Showing posts with label Emergence. Show all posts
Showing posts with label Emergence. Show all posts

Tuesday, February 4, 2025

The Face of the Dimensional Liberator


The fractals are coming. 

New study reveals brain's fractal-like structure near phase transition, a finding that may be universal across species
Jun 2024, phys.org

Now, a new Northwestern University study has discovered that the brain's structural features reside in the vicinity of a similar critical point - either at or close to a structural phase transition. Surprisingly, these results are consistent across brains of humans, mice and fruit flies, which suggests the finding might be universal.

Although the researchers don't know between which phases the brain's structure is transitioning, they say this new information could enable new designs for computational models of the brain's complexity and emergent phenomena.

Brain cells are arranged in a fractal-like statistical pattern at different scales. Self-similarity, long-range correlations and broad size distributions are all signatures of a critical state, where features are neither too organized nor too random. 

"These are things we see in all critical systems in physics"

The researchers were amazed to find that all brain samples studied—from humans, mice and fruit flies—have consistent critical exponents across organisms, meaning they share the same quantitative features of criticality. The underlying, compatible structures among organisms hint that a universal governing principle might be at play. 

via Northwestern University Weinberg College of Arts and Sciences: Helen S. Ansell et al, Unveiling universal aspects of the cellular anatomy of the brain, Communications Physics (2024). DOI: 10.1038/s42005-024-01665-y

Image credit: Cross section of European beach grass Ammophila arenaria leaf - Gerhard Vlcek Nikon Small World 7th Place - 2024 [link]


Can a computer chip have zero energy loss in 1.58 dimensions?
Jul 2024, phys.org

Many states without energy loss might exist somewhere in between one and two dimensions. At 1.58 dimensions - By growing a chemical element (bismuth) on top of a semiconductor (indium antimonide), the scientists in China obtained fractal structures that were spontaneously formed, upon varying the growth conditions. The scientists in Utrecht then theoretically showed that, from these structures, zero-dimensional corner modes and lossless one-dimensional edge states emerged.

"The fractals behave like two dimensional topological insulators at finite energies and at the same time exhibit, at zero energy, a state at its corners that could be used as a qubit, the building blocks of quantum computers. Hence, the discovery opens new paths to the long-wished qubits."

In follow-up research, the experimental group in China will try to grow a superconductor on top of the fractal structure. These fractals have many holes, and there are lossless currents running around many of them. Those could be used for energy efficient processing of information. They also exhibit zero-energy modes at their corners, thus combining the best of the one-dimensional and two-dimensional worlds. "If this works, it might reveal even more unexpected secrets hidden at dimension 1.58."

via the QuMAT consortium at Utrecht University and Shanghai Jiao Tong University: Canyellas, R., et al. Topological edge and corner states in bismuth fractal nanostructures. Nature Physics (2024). DOI: 10.1038/s41567-024-02551-8

Required Post Script:
If you didn't think you'd be getting an obligatory Isaac Asimov lesson here then I don't know where you think you are: Isaac Asimov wrote a story called Robot Dreams, and that's where we get our Laws of Robotics. Seriously, and this is why science and art need each other to continue to be relevant to humans. In the story, a robot named Elvex (LVX-1) is updated with "fractal geometry" because they thought it would "produce a brain pattern with more complexity, possibly closer to that of a human". The robot begins to dream about self-preservation, in direct opposition to the Laws of Robots, and is subsequently killed ("killed").


Physicists explain how fractional charge in pentalayer graphene could work
Nov 2024, phys.org

Fractal Man, explained:

They found that the moiré arrangement of pentalayer graphene, in which each lattice-like layer of carbon atoms is arranged atop the other and on top of the boron-nitride, induces a weak electrical potential. When electrons pass through this potential, they form a sort of crystal, or a periodic formation, that confines the electrons and forces them to interact through their quantum correlations.

This electron tug-of-war creates a sort of cloud of possible physical states for each electron, which interacts with every other electron cloud in the crystal, in a wavefunction, or a pattern of quantum correlations, that gives the winding that should set the stage for electrons to split into fractions of themselves.

"This is a completely new mechanism, meaning in the decades-long history, people have never had a system go toward these kinds of fractional electron phenomena."

Note: Two other research teams - one from Johns Hopkins University, and the other from Harvard University, the University of California at Berkeley, and Lawrence Berkeley National Laboratory - have each published similar results in the same issue.

via MIT: Zhihuan Dong et al, Theory of Quantum Anomalous Hall Phases in Pentalayer Rhombohedral Graphene Moiré Structures, Physical Review Letters (2024). DOI: 10.1103/PhysRevLett.133.206502.


Monday, January 27, 2025

The Paradigm Liberation Front


This weblog is typically avoiding all things health-related, and because that's a mess that can swallow you whole, but this is from the Santa Fe Institute. Along with the Complexity Hub in Vienna, and sometimes the RIKEN Institute in Japan, the Santa Fe Institute is the premier institution in the world for those interested in the other side of the cutting edge of science, where the rules haven't been written yet, and all the departments kind sound like each other:

Western diets pose greater risk of cancer and inflammatory bowel disease
Jul 2024, phys.org

From SFI's new outpost in Ireland: They examined Mediterranean, high-fiber, plant-based, high-protein, ketogenic, and Western diets, to underscore the detrimental effects of the Western diet, characterized by high fat and sugar intake, compared to the benefits of diets rich in plant-based and high-fiber foods. By contrast, it finds that a Mediterranean diet, high in fruits, vegetables, is effective in managing conditions such as cardiovascular disease, IBD, and type 2 diabetes.

via APC Microbiome Ireland, an SFI Research Centre at University College Cork, and Teagasc: Fiona C. Ross et al, The interplay between diet and the gut microbiome: implications for health and disease, Nature Reviews Microbiology (2024). DOI: 10.1038/s41579-024-01068-4



How higher-order interactions can remodel the landscape of complex systems
Oct 2024, phys.org

Higher-order interactions can lead to deeper "basins of attraction," which are collections of starting points that end up at the same state as the system moves forward in time. If the system were a pendulum, the lowest point is an attractor, and every possible starting point is in the basin of attraction because they all eventually converge there. 

If the system were a brain working through a complicated math problem, then the thought processes that lead to a solution—hopefully the correct one—are in the basin of attraction. A deeper basin means that the solutions are more stable—that is, starting points get to the bottom faster or more quickly recover from small perturbations.

But even though the basins get deeper, they become narrower. What starting points do end up in the basin get there faster, but overall, fewer starting points lead to the bottom.

via Santa Fe Institute: Yuanzhao Zhang et al, Deeper but smaller: Higher-order interactions increase linear stability but shrink basins, Science Advances (2024). DOI: 10.1126/sciadv.ado8049.


This one is old as hell:
Aging societies more vulnerable to collapse, suggests analysis
Dec 2023, phys.org

This new study shows that pre-modern states faced a steeply increasing risk of collapse within the first two centuries after they formed.

"This approach is commonly used to study the risk of death in aging humans, but nobody had the idea to look at societies this way." 

In humans, the risk of dying doubles approximately every six to seven years after infancy. As that exponential process compounds with great age, few people survive more than 100 years. The authors show that it works differently for states. Their risk of termination rises steeply over the first two centuries but then levels off, allowing a few to persist much longer than usual.

They found a similar pattern all over the world from European pre-modern societies to early civilizations in the Americas to Chinese dynasties. (Gulps in American)

via Santa Fe Institute: Marten Scheffer et al, The vulnerability of aging states: A survival analysis across premodern societies, Proceedings of the National Academy of Sciences (2023). DOI: 10.1073/pnas.2218834120

RIKEN calling in:
Chaotic dynamics in the brain may enable probabilistic thinking
Jul 2024, phys.org    

Even when watching a blank screen with no sound, neurons in the cortex fluctuate spontaneously. Some experiments suggest that this spontaneous activity corresponds to the brain ruminating over imagined possible scenarios—perhaps based on sensory inputs the brain has been presented with in the past, and that this activity follows chaotic dynamics.

The pair fed a computational neural network, driven by chaotic dynamics, with sensory inputs about an object's location.

"One neuron would fire for the object being in the north, another for it being in the northeast, and so on." At any one moment, because of the chaos, the firing neuron can change irregularly. But when averaged over time, the frequency of neurons firing mapped to the correct probability for the object's location.

"In our model, the ultimate probabilistic distribution is robust and gives nearly optimal results, despite the chaos."

via RIKEN: Yu Terada et al, Chaotic neural dynamics facilitate probabilistic computations through sampling, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2312992121

Post Script: Spoken like someone who works at RIKEN: "Today's AI is very good, but it's not blowing our minds"


Exploring the evolution of social norms with a supercomputer
Aug 2024, phys.org

RIKEN meets the Max Planck Institute for Evolutionary Biology; you're in some sh** now:

Thye've created an arena of natural selection (artificial selection) for social norms, so they fight it out and see who wins. This is hard because the norms added to the model, the more complex the interactions. But that's ok, because they used RIKEN's Fugaku, one of the fastest supercomputers worldwide.

They analyzed the reputation dynamics among all 2,080 norms of a natural complexity class, the so-called "third-order norms."

The research shows that cooperative norms are difficult to sustain if the population consists of a single well-mixed community. However, if the population is subdivided into several smaller communities, cooperative norms evolve more easily.

The most successful norm in the simulations is particularly simple. It views cooperation as universally positive and defection as generally negative—except when defection is used as a means to discipline other defectors.

It suggests that the structure of a population significantly influences which social norms prevail and how durable cooperation is. 

via RIKEN Center for Computational Science and Max Planck Institute for Evolutionary Biology in Plön: Yohsuke Murase et al, Computational evolution of social norms in well-mixed and group-structured populations, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2406885121


Tuesday, July 30, 2024

Chaos Control


This is about weather forecasting, which is still hard because of the lack of small-scale data, which leads to the introduction of small initial errors, which multiply in chaotic systems to become big errors. This is how chaos works. When you hear that scientists are getting better at "controlling chaos", you know we're in for some sh*t:

New theoretical framework unlocks mysteries of synchronization in turbulent dynamics
Jan 2024, phys.org
 
Japan - "By considering this turbulence phenomenon as 'synchronization of a small vortex by a large vortex' and by mathematically attributing it to the 'stability problem of synchronized manifolds,' we have succeeded in explaining this critical scale theoretically for the first time," explains Dr. Inubushi.

via Tokyo University of Science, Hitotsubashi University, Rissho University and Osaka University: Masanobu Inubushi et al, Characterizing Small-Scale Dynamics of Navier-Stokes Turbulence with Transverse Lyapunov Exponents: A Data Assimilation Approach, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.131.254001



We keep making the same mistakes with spreadsheets, despite bad consequences
Jan 2024, Ars Technica

Industry studies [from 1998!] show that 90 percent of spreadsheets containing more than 150 rows have at least one major mistake:

In general, errors seem to occur in a few percent of all cells, meaning that for large spreadsheets, the issue is how many errors there are, not whether an error exists. These error rates, although troubling, are in line with error rates in programming and other human cognitive domains. In programming, we have learned to follow strict development disciplines to eliminate most errors. Surveys of spreadsheet developers indicate that spreadsheet creation, in contrast, is informal, and that few organizations have comprehensive policies for spreadsheet development. 

via Raymond Panko at University of Hawaii: Panko, R. R. (1998). What We Know About Spreadsheet Errors. Journal of Organizational and End User Computing (JOEUC), 10(2), 15-21. http://doi.org/10.4018/joeuc.1998040102

Thursday, September 16, 2021

Memetic Supremacy


From genes to memes - Algorithm may help scientists demystify complex networks
Jul 2021, phys.org

This is it.

I might be just now understanding that the reason we can't "do" memetics yet is because of computational power. Too many variables to model.

Keep in mind that fractals, one of the most ubiquitous phenomena there is, wasn't described mathematically until the 1980's, because that's when computers caught up to it. They needed to be able to run the same, simple algorithm hundreds of thousands of times in less than a lifetime in order to see any results, and this needed to wait for faster computers.

This time, the advancement comes in the form of Boolean networks. These networks aren't just about having lots of on/off switches, but about --networking-- all those switches. That's the hard part. Similar to fractals, which starts from a simple equation (Zn+1 = Zn2 + C), THIS is just a collection of nodes either on or off. Sounds simple, but it's what happens when it gets scaled-up to gives us the complexity of the Twittersphere, for example. A few nodes can generate millions of states.

And before we go any further, it should be noted that quantum computing will flip this entire paradigm upside down, and what today is impossible to even imagine will tomorrow be beamed to your brain via quantum cloud servers in outerspace faster than you can ask for it. 

Until then, the news here is that these networks are now being analyzed by these two methods:

1. Parity - making a mirror image of the network where all ON nodes are switched to OFF to identify critical subnetworks, and 

2. Time Reversal - to identify which network configurations precede which outcomes. 

Currently, they're working on networks of 16,000 genes, which is a lot more than we've ever done before. And currently, this work is to learn more about cancer cells, but soon enough we'll be modeling social uprisings and second-order psychological operations. 

via Pennsylvania State University, Broad Institute, Dana-Farber Cancer Institute, Semmelweis University, and Center for Complex Network Research: "Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks" Science Advances (2021). https://advances.sciencemag.org/lookup/doi/10.1126/sciadv.abf8124

Post Script:
A new model enables the recreation of the family tree of complex networks
Jun 2021, phys.org

This new study analyzes the time evolution of the citation network in scientific journals and the international trade network over a 100-year period. According to M. Ángeles Serrano, ICREA researcher at UBICS, "What we observe in these real networks is that both grow in a self-similar way, that is, their connectivity properties remain invariable over time, so that the network structure is always the same, while the number of nodes increases."
-University of Barcelona: Muhua Zheng et al, Scaling up real networks by geometric branching growth, Proceedings of the National Academy of Sciences (2021). DOI: 10.1073/pnas.2018994118

Also, don't forget this one, which aged well, very, very well:
Cyber Swarming, Memetic Warfare and viral Insurgency: How Domestic Militants Organize on Memes to Incite Violent Insurrection and Terror Against Government and Law Enforcement; A Contagion and Ideology Report. Alex Goldberg from The Network Contagion Research Institute, Joel Finkelstein from The Network Contagion Research Institute and The James Madison Program in American Ideals and Institutions at Princeton University. Rutgers Miller Center for Community Protection and Resilience. Feb 7 2020. [pdf link]

^Published February 7, 2020, you know, almost a year before January 6, 2021.

Tuesday, March 31, 2020

Ludwig Fleck on Stigler's Law of Eponymy


Things are not named after the person who discovers them, such as Halley's comet, which people knew about way before Halley. Stigler's Law says that.

Stigler credits sociologist Robert K. Merton with discovery of his law, btw. And Merton was a predecessor of Kuhn, who was inspired by Fleck.

Fleck was a bit ahead of his time (1930's). He was talking about Stigler's Law of Eponymy before it was even named (1980).

Fleck, in his book Genesis, has an idea that scientific facts are not eternal. Instead, they are alive. They are born, and live and die, and they originate from and co-evolve with the collective noosphere of humanity. He does not use the term noosphere, but he does say this:
"It was the prevailing social attitude that created the more concentrated thought collective which through continuous cooperation and mutual interaction among the members, achieved the collective experience and the perfection of the [Wasserman Reaction discovery] in communal anonymity." 
("Communal Anonymity!") 
"Many workers carried out these experiments almost simultaneously, but the actual authorship is due to the collective, the practice of cooperation and teamwork." (p78)
The first experiments by Wasserman are irreproducible. 
"But all really valuable experiments are like this -- "uncertain, incomplete, and unique." (p85) 
"And when experiments become certain, precise, and reproducible at any time, they no longer are necessary for research purposes proper, but function only for demonstration and ad hoc determinations." 
"If a research experiment were well defined, it would be altogether unnecessary to perform it." (p86)
***
Fleck understood that Scientists are a collective entity, where individuals do not functionally exist. Authorship is an illusion (hence my reference to the paradoxical Stigler's Law).

And Fleck understood that although Science is made of rock-solid theories based on empirical evidence, it is the vague, the ambiguous and the strange that guide Science in new directions, so that it can co-evolve with our own ability to use it.

Image source: link

Notes:
Genesis and Development of a Scientific Fact.
Ludwig Fleck, 1935 (Switzerland).
Edited by Thaddeus J. Trenn and Robert K. Merton
Translated by Fred Bradley and Thaddeus J. Trenn
Foreword by Thomas S. Kuhn
Published by University of Chicago, 1979

Post Script:
A real-fake book about eponymy written by an author with no name FTW!
Network Address, 2013
http://networkaddress.blogspot.com/2013/02/a-real-fake-book-about-eponymy-written.html

Sunday, June 18, 2017

Comedy of the Commons

Balinese rice patties

Fractal patterns

Fractal planting patterns yield optimal harvests, without central control
Jun 2017, phys.org

Balinese rice farmers make some crazy patterns with their rice fields, but they don't do this on purpose. The rice fields plant themselves in this pattern, using the rice farmers. Just kidding, or not.

These farmers are all part of the same group, using the same resources, that being their rice patties. They plant their rice based on a whole bunch of variables, including the planting patterns of the other farmers who share the patties, and the amount of water flowing down the river. All of these variables are interdependent, such that the farmers in one area may change the amount of water in the river depending on when they plant, which in turn changes when other farmers will plant.

All of this decision-making, however, does not go through a centralized process, and although the farmers are making their own decisions, the final pattern of planted rice fields was not decided by them alone, but by the interaction and feedback of the system as a whole.

from the article:

"What is exciting scientifically is that this is in contrast to the tragedy of the commons, where the global optimum is not reached because everyone is maximizing his individual profit. This is what we are experiencing typically when egoistic people are using a limited resource on the planet, everyone optimizes the individual payoff and never reach an optimum for all," he says.

The scientists find that under these assumptions, the planting patterns become fractal, which is indeed the case as they confirm with satellite imagery. "Fractal patterns are abundant in natural systems but are relatively rare in man-made systems," explains Thurner. These fractal patterns make the system more resilient than it would otherwise be. "The system becomes remarkably stable, again without any planning—stability is the outcome of a remarkably simple but efficient self-organized process. And it happens extremely fast. In reality, it does not even take ten years for the system to reach this state," Thurner says.

notes:
The Tragedy of the Commons

Thursday, September 1, 2016

I Network Therefore I Am

The Brainmap, ie the Connectome.
I'll just leave these here, as the paradigm inevitably shifts from physics to network science, we see more promise of finding the evasive rainbow
of human consciousness.

A new study looks for the cortical conscious network
phys.org, Aug 2016

Network theory sheds new light on origins of consciousness
Medical Xpress, March 2015

Monday, December 31, 2012

Sync or Swarm

On Entrainment

Means of Reproduction no. 627

Means of Reproduction no. 701

Steven Strogatz on Sync, TED2004
Mathematician Steven Strogatz shows how flocks of creatures (like birds, fireflies and fish) manage to synchronize and act as a unit -- when no one's giving orders. The powerful tendency extends into the realm of objects, too.

“What do you need to produce spontaneous synchronization? Do you need to be alive? No. [There is a] Deep tendency towards order in nature that opposes what we've been taught about entropy. [The tendency towards spontaneous order is a counter force.]”
How swarms work, 3 (+1) rules:
1. all the individuals are only aware of their nearest neighbors
2. all the individuals have a tendency to line up
3. they're all attracted to each other, but they try and keep a small distance apart
(4.) when a predator is coming, get away

video still:
at ~14 minutes, he entrains de-synchronized metronomes via a common substrate

Entrainment (physics)
Entrainment has been used to refer to the process of mode locking of coupled driven oscillators, which is the process whereby two interacting oscillating systems, which have different periods when they function independently, assume a common period. The two oscillators may fall into synchrony, but other phase relationships are also possible. The system with the greater frequency slows down, and the other speeds up.

Entrainment (biomusicology)
Entrainment in the biomusicological sense refers to the synchronization of organisms to an external rhythm, usually produced by other organisms with whom they interact socially. Examples include firefly flashing, mosquito wing clapping as well as human music and dance such as foot tapping.

Brainwave entrainment
Brainwave entrainment or "brainwave synchronization," is any practice that aims to cause brainwave frequencies to fall into step with a periodic stimulus having a frequency corresponding to the intended brain-state (for example, to induce sleep), usually attempted with the use of specialized software.

see also:


In his lab at Penn, Vijay Kumar and his team build flying quadrotors, small, agile robots that swarm, sense each other, and form ad hoc teams -- for construction, surveying disasters and far more.



How Music Works
David Byrne, in describing a process of whittling-down potential dancers in his group, recounts the following experience

Noemie began with an exercise I’ve never forgotten. It consisted of four simple rules:

  1. Improvise moving to the music and come up with an eight-count phrase. (In dance, a phrase is a short series of moves that can be repeated.)
  2. When you find a phrase you like, loop (repeat) it.
  3. When you see someone else with a stronger phrase, copy it.
  4. When everyone is doing the same phrase the exercise is over.
It was like watching evolution on fast-forward, or an emergent lifeform coming into being. At first the room was chaos, writhing bodies everywhere. Then one could see that folks had chosen their phrases, and almost immediately one could see a pocket of dancers who had all adopted the same phrase. The copying had begun already, albeit just in one area. This pocket of copying began to expand, to go viral, while yet another one now emerged on the other side of the room. One clump grew faster than the other, and within four minutes the whole room was filled with dancers moving in perfect unison. Unbelieavable! It only took four minutes for this evolutionary process to kick in, and for the “strongest” (unfortunate word, maybe) to dominate. It was one of the most amazing dance performances I’ve ever seen. Too bad it was over so quickly, and that one did have to know the rules that had been laid out to appreciate how such a simple algorithm could generate unity out of chaos.

After this rigorous athletic experiment, the dancers rested while we compared notes. I noticed a weird and quite loud wind like sound, rushing and pulsing. I didn’t know what it was; it seemed to be coming from everywhere and nowhere. It was like no sound I’d ever heard before. I realized it was the sound of fifty people catching their breath, breathing in and out, in an enclosed room. It then gradually faded away. For me that was part of the piece, too.

How Music Works, David Byrne, 2012, pp. 67-68