Original Unreal Tournament is a pretty good one for this, I copied the install to a thumb drive on high school and played it on school computers all the time. Same with GZDoom
@inbounds isn't the problem, it's incorrect usage of it. The poor docstring is absolutely a problem though, you should be iterating over eachindex(A), not 1:length(A).
Dispatch ambiguity can really bite you, particularly if you start extending methods from other packages. An issue I often run into at the same time as method ambiguity is a stack overflow from self-calling constructors. If you try to define an outer constructor with default arguments, it's really easy to end up just calling that constructor from itself.
The metaprogramming trick for defining a set of methods at once is useful, but I wish there were a more compiler-level solution to sorting out ambiguities or determining what's more "specialized".
These don't really color my view on multiple dispatch, however. I find it to be a really useful tool and I don't run into dispatch issues very frequently. If you're meticulous about your typing it's usually easy to avoid these pitfalls, but sometimes they still crop up.
I found this app recently, it's great. It's a nice refresher on basic geometry, and I haven't done many geometric constructions in a while. It's a really neat way of exploring geometry and discovering insight after finishing a puzzle to try and optimize it
While I was in grad school, I had to teach some math-heavy engineering courses. This lesson came through very clearly there, and learning it early made my teaching much more effective.
You can't tell students anything, you have to show them, and you have to know where to start when you show them. Sometimes this meant starting back in the prerequisites to the course (a brief refresher on ODEs) and sometimes it meant arguing by anology before returning to the topic at hand.
I'm in the same boat. Most of my notes transfer over just fine because it's Markdown, but Confluence handles in-lining LaTeX significantly worse than pretty much any other CMS I've ever used.
MITM can only re-send the correct key if he knows the correct basis to measure in for every qubbit. The probability that he measures in the correct basis for every qubit is exponentially unlikely as the length of the bitstring grows. He can't just forward along the proper qubit to the receiver in this case.
You (Alice and Bob, where Alice is Tx/Bob is Rx) need to have agreed upon the basis in which you measure for each bit ahead of time. If you get MITM'd and they don't know the basis to measure in, then:
- They have a 50% chance of measuring in the correct basis and re-sending the proper qubit
- They have a 50% change of measuring in the incorrect basis, in which case their measurement means nothing and the qubit they send is in a superposition in the correct basis, leading to a chance Bob measures the wrong value
Over a very long string, it becomes exponentially unlikely that the MITM could guess the proper basis and then re-send the proper qubit to Bob. As that binary string grows in length, it's essentially impossible to MITM with any meaningful likelihood.
I used CircuiTikZ when I taught a circuits course. The figures turned out so well, it was nice to be able to have such a uniform and portable representation.
I suspect starting from TikZ proper would make some of the wiring easier; there's a lot of naming nodes and connecting between them that seemed unintuitive, and like I always missed an easier way to draw a circuit.
> The second scheme, on the right ... Calculations must be discarded rather than corrected when problems are found.
I understand the title is technically correct, and the field of quantum error correction (and error correction in general) encompasses the detection of errors as well as the correction of them. However error detection and error correction are different (but highly related!) problems, and there are are a variety of codes that are good at each. They tried out one error correcting code, and one error detecting (in this instance) code.
It's very cool to see the surface code put to use, and I've always found it intriguing how quantum computer design is motivated by the topology of the underlying error correcting codes. There's a similar proposal for ion-trapped quantum computing where you use a 2D array of trapped ions, rather than a single linear chain, to represent your qubits. You then use different atomic ions for your logical vs error correcting qubits, and you need some different fundamental operations than you do for interactions with a linear chain of ions.
This was certainly the case for me over the last year and a half. Up until the start of this year when I switched to a new, challenging job, I dove deep into a competitive shooter hole. I played ranked modes when available and focused a lot of mental effort into self-critiquing my play to improve. Making progress was the driving factor to keep playing, and I did see a lot of progress!
In the last six months I switched jobs into one that's more demanding of my time and mental efforts, and my gaming volume dropped significantly. I haven't booted any of the multiple-hours-per-day games I got into for the last couple of months.