a variety of situations. This approach has led to a revolution in how we can understand the realistic world because a statistical viewpoint is very useful for studying complex systems, such as many-body quantum mechanical aggregates (such as groups of electrons), dynamics of molecules inside a cell and the evolution of the stock market. Statistical physics plays a dominant role in all these situations. It has become a ubiquitous tool, making it difficult to directly connect it to basic principles of physics as taught in college textbooks and classrooms. It reminds me of a saying: if you are everywhere, then you are from nowhere.

This situation leads us back to the question: What is physics? John Hopfield himself offers an interesting definition related to this question, emphasizing that viewpoint is a crucial element. This perspective allows for greater freedom in using physics beyond conventional definitions. Among scientific disciplines, physics is always associated with its depth of understanding. This is a good opportunity to emphasize the breadth of physics, which is equally noteworthy.

In that light, the 2024 Nobel Prize in Physics should be welcomed as an expansion of the horizon of what constitutes physics. In a day and age where basic science has been questioned regarding its applicability to modern-day life and technology, this prize serves as a welcome change to showcase that basic science has played a fundamental role in establishing a contemporary tool of primary importance to society.

This point is particularly important because policymakers and politicians tend to focus on immediate issues and ask how they can influence them by using modern-day technology. Utility is central to this form of thinking. Given that basic sciences are often viewed as ‘not immediately useful’, this viewpoint diminishes the prominence of foundational disciplines: physics, chemistry, biology, and mathematics. In contrast, this prize reinforces the idea that building cutting-edge technology, which holds contemporary relevance and societal impact, has its roots in these foundational disciplines. In that sense, this prize is an important message because, like it or not, the Nobel Prize captures the attention not only of the scientific world but also of the public and, hence, of interest to politicians and policymakers.

Issac Asimov is attributed to have said: “There is a single light of science, and to brighten it anywhere is to brighten it everywhere.” The Nobel Prize in Physics 2024 fits that bill.

Physics is a point of view about the world

picture from : Hopfield, John J. “Whatever Happened to Solid State Physics?” Annual Review of Condensed Matter Physics 5, no. Volume 5, 2014 (March 10, 2014): 1–13. https://doi.org/10.1146/annurev-conmatphys-031113-133924.

The title of this blog is the closing line of an autobiographical essay written by John Hopfield (pictured above), one of the physics Nobel laureates today: “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”

In this essay, he retraces his trajectory across various sub-disciplines of physics and how he eventually used his knowledge of physics to work on a problem in neurobiology that further connects to machine learning.

The title of the essay is provocative(see below) but worth reading to understand how physics has evolved over the years and its profound impact on various disciplines.

Reference: Hopfield, John J. “Whatever Happened to Solid State Physics?” Annual Review of Condensed Matter Physics 5, no. Volume 5, 2014 (March 10, 2014): 1–13. https://doi.org/10.1146/annurev-conmatphys-031113-133924.

Thanks to Gautam Menon for bringing the essay to my notice.

By the way, Hopfield and Deepak Dhar shared the 2022 Boltzmann medal, and after the award, he gave a wonderful online talk at IMSc, Chennai. Thanks to Arnab Pal of IMSc for bringing this to my notice on X.

Let me end this post quoting Hopfield from the mentioned essay:

What is physics? To me—growing up with a father and mother who were both physicists—physics was not subject matter. The atom, the troposphere, the nucleus, a piece of glass, the washing machine, my bicycle, the phonograph, a magnet—these were all incidentally the subject matter. The central idea was that the world is understandable, that you should be able to take anything apart, understand the relationships between its constituents, do experiments, and on that basis be able to develop a quantitative understanding of its behavior. Physics was a point of view that the world around us is, with effort, ingenuity, and adequate resources, understandable in a predictive and reasonably quantitative fashion. Being a physicist is a dedication to the quest for this kind of understanding.

Let that quest never die!