🦋 When it comes to computation, biology is vastly more efficient than technology.
https://santafe.edu/news-center/news/astonishing-efficiency-life
https://santafe.edu/news-center/news/astonishing-efficiency-life
santafe.edu
The astonishing efficiency of life
<p>SFI researchers quantify the thermodynamic efficiency of a fundamental biological computation. </p>
The Conflict Between Complex Systems.pdf
109 KB
The Conflict Between Complex Systems and Reductionism
Frogs resolve computing issues
https://www.sciencedaily.com/releases/2015/10/151007111130.htm
https://www.sciencedaily.com/releases/2015/10/151007111130.htm
Complex Systems Studies
Frogs resolve computing issues https://www.sciencedaily.com/releases/2015/10/151007111130.htm
When male Japanese tree frogs sing at the same time, the females cannot differentiate between them in order to choose the best one. Therefore, the would-be suitors have come to an agreement and sing one by one. This natural lyrical desynchronisation has inspired the development of computational algorithms which can be used to design wireless systems and analyse social networks such as Facebook or Twitter.
#سمینارهای_هفتگی گروه سیستمهای پیچیده و علم شبکه دانشگاه شهید بهشتی
🔹دوشنبه، ۲۹ آبان ماه، ساعت ۴:۰۰ - کلاس۱ دانشکده فیزیک دانشگاه شهید بهشتی.
@carimi
🔹دوشنبه، ۲۹ آبان ماه، ساعت ۴:۰۰ - کلاس۱ دانشکده فیزیک دانشگاه شهید بهشتی.
@carimi
Machine learning meets complex networks via coalescent embedding in the hyperbolic space | Nature Communications
https://www.nature.com/articles/s41467-017-01825-5
https://www.nature.com/articles/s41467-017-01825-5
Nature
Machine learning meets complex networks via coalescent embedding in the hyperbolic space
Nature Communications - Mapping complex networks to underlying geometric spaces can help understand the structure of networked systems. Here the authors propose a class of machine learning...
Forwarded from انجمن علمی فیزیک دانشگاه اصفهان
سخنرانی دکتر اجتهادی
عضو هیئت علمی دانشگاه صنعتی شریف و رئیس انجمن فیزیک ایران
"از ذره تا ماده ی فعال"
سه شنبه 7آذر
ساعت14الی16
همایشگاه ابوریحان بیرونی
@uisaph
عضو هیئت علمی دانشگاه صنعتی شریف و رئیس انجمن فیزیک ایران
"از ذره تا ماده ی فعال"
سه شنبه 7آذر
ساعت14الی16
همایشگاه ابوریحان بیرونی
@uisaph
💠 Dan Dennett on meaning, information, patterns, and deep learning.
https://www.edge.org/conversation/daniel_c_dennett-a-difference-that-makes-a-difference
https://www.edge.org/conversation/daniel_c_dennett-a-difference-that-makes-a-difference
#سمینارهای_هفتگی گروه سیستمهای پیچیده و علم شبکه دانشگاه شهید بهشتی
🔹شنبه، ۴ آذرماه، ساعت ۴:۰۰ - کلاس۱ دانشکده فیزیک دانشگاه شهید بهشتی.
@carimi
🔹شنبه، ۴ آذرماه، ساعت ۴:۰۰ - کلاس۱ دانشکده فیزیک دانشگاه شهید بهشتی.
@carimi
🔖 Exponential or power law? How to select a stable distribution of probability in a physical system
Andrea Di Vita
🔗 https://arxiv.org/pdf/1711.07811
📌 ABSTRACT
A mapping of nonextensive statistical mechanics into Gibbs' statistical mechanics exists, which leads to a generalization of Einstein's formula for fluctuations. A unified treatment of stability of relaxed states in nonextensive statistical mechanics and Gibbs' statistical mechanics follows. The former and the latter are endowed with probability distribution of microstates ruled by power laws and Boltzmann exponentials respectively. We apply our treatment to the relaxed states described by a 1D nonlinear FokkerPlanck equation. If the latter is associated to the stochastic differential equation obtained in the continuous limit from a 1D, autonomous, discrete map affected by noise, then we may ascertain whether if a relaxed state follow a power law distribution (and with which exponent) by looking at both map dynamics and noise level, with no assumptions concerning the additive or multiplicative nature of the noise and with no numerical computation of the orbits. Results agree with the simulations of Sanchez et al. EPJ 143.1 (2007) 141-143 concerning relaxation to a Pareto-like distribution.
Andrea Di Vita
🔗 https://arxiv.org/pdf/1711.07811
📌 ABSTRACT
A mapping of nonextensive statistical mechanics into Gibbs' statistical mechanics exists, which leads to a generalization of Einstein's formula for fluctuations. A unified treatment of stability of relaxed states in nonextensive statistical mechanics and Gibbs' statistical mechanics follows. The former and the latter are endowed with probability distribution of microstates ruled by power laws and Boltzmann exponentials respectively. We apply our treatment to the relaxed states described by a 1D nonlinear FokkerPlanck equation. If the latter is associated to the stochastic differential equation obtained in the continuous limit from a 1D, autonomous, discrete map affected by noise, then we may ascertain whether if a relaxed state follow a power law distribution (and with which exponent) by looking at both map dynamics and noise level, with no assumptions concerning the additive or multiplicative nature of the noise and with no numerical computation of the orbits. Results agree with the simulations of Sanchez et al. EPJ 143.1 (2007) 141-143 concerning relaxation to a Pareto-like distribution.