Setting: you are sending bits through a communication channel, each bit has a random probability of getting flipped, and so you use some error correction code to achieve some minimal error, at the expense of longer messages.

This theorem sets an upper bound on how efficient you can be in your encoding, for any encoding.

The next big question, which the theorem does not cover is how to construct codes that reach or approach the limit. Important such codes include:

But besides this, there is also the practical consideration of if you can encode/decode fast enough to keep up with the coded bandwidth given your hardware capabilities.

news.mit.edu/2010/gallager-codes-0121 explains how turbo codes were first reached without a very good mathematical proof behind them, but were still revolutionary in experimental performance, e.g. turbo codes were used in 3G/4G.

But this motivated researchers to find other such algorithms that they would be able to prove things about, and so they rediscovered the much earlier low-density parity-check code, which had been published in the 60's but was forgotten, partially because it was computationally expensive.

Quantum is getting hot in 2019, and even Ciro Santilli got a bit excited: quantum computing could be the next big thing.

No useful algorithm has been economically accelerated by quantum yet as of 2019, only useless ones, but the bets are on, big time.

To get a feeling of this, just have a look at the insane number of startups that are already developing quantum algorithms for hardware that doesn't/barely exists! quantumcomputingreport.com/players/privatestartup (archive). Some feared we might be in a bubble: Are we in a quantum computing bubble?

To get a basic idea of what programming a quantum computer looks like start by reading: Section "Quantum computing is just matrix multiplication".

Some people have their doubts, and that is not unreasonable, it might truly not work out. We could be on the verge of an AI winter of quantum computing. But Ciro Santilli feels that it is genuinely impossible to tell as of 2020 if something will work out or not. We really just have to try it out and see. There must have been skeptics before every single next big thing.

Course plan:

Ciro Santilli participated in a double degree program, so he obtained have engineering degrees in both:

See also further remarks on Ciro Santilli's LinkedIn: www.linkedin.com/in/cirosantilli/

Despite studying in great institutions with great teachers, Ciro feels that:

This motivated Ciro to work on OurBigBook.com.

This is the true key question: what are the most important algorithms that would be accelerated by quantum computing?

Some candidates:

Do you have proper optimization or quantum chemistry algorithms that will make trillions?

Maybe there is some room for doubt because some applications might be way better in some implementations, but we should at least have a good general idea.

However, clear information on this really hard to come by, not sure why.

Whenever asked e.g. at: physics.stackexchange.com/questions/3390/can-anybody-provide-a-simple-example-of-a-quantum-computer-algorithm/3407 on Physics Stack Exchange people say the infinite mantra:

Lists:

Only NP-intermediate, which includes notably integer factorization:

Source on GitHub: github.com/stephenjordan/stephenjordan.github.io

The most comprehensive list is the amazing curated and commented list of quantum algorithms as of 2020.