در کافه فیزیک این هفته:

آغاز قرن ۲۱ام با یک انفجار همراه شده. برای مردم عادی، این انفجار در مورد انقلاب‌های فناوری است که از قرن ۱۹ میلادی شروع شده و توسعه آن، تاثیر به شدت محسوسی بر روی قوانین اقتصادی داشته است. با این وجود، برای دانشمندان، یکی از وجه‌های این انفجار، «انقلاب پیچیدگی» است. موضوعی که در همه حوزه‌های علمی مانند زیست‌شناسی و پزشکی مورد پژوهش و مطالعه قرار گرفته است. اکنون پرسشی مطرح می‌شود؛ نقش فیزیک به عنوان قدیمی‌ترین و ساده‌ترین علم چیست؟ آیا فیزیک نظری هم باید دچار تغییر شود؟

فیزیک نظری قرن ۲۰ام از دل انقلاب نسبیت و مکانیک کوانتومی به دنیا آمد و تماما در مورد سادگی و پیوستگی بود. ابزار اصلی آن حسابان (حساب دیفرانسیل و انتگرال) و تجلی نهایی آن نظریه میدان بود.

فیزیک نظری قرن ۲۱ام، از انقلاب آشوب بیرون آمده و درباره پیچیدگی است. ابزار اصلی آن کامپیوتر است و آخرین دستاورد آن هنوز مشخص نیست. ترمودینامیک، به عنوان یک بخش حیاتی فیزیک، در این جابه‌جایی نقش اساسی بازی خواهد کرد.


در كافه فيزيك اين هفته، با مرور تاریخ علم فیزیک و تحولات آن از زمان نیوتون، می‌خواهیم گریزی بزنیم به مفاهیمى چون آشوب، پیچیدگی و انتروپی و بیان کنیم که منظورمان از پیچیدگی چیست!

عباس کریمی، از گروه سیستم‌های پیچیده
sitpor.org/abbas

با كافه فيزيك همراه باشيد... ☕️ 😊
@sbu_physicscafe

#کافه_فیزیک هشتم

🗓 ۳شنبه ۲۳ آبان ١٣٩٦
🕰 ساعت ۱۱:۴۵

📍دانشكده فيزيك دانشگاه شهيد بهشتى، طبقه همكف.

صحبت در مورد "آشوب، پیچیدگی و بی‌نظمی"
عباس کریمی
http://sitpor.org/abbas

همراه هم خواهيم بود با كافه فيزيك! ☕️😊
@farzin23i
@sbu_physicscafe

🎞 Physical Applications of Stochastic Processes
IIT Madras Course , Prof. V. Balakrishnan

http://freevideolectures.com/Course/3702/Physical-Applications-of-Stochastic-Processes

🐘 Metabolism and power laws

https://www.johndcook.com/blog/2009/04/16/metabolism-and-power-laws/

Bigger animals have more cells than smaller animals. More cells means more cellular metabolism and so more heat produced. How does the amount of heat an animal produces vary with its size? We clearly expect it to go up with size, but does it increase in proportion to volume? Surface area? Something in between?

A first guess would be that metabolism (equivalently, heat produced) goes up in proportion to volume. If cells are all roughly the same size, then number of cells increases proportionately with volume. But heat is dissipated through the surface. Surface area increases in proportion to the square of length but volume increases in proportion to the cube of length. That means the ratio of surface area to volume decreases as overall size increases. The surface area to volume ratio for an elephant is much smaller than it is for a mouse.


If an elephant’s metabolism per unit volume were the same as that of a mouse, the elephant’s skin would burn up.


So metabolism cannot be proportional to volume. What about surface area? Here we get into variety and controversy. Many people assume metabolism is proportional to surface area based on the argument above. This idea was first proposed by Max Rubner in 1883. Others emphasize data that supports the theory that suggests metabolism is proportional to surface area.

In the 1930’s, Max Kleiber proposed that metabolism increases according to body mass raised to the power 3/4. (I’ve been a little sloppy here using body mass and volume interchangeably. Body mass is more accurate, though to first approximation animals have uniform density.) If metabolism were proportional to volume, the exponent would be 1. If it were proportional to surface area, the exponent would be 2/3. But Kleiber’s law says it’s somewhere in between, namely 3/4.

So why the exponent 3/4? There is a theoretical explanation called the #metabolic_scaling_theory proposed by #Geoffrey_West, Brian Enquist, and James Brown.


Metabolic scaling theory says that circulatory systems and other networks are fractal-like because this is the most efficient way to serve an animal’s physiological needs.


To quote Enquist:

Although living things occupy a three-dimensional space, their internal physiology and anatomy operate as if they were four-dimensional. … Fractal geometry has literally given life an added dimension.


The fractal theory would explain the power law exponent exponent 3/4 simply: it’s the ratio of the volume dimension to the fractal dimension. However, as I suggested earlier, this theory is controversial. Some biologists dispute Kleiber’s law. Others accept Kleiber’s law as an empirical observation but dispute the theoretical explanation of West, Enquist, and Brown.

To read more about metabolism and power laws, see chapter 17 of Complexity: A Guided Tour.

⛑ همراهان عزیز، برای کمک به مردم زلزله‌زده، راه‌های زیادی وجود داره. یکی از راحت‌ترین کارها واریز مبلغی به حساب کسایی هست که به این امور واقف هستن، مثلا جمعیت امام‌ علی(ع):

یکی دو هزار تومن پول زیادی نیست ولی قطره قطره جمع گردد...

شماره کارت شانزده رقمی:
۶۱۰۴۳۳۷۹۰۵۳۲۴۶۰۲
بانک ملت به نام جمعیت امداد دانشجویی امام علی (ع)
به حساب شماره ۵۳۲۵۰۴۳۸۷۷
درگاه پرداخت اینترنتی:
https://donate.sosapoverty.org/emdadresani


🆔 @imamalisociety

👌🏻 https://www.quantamagazine.org/the-beautiful-intelligence-of-bacteria-and-other-microbes-20171113/

😱 http://www.bbc.com/news/av/technology-41935721/why-these-faces-do-not-belong-to-real-people

Jaakko Lehtinen's interview on BBC is about the generative adversarial networks (GANs). This technique can generate photographs that look authentic to human observers. See for more information
http://research.nvidia.com/publication/2017-10_Progressive-Growing-of

📉 https://blogs.wsj.com/moneybeat/2017/11/03/can-fund-manager-bill-miller-use-earthquakes-to-predict-the-market/

🐘 گویا فیل‌ها کمتر از حد انتظار سرطان میگیرن:

https://www.wired.com/story/a-zombie-gene-protects-elephants-from-cancer/amp

💊 مدل‌سازی ریاضی داروی‌ ایدز:
https://sinews.siam.org/Details-Page/mathematically-modeling-hiv-drug-pharmacodynamics

شبیه‌سازی ۴۱ آونگ سه‌تایی که با شرایط اولیه تقریبا مشابهی رها می‌شوند ولی تحول متفاوتی دارند.
#آشوب #حساس_بودن_به_شرایط_اولیه

اسلایدهای «آشوب، پیچیدگی و انتروپی» در کافه فیزیک دانشگاه شهیدبهشتی

عباس کریمی
goo.gl/mFiZ1B

دانشکده مهندسی برق و کامپیوتر دانشگاه شهیدبهشتی

⭕️ https://en.wikipedia.org/wiki/Earthquake_prediction

⭕️ https://phys.org/news/2015-04-hard-earthquakes.html

⭕️ https://www.newscientist.com/article/dn20243-why-earthquakes-are-hard-to-predict/

The mesmerizing dynamics of sheep moving in these impressive drone footage

https://www.nengo.ai/summerschool 2018 Nengo Summer School

🔖 Beyond the thermodynamic limit: finite-size corrections to state interconversion rates

 Christopher T. Chubb, Marco Tomamichel, Kamil Korzekwa

🔗 http://arxiv.org/pdf/1711.01193.pdf

📌 ABSTRACT
Thermodynamics is traditionally constrained to the study of macroscopic systems whose energy fluctuations are negligible compared to their average energy. Here, we push beyond this thermodynamic limit by developing a mathematical framework to rigorously address the problem of thermodynamic transformations of finite-size systems. More formally, we analyse state interconversion under thermal operations and between arbitrary energy-incoherent states. We find precise relations between the optimal rate at which interconversion can take place and the desired infidelity of the final state when the system size is sufficiently large. These so-called second-order asymptotics provide a bridge between the extreme cases of single-shot thermodynamics and the asymptotic limit of infinitely large systems. We illustrate the utility of our results with several examples. We first show how thermodynamic cycles are affected by irreversibility due to finite-size effects. We then provide a precise expression for the gap between the distillable work and work of formation that opens away from the thermodynamic limit. Finally, we explain how the performance of a heat engine gets affected when one of the heat baths it operates between is finite. We find that while perfect work cannot generally be extracted at Carnot efficiency, there are conditions under which these finite-size effects vanish. In deriving our results we also clarify relations between different notions of approximate majorisation.

⚙ http://rsta.royalsocietypublishing.org/content/375/2109/20160338

🦋 When it comes to computation, biology is vastly more efficient than technology.

https://santafe.edu/news-center/news/astonishing-efficiency-life