📕 https://www.nature.com/nature/volumes/564/issues/7735?utm_source=twitter&utm_medium=social&utm_content=organic&utm_campaign=NGMT_2_SJH_Nature

🎲 @ComplexSys

imon DeDeo: From Atoms to Societies, Emergentism and Reductionism

we talk about the ways we can apply knowledge and mathematical models from Physics to the study of human social behavior ...

🎙 Data Reveals Most Influential Movies
🌐 yon.ir/ctpFQ

🎲 @ComplexSys

New cheatsheet: how to deal with reviewers' comments! https://t.co/lilVsoxHey #phdchat

#سمینارهای_هفتگی مرکز شبکه‌های پیچیده و مردم‌شناسی دانشگاه شهید بهشتی

⏰ یکشنبه، ۲۵ آذر، ساعت ۱۶:۴۵
🏛 محل برگزاری: سالن ابن هیثم
@mhakim

روز فیزیک در دانشگاه قم

⏪ وب‌گاه انجمن فیزیک ایران:
🌍 http://www.psi.ir

✅ به کانال خبرى انجمن فیزیک ايران بپيوندید:
👇👇🏽👇👇🏽👇👇🏽👇
http://t.me/psinews

⭕️ #Hints:

Imagine you are watching a rocket take off nearby and measuring the distance it has traveled once each second. In the first couple of seconds your measurements may be accurate to the nearest centimeter, say. However, 5 minutes later as the rocket recedes into space, the accuracy of your measurements may only be good to 100 m, because of the increased distance, atmospheric distortion and a variety of other factors. The data you collect would exhibit (heteroscedasticity)[https://en.wikipedia.org/wiki/Heteroscedasticity].

In statistics, a collection of random variables is #heteroscedastic (or heteroskedastic;[a] from Ancient Greek hetero “different” and skedasis “dispersion”) if there are sub-populations that have different variabilities from others. Here "variability" could be quantified by the variance or any other measure of statistical dispersion. Thus heteroscedasticity is the absence of #homoscedasticity.

ویکی‌گفت ۴۳

دکتر محرم ایردموسی

"اگه می‌تونی منو بگیر"

دوشنبه ۳ دی ۱۳۹۷
ساعت ۱۲ الی ۱۳
اتاق سمینار دانشکده ریاضی

@MathSBU

The statistical mechanics of Twitter

Gavin Hall, William Bialek

https://arxiv.org/format/1812.07029

We build models for the distribution of social states in Twitter communities. States can be defined by the participation vs silence of individuals in conversations that surround key words, and we approximate the joint distribution of these binary variables using the maximum entropy principle, finding the least structured models that match the mean probability of individuals tweeting and their pairwise correlations. These models provide very accurate, quantitative denoscriptions of higher order structure in these social networks. The parameters of these models seem poised close to critical surfaces in the space of possible models, and we observe scaling behavior of the data under coarse-graining. These results suggest that simple models, grounded in statistical physics, may provide a useful point of view on the larger data sets now emerging from complex social systems.

🤔 https://www.quora.com/What-is-the-best-machine-learning-paper-you-have-read-in-2018/answer/Yisong-Yue?ch=2&srid=3YXn

🔖 http://science.sciencemag.org/content/358/6365/eaan3184

⭕️ https://www.quantamagazine.org/emergence-how-complex-wholes-emerge-from-simple-parts-20181220/

🎞 Emergence and Minimal Models in Condensed Matter Physics and Biology

https://www.perimeterinstitute.ca/videos/emergence-and-minimal-models-condensed-matter-physics-and-biology

Nigel Goldenfeld

Abstract
Our ability to understand the physical world has to a large extent depended on the existence of emergent properties, and the separation of scales that permits effective field theory denoscriptions to be useful. Exploiting this fact, we can construct minimal models that enable efficient calculation of desired quantities, as long as they are insensitive to microscopic details. This works in many instances in physics, and I give some examples drawn from the kinetics of phase transitions mediated by topological defects. In other fields, such as biology, it is not so clear that these concepts are useful, and I will discuss to what extent emergence and effective theories might be useful.

🎞 https://www.aparat.com/v/dZ8yF

با سلام
نشست یکصدوشصت‌وچهارم باشگاه فیزیک تهران، ساعت ۱۷ روز دوشنبه 3 دی‌ماه 1397، در سالن آمفی تئاتر دانشکده فیزیک دانشگاه تهران (انتهای خیابان کارگرشمالی، روبه‌روی کوچه نوزدهم) برگزار خواهد شد.
آقای دکتر غلامرضا جعفری، از دانشکده فیزیک دانشگاه شهید بهشتی در این باشگاه از «داده‌های بزرگ، نظریه پیچیدگی و دوران پسامدرن» خواهند گفت. آقای علی فرنودی نیز در این باشگاه پرسش ماه را مطرح و خبر نشست را به آگاهی حاضران خواهند رساند.
مخاطبان این باشگاه، عموم علاقه‌مندان به فیزیک هستند. برای یادآوری به دوستان خود، با چاپ و نصب پوستر باشگاه در محل کار یا محل تحصیل خود، دیگر علاقه‌مندان فیزیک را آگاه کنید.
عضویت در #باشگاه_فیزیک و حضور در جلسات آن برای عموم علاقه‌مندان به علم فیزیک آزاد است.

با احترام
انجمن فیزیک ایران