scholarly journals QUANTUM LIMITATIONS ON THE STORAGE AND TRANSMISSION OF INFORMATION

1990 ◽  
Vol 01 (04) ◽  
pp. 355-422 ◽  
Author(s):  
JACOB D. BEKENSTEIN ◽  
MARCELO SCHIFFER
Keyword(s):  
Information Transfer ◽  
Occupation Number ◽  
Information Storage ◽  
Analytic Approximation ◽  
One Dimensional ◽  
Analytic Proof ◽  
Capacity Theory ◽  
Transmission Of Information ◽  
Quantum Limits ◽  
Natural Channel

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 described here. 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 considered. Finally, it is shown that acceleration of a receiver acts to block information transfer.

The Use of Mesoporous Systems for Preparation of One-Dimensional Ordered Magnetic Nanowires

2003 ◽  
Vol 788 ◽  
Author(s):  
Andrei A. Eliseev ◽  
Kirill S. Napolskii ◽  
Dmitry F. Gorozhankin ◽  
Alexei V. Lukashin ◽  
Yuri D. Tretyakov ◽  
...  
Keyword(s):  
Mesoporous Silica ◽  
Data Storage ◽  
Magnetic Measurements ◽  
Decomposition Temperature ◽  
Silica Matrix ◽  
Information Storage ◽  
Molar Ratio ◽  
Magnetic Nanowires ◽  
One Dimensional ◽  
Novel Variant

ABSTRACTHere we report the synthesis and investigation of iron and iron oxide nanowire arrays using mesoporous silica as a host material. In the present work a novel variant of synthesis of ordered magnetic nanowires in the mesoporous silica matrix was suggested. The method is based on the incorporation of a hydrophobic metal compound into the hydrophobic part of silica-surfactant composite. The amount of iron intercalated into the mesoporous matrix was measured by chemical analysis. In all samples it corresponds well to with the molar ratio SiO2: Fe = 9:1. To provide crystallinity of nanowires additional thermal treatment was performed. Thus prepared nanocomposites were characterized by TEM, ED, SAXS, SANS, BET and magnetic measurements. The anisotropy parameters of nanowires were determined using two non-correlated methods: temperature dependence of magnetic susceptibility and small angle polarized neutron scattering. It was found that the particle length increases with the increasing of the decomposition temperature of the metal complex. Obviously it deals with crystallization and growth of metal particles inside the pores at a constant diameter of a single particle. For iron containing sample annealed at 375 °C (form factor of nanowire is about 40), the coercive force at room temperature was found to be 145 Oe at saturation magnetization of 1.2 emu/g, which is not far from modern information storage. It was shown that particles shape and size are in good agreement with that of the pores. Particles are uniform and well ordered in the silica matrix. Thus, the suggested method leads to one-dimensional anisotropic nanostructures which could find an application as high-density data storage magnetic media.

scholarly journals Solvent viscosity facilitates replication and ribozyme catalysis from an RNA duplex in a model prebiotic process

2019 ◽  
Vol 47 (13) ◽  
pp. 6569-6577 ◽  
Author(s):  
Christine He ◽  
Adriana Lozoya-Colinas ◽  
Isaac Gállego ◽  
Martha A Grover ◽  
Nicholas V Hud
Keyword(s):  
Information Transfer ◽  
Rna World ◽  
Hammerhead Ribozyme ◽  
Information Storage ◽  
Additional Challenge ◽  
The Origin Of Life ◽  
World Hypothesis ◽  
Synthesis Reactions ◽  
Rna World Hypothesis ◽  
Single Sequence

Abstract The RNA World hypothesis posits that RNA was once responsible for genetic information storage and catalysis. However, a prebiotic mechanism has yet to be reported for the replication of duplex RNA that could have operated before the emergence of polymerase ribozymes. Previously, we showed that a viscous solvent enables information transfer from one strand of long RNA duplex templates, overcoming ‘the strand inhibition problem'. Here, we demonstrate that the same approach allows simultaneous information transfer from both strands of long duplex templates. An additional challenge for the RNA World is that structured RNAs (like those with catalytic activity) function poorly as templates in model prebiotic RNA synthesis reactions, raising the question of how a single sequence could serve as both a catalyst and as a replication template. Here, we show that a viscous solvent also facilitates the transition of a newly synthesized hammerhead ribozyme sequence from its inactive, duplex state to its active, folded state. These results demonstrate how fluctuating environmental conditions can allow a ribozyme sequence to alternate between acting as a template for replication and functioning as a catalyst, and illustrate the potential for temporally changing environments to enable molecular processes necessary for the origin of life.

scholarly journals Transitions in brain-network level information processing dynamics are driven by alterations in neural gain

2019 ◽  
Author(s):  
Mike Li ◽  
Yinuo Han ◽  
Matthew J. Aburn ◽  
Michael Breakspear ◽  
Russell A. Poldrack ◽  
...  
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Large Scale ◽  
Functional Integration ◽  
Brain Network ◽  
Information Storage ◽  
Transfer Entropy ◽  
Arousal System ◽  
Neural Gain ◽  
The Brain

AbstractA key component of the flexibility and complexity of the brain is its ability to dynamically adapt its functional network structure between integrated and segregated brain states depending on the demands of different cognitive tasks. Integrated states are prevalent when performing tasks of high complexity, such as maintaining items in working memory, consistent with models of a global workspace architecture. Recent work has suggested that the balance between integration and segregation is under the control of ascending neuromodulatory systems, such as the noradrenergic system. In a previous large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating neural gain led to a ‘critical’ transition in phase synchrony that was associated with a shift from segregated to integrated topology, thus confirming our original prediction. In this study, we advance these results by demonstrating that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing. Specifically, the dynamics of the subcritical (segregated) regime are dominated by information storage, whereas the supercritical (integrated) regime is associated with increased information transfer (measured via transfer entropy). Operating near to the critical regime with respect to modulating neural gain would thus appear to provide computational advantages, offering flexibility in the information processing that can be performed with only subtle changes in gain control. Our results thus link studies of whole-brain network topology and the ascending arousal system with information processing dynamics, and suggest that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain.Author summaryHigher brain function relies on a dynamic balance between functional integration and segregation. Previous work has shown that this balance is mediated in part by alterations in neural gain, which are thought to relate to projections from ascending neuromodulatory nuclei, such as the locus coeruleus. Here, we extend this work by demonstrating that the modulation of neural gain alters the information processing dynamics of the neural components of a biophysical neural model. Specifically, we find that low levels of neural gain are characterized by high Active Information Storage, whereas higher levels of neural gain are associated with an increase in inter-regional Transfer Entropy. Our results suggest that the modulation of neural gain via the ascending arousal system may fundamentally alter the information processing mode of the brain, which in turn has important implications for understanding the biophysical basis of cognition.

scholarly journals Encoding Temporal Regularities and Information Copying in Hippocampal Circuits

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Terri P. Roberts ◽  
Felix B. Kern ◽  
Chrisantha Fernando ◽  
Eörs Szathmáry ◽  
Phil Husbands ◽  
...  
Keyword(s):  
Information Transfer ◽  
Electrode Array ◽  
Information Storage ◽  
Cellular Mechanisms ◽  
Motor Processing ◽  
Fundamental Properties ◽  
Temporal Relationships ◽  
Array Technology ◽  
Critical Requirement

AbstractDiscriminating, extracting and encoding temporal regularities is a critical requirement in the brain, relevant to sensory-motor processing and learning. However, the cellular mechanisms responsible remain enigmatic; for example, whether such abilities require specific, elaborately organized neural networks or arise from more fundamental, inherent properties of neurons. Here, using multi-electrode array technology, and focusing on interval learning, we demonstrate that sparse reconstituted rat hippocampal neural circuits are intrinsically capable of encoding and storing sub-second-order time intervals for over an hour timescale, represented in changes in the spatial-temporal architecture of firing relationships among populations of neurons. This learning is accompanied by increases in mutual information and transfer entropy, formal measures related to information storage and flow. Moreover, temporal relationships derived from previously trained circuits can act as templates for copying intervals into untrained networks, suggesting the possibility of circuit-to-circuit information transfer. Our findings illustrate that dynamic encoding and stable copying of temporal relationships are fundamental properties of simple in vitro networks, with general significance for understanding elemental principles of information processing, storage and replication.

Stochastic chromatin packing of 3D mitotic chromosomes revealed by coherent X-rays

2021 ◽  
Vol 118 (46) ◽  
pp. e2109921118
Author(s):  
Daeho Sung ◽  
Chan Lim ◽  
Masatoshi Takagi ◽  
Chulho Jung ◽  
Heemin Lee ◽  
...  
Keyword(s):  
Information Transfer ◽  
3D Structure ◽  
Three Dimensional ◽  
Information Storage ◽  
Atomic Scale ◽  
Scaling Analysis ◽  
X Rays ◽  
Mitotic Chromosomes ◽  
Metaphase Chromosomes ◽  
Chromatin Packing

DNA molecules are atomic-scale information storage molecules that promote reliable information transfer via fault-free repetitions of replications and transcriptions. Remarkable accuracy of compacting a few-meters-long DNA into a micrometer-scale object, and the reverse, makes the chromosome one of the most intriguing structures from both physical and biological viewpoints. However, its three-dimensional (3D) structure remains elusive with challenges in observing native structures of specimens at tens-of-nanometers resolution. Here, using cryogenic coherent X-ray diffraction imaging, we succeeded in obtaining nanoscale 3D structures of metaphase chromosomes that exhibited a random distribution of electron density without characteristics of high-order folding structures. Scaling analysis of the chromosomes, compared with a model structure having the same density profile as the experimental results, has discovered the fractal nature of density distributions. Quantitative 3D density maps, corroborated by molecular dynamics simulations, reveal that internal structures of chromosomes conform to diffusion-limited aggregation behavior, which indicates that 3D chromatin packing occurs via stochastic processes.

Information Dynamics in Small-World Boolean Networks

2011 ◽  
Vol 17 (4) ◽  
pp. 293-314 ◽  
Author(s):  
Joseph T. Lizier ◽  
Siddharth Pritam ◽  
Mikhail Prokopenko
Keyword(s):  
Information Transfer ◽  
Small World ◽  
Boolean Networks ◽  
Information Storage ◽  
Systems Science ◽  
Small World Networks ◽  
Information Dynamics ◽  
Quantitative Evidence ◽  
Naturally Occurring ◽  
Complex Systems Science

Small-world networks have been one of the most influential concepts in complex systems science, partly due to their prevalence in naturally occurring networks. It is often suggested that this prevalence is due to an inherent capability to store and transfer information efficiently. We perform an ensemble investigation of the computational capabilities of small-world networks as compared to ordered and random topologies. To generate dynamic behavior for this experiment, we imbue the nodes in these networks with random Boolean functions. We find that the ordered phase of the dynamics (low activity in dynamics) and topologies with low randomness are dominated by information storage, while the chaotic phase (high activity in dynamics) and topologies with high randomness are dominated by information transfer. Information storage and information transfer are somewhat balanced (crossed over) near the small-world regime, providing quantitative evidence that small-world networks do indeed have a propensity to combine comparably large information storage and transfer capacity.

STORAGE OF INFORMATION IN ONE-DIMENSIONAL PIECEWISE-CONTINUOUS MAPS

2000 ◽  
Vol 10 (05) ◽  
pp. 1127-1137 ◽  
Author(s):  
SAMIR ROUABHI
Keyword(s):  
Neural Network ◽  
Information Processing ◽  
Associative Memory ◽  
Feedback Loop ◽  
Information Storage ◽  
Control Of Chaos ◽  
One Dimensional ◽  
Continuous Maps ◽  
Piecewise Continuous ◽  
Stored Information

A method of information storage via unstable cycles of one-dimensional piecewise-continuous maps is presented. This method consists in associating a well-defined cycle of a map with a given information to be stored. A neural network is proposed to emulate the information processing. A procedure of extracting the stored information using control of chaos by feedback loop is proposed. The retrieval of the information stored is done by control of chaos. An associative memory property is obtained.

scholarly journals Metallization-Induced Quantum Limits of Contact Resistance in Graphene Nanoribbons with One-Dimensional Contacts

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3670
Author(s):  
Mirko Poljak ◽  
Mislav Matić
Keyword(s):  
Integrated Circuits ◽  
Contact Resistance ◽  
Transport Properties ◽  
Graphene Nanoribbons ◽  
Wide Band ◽  
Quantum Limit ◽  
Metal Contacts ◽  
Worst Case ◽  
One Dimensional ◽  
Quantum Limits

Graphene has attracted a lot of interest as a potential replacement for silicon in future integrated circuits due to its remarkable electronic and transport properties. In order to meet technology requirements for an acceptable bandgap, graphene needs to be patterned into graphene nanoribbons (GNRs), while one-dimensional (1D) edge metal contacts (MCs) are needed to allow for the encapsulation and preservation of the transport properties. While the properties of GNRs with ideal contacts have been studied extensively, little is known about the electronic and transport properties of GNRs with 1D edge MCs, including contact resistance (RC), which is one of the key device parameters. In this work, we employ atomistic quantum transport simulations of GNRs with MCs modeled with the wide-band limit (WBL) approach to explore their metallization effects and contact resistance. By studying density of states (DOS), transmission and conductance, we find that metallization decreases transmission and conductance, and either enlarges or diminishes the transport gap depending on GNR dimensions. We calculate the intrinsic quantum limit of width-normalized RC and find that the limit depends on GNR dimensions, decreasing with width downscaling to ~3 Ω∙µm in 0.4 nm-wide GNRs, and increasing with length downscaling up to ~30 Ω∙µm in 5 nm-long GNRs. The worst-case total RC is only ~40 Ω∙µm, which demonstrates that there is room for RC improvement in comparison to the published experimental data, and that GNRs present a promising channel material for future extremely-scaled electronic nanodevices.

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