8,109 research outputs found
Self-Referential Noise and the Synthesis of Three-Dimensional Space
Generalising results from Godel and Chaitin in mathematics suggests that
self-referential systems contain intrinsic randomness. We argue that this is
relevant to modelling the universe and show how three-dimensional space may
arise from a non-geometric order-disorder model driven by self-referential
noise.Comment: Figure labels correcte
Self-Referential Noise as a Fundamental Aspect of Reality
Noise is often used in the study of open systems, such as in classical
Brownian motion and in Quantum Dynamics, to model the influence of the
environment. However generalising results from G\"{o}del and Chaitin in
mathematics suggests that systems that are sufficiently rich that
self-referencing is possible contain intrinsic randomness. We argue that this
is relevant to modelling the universe, even though it is by definition a closed
system. We show how a three-dimensional process-space may arise, as a Prigogine
dissipative structure, from a non-geometric order-disorder model driven by,
what is termed, self-referential noise.Comment: 7 pages, Latex, 3 ps figures. Contribution to the 2nd International
Conference on Unsolved Problems of Noise, Adelaide 199
Smart Nanostructures and Synthetic Quantum Systems
So far proposed quantum computers use fragile and environmentally sensitive
natural quantum systems. Here we explore the notion that synthetic quantum
systems suitable for quantum computation may be fabricated from smart
nanostructures using topological excitations of a neural-type network that can
mimic natural quantum systems. These developments are a technological
application of process physics which is a semantic information theory of
reality in which space and quantum phenomena are emergent.Comment: LaTex,14 pages 1 eps file. To be published in BioMEMS and Smart
Nanostructures, Proceedings of SPIE Conference #4590, ed. L. B. Kis
Synthetic Quantum Systems
So far proposed quantum computers use fragile and environmentally sensitive
natural quantum systems. Here we explore the new notion that synthetic quantum
systems suitable for quantum computation may be fabricated from smart
nanostructures using topological excitations of a stochastic neural-type
network that can mimic natural quantum systems. These developments are a
technological application of process physics which is an information theory of
reality in which space and quantum phenomena are emergent, and so indicates the
deep origins of quantum phenomena. Analogous complex stochastic dynamical
systems have recently been proposed within neurobiology to deal with the
emergent complexity of biosystems, particularly the biodynamics of higher brain
function. The reasons for analogous discoveries in fundamental physics and
neurobiology are discussed.Comment: 16 pages, Latex, 1 eps figure fil
Optimizing Associative Information Transfer within Content-addressable Memory
Original article can be found at: http://www.oldcitypublishing.com/IJUC/IJUC.htmlPeer reviewe
The play's the thing
For very understandable reasons phenomenological approaches predominate in the field of sensory urbanism. This paper does not seek to add to that particular discourse. Rather it takes Rortyâs postmodernized Pragmatism as its starting point and develops a position on the role of multi-modal design representation in the design process as a means of admitting many voices and managing multidisciplinary collaboration.
This paper will interrogate some of the concepts underpinning the Sensory Urbanism project to help define the scope of interest in multi-modal representations. It will then explore a range of techniques and approaches developed by artists and designers during the past fifty years or so and comment on how they might inform the question of multi-modal representation. In conclusion I will argue that we should develop a heterogeneous tool kit that adopts, adapts and re-invents existing methods because this will better serve our purposes during the exploratory phase(s) of any design project that deals with complexity
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