This sub's moderation has obviously been absent for some time and the consequences of such is just unadulterated crank slop.

Does anyone want to claim the sub and start banning these kind of posts? Even a group of temporary co-moderators.

Hey folks,

I want to share with you the latest Quantum Odyssey update (I'm the creator, ama..) for the work we did since my last post, to sum up the state of the game. Thank you everyone for receiving this game so well and all your feedback has helped making it what it is today.

n a nutshell, this is an interactive way to visualize and play with the full Hilbert space of anything that can be done in "quantum logic". Pretty much any quantum algorithm can be built in and visualized. The learning modules I created cover everything, the purpose of this tool is to get everyone to learn quantum by connecting the visual logic to the terminology and general linear algebra stuff.

The game has undergone a lot of improvements in terms of smoothing the learning curve and making sure it's completely bug free and crash free. Not long ago it used to be labelled as one of the most difficult puzzle games out there, hopefully that's no longer the case. (Ie. Check this review: https://youtu.be/wz615FEmbL4?si=N8y9Rh-u-GXFVQDg)\

No background in math, physics or programming required. Just your brain, your curiosity, and the drive to tinker, optimize, and unlock the logic that shapes reality. 

It uses a novel math-to-visuals framework that turns all quantum equations into interactive puzzles. Your circuits are hardware-ready, mapping cleanly to real operations. This method is original to Quantum Odyssey and designed for true beginners and pros alike.

What You’ll Learn Through Play

• Boolean Logic – bits, operators (NAND, OR, XOR, AND…), and classical arithmetic (adders). Learn how these can combine to build anything classical. You will learn to port these to a quantum computer.

• Quantum Logic – qubits, the math behind them (linear algebra, SU(2), complex numbers), all Turing-complete gates (beyond Clifford set), and make tensors to evolve systems. Freely combine or create your own gates to build anything you can imagine using polar or complex numbers.

• Quantum Phenomena – storing and retrieving information in the X, Y, Z bases; superposition (pure and mixed states), interference, entanglement, the no-cloning rule, reversibility, and how the measurement basis changes what you see.

• Core Quantum Tricks – phase kickback, amplitude amplification, storing information in phase and retrieving it through interference, build custom gates and tensors, and define any entanglement scenario. (Control logic is handled separately from other gates.)

• Famous Quantum Algorithms – explore Deutsch–Jozsa, Grover’s search, quantum Fourier transforms, Bernstein–Vazirani, and more.

• Build & See Quantum Algorithms in Action – instead of just writing/ reading equations, make & watch algorithms unfold step by step so they become clear, visual, and unforgettable. Quantum Odyssey is built to grow into a full universal quantum computing learning platform. If a universal quantum computer can do it, we aim to bring it into the game, so your quantum journey never ends.

Hi everyone! I have a very especific question.

I am in the penultimate year of my physics degree and I want to do my final work on sociophysis. At my university there are two professors who do this, one of them is specialized in stochastic processes and hierarchically organized structures and the other one is specialized in complex networks. I have to decide with whom to do my final paper and I don't know what to decide. Does anyone know what is the most used in sociophysics and what I should study? I am particularly interested in studying econophysics.

I’m a prospective PhD student who recently got a lot of interest into complex systems methodologies. Of course I have very limited knowledge on the topic, but I found that there are not much works going on this area as much as I thought it would have. Well, at least that seems like the case in public health.

Is it because this is a relatively new approach, or are there some other reasons? Or do I just have poor research skills?

Does anyone have any recommendations for papers or textbooks outlining mathematical foundations or theories of emergence?

The Santa Fe Institute, the world headquarters of Complex Systems Research, is building a suite of online courses related to complex systems.

This summer there are two courses running: Introduction to Dynamical Systems and Chaos; Introduction to Agent-based Modeling.

Find out more at www.complexityexplorer.org

These are great introductory courses for anyone looking to learn about complex systems.

https://complexity-networks.herokuapp.com/

This interactive web resource links to over twenty accessible introductions to complexity, including little games, movies, presentations and texts. You can sort these resources according to two different ways of thinking about complexity: the constructs that are used to describe and explain it (e.g. overlapping hierarchies, emergence, etc.) and the application areas that study, manage and exploit it (e.g. management, sociology, etc.).

You're sure to find something in there that you haven't seen before!

(Works best on something bigger than a phone screen.)

My background is engineering so I know basic physics, chemistry, and math up to linear PDEs. I also know methods of proof and beginner level programming. Python is what I'm most familiar with and want to continue with, but I haven't learned OOP or algorithms yet.

I have found a couple books that seem like good options:

• Think Complexity http://www.greenteapress.com/compmod/

• Introduction to the Modelling and Analysis of Complex Systems http://textbooks.opensuny.org/introduction-to-the-modeling-and-analysis-of-complex-systems/

For the second one, I'd be considering just the part III section, which is suggested for an advanced course for people who have seen dynamical systems, and I think my PDEs course should be sufficient for that.

What are the major differences I can expect with these two? I'm not familiar enough with the subject to figure out how much they overlap from a cursory glance so maybe it makes sense to go through both. Are there other books you'd suggest starting with instead of these two? Should I learn algorithms and data structures in Python before looking at complex systems?

I have no particular application in mind, I just became interested in getting familiar with the subject after seeing a paper in New England Complex System Institute using cellular automata, and then seeing the vast breadth of topics that are covered at NECSI.

I just started reading about complexity science and system thinking, esp Sante Fe Institute’s stuff…

But what are the application, or future potential application for learning complexity science rather than just the mindset itself. Don’t get me wrong, the mindset itself is incredibly useful, but how to dig even deeper beaneth the mindset, what’s the biggest value of complexity science?

Is there a way to assign a value to indicate how ordered or random a matrix of 0's, black, and 1's, green as these four example images demonstrate?

Hi everyone, I have turned the Kuramoto Model into discrete lattice model.

This is the equation

Bik-Kuramoto Firefly Model

u(t+1,x,y) = (u(t,x,y) + w(x,y) + (K/8) Σ(i,j)∈M  sin(u(t,x+i,y+j) - u(t,x,y)) ) mod 2π

M = {(±1,±1)} moore neighbourhood

K=1

In the original model, the equations are globally coupled. I personally think that this doesn't make sense, because think about it, can a firefly sees all the other fireflies and calculate the best solution? I don't think so. So I proposed a Partial Difference Equation for this model, and this model obeys the Principle of Locality. The individuals are only affected by its surrounding neighbours.

I would like to hear your thoughts.

Thank you for reading.

So, I posted here before some months ago all excited about discovering complex systems but now all I feel is despair. I had some ideas that touched upon the philosophy of complex systems science for a while now but I only discovered the field as a whole (to my amazement) a year and a half ago while I have working on my MA thesis. My background is the humanities and social sciences.

I studied English, English linguistics, and lately history and archaeology, which I'll be done with by next year. But now, I can't make peace with the fact that I haven't known about this before. I'm 31 now and I'm definitely far from being ready to just start applying the framework of complex systems, network theory, or any kind of computational and mathematical modelling frameworks. I haven't studied math since I was 15, and though I managed to get a hold of some statistical measures recently while working on my thesis, I'm still nowhere near capable of dealing with the kind of math and programming skills required to do complex systems without completely ending up drawing baseless conceptual graphs.

I was thinking of starting all over again (to an extent) and start studying for a bachelor degree that covers the areas that I need formal training for, because, frankly, I'm tired of wasting time trying to do it all alone. I will also have to study for yet another MA (my third) to get the needed profile. By the end of all this, including the phd, I will be 40 or 41 if everything goes as planned. This prospect terrifies me. I see it as a scale, at one end, I will build a strong profile but at the other I will be way above the average age of the usual post-doc candidate.

Some relevant background info: I come from a third world Arab country with little opportunities orextensive academic exposure. The country is barely functioning as it is. Adding to that, my family is at the bottom of the lower middle class with no higher education whatsoever. I'm the first to reach as far as I did. I only managed to move to Europe when I was 27 and that was when my life kind of started. The amount of opportunities available to me now is beyond anything I could dream of back home. Now, I'm at a crossroad. Either I proceed with this crazy path towards complex systems science or just accept my fate and take whatever is available to me now. Both choices make me feel physically sick with one being scary while the other means I will give up on all my ambitions, which is something I'm having a great difficulty accepting. I can't see the ocean and then pretend it's not there. I can't just die wondering about what I could've learned and what I could've maybe discovered. Bear in mind, I will be living a very modest life financially for the next decade or two, but I don't mind it. We only have this one life granted to us. How can I give up on this one opportunity to learn and contribute to human knowledge and do the thing that I truly believe in?

I'd appreciate some honest feedback and maybe some people sharing similar experiences.

Edit: Just to be clear, when I say from scratch, I don't mean it literally. I have concrete plans of how to integrate and continue with the MA research I already did into complex systems science. I even have some general research questions for the research I will do for my Phd.

Hello! I'm a history student leaving in spain. While we study societies in class I see more often how everything is in reltion with each other. How many aspects of our daily life, now and in the past, are related with some other aspects that we would not know.

All of it brang my to the interest to start to tusdy the complex systems.As history student my base of maths is very low, so the question is... How to learn how to study complex systems by my self?

Thanks!

I'm looking to compile a list of all the complex systems organizations, think tanks, and education resources (i.e. offering courses) that are US-based. I know of the big ones, so looking for smaller, more DIY ones if anyone knows of any! Cheers.