Braid Matrices and Quantum Gates for Ising Anyons Topological Quantum Computation

We study various aspects of the topological quantum computation scheme based on the non-Abelian anyons corresponding to fractional quantum hall effect states at filling fraction 5/2 using the Temperley-Lieb recoupling theory. Unitary braiding matrices are obtained by a normalization of the degenerate ground states of a system of anyons, which is equivalent to a modification of the definition of the 3-vertices in the Temperley-Lieb recoupling theory as proposed by Kauffman and Lomonaco. With the braid matrices available, we discuss the problems of encoding of qubit states and construction of quantum gates from the elementary braiding operation matrices for the Ising anyons model. In the encoding scheme where 2 qubits are represented by 8 Ising anyons, we give an alternative proof of the no-entanglement theorem given by Bravyi and compare it to the case of Fibonacci anyons model. In the encoding scheme where 2 qubits are represented by 6 Ising anyons, we construct a set of quantum gates which is equivalent to the construction of Georgiev.Comment: 25 pages, 13 figure

CAM-BRAIN - The Genetic Programming of an Artificial Brain Which Grows/Evolves at Electronic Speeds in a Cellular Automata Machine

This paper reports on a project which aims to build (i.e. grow/evolve) an artificial brain by the year 2001. This artificial brain should initially contain thousands of interconnected artificial neural network modules, and be capable of controlling approximately 1000 "behaviors" in a "robot kitten". The name given to this research project is "CAM-Brain", because the neural networks (based on cellular automata) will be grown inside special hardware called Cellular Automata Machines (CAMs). Using a family of CAMs, each with its own processor to measure the performance quality or fitness of the evolved neural circuits, will allow the neural modules and their interconnections to be grown/evolved at electronic speeds. State of the art in CAM design is about 10 to the power 9 or 10 cells. Since a neural module of about 15 connected neurons can fit inside a cube of 100 cells on a side (1 million cells), a CAM which is specially adapted for CAM-Brain could contain thousands of interconnected m..

Genetic programming. GenNets, artificial nervous systems, artificial morphogenesis

Doctorat en Sciencesinfo:eu-repo/semantics/nonPublishe

Genetic programming: Artificial nervous systems artificial embryos and embryological electronics

This paper shows that it is possible to build hyper-complex systems such as an artificial nervous system or an artificial embryo, despite the fact that their interactions or dynamics are (probably) too complicated to be analyzed. Genetic Programming (GP) is “applied evolution”, i.e. using the Genetic Algorithm (GA) [GOLDBERG 1989] to evolve hyper-complex systems. Future work using the GP paradigm will probably lead to electronic circuits being “grown” in (and having their functionality tested in) special hardware called “Darwin Machines”, thus creating a new field called “Embryonics” (i.e. Embryological Electronics).SCOPUS: cp.kinfo:eu-repo/semantics/publishe

'COMPO' conceptual clustering with connectionist competitive learning

This paper introduces the idea that conceptual clustering can be performed using connectionist competitive learning. Competitive learning is used to detect clusters of objects and their corresponding (qualitative) descriptions. A genetic algorithm is employed to choose a subset of these descriptions such that the objects matching them form partitions over the population of objects concerned. Hierarchical classification trees are built by recursing the above two steps (competitive learning 'clustering' and genetic algorithm 'partitioning') over the objects matching the descriptions at each node.SCOPUS: cp.pinfo:eu-repo/semantics/publishe

CAM-BRAIN - The Evolutionary Engineering of a Billion Neuron Artificial Brain by 2001 which Grows/Evolves at Electronic Speeds inside a Cellular Automata Machine (CAM)

This paper describes an ambitious 8 year research project which aims to implement a cellular automata based artificial brain with a billion neurons by 2001, which grows/evolves at (nano-)electronic speeds inside a Cellular Automata Machine - ATR's so-called "CAM-Brain Project". The states of the cellular automata (CA) cells and the CA state transition rules can be stored cheaply in gigabytes of RAM. By using state of the art cellular automata machines, e.g. MIT's "CAM8" machine ($40,000, which can update 200 million CA cells a second) it will be technically feasible by early 1996 to evolve artificial nervous systems containing a hundred thousand neurons, and within a few years, a million neurons. By the end of the current research project, i.e. 2001, it should be possible using nano-scale electronics to grow/evolve artificial brains containing a billion neurons and upwards. This is our aim. 1. Introduction Following on from the abstract above, to understand how CAs can be used to grow/..

THE "CAM-BRAIN" PROJECT - The Evolutionary Engineering of a Billion Neuron Artificial Brain which Grows/Evolves at Electronic Speeds in a Cellular Automata Machine - Part 1: Fundamentals

This 2 part paper reports on the "CAM-Brain Project", which is an 8 year research project, beginning in 1993, at ATR labs in Kyoto, Japan, which intends to build/grow/evolve an artificial brain containing billions of artificial neurons. The essential idea behind CAM-Brain is to use cellular automata [Codd 1968] based neural networks which grow/evolve at electronic speeds inside cellular automata machines (CAMs) [Toffoli & Margolus 1987]. State of the art in these machines is MIT's "CAM8" ($40,000), which can update 200 million cellular automata (CA) cells per second [Toffoli & Margolus 1990]. Since the states of the CA cells can be stored cheaply in gigabytes of RAM, and given the updating speed, it becomes realistic to evolve millions of artificial neural circuits, thus revolutionizing the field of neural networks, and creating a new field, called "Brain Building". 1. Introduction As mentioned in the abstract, the "CAM-Brain Project" is an 8 year research project at ATR labs in Kyoto,..