Looking back on 2023

The end of the year is good time to reflect on what went well and what didn't over the past twelve months, and what changes we hope to make in the year to come. Here's my list:

1. Presentations. I gave 11 talks this year to a variety of audiences (conferences, workshops, internal presentations, external seminars). Some went better than others. The main culprits for my bad talks are (still) trying to say too much in the time allotted, and failing to pitch well to the specific audience. It is particularly challenging to convey the broad strokes of the research to everyone present at a level that interests them while still going into enough depth to satisfy the few experts in the audience. The best presentations I gave involved audience participation using QR code polls - even including one or two over the course of an hour-long talk is a great way to get the audience to stop, think, and start paying attention again. The best talks I attended spent most of the time explaining the problem set up and broader context and very little time on the speaker's own contribution.

2. Publications. Midway through the year it seemed like I was going to put out fewer papers than usual. Then in November and December I ended up being swamped with finalising several manuscripts all at once (hence a reduced blogging frequency). The final tally is nine original manuscripts completed this year. Is this too many? Many decry the publish or perish culture, the endlessly increasing rate at which papers are being published, courtesy coauthorships, salami publishing, and whatnot. At least in my case, I think I have made a meaningful contribution to every paper I have coauthored this year, but I need to strike a better balance between deep work on new research directions and easier (but still time-consuming) work on existing areas of expertise.

3. Upskilling. I played around with using AI tools like StableDiffusion (text to image), LLama (text generation), whisper (speech to text), and a few different web-based academic paper summarisation / recommendation tools. Given the tendency of large language models to hallucinate and spit out falsehoods, it's hard to trust them when seeking new knowledge (e.g. summarising or suggesting new papers to read), but I've found them quite useful for rephrasing ideas in an amusing way or making cool images for talks (see below).

Happy 2024!

Towards fault-tolerant quantum computing with Rydberg atoms

 I'm a bit late to the party, but finally managed to get a chance to read the paper "Logical quantum processor based on reconfigurable atom arrays" by Harvard, QuEra, and collaborators, which hit the headlines a few weeks ago. My thoughts:

• Sadly many articles covering the paper gloss over the important distinction between error detection and error correction: QuEra's press release, The Harvard Gazette, EurekaAlert, and others. Optics & Photonics News provides more balanced coverage. The impressively high (above break-even) fidelities demonstrated in the paper require post-selection, discarding experimental runs where errors were detected. The post-selection probability is as low as 0.04% for the largest system sizes studied, and will get exponentially smaller for bigger circuits. The bottom line: scaling up to a useful size needs integration of error correction.
• How to integrate error correction? One needs to process the error detection measurements in real-time and then apply correcting gates to the qubits while the circuit is being run. Figure 4 of the paper does demonstrate implementation of measurement-dependent feedforward operations, but not yet integrated with error decoding and correction operations. This seems to be in principle an engineering challenge that can be solved with more hard work.
• Scaling up to more qubits and deeper circuits will require continuous pumping and replenishment of Rydberg atoms. Otherwise, the circuit width will be limited by the finite success probability for trapping each atom, and the depth by the ~10s trapping lifetime.
• The quantum processor architecture, involving separate storage, processing, and readout zones, as well as the ability to execute gates with arbitrary connectivity and in parallel using just a few structured laser beams, looks much more promising for scalability compared to superconducting quantum processors.

There is more discussion over at Shtetl-Optimized.

Dark horse papers

A journal's impact factor - the number of citations it receives in a year divided by the number of papers published in the preceding years - is often used as a proxy for the importance of the papers it publishes. But the impact factor is a poor predictor for individual articles, since article citation distributions are heavy-tailed, so their mean is strongly affected by rare outliers that receive many more citations than a typical article. 

It is difficult to estimate the impact a paper will have before it is published. Thus, one can find papers published in top journals that after several years have only attracted a handful of citations - the editors and referees overestimated the impact the article would have. Similarly, there are papers that were only published in a specialized (e.g. local society-run) journal and ended up having a big impact. Some examples:

S. Aubry and G. Andre, Analyticity breaking and Anderson localization in incommensurate lattices, Ann. Israel Phys. Soc. 3, 133 (1980). A conference proceedings article with more than a thousand citations and even its own wikipedia page, influential as a simple analytically-solvable toy model of a localization transition.

T. Fukui, Y. Hatsugai, and H. Suzuki, Chern Numbers in Discretized Brillouin Zone: Efficient Method of Computing (Spin) Hall Conductances, J. Phys. Soc. Japan 75, 074716 (2006). This is essential reading for anyone who wants to numerically compute Berry curvatures, since it solves the problem of how to fix a smooth gauge to compute the k-space derivatives of the Bloch functions. Also has more than a thousand citations.

M. Fujita, K. Wakabayashi, K. Nakada, and K. Kusakabe, Peculiar Localized State at Zigzag Graphite Edge, J. Phys. Soc. Jpn. 65, 1920 (1996). This was a paper that was ahead of its time, showing that certain edge configurations of graphene give rise to strongly localized edge states. This was more of a theoretical curiosity, until samples of graphene were isolated a few years later, as you can see in the time series of citing articles:

 

These are just a few examples I've come across in my own research. There are many more out there! Do you have your own favourite example?