The clouds at Neptune's South Pole seem to be caught in a giant vortex, according to a new images of the planet.

Something's afoot at Neptune's South Pole. Back in July 2007, astronomers took a series of infrared pictures of Neptune using the 10 metre W.M. Keck II telescope on Mauna Kea, Hawaii.

Astronomers have long been aware of a bright spot at Neptune's south pole. The feature first showed up in pictures taken during the Voyager spacecraft flyby and it has been spotted on various occasions since then using ground-based instruments.

So what happened in July 2007 puzzled them: the spot divided into two and then recombined a few days later.

Today, Statia Luszcz-Cook at the University of California Berkeley and a couple of buddies, say they now know what's going on. The white spots, they say, are probably methane clouds caught in a powerful vortex of winds at the south pole.

The reason they can tell is because a similar phenomena exists at Saturn's south pole and this has been extensively studied thanks to the marvellous images being sent back by Casini.

Although the hurricane on Neptune isn't directly visible, Luscz-Cook and co have studied the dynamics of clouds caught in Saturn's vortex and say the behaviour of the Neptunian clouds is remarkably similar.

These hurricanes have other interesting features. Although their scale is huge--they are thousands of kilometres wide--extraterrestrial hurricanes are remarkably similar to the ones that form on Earth. "The structure of Saturn's south polar vortex possesses similarities with terrestrial hurricanes, such as a well-formed central eye, concentric eyewalls and a surrounding ring of strong convection," say the team.

They also point out that the spots on Neptune are "consistent with clouds formed by the upwelling and condensation of methane gas." Which is another way of saying that it rains methane on Neptune.

The weather on Earth isn't as unique as we might imagine.

Ref: arxiv.org/abs/1003.3240: Seeing Double at Neptune's South Pole

The patterns of links between buyers and sellers of sex in an online forum differs in important ways from other internet related networks, says a new study. This may have important implications for the spread of sexually transmitted diseases

"Over the past decade, the Internet has become an increasingly important vehicle for sharing information about prostitution," say Luis Rocha at Umea University in Sweden and a couple of buddies. That makes it possible to study the network of links between buyers and sellers at a level of detail that has never been possible before. Today, Rocha and co reveal the results one such study of prostitute-related activity in Brazil.

The community they look at is a public online forum with free registration, financed by advertisements, in which men grade and categorise their sexual encounters with female escorts. The community appears large with over 10,000 buyers and more than 6000 sellers all of whom use anonymous nicknames. The study covers a period of 6 years from when the community was set up in 2002 until 2008.

The study throws up both expected and unexpected results. Among the expected results is the discovery that the geographical connections between buyers and sellers vary as an inverse square law rather than a power law as in many other internet mediated networks. That's not so hard to explain given that buyers or sellers have to travel to each other.

Another discovery is that a high rating for a particular sex worker is a good predictor of high ratings in the future. That's the kind of rich get richer effect that is seen in many internet phenomena (also known as the Matthew effect). However, average or poor ratings don't seem to affect future ratings either way.

Naturally, buyers tend to use more highly rated sex-workers more often. And over short timescales this can be seen in the data. However, look at longer timescales and the effect drops away. That's probably because sex-workers do not stay in their work for long periods of time, say Rocha and co.

Unexpectedly, these behaviours make the network different from traditional scale free networks in some subtle ways.

That could turn out to be significant. Much work has been done on the spread of disease and one important factor is the nature of the network in which infection takes place.

The evidence from Rocha and co is that real world network of links between buyers and sellers in the sex-market is different from traditional scale free networks (although that's something that needs to be checked in more detail).

So the questions that is left begging is this: what effect does this have on the spread of sexually transmitted disease?

Ref: arxiv.org/abs/1003.3089 : Information Dynamics Shape the Sexual Networks of Internet Mediated Prostitution

It's not just financial markets that experience bubbles, society does too. And the Human Genome Project is a perfect example, says a new study.

The world has become painfully familiar with the notion of financial bubbles in the last two years. These are periods of in which prices are temporarily raised above their fundamental value, sometimes by orders of magnitude.

But the contention put forward by Monika Gisler and a couple of pals at the Swiss Federal Institute of Technology in Zurich is that it's not just financial markets that experience bubbles. They say there is good evidence for the existence of social bubbles too. They point to the great boom of railway building in Britain in the 1840s, cloning of mammals such as Dolly the sheep, and the craze over Haute Couture, the so-called democratisation of fashion design.

All of these were characterised not by prices rising far above fundamental values, but by human expectations being inflated beyond reason. "These cases were all characterized by extremely high expectations concerning the outcome of the proposed research and/or innovation project," say Gisler and her colleagues.

Today, they show how the Human Genome Project is a particularly good example of a social bubble. They give a fascinating history of the project and the expectations associated with it and focus in particular on how it was funded. This, they say, is an objective way of assessing the enthusiasm for it project, at the time.

The Human Genome Project generated huge expectations that it would revolutionise the treatment of illness and disease and huge commercial opportunities for the development of drugs . The belief that this would dramatically change our society eventually persuaded the US government to spend around $3billion on the project.

It also led to a fierce battle between this government-funded project and a private company called Celera that aimed to complete the task first using cheaper, more powerful sequencing techniques.

This battle led to a kind of virtuous circle which reinforced investors' belief in the potential benefits and caused the scientists themselves to redouble their efforts.

But it also deflected attention from the huge uncertainties about the project. The fear, more or less ignored, was that the benefits would not be as great as imagined.

These fears have more or less come to pass. "Having the complete gene set on the table, the knowledge of the genetic map and sequence is now considered by experts to be only a starting point for future research in biology and medicine," says Gisler and co.

That's not to say it has been of little value. On the contrary, they say. "While there is little to show in terms of progress in medical diagnosis and treatment, in pharmaceutical development, in agriculture, and in other industrial sectors, the HGP catalyzed enormous technological progresses in DNA-based methods."

Gisler's point is that if managed correctly social bubbles can be hugely beneficial, even if they don't produce the desired outcome. But they require a careful hand on the tiller and that's not easy since they require the combined forces of industry, academia and government working towards a common goal.

There are various bubbles in the making today, such as the UK's investment in offshore windfarms in the North Sea, a project that will produce a quarter of the UK's electricity by 2020. This project is huge by any standards: equivalent to building 8 channel tunnels in the next ten years and requires the same kind of link between government, industry and academia to make it work.

There are other efforts that have not yet achieved the kind of terminal velocity necessary for bubble status. One of them is the human genome project''s successor: proteomics, the characterization of the entire array of proteins encoded by our genes, a task that is an order of magnitude more complex than the genome project.

Gisler and co say that the lessons from the Human Genome project could be used to create the same kind of bubble for proteomics. For the moment, however, investors, government and perhaps even the scientists themselves, have yet to achieve critical mass.

Ref: arxiv.org/abs/1003.2882: Exuberant Innovation: The Human Genome Project

Rhodospirillum Photometricum has a mechanism that allows it to harvest more light in dim conditions but protect its cellular machinery from photon damage when it's too bright.

A few years ago, scientists studying the light-harvesting bacteria, Rhodospirillum Photometricum, made a curious discovery. This bacteria is able to exploit solar energy because its cell membrane is filled with chromophore vesicles: regions containing pigment molecules capable of absorbing light and turning it into chemical fuel.

The strange thing about these bacteria was that the membrane came in two forms: one form with large numbers of pigment molecules and another with only a few. And the difference was determined by the amount of light the organism had been exposed to. Why should that be?

Today, Neil Johnson at the University of Miami and a few pals explain why with the aid of a sophisticated model of the behaviour of the membrane. They say that the membrane performs two competing functions. First, it needs to convert large numbers of photons into useful chemical energy. Second, it must protect the inside of the cell from an oversupply of photonic energy and the damage it can cause. Johnson and co say the puzzle is explained by the interplay of these two forces which cause the membrane to form one way or the other.

That's an interesting insight and not just because it explains the structural differences that appear during the growth of Rhodospirillum Photometricum. Johnson and co hint that a similar approach might be useful for creating a new generations of solar cells. They say: "this new quantitative understanding may help accelerate development of novel solar micropanels mimicking natural designs."

I guess the important point is that if we want to copy nature's machinery for harvesting light, we'll also need to copy the defensive mechanisms that evolved to protect this machinery from over exposure to sunlight. Rather like sun cream for solar cells.

Ref: arxiv.org/abs/1003.2443: Light-Harvesting In Bacteria Exploits A Critical Interplay Between Transport and Trapping Dynamics

String theory implies that black holes can come in all kinds of forms and flavors, according to a cosmologist who has catalogued all known types.

String theory is physicists' best guess at a unified theory of all interactions but it comes with some strange predictions. One of these is that spacetime consists of 10 dimensions rather than just the four we're familiar with. And that raises some interesting questions.

One of them is what shape singularities can form in this higher dimensional space. In four dimensions, the only solution is spherical and that's the type of black holes cosmologists have imagined all over the universe.

But in higher dimensions, there are all kinds of other solutions. We've looked at the possibility of black rings but today Maria Rodriguez at the Max Planck Institute for Gravitational Physics in Golm, Germany, compiles a catalogue of all know species of black hole.

It turns out there's a whole managerie of other black hole solutions. Here are just a few: the black saturn, the black helical ring, the di-ring, the black bowtie, and the bicycling black ring as well as the more general blackfolds.

While these solutions may exist mathematically, they may or may not exist in the real universe. In fact, Rodriguez is able to work out certain criteria that a solution must meet for it to have a hope of existing in the real world. For example, a black ring can only exist if there is enough centrifugal repulsion to prevent it from collapsing.

Rodriquez points out that the list is incomplete. "The catalog of different species (exact solutions) of black holes shows a very rich structure but seems far from being complete."

That makes it an interesting topic for ambitious cosmologists. But be warned: there's a good reason the list is incomplete. The solutions in this higher dimensional space are fiendishly difficult to find.

Nevertheless, it would be good to either rule out the possibility of their existence or work out if and how they can be distinguished observationally from common or garden spherical black holes.

Ref: arxiv.org/abs/1003.2411: On the Black Holes Species (By Means Of Natural Selection)

The best of the rest from the Physics arXiv this week:

Observation of an Antimatter Hypernucleus

A Signature of Cosmic Strings Wakes in the CMB Polarization

Self-Assembled Granular Walkers

Quantum Dating Market

A Computational Algorithm based on Empirical Analysis, that Composes Sanskrit Poetry

A new set of star velocity data indicates that Gliese 710 has an 86 percent chance of ploughing into the Solar System within the next 1.5 million years.

The Solar System is surrounded by thousands of stars, but until recently it wasn't at all clear where they were all heading.

In 1997, however, astronomers published the Hipparcos Catalogue giving detailed position and velocity measurements of some 100,000 stars in our neighbourhood, all gathered by the European Space Agency's Hipparcos spacecraft. It's fair to say that the Hipparcos data has revolutionised our understanding of the 'hood.

In particular, this data allowed astronomers to work out which stars we'd been closer to in the past and which we will meet in the future. It turns out that 156 stars fall into this category and that the Sun has a close encounter with another star (meaning an approach within 1 parsec) every 2 million years or so.

In 2007, however, the Hipparcos data was revised and other measurements of star velocities have since become available. How do these numbers change the figures?

Today, Vadim Bobylev at the Pulkovo Astronomical Observatory in St Petersburg gives us the answer. He's combined the Hipparcos data with several new databases and found an additional nine stars that have either had a close encounter with the Sun or are going to.

But he's also made a spectacular prediction. The original Hipparcos data showed that an orange dwarf star called Gliese 710 is heading our way and will arrive sometime within the next 1.5 million years.

Of course, trajectories are difficult to calculate when the data is poor so nobody has really been sure about what's going to happen.

What the new data has allowed Bobylev to do is calculate the probability of Gliese 710 smashing into the Solar System. What he's found is a shock.

He says there is 86 percent chance that Gliese 710 will plough through the Oort Cloud of frozen stuff that extends some 0.5 parsecs into space.

That may sound like a graze but it is likely to have serious consequences. Such an approach would send an almighty shower of comets into the Solar System which will force us to keep our heads down for a while. And a probability of 86 percent is about as close to certainty as this kind of data can get.

The good news is that Bobylev says the chances of Gliese 710 penetrating further into the Solar System, inside the Kuiper Belt, are much smaller, just 1 in a 1000. So that's all right, then.

Keep calm and carry on.

Ref: arxiv.org/abs/1003.2160: Searching for Stars Closely Encountering with the Solar System

21 Lutetia has puzzled astronomers since its discovery. Now they have made a daring set of predictions about what the Rosetta spacecraft will find when it flies past this mysterious asteroid in July.

On 10 July, the European Space Agency's Rosetta spacecraft will fly within a few thousand kilometres of 21 Lutetia, a main belt asteroid that orbits the Sun between Mars and Jupiter.

Lutetia is an unusual object. It is classified as an M-type asteroid, which are thought to be made mainly of nickel and iron. However, Lutetia's spectrum does not seem to show any evidence of metals. In fact, exactly what Lutetia is made of puzzles astronomers. That's partly why it was chosen for the fly by.

So come July, astronomers should know the answer to this conundrum. But in the run up, they're indulging in a little fun. The game they've invented is to see how good a prediction they can make about what Rosetta will find.

Today, Irina Belskaya at the Observatoire de Paris and a few friends take a stab. They make several detailed predictions about Lutetia based partly on observations dating back to the 1960s but mostly on data taken since 2004, when interest picked up after the asteroid was chosen as a flyby target.

So what do they think Rosetta will find?

Belskaya and company say that Lutetia will be 132x101x76 km in size (that's technically known as potato-shaped). They say its texture and mineral content will vary across its surface. At least part of Lutetia's surface will be covered by a layer of loose dust having a mean grain size less than 20 micrometres across. And Lutetia's surface will be made of stuff that has more in common with the carbonaceous chondrite meteorites found on Earth than the iron-nickel ones.

But they're most interesting prediction is that Lutetia will be "non-convex" in shape. That means a large crater will be visible on its surface. In fact its shape will be dominated by this crater.

Great fun to see a daring set of forecasts like this. And only four months until we find out how well they've done.

Ref: arxiv.org/abs/1003.1845: Puzzling Asteroid 21 Lutetia: Our Knowledge Prior To The Rosetta Fly-By

Apply an oscillating electric field to the anode of a lithium battery and the recharge time drops dramatically, say chemists.

One of the biggest problems with batteries is the time it takes to recharge them. Run out of juice and it'll be several hours before you're mobile again, a particular showstopper for electric vehicles.

Today, Ibrahim Abou Hamad at Mississippi State University and few buddies reveal an entirely new technique for charging lithium ion batteries that could lead to exponential improvements in charging time.

The business end of a lithium battery, the anode, consists of a graphite electrode, in other words a stack of graphene sheets, bathed in an electrolyte of ethylene carbonate and propylene carbonate molecules through which lithium and hexafluorophosphate ions diffuse. During charging, an electric field pushes the lithium ions towards and into the graphene sheets, where they have to cross a potential barrier to become embedded and stored, a process called intercalation.

The Mississippi team have studied the movement of these ions and molecules by creating a computer model of the forces acting on them. Their model consists of 160 carbon atoms arranged in 4 graphene sheets, 69 propylene carbonate and 87 ethylene carbonate molecules forming a liquid electrolyte and finally, two hexafluorophosphate ions and10 lithium ions. They then apply an electric field across this system and watch what happens.

It turns out that while the electric field pushes the lithium ions towards the graphene, the rate limiting step is the process of intercalation--the rate at which the lithium ions can cross the potential barrier into the graphene .

What Hamad and co have found is a relatively simple way to overcome this barrier. The trick is to superimpose an oscillating electric field onto the charging field. This has the effect of helping the lithium ions to hop over the barrier.

But get this: the team says there is an exponential relationship between the intercalation time and the oscillating field amplitude. So a small increase in amplitude of the field leads to a massive speed up of the process of intercalation.

"These simulations suggest a new charging method that has the potential to deliver much shorter charging times, as well as the possibility of providing higher power densities," they say.

That's a neat piece of work which should be relatively straightforward to test in a real battery.

That doesn't mean that we'll see a ten minute charging time for electric vehicles any time soon.

Battery performance is a complicated balance between huge numbers of competing factors. If this oscillating field does improve charging time in real batteries, manufacturers will then have to check its effect on other performance metrics such as the number of these charging cycles a battery can withstand and how long it holds its charge, to name just two.

Nevertheless, these Mississippi guys have come up with an interesting new approach that will have more than peaked the interest of battery makers around the globe.

Ref: arxiv.org/abs/1003.1678: A New Battery-Charging Method Suggested By Molecular Dynamics Simulations

Physicists have come up with a way to process information faster than the speed of light. But what could they do with such a hypercomputer?

The speed of light represents one of the fundamental limits of the laws of physics. Nothing can travel faster than the speed of light, right?

Well, yes and no, say Volkmar Putz and Karl Svozil at the Vienna University of Technology in Austria. They say there are several ways that signals can cross the superluminal line, although none of them allow the kind of time travel paradoxes beloved of science fiction writers. For example, the quantum phenomenon of entanglement occurs when two quantum particles are described by the same wave function. These particles can be separated by the diameter of the universe and yet a measurement on one will instantaneously influence the other.

So-called "nonlocal" phenomenon cannot be used to transmit information faster than the speed of light but Putz and Svozil today ask whether it can be used to process it, to carry out computational tasks at superluminal speeds. They say there is no reason why not, provided the processing does not lead to any time travel paradoxes.

How might such a machine work? Putz and Svozil point out that nonlocal phenomenon can lead to materials in which the index of refraction is less than one, thereby allowing superluminal speeds. For example, light travelling through a vacuum can be made to spontaneously form into an electron-positron pair--an entangled pair--which then recombine to form a photon again. This process happens instantaneously, allowing the photon to effectively "jump" across space.

A material in which this kind of pair formation and recombination was promoted would have a refractive index less than one, they say. Various physicists have proposed such materials made of things like metamaterials. Putz and Svozil themselves suggest that a vacuum filled with either electrons or positrons would do the trick.

Having created a medium in which the refractive index is less than one, Putz and Svozil's idea is simply to immerse a computer in it. That simple act (and presumably some clever design to create an optical computer in the first place) would allow superluminal computation to take place.

Assuming that this device could actually be built, what could you do with a superluminal computer? That's a good question that Putz and Svozil do not address directly. They say such a device would fall into a class of processing machine known as hypercomputers. These are hypothetical devices more powerful than Turing machines, that allow non-Turing computations. They were first discussed by Alan Turing in the 1930s.

In theory, hypercomputers can compute certain kinds of otherwise noncomputable functions. That sounds handy but even though there are uncountably many non-computable functions, it's actually quite hard to come up with an example of one that might seem useful. If you have any ideas, post them in the comments section.

Otherwise sit back and wait for a new era of superluminal hyprcomputers. But don't hold your breath.

Ref: arxiv.org/abs/1003.1238: On the physical limit of communication speed by light signals

Quantum cryptography only works if Alice and Bob share their relative positions in advance. Now physicists have worked out how to do it without this information.

The world of cryptography is currently undergoing a quantum revolution. The weird laws of quantum mechanics allow cryptographers to create codes that guarantee perfect secrecy. Until recently, the best cryptographers could aim for was just pretty good secrecy with codes that were always compromised in some way or another. Quantum cryptography, on the other hand, is perfect: theoretically and practically secure.

A few companies have even sprung up to sell the gear that can send perfectly secure messages, mainly to banks and governments (although the gear itself creates some loopholes that eavesdroppers can attack).

But it's still early days for this technology and naturally it suffers from several drawbacks. For example, one well known limitation is that quantum cryptography can only be used over point-to-point connections and not through networks where data has to be routed. That's because the routing process destroys the quantum properties of the photons used to secure messages.

A lesser known limitation is that the sender and receiver of quantum encrypted messages--the famous Alice and Bob--must be perfectly aligned so that they can carry out well-defined polarisation measurements on the photons as they arrive. Physicists say that Alice and Bob must share the same reference frame.

That's not so hard to do when Alice and Bob are both based in labs on the ground. But it's much harder when one or the other is moving, in a satellite, for example, which would be both spinning and orbiting the Earth.

Today, Anthony Laing from the University of Bristol and a few pals show how to get round this. The trick is to use entangled triplets of photons, so-called qutrits, rather than entangled pairs.

This solves the problem by embedding it in an extra abstract dimension, which is independent of space. So as long as both Alice and Bob know the way in which all these abstract dimensions are related, the third provides a reference against which measurements of the other two can be made.

That allows Alice and Bob to make any measurements they need without having to agree ahead of time on a frame of reference. There is one proviso: Alice and Bob cannot move too quickly during the measurements since this changes their relative orientation and a new qutrit will be needed to establish a reference.

That'll be useful for quantum encryption over satellite links, the kind of thing that government agencies and the military might want to do. But there's another, more valuable application.

If quantum encryption is ever to be widely used, it'll need to work between one microchip and another without the need to share a frame of reference in advance. That's always been a problem because the chips inside computers are constantly on the move (relative the the wavelength of light) and because photon polarisations drift as they move through optical fibres, introducing another source of error.

That's why quantum cryptography that is reference frame independent is an enabling technology and so potentially hugely valuable. It means that Laing and co may have made one of the key breakthroughs that will bring quantum cryptography to the masses.

Ref: arxiv.org/abs/1003.1050: Reference Frame Independent Quantum Key Distribution

Update: Anthony Laing writes:

I have a few clarifications which may be useful for your readers...

- The protocol is always bipartite - so two people, two particles,
one particle each.

- The protocol works best for particle dimensions of prime or power-
prime, including the 2 dimensional qubit, so an entangled pair of
qubits is the most simple case that works.

- The protocol works because security is guaranteed with a purity
measure on the joint 'entangled' space of Alice and Bob and this
purity would not be reduced too much in a reference frame that varies
slowly on the timescale of rate-of-pair-creation and measurement.

The best of the rest from the Physics arXiv this week:

A Definable Number Which Cannot Be Approximated Algorithmically

Memory Metamaterials

Sprite Discharges On Venus And Jupiter-Like Planets: A Laboratory Investigation

Interferometers As Holographic Clocks

Gravity as Quantum Entanglement Force

The efficiency of the Apollo reflector arrays drops by a factor of ten during a full moon. Now a new analysis may explain why.

Lunar laser ranging experiments have produced a treasure trove of interesting information about the Moon, for example that it is spiralling away from us at a rate of 38 mm per year.

The experiments are simple. Astronomers fire a laser pulse at a reflector placed on the lunar surface by the Apollo 15 mission and then use a telescope to look for the reflection, some 2 seconds later.

The observations are challenging. Of the 10^17 photons that set out towards the Moon in each pulse, only one makes it back, on average. And only then if seeing conditions are good.

When conditions are good, astronomers often take aim at the arrays left by the Apollo 11 and 14 missions which are only a third of the size of Apollo 15's and therefore harder to see. If the observers are feeling lucky, they might also try for the Russian Lunakhod 2 array (the Lunakhod 1 array hasn't been seen since 1971).

All in all, astronomers have been taking observations since 1969, first from the MacDonald Observatory in West Texas and later from the Apache Point Observatory in New Mexico . This gives them a substantial database with which to analyse the behaviour of the reflectors.

So how have these reflectors fared in the harsh conditions on the lunar surface over the years? That's the question addressed today by Tom Murphy at the University of California San Diego and a few buddies. And their analysis poses an interesting problem.

First of all they say that the efficiency of all three Apollo reflector arrays has fallen by an order of magnitude during their sojourn on the Moon. The Lunakhod reflector has fared even worse. When it arrived on the moon in 1973, its signal was 25 per cent stronger than Apollo 15's. Today it is ten times worse.

What's happened this gear?

The reflectors consist of an array of cubic prisms that operate by total internal reflection. In addition, the Lunakhod prisms have silvered surfaces and are more exposed. Degradation of this silvering probably explains its relative drop in performance.

But what has caused the degradation of the Apollo prisms? Anything that settles on or damages the optical surfaces of the prisms will reduce the efficiency of the total internal reflections. Murphy and co discuss several possibilities such as micrometeorite damage, lunar dust aggregation and the breakdown of the Teflon mounting rings which may have left deposits on the back surface of the prisms.

Any of these mechanisms could account for the drop but its hard to pin one down.

However, there is another more intriguing puzzle about the laser ranging data. When the Moon is full, the efficiency of all the Apollo reflectors drops by another factor of ten. Murphy and co have ruled out ground-based effects such as the saturation of their photon detectors when the moon is bright.

So why does this happen? One clue comes from the study of returns during total lunar eclipses. Within 15 minutes of an eclipse occurring, the efficiency of the reflectors returns to its normal levels. When the eclipse ends and the Moon is full again, the efficiency immediately drops again.

That strongly points to a thermal effect. When the Sun is low in the lunar sky, its rays cannot directly enter the prisms which are recessed in the arrays. But when the Sun is overhead (which is when the Moon appears full on Earth), its rays travel directly into the prisms. This is probably heating the prisms, distorting them and reducing the efficiency of their reflections.

But why now? The full Moon effect was not a problem in the early days of lunar ranging.

"Dust is perhaps the most likely candidate for the observed degradation," say Murphy and co. The sunlight is probably absorbed by dust on the optical surfaces which in turn heats the silica prisms.

Dust is known to hover above the lunar surface because of electrostatic forces and micrometeorite impacts probably send a few puffs into the lunar atmosphere on a regular basis.

Interesting work. And one that is of more than passing interest for many astronomers because it has implications for anybody thinking of sending gear to the Moon in future. Various astronomers want to send telescopes to the Moon, particularly the far side because of the tremendous seeing conditions there and its isolation from the Earth. Knowing how the Apollo gear has fared will be crucial when it comes to designing this stuff.

Ref: arxiv.org/abs/1003.0713: Long-Term Degradation Of Optical Devices On The Moon

If you ever share personal information with friends online you probably already use a special set of rules to determine what to reveal and what to keep secret. Now a new model of social networks attempts to capture that process.

If you ever chat online to friends, colleagues and relatives, you probably have a set of unwritten rules about the kind of information you share with whom. The sort of thing you might take into account is the likelihood that this person will share your information with others, who these other people might be and whether this will be good or bad for you. Above all, you will almost certainly accept that divulging personal details brings you certain benefits, if only that it will strengthen the social bond between you and your correspondent.

But this attitude to sharing personal information is probably in stark contrast to the way you think about the information you share when carrying out an electronic transaction such buying a book or signing up for a newsletter. In this case, most people feel strongly that they should minimise the information they share.

Strangely, most studies of privacy and the spread of personal information through networks have focused on the latter scenario.Today, Jon Kleinberg and Katrina Ligett at Cornell University redress the balance.

These guys have created a model of information sharing that attempts to capture these subtle rules. In the model, two people must agree to share information. The model assumes that they do this strategically to maximize their benefits they receive based on their expectations about what others will do. The model captures the benefit or disadvantage by allowing it take a positive or negative value.

The result is a kind of network formation game, in which players must decide which links to maintain and which to cut so as to maximize their benefits or minimise their losses.

Clearly, this is a game that can produce extremely rich behaviour. Kleinberg and Ligett's goal is to study the the most basic version of the model that is still rich enough to produce meaningful results.

What they find makes for interesting reading. For example, they say that the model provides an easy way to monitor social welfare, simply by adding up the benefits that everybody gets. They can also look for networks that maximise social welfare.

Kleinberg and Ligett look particularly at stable networks in which people are not forced to make and cut ties since these seem to best represent the ones that humans form naturally. But the new approach allows the researchers to ask an interesting question: are these the best types of network? In other words, are stable networks automatically the socially optimal ones? And if not, what is the difference between them in terms of social welfare?

And that's just the start of what's possible. Kleinberg and Ligett have only just begun analysing these networks. The results are at an early stage but the potential is fascinating.

All the more so because of Kleinberg's background: he has significant form when it comes to analysing networks. In the late 1990s, he developed the hubs and authorities model of websites. His idea was that some websites act as hubs directing surfers to authorities on certain topics and was hugely influential because it lead directly to an objective way of organising and therefore ranking websites . Kleinberg's work was a direct forerunner of Google's PageRank.

The question this later paper raises is whether Kleinberg is about trigger the same kind of revolution for social networks that he did for the world wide web. Worth watching.

Ref: arxiv.org/abs/1003.0469: Information-Sharing and Privacy in Social Networks

A new statistical approach reveals the intrinsic talent of sportsmen and women, regardless of the era in which they played.

It's a problem that leaves brows furrowed on barstools across the world: how to rate the sportsmen and women of the day against the stars of yesteryear.

There's no easy way to make meaningful comparisons when sports change so dramatically over the years. Even in endeavours like baseball where player stats have been meticulously kept for almost a hundred years, comparisons across the decades can be odious. Is it really fair to compare players from the 1920s against those of the last 20 years when so many external factors have changed such as the use of new equipment, better training methods and, of course, performance enhancing drugs?

In 1914, the National League Most Valuable Player was Johnny Evers with a batting average of 0.279, 1 Home Run and 40 Runs Batted In. That was impressive then but these stats would embarrass even a second rate player in today's game.

But what if there were a way to remove the systematic differences to reveal intrinsic talent? Today, Alexander Petersen at Boston University and a few pals explain just such a method that "detrends" the data leaving an objective measure of a player's raw ability.

The detrending process is a statistical trick that essentially rates all players relative only to their contemporaries. This effectively cancels out the effect of performance-enhancing factors which are equally available to everybody in a given era. The detrended stats then allows them to be objectively compared with players from other eras and the end product is a ranking of pure talent.

Petersen and co compare the detrended rankings against the traditional ones for several standard baseball metrics, such as Career Home Runs, Season Home Runs and so on.

The results will be an eye-opener for some fans and Petersen and co provide an interesting commentary on the new tables. For example, their new list of the top 50 individual home run performances by season does not contain a single entry after 1950. Not even the performance of Barry Bonds in 2001 or of Mark McGwire in 1998 make the list. In fact, Babe Ruth's achievements from the 1920s fill seven of the top ten slots.

Petersen and co are at pains to point out why this is: "It behooves us to point out that these results do not mean that Babe Ruth was a better slugger than any other before or after him, but rather, relative to the players during his era, he was the best home run hitter, by far, of all time."

The Boston team say their method can be applied to other sports with professional leagues such as American basketball, Korean baseball and English football. And it also works in ranking research scientists too.

Petersen and co may not actually settle any barstool brow-creasers with this paper but they've clearly had some fun in trying.

Ref: arxiv.org/abs/1003.0134: Detrending Career Statistics In Professional Baseball: Accounting For The Steroids Era And Beyond

The first detailed measurements of flapping wings bending in flight should help aerodynamicists build more efficient bird-like flyers

Flap your arms for a while and you'll soon notice that the constant cycle of acceleration and deceleration requires and even wastes huge amounts of energy. And yet for birds, wing flapping is a highly efficient means of propulsion. A questions that still puzzles aerodynamicists is how birds are able to minimise the energy costs involved in flight while generating useful aerodynamic forces.

Engineers have long realised that the elasticity of a flapping wing is part of the answer but have little more than hand-waving arguments to explain why. The thinking is that the wing stores elastic potential energy as it bends and later releases it in a favourable part of the flapping cycle. But the absence of good experimental evidence to quantify this process means that the understanding is still sketchy.

Until today. Benjamin Thiria and Ramiro Godoy-Diana at Université Denis Diderot in Paris built a self-propelled flapping wing and studied the forces at work as it moves through the air and how this deforms the wing, which is attached to a "merry-go-round" so it goes round in circles as it flaps (see above).

The results provide an important insight into the mechanics of flapping flight. They say: "the effect of wing flexibility on the efficiency of flapping flyers can be thought of as a two-step process: a solid mechanics problem, where the balance between inertial and elastic forces determines the instantaneous shape of the flexible wings, followed by a fluid dynamics problem, where the boundary conditions set by the previous step govern the distribution of aerodynamic forces."

Consequently, the ratio of the inertial forces deforming the wing to the elastic forces restoring its shape is an important structural parameter. They call this ratio the elasto-inertial number.

Understanding this ratio, which may change in different parts of a wing, could turn out to be a crucial part of the puzzle for engineers attempting to design and build better flapping flyers: the take home point is that the flexibility of the wings is important.

It also has important implications for the efficiency of flight. Thiria and Godoy-Diana say: "Our measurements show that the elastic nature of the wings can lead not only to a substantial reduction of the consumed power, but also to an increment of the propulsive force." Which finally confirms the engineers' suspicions about the storage and release of elastic energy.

Ref: arxiv.org/abs/1002.4890: Bending to fly

A newfound ability to model the complex feedback loops that control plant clocks could have important implications for computing.

One of the limitations of conventional thinking in computation is that computable functions proceed in a sequential manner, one independent step after another. When computer scientists talk of parallelism, they usually mean carrying out more than one of these independent linear computations at the same time.

In the biological world, things are more complex because steps in biological computations may not be independent. Take, for example, the circadian rhythm in plants, the 24 hour cycle of biochemical processes that govern behaviour. The cycle has various important features such as the ability to synchronise with an external periodic light source and to continue to oscillate even in the absence of variations in illumination.

Biochemists have long known that these cycles are the result of various biochemical feedback loops in which the transcription of genes is boosted and damped.

Each feedback loop is part of a hugely complex biochemical network and is affected by many factors simultaneously, not least of which is the presence or absence of light and the state of the network with which it is most closely linked, which themselves may be interdependent feedback loops.

Of course, plant clocks have been studied for hundreds of years and a huge amount is known about how they work, particularly about Arabidopsis thaliana, a small flowering plant that is the standard object of study for plant biologists.

The trouble is that nobody has been able to accurately model the behaviour of these rhythms from first principles.

As luck would have it, just such a system has been waiting in the wings. Process algebra is a form of computation that can handle multiple simultaneous interdependent steps and this makes it perfect for modelling these tricky biochemical networks and the feedback loops that drive them.

The trouble is putting it into practice: process algebra is not an easy toy to play with.

Today, however, Ozgur Akman at the University of Edinburgh and a few pals outline how they've used this approach to model the circadian rhythm of the green alga Ostreococcus tauri, which has the honour of possessing the simplest planet clock yet discovered.

Akman and co created a model of the various feedback loops in the Ostreococcus clock using a process algebra known as Bio-PEPA. This allowed them to explore how the clock responds to factors such as changes in illumination patterns and to genetic mutations, a factor that effects how the clock might change over evolutionary time scales.

The team has even been able to use the model to make some predictions about the behaviour of the real Ostreococcus populations. "We predict that the qualitative behaviour of the free-running clock will be dependent on the size of the cellular population; while damped oscillations will be observed in large populations," say Akman and co.

That's interesting and important science and not just because these predictions should be straightforward to test or because of the important insights they give into plant biology.

The real importance is more subtle. An often overlooked property of process algebra is that it is not equivalent to a standard sequential Turing machine. Because process algebra encompasses concurrent processes and the communication between them, it is subtly different and potentially more powerful.

In exactly what ways isn't yet clear, however. The study of process algebra is relatively recent. One important question asks what can be done with process algebra that cannot be done with a Turing machine. One answer may be related to the efficiency of calculations.

Several orders of magnitude separate the efficiency of biological computation from what is possible with silicon. If that difference turns out to be the result of process algebra, then the study and manipulation of networks such as the Ostreococcus clock, may turn out to be the trigger for a new generation of super-efficient computing.

Ref:arxiv.org/abs/1002.4661: Complementary Approaches To Understanding The Plant Circadian Clock

The best of the rest from Physics arXiv this week:

Towards Graphene Nanoribbon-based Electronics

"Pretty Good" Private Queries Based On A Quantum Key Distribution Protocol

Mechanisms Of Viral Capsid Assembly Around A Polymer

Photostop: Production Of Zero-Velocity Molecules By Photodissociation In A Molecular Beam

An Invisible Quantum Tripwire

Can humans distinguish between sequences of real and randomly generated financial data? Scientist have developed a new test to find out.

Various economists argue that the efficiency of a market ought to be clearly evident in the returns it produces. They say that the more efficient it is, the more random its returns will be and a perfect market should be completely random.

That would appear to give the lie to the widespread belief that humans are unable to tell the difference between financial market returns and, say, a sequence of coin tosses. A number of experiments seem to back up this belief, showing for example that humans studying randomly generated data very quickly identify 'trends' in the data and develop hypotheses about them.

To find out whether humans can reliably distinguish between real and random market data, Jasmina Hasanhodzic at AlphaSimplex, an investment strategy company in Cambridge, Mass, Andrew Lo at MIT's Sloan School of Management, who founded AlphaSimplex and Emanuele Viola at NorthEastern University, have devised a simple experiment.

They have created a computer game in which a player is shown two time-series of data. One is real data from a financial market such as the US Dollar Index, or the spot price of Gold. The other is the same data randomly rearranged. The player has to guess which is the real series and is immediately told whether the guess is right or wrong.

Hasanhodzic and co call this a financial Turing test and anybody can sign up and take the test on their website.

In their experiment, 78 people took the test, with each contest lasting two weeks.

The results show that that humans are actually rather good at this game. After a few guesses most people quickly learn how to distinguish the real data from the random stuff. "The results provide overwhelming statistical evidence (p-values of at most 0.5%) that humans can quickly learn to distinguish actual price series from randomly generated ones," say Hasanhodzic and co.

It's not hard to see why. In feedback sessions, the players say that the real data was smoother than the randomised data or vice versa and that these patterns were easy to spot after a few goes.

That's an intriguing result but what to make of it? First let's look at what the study does not address. The study does not address any notion of predictability. A truly random market is entirely unpredictable, by definition. There is good evidence that real markets are not random and that their behaviour can be described by fairly simple principles. That doesn't make them predictable, however (although we have looked at evidence that certain kinds of bubble markets might be predictable here, here and here).

Neither does the study address whether humans are good at making predictions; whether they are better at predicting the future performance of a market than, say, a coin toss.

So what does it show? It shows that humans are good at pattern recognition. Nothing more and nothing less.

Ref: arxiv.org/abs/1002.4592: Is It Real, or Is It Randomized?: A Financial Turing Test

One way to steal data is to embed it in a voice call over the internet. Now network engineers are learning how to spot such attacks.

ISo-called Voice of Internet Protocol or VoIP makes for cheaper and more convenient calling but it also opens an important issue of security. Various people have described how it might be possible to to hi-jack VoIP signals to send confidential information.

These services break down voice signals into digital packets and send it over the internet, in exactly the same way as email or web traffic. Such a malicious attack might involve scanning your computer for interesting tidbits and sending them to a third party each time you make a VoIP call by modifying these packets in some way.

But how easy is it to embed data in a VoIP stream without being noticed? In theory, that ought to be easy to answer. After all, the protocols used to send information are well known. Surely it should be easy to see whether extra data has been added.

Actually no. One way to embed data is to change the order in which packets are sent according to a code. A malicious receiver can retrieve the embedded data by monitoring and re-ordering the packets without the listener being any the wiser. A simple measure of data rate would not spot such a scheme.

Then there is the technique of deliberately delaying certain packets filled with secret information, a technique called Lost Audio Packet Steganography or LACK. Delays are common on the internet and receivers deal with them by simply ignoring late arrivals. However, a suitably equipped receiver could extract any confidential information hidden in these delayed packets.

The only way to spot such attacks is to compare the traffic to ordinary signals and to see how it differs. But what does ordinary traffic look like?

Today, Wojciech Mazurczyk and buddies at the Warsaw University of Technology in Poland publish their study of the characteristics 100 ordinary VoIP calls made between Warsaw and Cambridge in the UK, a distance of some 1800 km . Their idea is characterise ordinary call data so that steganographic attacks can be easily spotted.

Their study throws up some surprises. It turns out that packets are never normally re-ordered in a way that could be used to hide data. So this kind of attack would be easy to spot.

However, data packets routinely get lost so distinguishing these from those that are deliberately delayed by a malicious attacker is hard.

So while VoIP might be cheaper and easier than other forms of voice calling, it may also be less secure. Mazurczyk and co say that more data is needed to study the natural charactersitics of VoIp over a wider range of conditions. But for the moment, it looks as if LACK is a real threat.

Ref: arxiv.org/abs/1002.4303: What are suspicious VoIP delays?