161,008 research outputs found
Quantum Limitations on the Storage and Transmission of Information
Information must take up space, must weigh, and its flux must be limited.
Quantum limits on communication and information storage leading to these
conclusions are here described. Quantum channel capacity theory is reviewed for
both steady state and burst communication. An analytic approximation is given
for the maximum signal information possible with occupation number signal
states as a function of mean signal energy. A theorem guaranteeing that these
states are optimal for communication is proved. A heuristic "proof" of the
linear bound on communication is given, followed by rigorous proofs for signals
with specified mean energy, and for signals with given energy budget. And
systems of many parallel quantum channels are shown to obey the linear bound
for a natural channel architecture. The time--energy uncertainty principle is
reformulated in information language by means of the linear bound. The quantum
bound on information storage capacity of quantum mechanical and quantum field
devices is reviewed. A simplified version of the analytic proof for the bound
is given for the latter case. Solitons as information caches are discussed, as
is information storage in one dimensional systems. The influence of signal
self--gravitation on communication is considerd. Finally, it is shown that
acceleration of a receiver acts to block information transfer.Comment: Published relatively inaccessible review on a perennially interesting
subject. Plain TeX, 47 pages, 5 jpg figures (not embedded
Quantum-mechanical communication theory
Optimum signal reception using quantum-mechanical communication theor
Roman roads: The hierarchical endosymbiosis of cognitive modules
Serial endosymbiosis theory provides a unifying paradigm for examining the interaction of cognitive modules at vastly different scales of biological, social, and cultural organization. A trivial but not unimportant model associates a dual information source with a broad class of cognitive processes, and punctuated phenomena akin to phase transitions in physical systems, and associated coevolutionary processes, emerge as consequences of the homology between information source uncertainty and free energy density. The dynamics, including patterns of punctuation similar to ecosystem resilience transitions, are large dominated by the availability of 'Roman roads' constituting channels for the transmission of information between modules
Optimum detection for extracting maximum information from symmetric qubit sets
We demonstrate a class of optimum detection strategies for extracting the
maximum information from sets of equiprobable real symmetric qubit states of a
single photon. These optimum strategies have been predicted by Sasaki et al.
[Phys. Rev. A{\bf 59}, 3325 (1999)]. The peculiar aspect is that the detections
with at least three outputs suffice for optimum extraction of information
regardless of the number of signal elements. The cases of ternary (or trine),
quinary, and septenary polarization signals are studied where a standard von
Neumann detection (a projection onto a binary orthogonal basis) fails to access
the maximum information. Our experiments demonstrate that it is possible with
present technologies to attain about 96% of the theoretical limit.Comment: 10 pages, 11 figures, to be submitted to Phys. Rev. A Converted to
REVTeX4 format, and a few other minor modifications according to the comments
from PRA referre
Information Processing, Computation and Cognition
Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both â although others disagree vehemently. Yet different cognitive scientists use âcomputationâ and âinformation processingâ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism and connectionism/computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debatesâ empirical aspects
Optimal measurement of visual motion across spatial and temporal scales
Sensory systems use limited resources to mediate the perception of a great
variety of objects and events. Here a normative framework is presented for
exploring how the problem of efficient allocation of resources can be solved in
visual perception. Starting with a basic property of every measurement,
captured by Gabor's uncertainty relation about the location and frequency
content of signals, prescriptions are developed for optimal allocation of
sensors for reliable perception of visual motion. This study reveals that a
large-scale characteristic of human vision (the spatiotemporal contrast
sensitivity function) is similar to the optimal prescription, and it suggests
that some previously puzzling phenomena of visual sensitivity, adaptation, and
perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and
Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional
and Intelligent Paradigms, Intelligent Systems Reference Library,
Springer-Verlag, Berli
On Fields with Finite Information Density
The existence of a natural ultraviolet cutoff at the Planck scale is widely
expected. In a previous Letter, it has been proposed to model this cutoff as an
information density bound by utilizing suitably generalized methods from the
mathematical theory of communication. Here, we prove the mathematical
conjectures that were made in this Letter.Comment: 31 pages, to appear in Phys.Rev.
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