💡 "Bridging Data Science and Dynamical Systems Theory" (by Tyrus Berry, Dimitrios Giannakis, and John Harlim; in Notices of the #amermathsoc):

https://t.co/5JSi8rZBV0

🦠 Coronavirus (COVID-19) Collection (@APSphysics, Physical Rev journals): https://t.co/hjO6nZpYlf

Freely available.

"The scope of the collection includes any articles that mention coronavirus, as well as those classified as relevant to epidemiology and epidemic spreading models."

دانشگاه آلتو دوره‌‌ای شروع کرده به اسم Python for Scientific Computing. این دوره ۴ روزه است و دیروز جلسه اول آن برگزار شد. ویدیو جلسه گذشته در اینجا و جزئیات آن در اینجا قابل مشاهده است.

جلسه بعدی، فردا (چهارشنبه) است. شما می‌توانید به صورت آنلاین در این کلاس‌ها حاضر شوید:

🔗 https://scicomp.aalto.fi/training/scip/python-for-scicomp/

LML Online conference in January 2021 will explore the concepts of Ergodicity Economics and their application to research in economics and other fields, including neuroscience, psychology, marketing and medicine.
https://t.co/Nbpx52yvWQ

💡 A workshop on computational (and statistical!) phase transitions at Simons Institute. A lot of exciting progress.
https://t.co/8pVYZlZWeI

Paper-Writing in Applied Mathematics: A Tutorial (by Mason A. Porter)
https://www.aparat.com/v/EeZDY/Paper-Writing_in_Applied_Mathematics%3A_A_Tutorial_%28by_Mason_A._Porter%29

🔵 network catalogue, repository and centrifuge:

https://networks.skewed.de/

💰 #PhD #postdoc

We are hiring doctoral and postdoctoral researchers at the Social Networks Lab of ETH Zürich.🇨🇭

Details and application: https://t.co/RAtrd5HL0T

Renormalization, writes David Tong, a theorist at the University of Cambridge, is “arguably the single most important advance in theoretical physics in the past 50 years.”

I agree! Ken Wilson "changed physics forever."

https://t.co/R4FbcVY6ie

💰 I am looking to hire a #postdoc (start date flexible) @SFUPhysics in Vancouver, to do #nonequilibrium #thermodynamics (theory, computation, and collaboration with experiments) applied to #molecularmachines. Details:
https://t.co/MX9ZqsKt5T

دو نوشته مهم برای کسانی که به تازگی در #کنکور #کارشناسی شرکت کرده‌اند و قصد #تحصیل در رشته #فیزیک را دارند:

🎯 چهارسال فیزیک!

🎯 کنکوری‌ها حواستان باشد جوگیر نشوید؛ در علم جایی برای جوگیرها نیست!

@sitpor

کوانتا مگزین نوشته جالبی منتشر کرده در مورد بازبهنجارش و اثرش روی فیزیک. شاید برای هر کسی که سر و کارش با فیزیکه، اوایل موضوعاتی مثل نسبیت و مکانیک کوانتومی ذهنشو درگیر کنه، اما به نظر من برای کسی که تجربه‌ بیشتری در فیزیک داشته باشه قطعا یکی از هیجان‌انگیزترین ایده‌ها، ایده بازبهنجارشه.

💡یک دوره کوتاه و مقدماتی در مورد بازبهنجارش در سیتپور وجود داره:
🔗 sitpor.org/complex-systems/renormalization/

برای یک مقدمه فنی‌تر می‌تونید به درس‌گفتارهای دیوید تانگ یا دکتر کریمی‌پور نگاه کنید.
—————
@sitpor

💡 nature.com/articles/s41567-020-1018-2

💡 nature.com/articles/s41567-020-0981-y

🎲 alexdanco.com/2020/04/09/life-is-made-of-unfair-coin-flips

Breaking news at #netsci2020: this year Euler Award has just been announced and it goes to Prof. ​Alessandro Vespignani!

https://t.co/j6njDNY7ye

#articles Generalized entropies, density of states, and non-extensivity

Sámuel G. Balogh, Gergely Palla, Péter Pollner & Dániel Czégel

Scientific Reports volume 10, Article number: 15516 (2020)

Abstract
The concept of entropy connects the number of possible configurations with the number of variables in large stochastic systems. Independent or weakly interacting variables render the number of configurations scale exponentially with the number of variables, making the Boltzmann–Gibbs–Shannon entropy extensive. In systems with strongly interacting variables, or with variables driven by history-dependent dynamics, this is no longer true. Here we show that contrary to the generally held belief, not only strong correlations or history-dependence, but skewed-enough distribution of visiting probabilities, that is, first-order statistics, also play a role in determining the relation between configuration space size and system size, or, equivalently, the extensive form of generalized entropy. We present a macroscopic formalism describing this interplay between first-order statistics, higher-order statistics, and configuration space growth. We demonstrate that knowing any two strongly restricts the possibilities of the third. We believe that this unified macroscopic picture of emergent degrees of freedom constraining mechanisms provides a step towards finding order in the zoo of strongly interacting complex systems.