mattheww

Yes, the basic ideas underlying cosmology are the assumptions of isotropy (it looks the same in every direction) and homogeneity (it is the same everywhere). These two assumptions combine to tell you that it looks the same in every direction from wherever you are sitting.

Edit: grammar

Just so we're clear, there is no real physics in this talk. There is no information in this talk.

It's true that the value of the speed of light depends on units that are relevant to humans. To suggest that this implies something about physics is absurd. Physics is in fact independent of the actual value of the speed of light.

The idea that the speed of light in vacuum is constant in all reference frames is a postulate of special relativity. Both special relativity and general relativity are confirmed by numerous experiments.

Edit: Note this is also a TEDx talk, not regular TED.

Thanks, I checked the book out from the library; it's exactly what I was looking for.

Wikipedia paraphrasing of a related Shakespeare scene, which is one of my favorite ways to remember an important lesson:

Caesar saw the seer and joked "Well, the Ides of March have come," to which the seer replied "Ay, they have come, but they are not gone."

Somebody posted the original article here: http://news.ycombinator.com/item?id=1151369

If you don't know where the peak is, you can't argue that raising taxes will reduce GDP because you don't know if you're going up the hill or down it.

One obvious issue with the Laffer curve: Nobody actually knows where the peak is.

We used 3.8 TW-hrs in 2005 (which translates to average 434 GW usage, so 500GW is probably a bit low for peak).

DOE (http://www.eia.doe.gov/oiaf/aeo/pdf/overview.pdf) projects usage of 5.3 TW-hours in 2035, which translates to about 605 GW average. We probably need 1+ TW capacity in the US to handle peak usage.

The work discussed was actually done at the PHENIX detector, not STAR.

Short answer: glitch isn't the right word. There was almost certainly a particle with an extremely high energy. Whether they can measure energies that high is questionable.

Long answer: I'm not familiar with this specific experiment, but I am familiar with ones that try to measure the same thing.

The thing about most of these devices is that they have a sweet spot in which they have the highest accuracy. These detectors have a sweet spot which is a few orders of magnitude below the energy measured here. So there is always the question of how well you can extrapolate.

You'll notice there is no uncertainty quoted on the energy. It would not be unreasonable to expect that uncertainty is at least 1 order of magnitude in each direction. Probably more.

While that might seem like a lot, it's also important to know that the relevant measurement is not the particle's energy, but actually the number of particles above a certain energy. So they don't care so much if the energy measurement is off by a lot, as long as it's really big.

You can't skip the story about Niels Bohr at the bottom.

If they can reach create a controlled fusion reaction, a commercial reactor would be designed to continually feed fuel into it to continue the reaction. Reaching "break-even" is when the lasers don't have to be fired for the reaction to continue.

Your concerns are certainly legitimate, and I'm sure there are some situations where they apply. However, in many physical sciences (I would venture to say the vast majority), simulations are not chaotic. They are based on stochastic models that have converging behavior. So, in general, it really is fair for most people to rely on the stability of the simulations.

As for your other points, the issue of simulation accuracy is already taken very seriously in the areas where I've seen it used.

Let me give an example from my field (high energy physics). The pre-eminent event generator of choice is called PYTHIA. It incorporates as much known physics as possible, and is continually updated. There are groups that regularly convene to compare the distributions it produces to those seen in real experiments and adjust the parameters to improve the results. The code is open source, so you can readily make improvements and submit them to the maintainers for inclusion in official releases.

Now the primary uses of these simulations are to either tune your analysis to separate signal from background or calculate corrections for different kinds of detector acceptance issues. No reviewer would ever accept a publication that used simulation if the paper did not include clear evidence that the simulation was valid, usually in the form of a data/simulation comparison.

Regarding reproducabilility, I think you're a little off the mark. The idea is not that you should simply repeat my analysis to get the same answer (this important verification step should be, and usually is, present in all scientific groups). Ideally, you should collect your own data, make your own simulations, and do your own analysis. Then we should see if we got the same answer.

Edit: grammar

"I'd say emergent, especially intelligent life would make the stats pages. Given the age of the universe and how long it has taken for Earth to evolve an intelligent lifeform I'd say it's even possible we are one of the first, if not THE first, intelligent lifeform"

a) That's one hell of a sampling bias.

b) The universe is roughly 14 billion years old, though stars only started forming about 12 billion years ago. The Earth is roughly 4.5 billion years old. I don't see how you are able to draw that conclusion. Other factors that we are unable measure might allow us to make the conjecture if they take certain values.

Edit: formatting

It's interesting to see that when you look at all of the pictures of Obama, mostly the same people show up.

If all of the data is positive, but the mean - 1*sigma is negative, the gaussian approximation probably isn't very good....

Display the H-index of users on the leaders board: http://en.wikipedia.org/wiki/H-index

Could you add a couple from multiple angles (including front)? It's not clear to me what the whole case looks like.

I work in a fairly large scientific collaboration. Our data sets are on the scale of a few hundred terabytes per year. So, there's a lot of software to convert from the bits that stream out of the detectors to something that end users (grad students) can analyze.

We have a software group devoted to maintaining the core code. Our code has a nightly autobuild for development code and libraries are released every couple months.

The code is based on the ROOT package (about one million lines of code) maintained by folks at CERN and is well established within the community and elsewhere. Our libraries probably come to about a million more lines of code, which is maintained scrupulously by our collaboration.

Now neither of these sets of code actually do any analysis, they just make it so that the data is usable. In my analysis, there is probably ~10k lines of code to do the analysis and make the figures. In total, there's probably 500k or more lines of analysis code that is not officially maintained.

That doesn't include all of the code loaded onto FPGAs and custom chips reading out the detectors or the code in the trigger system. Nor does it include code written into various simulators used to determine "expected" response of the detectors.

So for peer review to look at code at the level suggested, people would have to look over literally millions of lines of code. To even be able to make it run, a user would have to set up an environment that would take between a few days and a week.

Instead, when I go to publish something, I lay out both my method and how I verified that it works. Reviewers then check that my method is sound and that my verification looks right. They have to trust that I implemented the method as I said I did.

In my collaboration, there is actually an internal review process that verifies code runs and for which a much longer private note must be written to explain all of the details of the analysis. However, there is still a high level of trust that everything was implemented as stated. This review does not qualify as "peer" review because it's conducted by people who will be listed as authors.

While I agree that more review is better than less, I hope this comment illustrates why software peer review is not a reasonable expectation.

With regard to investing into superstars, I can't help but think I already have two investors: my parents.

And to ruin the sentimentality, I guess I've probably returned 2-3% of my gross in gifts, though I never thought of it that way until now. And $300k is probably in the ball park of what they spent to "raise" me.

I turn it off on weekends. It's easier to remember where I was the day before if I leave everything open.

"What you say is well-put, but to nitpick the last paragraph: the limits of quantum mechanics are well-established. QM is a special case of quantum electrodynamics, which is a low-energy special case of the Grand Unified Theory."

Somewhat misleading. The difference between quantum mechanics and quantum electrodynamics is not really pertinent to a discusion of the limits of quantum mechanics. Most people who are familiar with quantum mechanics will use the term to refer to the whole tree of theories that require quantization anyway (quantum mechanics (QM), quantum field theory (QFT)). The limits of QM is that we are really not able to calculate things in certain energy regimes.

Also, it is not really accurate to call QM a special case of QFT because different things are being quantized (particle states vs field states). Certain operators in QFT are then interpreted as particles.

Quantum Electrodynamics (QED) is an example of a QFT. People postulate the existence of a Grand Unified Theory (GUT), of which QED would be special case. The only evidence of the GUT is a plot that extrapolates the strength of strong, weak, and electromagnetic interactions over many orders of magnitude.

Newsweek also recently devoted its cover to shortening 4 year college programs to 3 years (http://www.newsweek.com/id/218183) and also asked a team of "experts" to discuss the idea (http://www.newsweek.com/id/218234).

Much like the blog post here, there was no discussion of the quality of education. No statistics about the quality, effectiveness, or usefulness were presented. The primary focus was cost and arguments about "development."

Unfortunately, discussions without supporting data seem to be the norm on this topic.

Multi-pupil gestures? Cross your eyes to zoom out!

That's an extremely interesting choice of style settings. The combination of black background with small, dark gray text forces the reader to focus very hard to read it.

This is one of the few times I've noticed some sort of contrast optical illusion after viewing a web site (ie when I clicked the back button to return to HN after reading the post).

I accept the fact that not many people will read my thesis.

Scientists in the field will not read it because they are not interested in all of the details of the analysis. They are only interested in the result, which will be published in a four page paper that only broadly explains the methods of the analysis.

My mother will not read it because I won't be writing it for her. When she asks me what I did, I will explain it in a way that she can understand. If I'm lucky, some science journalist will write an article about it, and I can send her the link.

Actually a study in Colorado showed that sitting in front does improve performance:

http://www.psycho.uni-duesseldorf.de/abteilungen/ddp/Dokumen...

Incidentally, if I wanted to put my math skills to work in a casino, I would play poker. This game is one where the odds have not been stacked against me and a little math drastically alters my expected values.

In a machine like the LHC, there are two important quantities: \sqrt{s} = the collision energy which is designed to be 14 TeV and L = the luminosity which gives you an idea of how often there will be collisions. IIRC, this is designed to be two orders of magnitude above the Tevatron.

\sqrt{s} tells you what kind of "range" you have in discovering new physics. Even at 8 TeV (both beams at 4 TeV), the reach is increased over the Tevatron by a factor of four. This puts the most likely Higgs mass in reach. More extravagant physics may or may not be out of range until the design energy of 14 TeV is reached.

L tells you how long (as in hours of running) it takes to achieve certain statistical significance in a given result. Rarer results take longer to achieve. The difficulties in achieving this goal are not addressed in the article, but are roughly tangential to those of achieving high energy. From what we heard during the couple weeks of running last year, everything was on track to make their goal possible.

What's notable about the article is that the experimentalists are all fairly happy about the performance. While last year's mishap was worse than what anyone hoped for, nobody was expecting to be at the full energy even by now.

On the other hand, it's interesting that the theorists are so pessimistic about the delays. A lot of them have spent the last 15-20 years coming up with predictions for what the LHC will see. A lot of those predictions will be invalidated when the first LHC results are published.

At my university, the campus security used Segways. I imagine that they were able to cover ground more easily than on foot and it was easier to stop and talk to people than if they were on bicycles (referenced by another commenter). The campus was small enough that there wasn't much road access within.

They didn't look that dorky either, even with their helmets.