Funding:

Crystallography determination with a transmission electron microscopy instead of the more classical X-ray crystallography.

Some people call it "operating System".

The main parts of those systems are:

The most beautiful ones:see also Section "Animations of molecular biology processes"

One important area of research and development of quantum computing is the development of benchmarks that allow us to compare different quantum computers to decide which one is more powerful than the other.

Ideally, we would like to be able to have a single number that predicts which computer is more powerful than the other for a wide range of algorithms.

However, much like in CPU benchmarking, this is a very complex problem, since different algorithms might perform differently in different architectures, making it very hard to sum up the architecture's capabilities to a single number as we would like.

The only thing that is directly comparable across computers is how two machines perform for a single algorithm, but we want a single number that is representative of many algorithms.

For example, the number of qubits would be a simple naive choice of such performance predictor number. But it is very imprecise, since other factors are also very important:

Quantum volume is another less naive attempt at such metric.

Dan, if you ever Google yourself here, please contact Ciro Santilli: Section "How to contact Ciro Santilli" to do something with OurBigBook.com. Cheers.

This post-quantum cryptography competition by NIST is a huge milestone of the field.

It was mind blowing when in 2022, after several years of selection, one of the 7 finalists was broken on a classical computer, not even in a quantum computer! news.ycombinator.com/item?id=30466063 | eprint.iacr.org/2022/214 Breaking Rainbow Takes a Weekend on a Laptop by Ward Beullens. Dude announced he had a break a few days before submission: twitter.com/WardBeullens/status/1492780462028300290 On Twitter. He's so young. Epic.

Edit: and then, after the third round, things were a bit unclear, so they made a fourth round with 4 choices out of the 7 from round 3, and in August 2022 one of the four was broken again on a classic CPU!!! OMG: arstechnica.com/information-technology/2022/08/sike-once-a-post-quantum-encryption-contender-is-koed-in-nist-smackdown/

Unfortunately accused of sexual misconduct: www.theguardian.com/technology/2019/mar/11/google-executive-payout-harassment-amit-singhal. But one can still do good despite our defects:

Pitched OurBigBook.com to him:

Besides of course sexual selection, considering in this section only "formal learning" activities.

Consider e.g. the 2020 University of Oxford, where many many people are taking courses without any laboratory work (and also without much use at all) like literature and history, and they are paying about 9k pounds/year for it: how much it costs to study at the University of Oxford?.

Basically all of this could be done online from books.

Laboratories are impossible however, because expendables of every experiment you do cost from hundreds to thousands of dollars, not to mention crazy upfront equipment costs.

For this reason, the brick and mortar aspect universities should focus exclusively on laboratories, and ensuring that the students with the most relevant knowledge (which can be readily obtained online) get access to those laboratories. Students should of course fully master every aspect of theory pertinent to their experiments. principal investigators should hand pick whichever criteria they want to select their students, possibly based partly on exam as a service if they find it a useful metric.

Furthermore, the use of laboratories should put great focus on novel research. A lot of laboratory instruction could be done from video of an experiments. As much as possible, we should use laboratories for novel research. Related: Section "Videos of all key physics experiments".

Ciro Santilli's general feeling is that university should not own IP, it should belong to the researchers. Instead, university should help researchers make their startups, so they can become big, and then we can tax them and reinvest in the universities.

Of course, this goes through the nonprofit impact measurement difficulty. Maybe we could instead limit the IP to some reasonably small percentage, like 10%?

But still, as of 2020, if feels like universities are way too greedy.