timnic

The Theoretical Minimum lecture series on theoretical physics by Leonard Susskind. Covers the basics in a very approachable way. I wish this had been available when I studied physics.

When I was in school "scientific method" wasn’t teached as a separate topic, but more like the result of "osmosis": you are given many examples of how science works and you somehow learn by this the process of science itself. Ok, you are taught how do do proofs in maths and how to do experiments, but no direct reference to a concept like the scientific method.

An (maybe) interesting fact is, that in Germany the notion „scientific method“, to my knowledge, is largely unknown. For example, there is no link in the english wikipedia entry you have given to the german wikipedia. When I studied physics in Germany no one ever used that term.

There is some more information available here: https://www.mulle-kybernetik.com/weblog/2015/mulle_objc_a_ne...

There is a free PDF on the nature site, but the paper is also available on arxiv (https://arxiv.org/abs/1407.4437), the first version on the arxiv dates back to 2014. It's strange, but I find the arxiv version much more readable in terms of typesetting than the polished version in nature. Also there are additional appendices in the arxiv version.

Can you provide a link to the real paper that started the discussion? I looked through the references in the linked arxiv paper but could not find it.

I do not know "Mathematics: From the birth of numbers" but judging from the Amazon quick view it seems to cover a lot of ground (BTW: one thing I missed in my list are the basics of differential equations).

Over 1000 pages is quite a long read, though. I never managed to read a (science) book as big as that from cover to cover myself. One thing I learned through the years is to never use only one book for learning. Books have different styles and not every style fits to every student. Additionally one book might be good at one specific topic and weak on another. So nowadays I always use a couple of books (or online resources) to learn a new topic.

This is discussed by Feynman as “physiological” work. See: http://www.feynmanlectures.caltech.edu/I_14.html#Ch14-S1

Math is wide and deep. You won’t need to cover every topic in math to get going with physics. If you really are interested in physics there are many things in math, which are, well, less important (for doing basic physics). For example LCM, GCD and factoring. I guess, these things are somewhat important in Computer Science, but I never encountered them in a physics problem. So to get started with physics, I would suggest that you focus mainly on analysis (differentiation and integration) and vector algebra. As an addition maybe the basics of complex numbers. This can be learned relatively quickly.

With these you should be able to follow the Feynman lectures or watch the very fine „Theoretical Minimum“ series by Susskind (http://theoreticalminimum.com)

I just noticed in the article the passage from "The Dead Mountaineer’s Inn" ("Haven’t you ever noticed how much more interesting the unknown is than the known?") which is missing in the german translation from "edition wunschmaschine". I did a rough comparison based on the amazon preview of the english translation and found some other paragraphs missing in the german translation. This specific german translation was licensed from the former GDR publishing company "Verlag Volk & Welt".

Preprint: http://arxiv.org/abs/1412.7790

The arxiv link seems to be http://arxiv.org/abs/1401.4318

Yes, obviously the examples given in the link are bad style of comments. But sometimes you need to explain the reasons behind the (Haskell) equations, just like one would do in a Math paper. So there's a use case for the literate Haskell files *.lhs (http://www.haskell.org/haskellwiki/Literate_programming).

No, the energy gained will be equal or (most likely) less than the energy used. This is because we have conservation of energy, so a process like

energy (the original photons) -> matter (electron/positron) -> energy

can not produce more energy than was put in.

Mass is not a conserved quantity. Energy for example is a conserved quantity. So like in a nuclear fission reaction we loose mass but this lost mass is then converted into energy. I have not read the article in detail, but I suppose they want to turn part of the photons energy into masses for the electron and the positron. Mass and energy are linked via E = mc^2.

IANAL, so all this is layman wisdom:

Yes, there are some checks in Germany.

First of all this law has to pass the "Bundesrat", the representation of the 16 "Bundesländer" (states of Germany).

If this council passes the law one still has the opportunity to "go to Karlsruhe", which means appeal to the Federal Constitutional Court that is located in Karlsruhe.

In the german online community this has been the hot topic of the last weeks and the german pirate party (http://piratenpartei.de/) has mainly focused on this issue .

Concerning software abstraction layers: What do you think of OpenCL? It's advertised as a way to utilise the combined computing power of multi-cores and GPUs. I am not at all an expert on this but it seems just too good to be true.

I was watching a video by Elizabeth Warren of Harvard Law School on the topic the other day. The gist of it is (I think) basically that housing and healthcare are taking up most of the money of the middle class. In the 1970-ties a single earner could bring in enough money to support the whole family. Now in the middle class both parents have to work, which doubles the financial risk for the family if one of them (for example) looses a job. If you are interested: the link is http://www.youtube.com/watch?v=akVL7QY0S8A

I think they were referring to "Core Animation", a Cocoa framework for building smooth transitions in the GUI. This was AFAIK a by-product of the iPhone development.

But development for Leopard is also nicer because you can now use Objective-C 2.0 and garbage collection and lots of other new classes, like e.g. NSOperation which helps development for multi-core processing.