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Comment Re:Five Star (Score 1) 627

It is extremely reactive, so I'd imagine refining it is pretty difficult as well. Also, it is not "right up there on the most abundent element on this planet". It's actually only the 33rd most abundant element in the Earth's crust (out of 78 elements occuring naturally in the crust). Occurrence is only about 20 parts per million. http://en.wikipedia.org/wiki/Abundance_of_elements_in_Earth's_crust

Comment Re:At least they're not rolling their own. (Score 2) 138

You should not write a C++ interpreter. You especially shouldn't write an interpreter of a language that looks almost just like C++, but is different from it in unpredictable ways, some of which contribute to bad coding habits and/or make normal C++ more difficult to learn.

Strictly sequential files are a bad model for data if most of your time is spent constructing more-and-more elaborate subsets of that data. When we want to examine a subset, we practically have to make a complete copy of all the data falling into that subset. You want to make a small tweak to your selection? Make a new copy all over again.

Comment Re:At least they're not rolling their own. (Score 2) 138

Cycles are rarely the issue for us in HEP, and when they are, all we need is more nodes to split the problem into smaller pieces (wiki: embarassingly parallel problem). The actual computational needs are (typically) pretty small. The main bottleneck is usually data throughput. We discard enormous amounts of data (that may or may not be useful, depending on who you ask) simply because we can't store it anywhere close to as fast as we can make it (many orders of magnitude difference between the data production rate and the data storage rate). And then, when we're analyzing the data we've taken, our CPUs tend to sit idle while they wait on the disk to read another block of events, which then take a only a few cycles to add in to the necessary histograms. It only gets worse when the data is somewhere far away on the network. And it gets even worse when you want to select a subset of the data -- with our systems you have to make a full copy of the subset.

There are two big wins that modern big data has developed that we could benefit greatly from if the switchover costs weren't too high. The first is distributing data over many disks on many nodes and bringing the code to the data instead of bringing the data to the code. The more disks your data is on, the less you have to wait on seek times. The second is storing the data in a way that is not strictly sequential in a single set of files, so that if you want to look at a subset of the data, you can effectively do that without having to make a copy of that subset.

Comment Re: Proof is already from 1929 (Score 1) 158

You say to yourself something like:

Ok, here is some mathematical object called a state. What can I do with a state? Well, I can apply linear operators to a state. Given the properties of linear operators, there are some states that are unaffected (up to an overall scalar multiplication) by each operator. Call those "eigenstates". Call one of the operators the "position" operator. Find the eigenstates of the position operator. Now, I can compute, for any given state, how much overlap with each position eigenstate there is as a function of the corresponding eigenvalue. That overlap is a complex scalar function of position, which we can call a wave function, if we like.

It's actually much cleaner to start from this sort of abstraction and define the more concrete "wave function" from it than the other way around, partly because it allows you to more easily consider state spaces that, for example, don't have any operators with continuous eigenvalue spaces, like the spins of the ions in a ferromagnetic lattice, or the excitations of atoms/molecules in laser cavity.

Comment Re:Fixed the summary (Score 1) 158

Check chapter 9, (pages 237 and following), of the second edition of Principles of Quantum Mechanics by Ramamurti Shankar. Or, section 1.6 (page 18-20) and section 3.5 (page 110-118), of the second edition of Introduction to Quantum Mechanics by David J. Griffiths.

I'm sorry that I can't hyperlink to a physical book. But maybe you could go to your local public library and find a copy of one of them.

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