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Paul N

Have We Been Interpreting Quantum Mechanics Wrong This Whole Time? - 6 views

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    "The experiments involve an oil droplet that bounces along the surface of a liquid. The droplet gently sloshes the liquid with every bounce. At the same time, ripples from past bounces affect its course. The droplet's interaction with its own ripples, which form what's known as a pilot wave, causes it to exhibit behaviors previously thought to be peculiar to elementary particles - including behaviors seen as evidence that these particles are spread through space like waves, without any specific location, until they are measured." Pilot-wave theory reresurrected. Maybe something for the next "fundamental" :P physics RF?
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    And for the next 'Experimental Physics Stagiaire' position why not try to do "Unpredictable Tunneling of a Classical Wave-Particle Association" http://stilton.tnw.utwente.nl/people/eddi/Papers/PhysRevLett_TUNNEL.pdf, there are some rumors online that the results of Yves Couder Experiments can be reproduced with simple DIY vibrating tables! It is very funny to see the videos of the MIT's replication of this experiment (with lightening legends for those who are uncomfortable with the concepts involved https://www.youtube.com/watch?v=YF5iHQMjcsM)
Thijs Versloot

Is increased light exposure from screens and phones bad for your health? @Wired - 1 views

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    As Stevens says in the new article, researchers now know that increased nighttime light exposure tracks with increased rates of breast cancer, obesity and depression. Correlation isn't causation, of course, and it's easy to imagine all the ways researchers might mistake those findings. The easy availability of electric lighting almost certainly tracks with various disease-causing factors: bad diets, sedentary lifestyles, exposure to they array of chemicals that come along with modernity. Very difficult to prove causation I would think, but there are known relationships between hormone levels and light.
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    There is actually a windows program called flux, that changes the temperature on your screen to match normal light cycles. When the sun sets it switches to a "warmer" more reddish tint on your screen to promote sleepiness. The typically bright blue/neon white settings of most pc settings is quite "awakening" and keeps your brain running for longer. This impacts your sleeping patterns and all the consequences of that. Amazingly, this flux thing does have an effect. That being said, I wouldn't be too quick to blame it all on PC/artificial lighting time. Sedentary lifestyles, etc can very well place one in a position of long term pc/phone usage so it's quite hard to draw a causal link.
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    nice - also exists for MAC btw: https://justgetflux.com/news/pages/mac/
Alexander Wittig

Scientists discover hidden galaxies behind the Milky Way - 1 views

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    Hundreds of hidden nearby galaxies have been studied for the first time, shedding light on a mysterious gravitational anomaly dubbed the Great Attractor. Despite being just 250 million light years from Earth-very close in astronomical terms-the new galaxies had been hidden from view until now by our own galaxy, the Milky Way. Using CSIRO's Parkes radio telescope equipped with an innovative receiver, an international team of scientists were able to see through the stars and dust of the Milky Way, into a previously unexplored region of space. The discovery may help to explain the Great Attractor region, which appears to be drawing the Milky Way and hundreds of thousands of other galaxies towards it with a gravitational force equivalent to a million billion Suns. Lead author Professor Lister Staveley-Smith, from The University of Western Australia node of the International Centre for Radio Astronomy Research (ICRAR), said the team found 883 galaxies, a third of which had never been seen before. "The Milky Way is very beautiful of course and it's very interesting to study our own galaxy but it completely blocks out the view of the more distant galaxies behind it," he said. Professor Staveley-Smith said scientists have been trying to get to the bottom of the mysterious Great Attractor since major deviations from universal expansion were first discovered in the 1970s and 1980s. "We don't actually understand what's causing this gravitational acceleration on the Milky Way or where it's coming from," he said. "We know that in this region there are a few very large collections of galaxies we call clusters or superclusters, and our whole Milky Way is moving towards them at more than two million kilometres per hour." The research identified several new structures that could help to explain the movement of the Milky Way, including three galaxy concentrations (named NW1, NW2 and NW3) and two new clusters (named CW1 and CW2).
Juxi Leitner

How To Make The World's Easiest $1 Billion - 7 views

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    wow, i want to do that !!! The suggestion of raising the funds on facebook is a good idea :) Look at this video, the future of banking, frightening isn't it ? http://www.youtube.com/watch?v=cqESjpfb3OE&feature=player_embedded
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    ah yeah The Long Johns, very cool try googleing there video of the subprime crisis
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    If it worked, they wouldn't write about it - they'd do it.
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    the first step is already not that trivial it seems to me: STEP 1: Form a bank.
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    depends on the country and of course the type of the bank :)
Juxi Leitner

ESA Servers Hacked - 11 views

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    uups :)
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    whoops indeed
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    sounds really bad ... how bad is it???
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    Heads will fall in ESRIN... And now I know who crashed my computations on sophia ;-) [Edit] A lesson for everyone: look at the file with email passwords and see how many you are able to guess even though they're supposed to be scrambled by removing a middle part... [Edit] And a hilarious quote from the hacker's "about me": "I had another blog, more exactly www.tinkode.baywords.com but I forgot the password, so now I created this one."
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    got the reply from IT security today: they had dealt with apparently the very same day and all under control :-)
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    Well, I wouldn't expect a reply: "all our past emails have been downloaded and sold to NASA" even if that was the case.
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    Of course Marek is right... What matters is the theatre of security, not security itself. Just like in airports :)
Ma Ru

Map of all geo-tagged articles on Wikipedia - 4 views

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    I know you like these... [Edit] And by the way, this website contains also more practical stuff, like this
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    they must have tricked the data in favour of Poland ...
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    of course, "they" being Polish Wikipedia contributors who geo-tag like mad...
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    Have you had a look on Japan? It looks like they just geo-tagged all their train stations.
Dario Izzo

Miguel Nicolelis Says the Brain Is Not Computable, Bashes Kurzweil's Singularity | MIT ... - 9 views

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    As I said ten years ago and psychoanalysts 100 years ago. Luis I am so sorry :) Also ... now that the commission funded the project blue brain is a rather big hit Btw Nicolelis is a rather credited neuro-scientist
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    nice article; Luzi would agree as well I assume; one aspect not clear to me is the causal relationship it seems to imply between consciousness and randomness ... anybody?
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    This is the same thing Penrose has been saying for ages (and yes, I read the book). IF the human brain proves to be the only conceivable system capable of consciousness/intelligence AND IF we'll forever be limited to the Turing machine type of computation (which is what the "Not Computable" in the article refers to) AND IF the brain indeed is not computable, THEN AI people might need to worry... Because I seriously doubt the first condition will prove to be true, same with the second one, and because I don't really care about the third (brains is not my thing).. I'm not worried.
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    In any case, all AI research is going in the wrong direction: the mainstream is not on how to go beyond Turing machines, rather how to program them well enough ...... and thats not bringing anywhere near the singularity
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    It has not been shown that intelligence is not computable (only some people saying the human brain isn't, which is something different), so I wouldn't go so far as saying the mainstream is going in the wrong direction. But even if that indeed was the case, would it be a problem? If so, well, then someone should quickly go and tell all the people trading in financial markets that they should stop using computers... after all, they're dealing with uncomputable undecidable problems. :) (and research on how to go beyond Turing computation does exist, but how much would you want to devote your research to a non existent machine?)
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    [warning: troll] If you are happy with developing algorithms that serve the financial market ... good for you :) After all they have been proved to be useful for humankind beyond any reasonable doubt.
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    Two comments from me: 1) an apparently credible scientist takes Kurzweil seriously enough to engage with him in polemics... oops 2) what worries me most, I didn't get the retail store pun at the end of article...
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    True, but after Google hired Kurzweil he is de facto being taken seriously ... so I guess Nicolelis reacted to this.
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    Crazy scientist in residence... interesting marketing move, I suppose.
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    Unfortunately, I can't upload my two kids to the cloud to make them sleep, that's why I comment only now :-). But, of course, I MUST add my comment to this discussion. I don't really get what Nicolelis point is, the article is just too short and at a too popular level. But please realize that the question is not just "computable" vs. "non-computable". A system may be computable (we have a collection of rules called "theory" that we can put on a computer and run in a finite time) and still it need not be predictable. Since the lack of predictability pretty obviously applies to the human brain (as it does to any sufficiently complex and nonlinear system) the question whether it is computable or not becomes rather academic. Markram and his fellows may come up with a incredible simulation program of the human brain, this will be rather useless since they cannot solve the initial value problem and even if they could they will be lost in randomness after a short simulation time due to horrible non-linearities... Btw: this is not my idea, it was pointed out by Bohr more than 100 years ago...
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    I guess chaos is what you are referring to. Stuff like the Lorentz attractor. In which case I would say that the point is not to predict one particular brain (in which case you would be right): any initial conditions would be fine as far as any brain gets started :) that is the goal :)
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    Kurzweil talks about downloading your brain to a computer, so he has a specific brain in mind; Markram talks about identifying neural basis of mental diseases, so he has at least pretty specific situations in mind. Chaos is not the only problem, even a perfectly linear brain (which is not a biological brain) is not predictable, since one cannot determine a complete set of initial conditions of a working (viz. living) brain (after having determined about 10% the brain is dead and the data useless). But the situation is even worse: from all we know a brain will only work with a suitable interaction with its environment. So these boundary conditions one has to determine as well. This is already twice impossible. But the situation is worse again: from all we know, the way the brain interacts with its environment at a neural level depends on his history (how this brain learned). So your boundary conditions (that are impossible to determine) depend on your initial conditions (that are impossible to determine). Thus the situation is rather impossible squared than twice impossible. I'm sure Markram will simulate something, but this will rather be the famous Boltzmann brain than a biological one. Boltzman brains work with any initial conditions and any boundary conditions... and are pretty dead!
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    Say one has an accurate model of a brain. It may be the case that the initial and boundary conditions do not matter that much in order for the brain to function an exhibit macro-characteristics useful to make science. Again, if it is not one particular brain you are targeting, but the 'brain' as a general entity this would make sense if one has an accurate model (also to identify the neural basis of mental diseases). But in my opinion, the construction of such a model of the brain is impossible using a reductionist approach (that is taking the naive approach of putting together some artificial neurons and connecting them in a huge net). That is why both Kurzweil and Markram are doomed to fail.
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    I think that in principle some kind of artificial brain should be feasible. But making a brain by just throwing together a myriad of neurons is probably as promising as throwing together some copper pipes and a heap of silica and expecting it to make calculations for you. Like in the biological system, I suspect, an artificial brain would have to grow from a small tiny functional unit by adding neurons and complexity slowly and in a way that in a stable way increases the "usefulness"/fitness. Apparently our brain's usefulness has to do with interpreting inputs of our sensors to the world and steering the body making sure that those sensors, the brain and the rest of the body are still alive 10 seconds from now (thereby changing the world -> sensor inputs -> ...). So the artificial brain might need sensors and a body to affect the "world" creating a much larger feedback loop than the brain itself. One might argue that the complexity of the sensor inputs is the reason why the brain needs to be so complex in the first place. I never quite see from these "artificial brain" proposals in how far they are trying to simulate the whole system and not just the brain. Anyone? Or are they trying to simulate the human brain after it has been removed from the body? That might be somewhat easier I guess...
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    Johannes: "I never quite see from these "artificial brain" proposals in how far they are trying to simulate the whole system and not just the brain." In Artificial Life the whole environment+bodies&brains is simulated. You have also the whole embodied cognition movement that basically advocates for just that: no true intelligence until you model the system in its entirety. And from that you then have people building robotic bodies, and getting their "brains" to learn from scratch how to control them, and through the bodies, the environment. Right now, this is obviously closer to the complexity of insect brains, than human ones. (my take on this is: yes, go ahead and build robots, if the intelligence you want to get in the end is to be displayed in interactions with the real physical world...) It's easy to dismiss Markram's Blue Brain for all their clever marketing pronouncements that they're building a human-level consciousness on a computer, but from what I read of the project, they seem to be developing a platfrom onto which any scientist can plug in their model of a detail of a detail of .... of the human brain, and get it to run together with everyone else's models of other tiny parts of the brain. This is not the same as getting the artificial brain to interact with the real world, but it's a big step in enabling scientists to study their own models on more realistic settings, in which the models' outputs get to effect many other systems, and throuh them feed back into its future inputs. So Blue Brain's biggest contribution might be in making model evaluation in neuroscience less wrong, and that doesn't seem like a bad thing. At some point the reductionist approach needs to start moving in the other direction.
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    @ Dario: absolutely agree, the reductionist approach is the main mistake. My point: if you take the reductionsit approach, then you will face the initial and boundary value problem. If one tries a non-reductionist approach, this problem may be much weaker. But off the record: there exists a non-reductionist theory of the brain, it's called psychology... @ Johannes: also agree, the only way the reductionist approach could eventually be successful is to actually grow the brain. Start with essentially one neuron and grow the whole complexity. But if you want to do this, bring up a kid! A brain without body might be easier? Why do you expect that a brain detached from its complete input/output system actually still works. I'm pretty sure it does not!
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    @Luzi: That was exactly my point :-)
LeopoldS

The Moon's mantle unveiled - 2 views

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    first science results reported in Nature (as far as I know) from the Yutu-2 and Chang'e mission .... and they look very good!
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    Sure they are very useful! It will be even better if they manage to fit the data to modeled circulation of the lunar magma ocean that was formed posterior to the "Theia" body collision with Earth. The collision was the cause of the magma ocean in the first place. The question now is how this circulation pattern of the lava-moon "froze" in time upon phase transition to solid. Because, what crystallizes last in sequence, is more rich in "incompatible" with the crystal structure, elements, we might combine data+models to predict their location. Those incompatible tracers are mainly radioactively decaying elements that produce heat (google publications about lunar KREEP elements (potassium (K), rare earth elements(REE), and phosphorus(P)). By knowing where the KREEP is: - we know where to dig for them mining (if they are useful for something, eg. Phosphorus for plants to be grown on the Moon) - we avoid planning to build the future human colony on top of radioactives, of course. The hope is that the Moon, due to lack of plate tectonics, has preserved this "signature of the freezing sequence". Let's see.
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    thanks Nasia! very interesting comment
Marion Nachon

NASA Next Mars Rover Mission: new landing technology - 3 views

JPL is also developing a crucial new landing technology called terrain-relative navigation. As the descent stage approaches the Martian surface, it will use computer vision to compare the landscape...

technology space

started by Marion Nachon on 15 Jan 18 no follow-up yet
jaihobah

Tajmar tests the EM drive with DLR funding and the result is... - 4 views

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    it works! No, of course it doesn't. I've wasted your time just posting this.
Luzi Bergamin

[1107.0167] Nonlinear transformation optics and engineering of the Kerr effect - 9 views

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    The best paper on transformation optics written ever :-)
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    Finally something worth to read in the MM field!. The idea is excellent, congratullations. However, I think there is a typo or mistake in the definition of l=3x10-13 m, the "waist" of the laser beam. Seems clear that 0.3 pm is too small for being a waist of any laser beam.
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    Thanks for your commendation. Of course, the problem with nonlinear transformation optics is the same as with linear: it's very easy to come up with theoretical descriptions of devices that have the most absurd properties, but it will be extremely hard to fabricate them. But if you have any good suggestion, please shoot! About the laser beam: Pekka made the simulations, since I am not a "Comsolist", but still I think the numbers are correct. You are right that we should not call this a laser beam. Our problem was the following: we need to have a very simple model that can be simulated exactly (full Maxwell equations) but naturally exhibits self focusing. The Gaussian beam was the simplest solution. Since our model is purely classical and moreover we do not take into account diffraction effects, the parameter "l" is of minor importance. Taking "l" much larger gives almost the same picture but requires much more computer power to simulate. I guess that's why Pekka chose an unnaturally small number.
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    Concerning the fabrication... as usual, no idea. I agree that this is the main drawback of MM, and certainly difficult to overcome. I would double check that number, because its value is related with the beam shape of Fig. 1 A. I believe that the simulations are correct, it's just a detail.
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    wow ... still publishing despite babysitting and new job!!
Athanasia Nikolaou

Measuring the predictability of life outcomes with a scientific mass collaboration | PNAS - 3 views

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    This is a social sciences paper trying to make use of ML. Quote from text: "Social scientists studying the life course must find a way to reconcile a widespread belief that understanding has been generated by these data-as demonstrated by more than 750 published journal articles using the Fragile Families data (10)-with the fact that the very same data could not yield accurate predictions of these important outcomes." "(...) In other words, the submissions were much better at predicting each other than at predicting the truth."
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    an important message to learn from
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