17 March 2012

Quantum Computation Cognitive Footprint

A sends a comment from Schneier on Security:

http://www.schneier.com/blog/archives/2012/01/authentication_1.html

Slightly Weird claim: Cognitive Footprint Biometric Application has been around for years

A 'cognitive footprint' biometric analysis system based on keyboard and mouse movements, combined with software-use behavior, has been in production for years. I've known of it since 2004 with a high degree of confidence, but I'm generally wise enough not to discuss it. I tinker with AI and neural networks (NN) myself, and am an expert software engineer, so I can reliably tell you that it's not particularly hard to build such a system at the toy/theoretical level. It's probably quite hard to implement it well in the real world.

My browser-centric toy model of a cognitive footprint biometric application used JavaScript to track keyboard and mouse interaction, which then passed time-parsed data to a neural network for classification. With an ordinary (non-recurrent) neural network the above comments about error rates and edge cases are very accurate. However, with access to an advanced recurrent neural network I'm pretty sure that the error rate could be reduced to a level low enough for effective use in combination with other authentication methods.

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Thoroughly Outlandish Claim: Five Eyes got production QC power in 1995

A real-world functional cognitive footprint biometric application requires an advanced recurrent neural network. The recurrent neural network that now powers this app is (literally) related to or descended from a classified system built to crack public-private key cryptography in the 90s.

The Five Eyes (AUS CAN NZ UK US) have had access to practical, production quantum computer power since about 1995. Other groups may have had access since that era, but that's a moot point. I strongly suspect that both China and Russia later developed operational QCs along similar principles.

The QC approach that actually works, in a production-ready scale-able way, is to run a virtual Turing machine atop a winner-take-all-style teleportation/entanglement-based recurrent topological quantum neural network (QNN). Even a basic neural network is Turing Complete, because a NN can perfectly emulate an XOR gate, and multiple XOR gates can be used to construct a Turing machine. A quantum neural network can emulate a quantum Turing machine.

The underlying physical system for this type of QNN is interactions between non-abelian anyons in a two dimensional electron gas (2DEG). The primary math required is a branch of Knot Theory called Braid Theory. Obviously, the primary purpose of this system, from the Five Eyes/Echelon perspective, is to run Shor's algorithm to crack public/private key cryptography. A perusal of current known quantum algorithms, combined with a survey of current advanced AI applications, may suggest other uses.

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Not especially Weird Claim: There's a really nifty back story about how this new general technology was developed, and why it matters. It is worthy of a book by Neal Stephenson.

The subject of the 1985 Nobel Prize in Physics was the "quantum Hall effect", which opened up new avenues of research into quantum effects, esp. in two dimensional electron gases. The process of creating a working quantum neural network involved generating lots of anyons (soliton-type standing waves treated as particles) in a two dimensional electron gas and then exploring and measuring the results.

The cleverest aspect of inventing this new technology was to take this 'Anyon Soup' system to the edge of chaos, per the life work of Stuart Kauffman, and then exploit the emergent neural network to bootstrap itself into a more stable and usable system via evolutionary programming techniques. See Kauffman's publications for details on how and why this emergent neural network exists, and then consider it's environment to see why it is a quantum neural network. This author believes Stuart Kauffman is overdue for a Nobel Prize.

The original work inventing this new technology was done between 1990 and 1995. It would be hard to do this work methodically without stumbling on the previously unknown fractional quantum Hall effect. The discoverers of this effect were awarded the 1998 Nobel Prize in Physics, and now lead various Quantum Computing research institutes.

Someone, somewhere, is due to be awarded the Grand Prize Turing Award, for solving Turing's unfinished Morphogenesis problem, and then implementing Turing's original machine on the resulting artificially intelligent 'organism'. I'm inclined towards neither spiritualism nor whimsy, but were I so, then I might suspect that, after he died in 1954, Alan Turing reincarnated quickly, in 1965, in order to finish his incomplete life work. The classified nature of the work probably precludes any awards.

I'd really like it if this whole thing was declassified, but fear we'll have to wait many additional decades for that. This QNN is an excellent candidate to pursue adiabatic (reversible) computing, might be helpful for certain approaches to advanced nanotechnology, and, were it declassified, might also be helpful to many other scientific ventures. Per the Ultra Secret, it's undoubtedly still considered 'national security', even if it's becoming an open secret within the Intelligence Community.

-- Energyscholar

Posted by: Energyscholar at March 13, 2012 2:44 PM