Over a year in the making, the mega paper about continuous variable cluster states has finally been published on the archives. Titled, `Quantum Computing with Continous Variable Clusters‘, the paper is essentially a refinement of the idea I jointly proposed as a first year PhD student that it would be pretty cool to have an formulation of measurement based computation where each node was a quantum harmonic oscillator.

Though the idea seemed fairly second nature at the time (hey, just take qubits and replace them with optical modes!), the level of interest in it has been quite a pleasant surprise. The second follow-up paper aims at polishing the idea, and includes a lot of the details that was sort of brushed away during the initial proposal.

Quantum Computing with Continuous-Variable Clusters
Mile Gu, Christian Weedbrook, Nicolas C. Menicucci, Timothy C. Ralph, Peter van Loock

Continuous-variable cluster states offer a potentially promising method of implementing a quantum computer. This paper extends and further refines theoretical foundations and protocols for experimental implementation. We give a cluster-state implementation of the cubic phase gate through photon detection, which, together with homodyne detection, facilitates universal quantum computation. In addition, we characterize the offline squeezed resources required to generate an arbitrary graph state through passive linear optics. Most significantly, we prove that there are universal states for which the offline squeezing per mode does not increase with the size of the cluster. Simple representations of continuous-variable graph states are introduced to analyze graph state transformations under measurement and the existence of universal continuous-variable resource states.

Arxiv Link

Not the most exciting paper, but it has pretty pictures, including my first ever attenmpt at doing rendering wtih 3D studio max. That’s got to be worth something right? Also, I must thank Christian Weedbrook, who capacity in eliminating all of my typos as I busily hammered away at furniture here in Singapore is so remarkable that I’m convinced he secretly hides a quantum computer in his back yard!

Let us all share a moment of silence for the glorious free tail bat who bravely ventured into the depth of space. Our nameless hero clungly resolutely to the fuel tanks of the spaceshuttle Discovery, as it launched itself into orbit a mere 3 days ago. The fate of the bat so far, remains unknown, though NASA officially speculate that it was either frozen in the void of space or charred during the fiery lunch sequence. Whatever the case, all bats today can hang proud, knowing that one of their own has made the first steps towards space.

Oh, you can also read NASA’s much less inspiring statement on the matter.

So… there I was, the guinea pig of the new `research siminar’ series, where members of the Center for Quantum Technology presented their work in progress to public, in an effort to improve inter-department collaboration. Such political correctness, and so good on paper! Yet, you still want to give a talk with no major loopholes, and that not an easy task for you’re giving a 1 hour presentation on 4 days of work! Yet, somehow, I persevered (though my sleeping patterns did not), and all animations prepared. The notebook plugged in… the presentation ready to execute….

Yet, the $15,000 dollar presentation system laughed, and proceeded to perform the blue screen of death. So, yup, the entire session ended up being a whiteboard presentation. So, here’s the promised digital version, totally free and available online! The basic idea is thus:

Occam’s Razor states that the few assumptions an explanation makes, the more preferable and likely it true. When applied to modelling the output of a string of bits from a black box, one interpretation measures the simplicity of a given by the number of bits that the model must keep track of to execute. The fewer the number of bits, the sharper the razor. Crutchfield then showed that the sharpest of classical razors was the Epsilon machine… our question is, can Quantum mechanics sharpen that razor further? 

• Classical and Quantum Razors (321)

The talk first reviews how classical Occam’s Razor can be formalised through use of Epsilon Machines, and proceeds to outline some of my thoughts on how a Quantum version of Occam’s Razor could be superior. I hope to have a nice article on this stuff in a next few days. In the mean time, feel free to make sense of the presentation! There’s obviously lots of holes to fill, and in fact, Valerio pointed out one during the talk… see if you can find it too, but I promise that its already been addressed!

The Telegraph has reported interesting research that concludes many aspects of human intelligence peak at 22, and significantly decline by the age of 27.

The first age at which performance was significantly lower than the peak scores was 27 – for three tests of reasoning, speed of thought and spatial visualisation. Memory was shown to decline from the average age of 37. In the other tests, poorer results were shown by the age of 42.

Yup, Reasoning, Speed of Though… Visualisation… three of the most important skills for physicists, mathematicians and computer scientists! Looks like the colloquil belief held by Mathematicians that you do your best work before 30 is correct…

This is another one of those signs that something serious needs to be done about the education system. Most 22 year olds studying sciences are still… well studying. With the recent decline in accelerated education programs in many western universities, this doesn’t spell positives for the development of scentific breakthroughs.

And yelp! Looks like I don’t have much time left!

One of my current research projects have lead me to an rather interesting side problem. The basic idea is this:

If you’re given some random data streams from an unknown physical object… can you make a good argument to say that the object works on quantum principles? Obviously, there’s always a classical explanation, given that classical computers can simulate quantum computers, albeit inefficiently. However, could you call upon Occam’s Razor and argue that the simplest explanation is quantum?

To do this, one needs first a good mathematical formulation of Occam’s Razor for classical systems. It turns out that one good candidate are what’s called epsilon machines. So, I thought I’d write a quick research note of these objects:

• Epsilon Machines: Formalizing Occam’s Razor

Now… just need to find a meaningful way of quantizing it!

When Deep Blue beat Kasporav in Chess on 1997, it was a important for artificial intelligence. Often regarded as one of the perennial tests of intelligence, here is one of the milestones that seemed to indicate that computers are capable surpassing human intellect, a sign of true artificial intelligence… or was it?

Despite its successes in the abstract world of chess, ambitious attempts of machine intelligence in other areas of life has been met with dissappointment. Even the simple task of identifying a 3D object in the everyday world proved tricky… much less a computer capable of surviving all by itself in society. Terminator, unfortunately (or fortunately) is not something that is going to happen anytime soon.

Chess is arguably a game of tactics. To win, a player simply need to compute a dozen or so moves ahead. Such tasks, while tricky for most  humans, is ideal for computers. All a processor needs to do is systematically search through every decision tree, a task that a computer does every day when you attempt to find that elusive file on your hard drive. Thus, while the achievements of Deep Blue are spectacular, it was only a little  more than a glorified search on a decision tre, a far from any semblance of actual `intelligent thought’. There was no need more human qualities, such as intuition or creativity.

So, is there actually board game, whose success depends on such qualities?

The answer could quite well be Go (alternatively referred to as Weiqi).

In comparison to Chess, a blind search of decisions trees in Go could well be futile.  A typical Chess game involves around 30 possible moves each turn, while a typical Go game will involve about 300. Escalate this by the fact that there are typically many more turns in a game of Go, and you arrive with a probability space that is inconceivably larger.  Where’s a Chess game can end in about possible ways, a game of go has possible endings. That’s orders of magnitude higher. And if we’re talking about the number of paths that a game can possibly take… well, the number skyrockets to . 

If we could fit a computer capable of beating a Human player using brute search into a single atom, we would still need a computer with the mass of universes to beat a Human player is a game of Go.

With Go being such an complex game, a capable human player is certainly doing a lot more than just brute search. There is a lot of differences between playing Go and playing Chess. Chess is a game of absolutes, you win by capturing the enemy king, what is left is simply how you get there, and the majority of the thought is pattern recognition, and the capacity to compute all the possible ways to reach favorable patterns.

In contrast, though abilities are also crucial in Go, much more is involved. Victory is not defined by a capture, but by the accumulation of territory. There are simply too many possibilities to predict the outcome of any particular skirmish, and the key to identifying good moves comes from what professionals refer to as `intuition’. While in a professional Chess game, the loss of a single pawn can mean the difference between victory and defeat, Go is game of many battles, where the analogue a dead `pawn’ still has its role to play.

The outcome of a particular battle may be unfavourable locally, but its structure can potentially be exploited for profound implications hundreds of moves down the track. This effect is impossible to determine by brute force, and the king distinguishing between armature chess covert and a professional Go player is their capacity to judge how to steer a battles by `intuition’. Indeed, recent studies demonstrate that the right hemisphere of the brain activated far more in game of Go, which suggests that Go calls upon the intuitive, in addition the the computational aspects of the brain.

It is this human quality that has elevated Go into one of the perennial positions of Chinese culture amongst the educated class throughout history, while the Chinese variant of chess was often regarded as a game for the commoners. Indeed, in ancient China, Go is regarded as one of the four qualities of a gentlemen, on par with calligraphy, art, and poetry. And thus, for many computer scientists, the construction of a computer program capable of defeating professional Go players would be one of the great milestones in artificial intelligence.

So far, however, despite two decades of dedicated research, their target is still far from the horizon.

The current top computers, running a massive networks, has made a notable mark by defeating a Human professional 9-dan with a 7 stone handicap and a 1-dan with a 6 stone handicap [link]. While this may sound impressive, a 7 stone handicap is akin to playing a game of chess with your Queen and a Rook removed. Even capable 12 year olds are able to achieve this feat. Indeed, when I had professional Go training at the age of 10 with a professional 7 Dan, the handicap given was at around the 7 stone mark, where games were won and lost on a 50/50 basis.  And what of software that run on standard PCs? Well, I (who is nowhere near professional level) can beat the downloadable GnuGO easily while giving it a 9 stone handicap.

In order to program a capable Go AI, programmers need to mimic human intuition, and that makes the pursuit of an AI for Go worthy science. The methods gleamed in the development of a capable artificial Go player could well be applied to tasks considered intractable today.

There’s a long road ahead, and meanwhile, I invite anyone to give the game of Go a try. For many, such as my housemate and fellow researcher here at NUS (who was one of the finalists in youth Chess competitions), makes Chess look remarkably 1-dimensional. And besides, the Nobel Prize winner in physics, Anderson, holds a 1-Dan in Go… so you’re in good company!

References:

1. Wikipedia on Go - Where I got facts for this article from!
2. Sensei’s Go Library - A good online resource for go
3. Hikaru no Go - A great Anime that accurately portrays the world of Go.

The the jounral BMC bioinformatics, a recent paper was published… not about the intricate details of our genetic code, but rather how you shouldn’t use Microsft Excel to do any bioinformatics.

While I am sure the news is extremely useful, physicists can only dream of publishing papers by finding bugs in computer programs. Well, at least its not a randomly generated paper!

Walking for 11kms in the blistering heat of Singapore is quite a feat, but walking in it after a Monkey takes your drink bottle? Well, it least the process was amusing, and demonstrates how wild animals can quickly adapt to their changing enviroments. At the very least, monkeys have certainly discovered the art of opening bottles. So, here’s the mug shot.

If you ever see this Monkey, charge him with theft. Oh, and since he’s in Singapore, give have a $200 fine for littering while you’re at it.

• More Monkey Photos

Note: Visitor’s of Singapore beware. Monkeys are fully capable of opening your hotel fridge door and stealing all contents in the mini-bar. They’ve evolved.