Showing posts with label chaos. Show all posts
Showing posts with label chaos. Show all posts

Thursday, April 17, 2025

The Hofstadter Regime Converges Upon Us


AKA Fine-Tuning The Chaos Machine 

The above image is the perfect example of a moiré lattice and where it comes from. I noticed it while watching a lecture by a scientist cited below, for being the first to discover Hofstadter's Butterfly in real life. It's just the best image I've seen to explain what a moiré lattice is.

Credit: Graphene hBN Moire Lattices - taken from the presentation Bloch, Landau, and Dirac - Hofstadter's Butterfly in Graphene by Philip Kim - Kavli Inst 2018 [youtube link]

The perimeter of ignorance in science is also the front door of chaos theory. You could call it a lot of other things, most of which are listed in the tags for this post, but mostly, anything that's "too complicated" for us to understand right now, it's chaos-related. Discoveries in this field come from a bunch of different places, like interdimensional graphene, like topological operators, like epilepsy surgery.

Harnessing chaos: How the brain turns randomness into robust memory
Jan 2025, phys.org

Previous work on brain-imitating artificial intelligence systems known as neural networks suggested that injecting random fluctuations into their activity could actually improve their performance as they learned to perform a task. 

Noise appears to increase the amount of time it takes for inhibitory neuron connections with other neurons to weaken. This slowing effect in turn stabilizes neural patterns of activity related to memories, helping them persist over time.

(This whole thing makes me think very differently about background noise, and maybe even the idea of 'functional music')...

via Columbia Engineering Systems Intelligence Laboratory: Nuttida Rungratsameetaweemana et al, Random noise promotes slow heterogeneous synaptic dynamics important for robust working memory computation, Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2316745122


How topology drives complexity in brain, climate and AI
Feb 2025, phys.org

Yes it does 

Transformative framework for understanding complex systems, using the new field of higher-order topological dynamics, and creating a connection between topological structures and emergent behavior. This comes from the field of information theory, and combines fusion of topology, higher-order networks, and non-linear dynamics.

via University of London: Ana P. Millán et al, Topology shapes dynamics of higher-order networks, Nature Physics (2025). DOI: 10.1038/s41567-024-02757-w

(Many body problem and higher order networks are the same thing - "interactions that extend beyond simple pairwise relationships".)

Most of us need to know: Hofstadter's butterfly (1976) was discovered before Mandelbrot coined the term "fractal" (1980), so he didn't know what to call it.

Hofstadter's butterfly: Quantum fractal patterns visualized
Feb 2025, phys.org

"Our discovery was basically an accident. We didn't set out to find this."

This is the first time Hofstadter's butterfly has been directly observed experimentally in a real material.

It was found using a moiré lattice - they were investigating superconductivity in twisted bilayer graphene, and when you hear twisted layers, you know we're also talking magic angle sandwiches. They used a scanning tunneling microscope to image moiré crystals at atomic resolution and examine their electron energy levels. The microscope works by bringing a sharp metallic tip less than a nanometer from the surface to allow quantum "tunneling" of electrons from the tip to the sample.

via Princeton University: Kevin P. Nuckolls et al, Spectroscopy of the fractal Hofstadter energy spectrum, Nature (2025). DOI: 10.1038/s41586-024-08550-2


Fitness centrality: New tool finds critical points in everything from cybersecurity to ecological conservation
Jan 2025, phys.org

The Vienna Complexity hub making waves

This approach is particularly good at finding nodes that, if removed, would isolate many other parts of the network—similar to a server failure interrupting the connection of many users in a communication network or a pump failure in a water supply network paralyzing the supply of water to districts.

Species in ecological networks, nodes in cybersecurity, roads in transportation networks. That's great. But it's people where this really has impact. Imagine trying to disable a social movement that could disturb the social fabric of a nation. You find the people, the nodes, at the center of the social network, and ... remove them, let's say. 

via Complexity Science Hub Vienna: Vito D P Servedio et al, Fitness centrality: a non-linear centrality measure for complex networks, Journal of Physics: Complexity (2025). DOI: 10.1088/2632-072X/ada845

Thursday, February 13, 2025

Diffusion Flux Propagation

 

Anything related to chaos theory, network science, complex systems, emergent phenomena, or whatever you want to call this large class of things and ideas, it's going to be heavy, like population level mind control psychometrics heavy. 

From branches to loops: The physics of transport networks in nature
Sep 2024, phys.org

I have noticed that when papers from Poland make it to the main feed you know you're in for some shit:

An important advantage of looping networks is their reduced vulnerability to damage; in networks without loops, the destruction of one branch can cut off all connected branches, whereas in networks with loops, there is always another connection to the rest of the system.

Many transport networks grow in response to a diffusive field, such as the concentration of a substance, the pressure in the system, or the electric potential. The fluxes of such a field are much more easily transported through the branches of the network than through the surrounding medium.

"We showed that a small difference in resistance between the network and the medium can lead to attraction between growing branches and the formation of loops."

"Analyzing the development of these [jellyfish gastrovascular] canals over time, I noticed that when one of them connects to the jellyfish's stomach (the boundary of the system) then the shorter canals are immediately attracted to it and form loops."

"Our model predicts that the attraction between neighboring branches after a breakthrough occurs regardless of the geometry of the network or the difference in resistance between the network and the surrounding medium." -Prof. Piotr Szymczak from the Faculty of Physics at the University of Warsaw

via University of Warsaw: Stanisław Żukowski et al, Breakthrough-induced loop formation in evolving transport networks, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2401200121



Computational method pinpoints how cause-and-effect relationships ebb and flow over time
Nov 2024, phys.org

"Currently available methods for studying complex systems tend to assume that the system is approximately stationary—that is, the system's dynamical properties stay the same over time. Other commonly introduced simplifications such as linearity and time invariance can produce incorrect expectations that fail to quantify changes in the strength or direction of these relationships."

To address this gap, the research team developed a novel machine-learning model called Temporal Autoencoders for Causal Inference (TACI) to identify and measure the direction and strength of causal interactions that vary over time. 

They used an established model of a dynamic system but generated a dataset where interactions (couplings) changed over time, and found that TACI was able to detect how the strength of the causal relationship changed. 

Next they looked at real data, starting with weather data, and found that causal interactions peak during times when the temperature drops—demonstrating that TACI can accurately predict true variations over time from messy real-world data. Then with brain data on anesthetized monkeys, and found almost all interactions disappear during the anesthetized period, and then begin to re-emerge during recovery.

via Department of Physics Emory University: Josuan Calderon et al, Inferring the time-varying coupling of dynamical systems with temporal convolutional autoencoders, eLife (2024). DOI: 10.7554/eLife.100692.1

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


Saturday, January 25, 2025

Peak Climate Confusion


There's a lot happening in the climate news, but Network Address is less interested in the facts, and more interested in the meta-facts, like how many superlatives an article uses, or how many new words have to be coined in order to keep track of what the heck is going on, or just cases where the weather centers monitoring disasters are themselves in the disaster zone, or maybe just outer space observatories that were never meant to be weather stations yet provide more accurate data than actual weather stations. It's all in there:

But first! More examples of scientists saying the word "crazy"
Hurricane Beryl supercharged by ‘crazy’ ocean temperatures, experts say
Jul 2024, The Guardian

“In the Caribbean Sea it has actually been warmer than its usual peak since mid-May, which is absolutely crazy,” said McNoldy. “If the ocean already looks like it’s the peak of hurricane season, we are going to get peak hurricanes.” [Not just crazy but absolutely crazy.]



Shipping emissions regulations enacted in 2020 improved air quality but accelerated warming
Aug 2024, phys.org

Regulations put into effect in 2020 by the International Maritime Organization required a roughly 80% reduction in the sulfur content of shipping fuel used globally.

They scanned over a million satellite images and quantified the declining count of ship tracks, estimating a 25 to 50% reduction in visible tracks. Where the cloud count was down, the degree of warming was generally up.

Further work by the authors simulated the effects of the ship aerosols in three climate models and compared the cloud changes to observed cloud and temperature changes since 2020. Roughly half of the potential warming from the shipping emission changes materialized in just four years, according to the new work. In the near future, more warming is likely to follow as the climate response continues unfolding. (Although it is noted that the magnitude of warming in 2023 is too significant to be attributed to the emissions change alone, according to their findings.)

via Department of Energy's Pacific Northwest National Laboratory: A. Gettelman et al, Has Reducing Ship Emissions Brought Forward Global Warming?, Geophysical Research Letters (2024). DOI: 10.1029/2024GL109077


Say something about the speed of new word occurrence in a general field as related to a kind of turbulence or unpredictability or some kind of measurement of entropy in a system: 

Mexico counting dead from 'zombie storm' John
Sep 2024, BBC News

The term "zombie storm" was first used by meteorologists from the US National Weather Service in 2020 to describe a storm which dissipates only to regenerate again.

This storm hit Mexico's Pacific Coast, then dissipated over the mountains before regaining strength over the waters of the Pacific and hitting the Mexican coast a second time.


We’re only beginning to understand the historic nature of Helene’s flooding
Sep 2024, Eric Berger for Ars Technica

The National Climatic Data Center maintains the world's largest climate data archive and provides historical perspective to put present-day weather conditions and natural disasters into context in a warming world due to climate change.

Unfortunately, the National Climatic Data Center is based in Asheville, North Carolina. As I write this, the center's website remains offline. That's because Asheville, a city in North Carolina's Blue Ridge Mountains, is the epicenter of catastrophic flooding from Hurricane Helene that has played out over the last week. The climate data facility is inoperable because water and electricity services in the region have entirely broken down due to flooding.

N.J. weather - Is this our driest October ever?
Oct 2024, nj.com

So many superlatives:
If our long streak of dry weather continues, this not only will turn out to be the driest October in most areas of New Jersey — but also the driest of any month on record.

If the month ended today, this would be the driest October ever recorded in the Newark, Trenton and Atlantic City areas, as well as New York City and Philadelphia.

It also would be number one for the least amount of rain to fall from the sky in any month of any year — not just October, according to the weather data.


Observatory finds local 1.1 ºC increase in 20 years, twice as much as predicted by climate models
Oct 2024, phys.org

Surprise - At the observatory, the weather station has sent data on temperature, relative humidity, atmospheric pressure and wind speed and direction every two seconds for the past twenty years. "The station was built with the intention to have some guidance for telescope operations, not to characterize local weather professionally, let alone the effects of climate change on the measured parameters. But the fact that they were relatively low-cost devices has been an advantage, since they had to be changed and recalibrated every two years or so, which has favored the reliability of the data and greatly limited the effects of long-term sensor drifts, which are difficult to detect."

But alas - The experimental data obtained show an increase of 1.1ºC over the past 20 years, i.e., 0.55ºC per decade. This is more than double the increase predicted by climate models for the same area, and even more than expected for the next 20 years.

via Department of Physics of the Autonomous University of Barcelona and the Roque de los Muchachos  Observatory: Markus Gaug et al, Detailed analysis of local climate at the CTAO-North site on La Palma from 20 yr of MAGIC weather station data, Monthly Notices of the Royal Astronomical Society (2024). DOI: 10.1093/mnras/stae2214


'Doomsday' Antarctic glacier melting faster than expected, fueling calls for geoengineering
Nov 2024, phys.org

This is about glacial geoengineering not just the "regular kind" (i.e., stratospheric injection)

One example - creating a giant submarine curtain that would at least partially prevent warm tidal currents from reaching the glacier ice. 

via the Columbia University Climate School


Unexplained heat-wave 'hotspots' are popping up across the globe
Nov 2024, phys.org

Just here for the ad copy:

Distinct regions are seeing repeated heat waves that are so extreme, they fall far beyond what any model of global warming can predict or explain.

For instance, a nine-day wave that hammered the U.S. Pacific Northwest and southwestern Canada in June 2021 broke daily records in some locales by 30°C, or 54°F. This included the highest ever temperature recorded in Canada, 121.3°F, in Lytton, British Columbia. The town burned to the ground the next day ... .

via Columbia Climate School's Lamont-Doherty Earth Observatory: Kai Kornhuber et al, Global emergence of regional heatwave hotspots outpaces climate model simulations, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2411258121

You know we're having a problem making sense of what's happening with the climate when we're willing to take into consideration the quantum effects of water:

Quantum mechanism identified as a key to accelerating ocean temperatures
Nov 2024, phys.org

Professor Smith said the apparent role of non-thermal energy in accelerating ocean temperatures now needs to be factored into climate models:

"When ocean water is heated by radiation from the sun and the sky it stores energy not only as heat, but as hybrid pairs of photons coupled to oscillating water molecules.

"These pairs are a natural form of quantum information, different to the information researchers are pursuing in the development of quantum computing. This extra store of energy has always been present and aided ocean thermal stability prior to 1960.

"But now the average heat dissipated overnight from each day's heating is no longer stable as extra heat input from Earth's atmosphere raises both forms of stored energy [including the quantum energy described above]."

via University of Technology Sydney: G B Smith, A many-body quantum model is proposed as the mechanism responsible for accelerating rates of heat uptake by oceans as anthropogenic heat inputs rise, Journal of Physics Communications (2024). DOI: 10.1088/2399-6528/ad8f11


On the heels of recent concern over the use of the word "tipping point" as having become kind of useless, and the scientific community is asking to stop using the word because it's confusing and counterproductive:

Rapid surge in global warming mainly due to reduced planetary albedo, researchers suggest
Dec 2024, phys.org

Far worse than expected - not only is it yes to the shipping sulfur aerosols, but also the warming itself is doing this, which means we've passed the tipping point (decades early).

"The 0.2-degree-Celsius 'explanation gap' for 2023 is currently one of the most intensely discussed questions in climate research."

One trend appears to have significantly affected the reduced planetary albedo: the decline in low-altitude clouds in the northern mid-latitudes and the tropics. In this regard, the Atlantic particularly stands out, i.e., exactly the same region where the most unusual temperature records were observed in 2023. [Albedo being the reflection of sunlight back off the earth, so that it never accumulates as heat.]

"It's conspicuous that the eastern North Atlantic, which is one of the main drivers of the latest jump in global mean temperature, was characterized by a substantial decline in low-altitude clouds not just in 2023, but also—like almost all of the Atlantic—in the past 10 years." 

It appears global warming itself is reducing the number of low clouds.

"If a large part of the decline in albedo is indeed due to feedbacks between global warming and low clouds, as some climate models indicate, we should expect rather intense warming in the future. We could see global long-term climate warming exceeding 1.5 degrees Celsius sooner than expected to date."

via Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, and European Center for Medium-Range Weather Forecasts: Helge F. Goessling, Recent global temperature surge intensified by record-low planetary albedo, Science (2024). DOI: 10.1126/science.adq7280.

Friday, January 10, 2025

Everything is Everywhere All of the Sudden


I usually don't post artist renderings like this, but this is what I see when imagining everything made of computers, using ambient energy like light to control different particles each designed to take it and do different things with it but all in one jumble of matter, like an intelligent matter: Above image: An artistic depiction of a wavelength-multiplexed diffractive optical processor for 3D quantitative phase imaging. Credit: UCLA Engineering Institute for Technology Advancement [link]

On what could be called "ubiquitous computing", a legend of artificial intelligence (Hinton) describes it really well:
(What's next in computing?) My last years at Google I was thinking about analog computing ... run these big language models in analog hardware ... if you're gonna use that low power analog computation, every piece of hardware is gonna be a bit different. And the idea is that the learning is gonna make use of the specific properties of that hardware.
--Geoffrey Hinton interview, "On Working w Ilya, Choosing Problems, and the Power of Intuition", July 2024 30min?

Researchers use 'smart' rubber structures to carry out computational tasks
May 2024, phys.org

"We now know how to design simple materials so they can process information."

The research team created a rubber computer that can act as a two-bit binary counter using slender rubber elements as mechanical bits, and assembling multiple bits together in a metamaterial.

Note: The title of their demonstration video is "Can Rubber Compute?" and I now see it all as a series of experiments like the Will It Blend series, where they just do it to everything - can crystals compute? (Yes, we already know that) Can light compute? (Yes we already know that too) Can slime mold compute? But can salt compute? (Actually yes, like in a gradient of fresh water and salt water, but I was talking about a pile of table salt.) Can my sneakers compute? (I mean obviously) Can my front door compute? (Also obvious, its whole thing is to open and close like 1/0) I'm not talking about a computer screwed on top of my doorknob, I mean the door itself, the whole thing, is a computer, just by the way its materials are put together.  The garbage can? Definitely garbage cans will compute. 

via Leiden University and AMOLF: Jingran Liu et al, Controlled pathways and sequential information processing in serially coupled mechanical hysterons, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2308414121


Using DNA origami, researchers create diamond lattice for future semiconductors of visible light
May 2024, phys.org

With headlines like that, there is no further explanation. 

via Ludwig Maximilian University of Munich: Gregor Posnjak et al, Diamond-lattice photonic crystals assembled from DNA origami, Science (2024). DOI: 10.1126/science.adl2733

Also: Hao Liu et al, Inverse design of a pyrochlore lattice of DNA origami through model-driven experiments, Science (2024). DOI: 10.1126/science.adl5549


Mechanical computer relies on kirigami cubes, not electronics
Jun 2024, phys.org

It's a mechanical computer, one that doesn't use electronics. Is that all we need to call it? A mechanical computer?

Historically, these mechanical components have been things like levers or gears. But cubes can have five or more different states. Theoretically, that means a given cube can convey not only a 1 or a 0, but also a 2, 3 or 4.

When any of the cubes are pushed up or down, this changes the geometry—or architecture—of all of the connected cubes. This can be done by pushing up or down on one of the cubes with a magnetic field. These 64-cube functional units can be grouped together into increasingly complex metastructures that allow for storing more data or for conducting more complex computations.

The cubes are connected by thin strips of elastic tape. To edit data, you have to change the configuration of functional units. That requires users to pull on the edges of the metastructure, which stretches the elastic tape and allows you to push cubes up or down. When you release the metastructure, the tape contracts, locking the cubes—and the data—in place.

"One potential application for this is that it allows for users to create three-dimensional, mechanical encryption or decryption"

via North Carolina State University: Yanbin Li et al, Reprogrammable and reconfigurable mechanical computing metastructures with stable and high-density memory, Science Advances (2024). DOI: 10.1126/sciadv.ado6476 , www.science.org/doi/10.1126/sciadv.ado6476


New material paves the way to on-chip energy harvesting
Jul 2024, phys.org

They utilize the waste heat generated during operation and convert it back into electrical energy, called "on-chip energy harvesting", and it works because they put tin in the germanium (Ge+Sn). 

via Forschungszentrum Jülich and IHP—Leibniz Institute for High Performance Microelectronics in Germany, University of Pisa, University of Bologna, University of Leeds: Omar Concepción et al, Room Temperature Lattice Thermal Conductivity of GeSn Alloys, ACS Applied Energy Materials (2024). DOI: 10.1021/acsaem.4c00275


A first physical system to learn nonlinear tasks without a traditional computer processor
Jul 2024, phys.org

They made a contrastive local learning network where components evolve on their own based on local rules without knowledge of the larger structure, similar to how neurons in the human brain don't know what other neurons are doing and yet learning emerges.

"It can learn, in a machine learning sense, to perform useful tasks, similar to a computational neural network, but it is a physical object."

(Physical object, that's the key)

"Because the way that it both calculates and learns is based on physics, it's way more interpretable. You can actually figure out what it's trying to do because you have a good handle on the underlying mechanism. That's kind of unique because a lot of other learning systems are black boxes where it's much harder to know why the network did what it did.

via University of Pennsylvania: Sam Dillavou et al, Machine learning without a processor: Emergent learning in a nonlinear analog network, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2319718121

The optical era of science reporting where every picture has rainbows in it: Artistic depiction of diffractive information processing - Ozcan Lab at UCLA - Jul 2024

Scientists demonstrate chemical reservoir computation using the formose reaction
Jul 2024, phys.org

Good explanation by the writeup author here, Tejasri Gururaj: The field of molecular computing interests researchers who wish to harness the computational power of chemical and biological systems. In these systems, the chemical reactions or molecular processes act as the reservoir computer, transforming inputs into high-dimensional outputs. ...

The formose reaction is the only example of a self-organizing reaction network with a highly non-linear topology, containing numerous positive and negative feedback loops.

The researchers used a continuous stirred tank reactor (CSTR) to implement the formose reaction. The input concentrations of four reactants—formaldehyde, dihydroxyacetone, sodium hydroxide, and calcium chloride—are controlled to modulate the reaction network's behavior.

The output molecule is identified using a mass spectrometer, which allows them to track up to 106 molecules. 

This setup can be used to do calculations, with the reactant concentrations being the input value to any function that needs to be computed.

The team showed that it could predict the behavior of a complex metabolic network model of E. coli, accurately capturing both linear and nonlinear responses to fluctuating inputs across various concentration ranges.

Furthermore, the system demonstrated the ability to forecast future states of a chaotic system (the Lorenz attractor), accurately predicting two out of three input dimensions several hours into the future.

via Institute for Molecules and Materials at Radboud University: Mathieu G. Baltussen et al, Chemical reservoir computation in a self-organizing reaction network, Nature (2024). DOI: 10.1038/s41586-024-07567-x

Thursday, January 9, 2025

Body Problems


Many Body is the New Three-Body:

Fluctuating hydrodynamics theory could describe chaotic many-body systems, study suggests
Sep 2024, phys.org

"The entire behavior of a system may be determined by a single quantity: the diffusion constant - even though the physics are very complex and chaotic at the microscopic level." This is similar to how we measure the randomness of fluctuating hydrodynamics. 

The team prepared a quantum system of ultracold cesium atoms in optical lattices in a non-equilibrium initial state and then let it evolve freely, so they could measure it. They found that despite their microscopic complexity, these systems can be described simply as a macroscopic diffusion process - similar to Brownian motion.

via Ludwig Maximilian University of Munich: Julian F. Wienand et al, Emergence of fluctuating hydrodynamics in chaotic quantum systems, Nature Physics (2024). DOI: 10.1038/s41567-024-02611-z

Totally unrelated image credit: SARS-CoV-2 blocking expression of interferons - NIAD NIH - Aug 2024


Researcher discusses a new type of collective interference effect
Sep 2024, phys.org

In our interference scenario, the particles' entanglement bridges the spatial gap between separate interferometers, introducing an interference pattern that depends on the overall quantum state of all the particles involved, and is inaccessible when one or more particles are excluded from the dynamics.

So interference patterns are influenced not only by the quantum states of the individual particles but also by the entanglement shared among some of them (like the total state).

via Department of Experimental Physics at University of Innsbruck, University of Freiburg, and Heriot-Watt University UK: Tommaso Faleo et al, Entanglement-induced collective many-body interference, Science Advances (2024). DOI: 10.1126/sciadv.adp9030


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, January 4, 2024

The Fractal Frontier


How chaos theory mediates between quantum theory and thermodynamics
Dec 2022, phys.org

Sounds important, not sure I understand:

When a large number of quantum particles are in play at the same time, the equations of quantum theory become so complicated that even the best supercomputers in the world have no chance of solving them [and therefore we can't get temperature from quantum particles, only classical ones]. 

Only where chaos prevails do the well-known rules of thermodynamics follow from quantum physics [according to their super-simulations].

[They describe a system as behaving "quantum chaotically".]

This is one of the first cases in which the interplay between three important theories has been rigorously demonstrated by many-particle computer simulations: quantum theory, thermodynamics and chaos theory.

via Institute of Theoretical Physics at Vienna University of Technology: Mahdi Kourehpaz et al, Canonical Density Matrices from Eigenstates of Mixed Systems, Entropy (2022). DOI: 10.3390/e24121740


Researchers discover superconductive images are actually 3D and disorder-driven fractals
May 2023, phys.org

"Electronic fractals" it's being called. And I guess we already know this: "Advancements with superconductivity hinge on advances in quantum materials. When electrons inside of quantum materials undergo a phase transition, the electrons can form intricate patterns, such as fractals."

But now, with better, higher resolution imaging, they see that the fractals are not just on the surface, but indeed 3-dimensional, so the entire crystal is made of them.

Sudden implication: "Correlation length -- the distance over which the nematic order maintains coherence -- is larger than the field of view of the experiment" (because you know fractals are fractional dimensions that seem to "steal" space from the higher dimension).

In case you were wondering: Superconductor Bi2-xPbzSr2-yLayCuO6+x (BSCO), that's it's name.

via Purdue, Harvard, University of Illinois at Urbana-Champaign, and Penn State: Can-Li Song et al, Critical nematic correlations throughout the superconducting doping range in Bi2-xPbzSr2-yLayCuO6+x, Nature Communications (2023). DOI: 10.1038/s41467-023-38249-3


The brain's ability to perceive space expands like the universe
Jan 2023, phys.org

Salk scientists have discovered that time spent exploring an environment causes neural representations to grow in surprising ways.

Neurons in the hippocampus essential for spatial navigation, memory, and planning represent space in a manner that conforms to a nonlinear hyperbolic geometry—a three-dimensional expanse that grows outward exponentially.

The size of that space grows with time spent in a place, increasing in a logarithmic fashion that matches the maximal possible increase in information being processed by the brain.

via the Salk Institute: Huanqiu Zhang et al, Hippocampal spatial representations exhibit a hyperbolic geometry that expands with experience, Nature Neuroscience (2022). DOI: 10.1038/s41593-022-01212-4

See also: New research finds that collective neural activity is shaped like the surface of a doughnut via Norwegian University of Science and Technology's Kavli Institute for Systems Neuroscience: Richard J. Gardner et al, Toroidal topology of population activity in grid cells, Nature (2022). DOI: 10.1038/s41586-021-04268-7

And: New method to determine the dimensionality of complex networks through hyperbolic geometry via University of Barcelona: Pedro Almagro et al, Detecting the ultra low dimensionality of real networks, Nature Communications (2022). DOI: 10.1038/s41467-022-33685-z

An artistic depiction of a wave encountering an exponentially curved spacetime - Matias Koivurova, University of Eastern Finland - 2023

Fractons as information storage: Not yet tangible, but close
May 2023, phys.org

Fuck is a fracton come on man (we're copying most of the article here, dense stuff)

Fractons are fractions of spin excitations and are not allowed to possess kinetic energy. As a consequence, they are completely stationary and immobile. This makes fractons new candidates for perfectly secure information storage. Especially since they can be moved under special conditions, namely piggyback on another quasiparticle.

"Fractons have emerged from a mathematical extension of quantum electrodynamics, in which electric fields are treated not as vectors but as tensors -- completely detached from real materials" 

In order to be able to observe fractons experimentally in the future, it is necessary to find model systems that are as simple as possible: Therefore, octahedral crystal structures with antiferromagnetically interacting corner atoms were modeled first. 

(Obviously)

...included quantum fluctuations in the calculation of this octahedral solid-state system for the first time, and see they do not enhance the visibility of fractons, but on the contrary, completely blur them, even at absolute zero temperature

via Helmholtz Association of German Research Centres, Indian Institute of Technology in Chennai: Nils Niggemann et al, Quantum Effects on Unconventional Pinch Point Singularities, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.130.196601


Punctuation in literature of major languages is intriguingly mathematical
Apr 2023, phys.org

First, can someone just tell me how an institute of nuclear physics started doing research on punctuation usage?

Punctuation turns out to be a universal and indispensable complement to the mathematical perfection of every language studied.

Thanks. 

And this isn't their first study on the topic:

"The present analyses are an extension of our earlier results on the multifractal features of sentence length variation in works of world literature. After all, what is sentence length? It is nothing more than the distance to the next specific punctuation mark— the full stop. So now we have taken all punctuation marks under a statistical magnifying glass, and we have also looked at what happens to punctuation during translation," 

The attention of the Cracow researchers was primarily drawn to the statistical distribution of the distance between consecutive punctuation marks. It soon became evident that in all the languages studied, it was best described by one of the precisely defined variants of the Weibull distribution.

The Weibull distribution is usually used to describe survival phenomena (e.g. population as a function of age), but also various physical processes, such as increasing fatigue of materials.

Further findings:

The language characterized by the lowest propensity to use punctuation is English, with Spanish not far behind; Slavic languages proved to be the most punctuation-dependent. German proved to be the exception. Its hazard function is the only one that intersects most of the curves constructed for the other languages. German punctuation thus seems to combine the punctuation features of many languages, making it a kind of Esperanto punctuation. Also, the language most faithfully transforming punctuation from the original language to the target language turned out to be German.

And here is just a great explanation of the mathematical constraints on language:

"Creating a sentence by adding one word after another while ensuring that the message is clear and unambiguous is a bit like tightening the string of a bow: it is easy at first, but becomes more demanding with each passing moment. If there are no ordering elements in the text (and this is the role of punctuation), the difficulty of interpretation increases as the string of words lengthens. A bow that is too tight can break, and a sentence that is too long can become unintelligible. Therefore, the author is faced with the necessity of 'freeing the arrow', i.e. closing a passage of text with some sort of punctuation mark. This observation applies to all the languages analyzed, so we are dealing with what could be called a linguistic law," states Dr. Tomasz Stanisz (IFJ PAN), first author of the article in question.

Also: The Journal of Chaos, Solitons and Fractals 

via The Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences: Tomasz Stanisz et al, Universal versus system-specific features of punctuation usage patterns in major Western languages, Chaos, Solitons & Fractals (2023). DOI: 10.1016/j.chaos.2023.113183

Image credit: AI Art - Ouroboros - 2023

Harnessing chaos - Simulation experiment demonstrates way to mitigate extreme weather events
Jun 2023, phys.org

Is this even real? This is the most sci fi shit I've ever heard. Diabolical, and if it wasn't from RIKEN, I wouldn't even post it; it was also part of a national competition in Japan:

RIKEN scientists have demonstrated a way to make small tweaks in weather systems as a means to prevent, or at least reduce, the severity of extreme weather events such as torrential rain. They did this by taking advantage of the chaos that is inherent to such systems. Through this work they hope to develop ways to prevent extreme weather events, which have become more common in recent years.

His group took on this challenge as part of the Japanese government's moonshot-millennia program, and in previously published work, they described the possibility of controlling weather by initiating small changes in it as it forms. At that time, they used the simple Lorenz 63 weather model, which only has a few variables, and showed that it would be possible to induce small perturbations in the system to keep it on one side of a so-called "butterfly pattern." (I don't know why they're not calling it the butterfly effect)

Their new study published in Nonlinear Processes in Geophysics goes beyond the simple model. In it, the team adopted the Lorenz 96 model. Essentially, it sets a weather variable for 40 points along a line of latitude around the Earth, and looks at how each of these points changes as it interacts with neighboring points throughout the year. Approximately once or twice a year, the points show large variations, which correspond to extreme weather events. As part of a control simulation experiment, the members of the team were able to eliminate the extreme events by making small tweaks in a 100-year run of the model.

The control simulation experiment essentially took advantage of the chaotic nature of the system; small perturbations—which might for example involve making centimeter/second changes in wind speed to prevent a typhoon with winds that are many times more powerful—done strategically ahead of time could prevent the system from entering an undesired area, meaning that they could stop extreme events from happening.

via RIKEN: Qiwen Sun et al, Control simulation experiments of extreme events with the Lorenz-96 model, Nonlinear Processes in Geophysics (2023). DOI: 10.5194/npg-30-117-2023

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.