59534561
submission
KentuckyFC writes:
In June 1972, nuclear scientists at the Pierrelatte uranium enrichment plant in south-east France noticed a strange deficit in the amount of uranium-235 they were processing. That’s a serious problem in a uranium enrichment plant where every gram of fissionable material has to be carefully accounted for. The ensuing investigation found that the anomaly originated in the ore from the Oklo uranium mine in Gabon, which contained only 0.600% uranium-235 compared to 0.7202% for all other ore on the planet. It turned out that this ore was depleted because it had gone critical some 2 billion years earlier, creating a self-sustaining nuclear reaction that lasted for 300,000 years and using up the missing uranium-235 in the process. Since then, scientists have studied this natural reactor to better understand how buried nuclear waste spreads through the environment and also to discover whether the laws of physics that govern nuclear reactions may have changed in the 1.5 billion years since the reactor switched off. Now a review of the science that has come out of Oklo shows how important this work has become but also reveals that there is limited potential to gather more data. After an initial flurry of interest in Oklo, mining continued and the natural reactors--surely among the most extraordinary natural phenomena on the planet-- have all been mined out.
59290225
submission
KentuckyFC writes:
Memes are the cultural equivalent of genes: units that transfer ideas or practices from one human to another by means of imitation. In recent years, network scientists have become increasingly interested in how memes spread, work that has led to important insights into the nature of news cycles, into information avalanches on social networks and so on. But what exactly makes a meme and distinguishes it from other forms of information is not well understood. Now a team of researchers has developed a way to automatically distinguish scientific memes from other forms of information for the first time. Their technique exploits the way scientific papers reference older papers on related topics. They scoured the half a million papers published by Physical Review between 1893 and 2010 looking for common words or phrases. They define an interesting meme as one that is more likely to appear in a paper that cites another paper in which the same meme occurs. In other words, interesting memes are more likely to replicate. They end up with a list of words and phrases that have spread by replication and can also see how this spreading has changed over the last 100 years. The top five phrases are: loop quantum cosmology, unparticle, sonoluminescence, MgB2 and stochastic resonance; all of which are important topics in physics. The team say the technique is interesting because it provides a way to distinguish memes from other forms of information that do not spread in the same way through replication.
59204713
submission
KentuckyFC writes:
Face recognition has come a long way in recent years. In ideal lighting conditions, given the same pose, facial expression etc, it easily outperforms humans. But the real world isn't like that. People grow beards, wear make up and glasses, make strange faces and so on, which makes the task of facial recognition tricky even for humans. A well-known photo database called Labelled Faces in the Wild captures much of this variation. It consists of 13,000 face images of almost 6000 public figures collected off the web. When images of the same person are paired, humans can correctly spot matches and mismatches 97.53 per cent of the time. By comparison, face recognition algorithms have never come close to this. Now a group of computer scientists have developed a new algorithm called GaussianFace that outperforms humans in this task for the first time. The algorithm normalises each face into a 150 x 120 pixel image by transforming it based on five image landmarks: the position of both eyes, the nose and the two corners of the mouth. After being trained on a wide variety of images in advance, it can then compare faces looking for similarities. It does this with an accuracy of 98.52 per cent; the first time an algorithm has beaten human-level performance in such challenging real-world conditions. You can test yourself on some of the image pairs on the other side of the link.
59038463
submission
KentuckyFC writes:
Typeface design is something of an art. For many centuries, this art has been constrained by the materials available to typographers, mainly lead and wood. More recently, typographers have been freed from this constraint with the advent of digital typesetting and the number of typefaces has mushroomed. Verdana, for example, is designed specifically for computer screens. Now a father and son team of mathematicians have devised a number of typefaces based on problems they have studied in computational geometry. For example, one typeface is inspired by the folds and valleys generated by computational origami designs. Another is based on the open problem of “whether every disjoint set of unit disks (gears or wheels) in the plane can be visited by a single taut non-self-intersecting conveyer belt.” Interestingly, several of the new typefaces also serve as puzzles in which messages are the solutions.
58944499
submission
KentuckyFC writes:
Iapetus, Saturn’s third largest moon, was first photographed by the Cassini spacecraft on 31 December 2004. The images created something of a stir. Clearly visible was a narrow, steep ridge of mountains that stretch almost halfway around the moon’s equator. The question that has since puzzled astronomers is how this mountain range got there. Now evidence is mounting that this mountain range is not the result of tectonic or volcanic activity, like mountain ranges on other planets. Instead, astronomers are increasingly convinced that this mountain range fell from space. The latest evidence is a study of the shape of the mountains using 3-D images generated from Cassini data. They show that the angle of the mountainsides is close to the angle of repose, that’s the greatest angle that a granular material can form before it landslides. That’s not proof but it certainly consistent with this exotic formation theory. So how might this have happened? Astronomers think that early in its life, Iapetus must have been hit by another moon, sending huge volumes of ejecta into orbit. Some of this condensed into a new moon that escaped into space. However, the rest formed an unstable ring that gradually spiralled in towards the moon, eventually depositing the material in a narrow ridge around the equator. Cassini’s next encounter with Iapetus will be in 2015 which should give astronomers another chance to study the strangest mountain range in the Solar System.
58795199
submission
KentuckyFC writes:
Imagine the following scenario. The end of civilisation has occurred, zombies have taken over the Earth and all access to modern technology has ended. The few survivors suddenly need to know the value of pi and, being a mathematician, they turn to you. What do you do? According to a couple of Canadian mathematicians, the answer is to repeatedly fire a Mossberg 500 pump action shotgun at a square aluminium target about 20 metres away. Then imagine that the square is inscribed with an arc drawn between opposite corners that maps out a quarter circle. If the sides of the square are equal to 1, then the area of the quarter circle is pi/4. Next, count the number of pellet holes that fall inside the area of the quarter circle as well as the total number of holes. The ratio between these is an estimate of the ratio between the area of the quarter circle and the area of a square, or in other words pi/4. So multiplying this number by 4 will give you an estimate of pi. That's a process known as a Monte Carlo approximation and it is complicated by factors such as the distribution of the pellets not being random. But the mathematicians show how to handle these too. The result? According to this method, pi is 3.13, which is just 0.33 per cent off the true value. Handy if you find yourself in a post-apocalyptic world.
58684937
submission
KentuckyFC writes:
One of the great theories of modern cosmology is that the universe began in a Big Bang. This is not just an idea but a scientific theory backed up by numerous lines of evidence, such as the cosmic microwave background and so on. But what caused the Big Bang itself? For many years, cosmologists have fallen back on the idea that the universe formed spontaneously; that the big bang was result of quantum fluctuations in which the universe came into existence from nothing. But is this compatible with what we know about the Big Bang itself and the theories that describe it? Now cosmologists have come up with the first rigorous proof that the Big Bang could indeed have occurred spontaneously and produced the universe we see today. The proof is developed within a mathematical framework known as the Wheeler-DeWitt equation. Heisenberg’s uncertainty principle allows a small region of empty space to come into existence probabilistically due to quantum fluctuations. Most of the time, such a bubble will collapse and disappear. The question these guys address is whether a bubble could also expand exponentially to allow universe to form in an irreversible way. Their proof shows that this is indeed possible. There is an interesting corollary which is that the role of the cosmological constant is played by a property known as the quantum potential. This is a property introduced in the 20th century by the physicist David Bohm which has the effect of making quantum mechanics deterministic while reproducing all of its predictions. It’s an idea that has never caught on. Perhaps that will change now.
58605259
submission
KentuckyFC writes:
Last month, astronomers announced the discovery of the most distant body in the Solar System, a dwarf planet called 2012VP113. They also said this body's orbit was strangely aligned with several other dwarf planets in the Kuiper Belt and that this could be the result of these bodies being herded by a much larger Planet X even further from the Sun. They calculated that this hidden planet could be between 2 and 15 times the mass of the Earth and orbiting at a distance of between 200 AU and 300 AU, an announcement that triggered excited headlines around the world. Now it looks as though these predictions were wildly optimistic. It turns out that the position of Planet X can be constrained more tightly using orbital measurements of other planets. And when this data is added into the mix, Planet X can only only orbit at much greater distances, if it exists at all. The new calculations suggest that a planet twice the mass of Earth cannot orbit any closer than about 500 AU. And a planet 15 times the mass of Earth must be at least 1000 AU distant. What's more, the New Horizons mission currently on its way to Pluto, should constrain the distance to beyond 4700 AU. So any Planet X hunters out there are likely to be disappointed.
58515455
submission
KentuckyFC writes:
The resolving power of telescopes is limited by the diffraction limit, a natural bound on resolution caused by the way light diffracts as it passes through a lens. But in recent years, physicists have worked out how to use quantum techniques to beat the diffraction limit. The trick is to create a pair of entangled photons, use one to illuminate the target and the other to increase the information you have about the first. All this is possible in the lab because physicists can use their own sources of light. Indeed, last month, physicists unveiled the first entanglement-enhanced microscope that beats the diffraction limit. But what about astronomy where the light comes from distant astrophysical sources? Now one physicist has worked out how to use quantum techniques to beat the diffraction limit in telescopes too. Her idea is to insert a crystalline sheet of excited atoms into the aperture of the telescope. When astrophysical photons hit this sheet, they generate an entangled pair of photons. One of these photons then passes through the telescope to create an image while the other is used to improve the information known about the first and so beat the diffraction limit. Of course, all this depends on improved techniques for increasing the efficiency of the process and removing noise that might otherwise swamp the astrophysical signal. But it's still early days in the world quantum imaging and at least astronomers now know they're not going to be excluded form the fun.
58390075
submission
KentuckyFC writes:
One of the greatest mysteries in science is why we don't see quantum effects on the macroscopic scale; why Schrodinger's famous cat cannot be both alive and dead at the same time. Now one theorist has worked out why and says the answer is because P is NOT equal to NP. Here's the thinking. The equation that describes the state of any quantum object is called Schrodinger's equation. Physicists have always thought it can be used to describe everything in the universe, even large objects and perhaps the universe itself. But the new idea is that this requires an additional assumption--that an efficient algorithm exists to solve the equation for complex macroscopic systems. But is this true? The new approach involves showing that the problem of solving Schrodinger's equation is NP-hard. So if macroscopic superpositions exist, there must be an algorithm that can solve this NP-hard problem quickly and efficiently. And because all NP-hard problems are mathematically equivalent, this algorithm must also be capable of solving all other NP-hard problems too, such as the travelling salesman problem. In other words, NP-hard problems are equivalent to the class of much easier problems called P. Or P=NP. But here's the thing: computational complexity theorists have good reason to think that P is not equal to NP (although they haven't yet proven it). If they're right, then macroscopic superpositions cannot exist, which explains why we do not (and cannot) observe them in the real world. Voila!
58362689
submission
KentuckyFC writes:
The single-celled organism slime mould, or Physarum polycephalum, is an extraordinary creature. It explores its world by extending protoplasmic tubes into its surroundings in search of food and it does this rather well. Various researchers have exploited this process to show how Physarum can find optimal routes between different places and even solve mazes. Now one researcher has worked out how to use these protoplasmic tubes as clock-like electronic oscillators. His experiment was straightforward. He encouraged the growth of protoplasmic tubes between two blobs of agar sitting on electrical contacts. He then measured the resistance of the tubes at various voltages. This turns out to be about 6 megaohms. But the results show something else too: that the resistance oscillates over a period of about 73 seconds. That's due to the tubes contracting as waves of calcium ions pass through them. So altering the period of oscillation should be possible by influencing the production of calcium ions, perhaps using light or biochemistry. Electronic oscillators are significant because they are basic drivers of almost all active electronic devices. But this guy's goal is bigger than this. The plan is to grow a "Physarum chip" that acts as a general purpose computer, a device that will need some kind of oscillator or clock to co-ordinate activity, just as in an ordinary processor, although speed will not be its chief characteristic.
58321149
submission
KentuckyFC writes:
The question of what makes puzzles hard for humans is deceptively tricky. One possibility is that puzzles that are hard for computers must also be hard for people. That's undoubtedly true and in recent years computational complexity theorists have spent some time trying to classify the games people play in this way (Pac Man is NP hard, by the way). But humans don't always solve problems in the same way as computers because they don't necessarily pick the best method or even a good way to do it. And that makes it hard to predict the difficulty of a puzzle in advance. Cognitive psychologists have attempted to tease this apart by measuring how long it takes people to solve puzzles and then creating a model of the problem solving process that explains the data. But the datasets gathered in this way have been tiny--typically 20 people playing a handful of puzzles. Now one researcher has taken a different approach by mining the data from websites in which people can play games such as Sudoku. That's given him data on the way hundreds of players solve over 2000 puzzles, a vast increase over previous datasets and this has allowed him to plot the average time it takes to finish different puzzles. One way to assess the difficulty of Sudoku puzzle is in the complexity of each step required to solve it. But the new work suggests that another factor is important too--whether the steps are independent and so can be attempted in parallel or whether the steps are dependent and so must be tried in sequence, one after the other. A new model of this puzzle-solving process accurately reproduces the time it takes real humans to finish the problems and that makes it possible to accurately predict the difficulty of a puzzle in advance for the first time. It also opens the way for other studies of human problem solving using the vast datasets that have been collected over the web. Indeed work has already begun on the Sudoku-like puzzle game, Nurikabe.
58124227
submission
KentuckyFC writes:
The origin of the heat generated inside the Earth is one of the great mysteries of geophysics. Researchers know that almost all this heat is generated by the decay of radioactive elements such as potassium-40, thorium-232 and uranium-238. But what they don't know is how these elements are distributed inside the planet and how much heat each contributes. In the next few years, they hope to get some answers thanks to the emerging science of antineutrino geophysics. Since radioactive decay produces antineutrinos, an experiment that measures these particles coming out of the Earth should provide a detailed picture of the distribution of the elements within it. But there's a problem. Nuclear reactors also produce copious numbers of antineutrinos and these can swamp the signal from inside the Earth. What's needed is a map showing the distribution of reactor antineutrinos so that geophysicists can choose the best places to put their experiments. Just such a map is exactly what a team of nuclear physicists has now produced. The map shows that planned experiments in Hawaii and Curacao, off the coast of Venezuela, are in excellent locations and that Japan has recently become a much better site thanks to the shut down of the country's nuclear industry following the 2011 Tohoku earthquake. But a European experiment currently being planned in south-east France doesn't come off so well.
58051333
submission
KentuckyFC writes:
If you've been living under a stone, you might not have heard last week's announcement that astrophysicists from the BICEP2 experiment have found the first evidence of two extraordinary things. The first is primordial gravitational waves--ripples in spacetime from the very first moments after the Big Bang. The second is that these waves are evidence of inflation, the theory that the universe expanded rapidly, by twenty orders of magnitude in the blink of an eye after the Big Bang. But that can only be possible if the gravitational waves formed before inflation occurred. Now critics have begun to mutter that the waves might have formed later and so provide no evidence of inflation. The new thinking is that as the universe cooled down after inflation, various phase changes occurred in the Universe which generated the laws of physics we see today. These phase changes would have been violent events that generated their own ripples in space time, which would look very much like the primordial gravitational waves that the BICEP2 team claims to have found. So the BICEP2 team must rule out this possibility before they can claim evidence of inflation. But the critics say the data does not yet allow this to be done. That doesn't mean inflation didn't occur. Indeed, the critics say this is still the most likely explanation. But until the phase change possibility is ruled out, the result must be considered ambiguous. So put the champagne back in the fridge.
57907037
submission
KentuckyFC writes:
The recent development of vast databases that link words to the emotions they conjure up is changing the way researchers study text. Sentiment analysis, for example, is increasingly used to gauge the mood of society on topics ranging from politics to movies. Now researchers have used the same technique to measure the "emotional temperature" throughout a novel and then to automatically compose music that reflects the content. The key advance in this work is the development of rules that map the emotional changes into musical qualities such as tempo, key pitch and so on. The team has fed a number of well known books through the algorithm, which they call TransProse. These include lighter texts such as Peter Pan and much darker novels such as The Road and Heart of Darkness. And the music isn't bad (to my untrained ear). The teams say the new algorithm could lead to audio-visual e-books that generate music that reflects the mood on open pages. And it may even be possible to use the algorithm in reverse to recommend known songs that reflect the mood in a book.
