And more items of interest

 Here are some outreach/popularization tidbits:

• Maryam Tsegaye won the 2020 Breakthrough Junior Challenge with this video explaining quantum tunneling.  Very fun, and scholarships are a great use of the Breakthrough resources.
• Here is a Harvard physics colloquium given by Prof. Xiaoxing Xi, about "Scientific espionage, open exchange, and American competitiveness".  Prof. Xi was a victim of a ridiculous accusation by the FBI, and was quite rightly exonerated.
• Here is a well done three video series (part 1, part 2, part 3) about Jan Hendrik Schön.  I've written about my perspective on this a couple of years ago.
• This is a nice article by John C. Baez about The Joy of Condensed Matter.  Welcome aboard, John :-)  For those who don't know, John's "This Week's Finds" columns were a fantastic contribution to the larger community, and a staple of my time as a grad student, right up there with Bob Park's always snarky and informative "What's New" articles.

Brief items

Here are a few items I came across in the last few days that may be of broader interest:

• John Preskill's lectures for his quantum computing course (cross-listed between physics and CS at Cal Tech) are now available on youtube here.  Here are the lecture notes. 
• Christopher Gutiérrez at UCLA had previously made a very helpful set of tutorials for using Adobe Illustrator and Blender to make high quality scientific figures, and those are here.
• Here is a nice article explaining in some detail about what will be required for semiconductor fabrication (particularly the metal vias) to reach the "2 nm node" (which does not mean that minimum feature sizes will be 2 nm).  
• Along those same lines, the Semiconductor Research Corporation has released their Decadal Plan for Semiconductors.  Themes include a renewed interest in analog electronics for AI and machine learning (hello neuromorphic computing), and a critical need for new memory technologies as projected demand for memory will outstrip foundry production capacity if traditional memory architectures are followed.
• APS and AAPT have released large portions of their Effective Practices for Physics Programs guide.
• The video of the landing of the Perseverance rover on Mars is just fantastic.

Grad school admissions this year

Based on conversations with my colleagues at my institution and across the US, graduate program application rates in the US seem to be up quite a bit this year, including in physics and astronomy.  This is happening at the same time that many graduate programs are still working to handle the exceptional circumstances that arose due to the pandemic.  These include: 

• lower graduation rates (as students are slower to graduate when there is increased uncertainty in the post-degree employment market, academic or otherwise); 
• continued visa challenges with international students (e.g., students who have enrolled remotely from outside the US in fall '20 but have not yet been able to get here, and therefore may well need extra time to affiliate with a research advisor once they get to the US, presumably in the late spring or summer); 
• restricted budgets to support existing and incoming students (especially at some public universities whose finances have been hardest hit by the pandemic-related economic fallout)

This whole mess increases the stress on graduate applicants by making an already fraught process even more competitive, in the sense of more people vying for fewer openings.  Graduate admissions is a complicated process driven very strongly by detailed needs that are often not visible to the applicant (e.g., if researchers in an area don't have a need for more students in a given year, something that may not be clear until January, admissions offers in that area are going to be limited).  I hope people know this, but it's worth stating explicitly:  Not getting admitted to a program is about the fit at the time between the needs of the program and the particular profile of the applicant, not a vote on anyone's worth as a scientist or person.  

For additional reference, here is the post I made last year about choosing a graduate program.

Majoranas - a brief follow-up

As you can always tell by the frequency of my posting, work-related activities have been dominating my schedule of late.  In addition to the usual stuff (papers, proposals, the normal academic activities), this is the time of year when as department chair there are deadlines and activities associated with faculty and staff evaluations, departmental budgets, graduate admissions, teaching assignments for next year, etc.  Still, in the wake of this article from Wired and some breathless reactions in the news and social media, it's worth following up my prior post on the topic of solid state implementations of Majorana fermions and what the pending retraction of this paper means. 

There are two main issues.  First, it has become clear that it can be very challenging to achieve the experimental conditions needed to have clear, unambiguous evidence of Majorana quasiparticles in the superconductor/semiconductor nanowire architecture.  This is explained in detail here, for example.   The interface quality of the semiconductor and of the semiconductor/superconductor boundary is extremely important, as disorder can lead to various confounding effects.  Interfaces are notoriously challenging.  ("God created the bulk; surfaces were invented by the devil." - Pauli)  There is no reason to think that it is impossible to reach the cleanliness level needed to see Majoranas in this type of structure, but like many material-related problems, this seems like it will require even more effort. 

Second is the particular issue of data presentation in this paper and whether it was misleading.  I have not personally looked at this in depth, but others have (twitter thread).  Snipping out segments of gate voltage without making that clear, and only plotting a limited range of gate voltage (leaving out where the conductance exceeds what is supposed to be the limiting value), is problematic.  

It's important to separate these two issues.  The issues with this particular paper are not a reason to stop this experimental approach or give up trying to confirm Majoranas this way.  It's just hard, the community isn't there just yet, and this is a cautionary tale about triumphal press releases.

Bringing modern industrial nanofab to quantum computing

One big selling point of solid-state quantum computing platforms is the notion of scalability. The semiconductor industry has spent billions of dollars and millions of person-hours developing the capability of fabricating tens of billions of nanoscale electronic components in parallel with remarkable reliability.   Surely it's not crazy to think that this will be the key to creating large numbers of functioning qubits as well.

Like many ideas that look plausible at first glance, this becomes very complicated under greater scrutiny.  Many of the approaches that people have in mind for solid-state quantum computing are not necessarily compatible with the CMOS manufacturing processes that produced the chips powering the computer you're currently using.  Virtually all of the university groups working on these systems use university-type fabrication methods - electron beam lithography for patterning, lift-off processing, etc.  In contrast, industrial chip makers use very different processes: elaborate immersion photolithography, subtractive patterning, and a whole host of clever tricks that have driven forward the mass production of silicon nanoelectronics.  The situation gets even worse in terms of materials development if one considers attempts to use more exotic systems.  The most reasonable quantum computing platform to approach first, if one is worried about industrial compatibility is probably using spins in gate-defined quantum dots in silicon.  

A team from Delft and Intel has done just that, as shown in this preprint.  They successfully demonstrate basic single-qubit effects like Rabi oscillations in single spins in quantum dots (single-electron transistors) defined in FinFETs, which they have patterned across a full 300 mm wafer (!) of isotopically pure 28Si (to avoid decoherence issues associated with nuclear spin).  They present data (which I have not read carefully) about how reproducible the properties of the single-electron transistors are across the wafer.   

The contrast between Si quantum devices
produced through university fab(top) and 
elite industrial fab (bottom).

I think the figure here from their paper's supplementary material really shows the point in terms of fabrication methods.  At the top is a cross-sectional TEM image of a chain of quantum dot devices, where the bright lumpy features are the defining metal gates that were patterned by e-beam lithography and deposited by lift-off processing.  In contrast, at the bottom is a cross-sectional TEM of the nominally equivalent industrially made device.  Behold the result of the accumulation of decades of technique and experience.

Of course, they were able to do this because Intel decided that it was worth it to invest in developing the special purpose masks and the process flow necessary.   Universities ordinarily don't have access to the equipment or the specialists able to do this work.  This makes me wonder again, as I have several times over the years, whether it would have been worthwhile for DOE or NSF to have set up (perhaps with Intel or IBM as a public-private partnership) some fabrication hub that would actually give the broader university research community access to these capabilities and this expertise.   It would be very expensive, but it might have pushed technology farther ahead than having several "nanocenters" that don't necessarily have technology much different than what is available at the top two dozen university cleanrooms.