#PhysicsJournalClub "Temperature as joules per bit" by C.A. Bédard, S. Berthelette, X. Coiteux-Roy, and S. Wolf Am. J. Phys. 93, 390 (2025) doi.org/10.1119/5.01... 🧵1/ #Physics #Entropy #Thermodynamics

Temperature as joules per bit

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"Temperature as joules per bit"
by C.A. Bédard, S. Berthelette, X. Coiteux-Roy, and S. Wolf

Am. J. Phys. 93, 390 (2025)
https://doi.org/10.1119/5.0198820

Entropy is an important but largely misunderstood quantity. A lot of this confusion arise from its original formulation within the framework of Thermodynamics. Looking at it from a microscopic point of view (i.e. approaching it as a Statistical Mechanics problem) makes it a lot more digestible, but its ties to Thermodynamics still creates a lot of unnecessary complications.
In this paper the authors suggest that by removing the forced connection between entropy and the Kelvin temperature scale, one can rethink entropy purely in terms of information capacity of a Physical system, which takes away a lot of the difficulties usually plaguing the understanding of what entropy is actually about.
I don't think the SI will ever consider their suggestion to remove Kelvins as a fundamental unit and include bits, but this paper will be a great boon to any student banging their head against the idea of entropy for the first (or second, or third) time.

#Physics #Entropy #Thermodynamics #StatisticalMechanics

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"Direct observation of colloidal quasicrystallization"
by Y. Gao, B. Sprinkle, DWM Marr, and N. Wu

Nat. Phys. (2025)
doi.org/10.1038/s41567-025-02859-z

Quasicrystals are weird. When you solidify something it tends to get into a high-order state: a crystal. If you cool it down too fast so it doesn't manage to make a monocrystal it will form a polycrystalline state or, worse case scenario, something completely amorphous like a glass.
But quasicrystals are weird. They are ordered structures that lack a periodicity and making them is not easy.
In this paper the authors show how paramagnetic colloidal microspheres (i.e. big enough to be clearly visible under a microscope) subject to an electromagnetic field spontaneously arrange themselves into a quasicrystal.

This is 100% not my field, but the ability to create quasicrystals on demand looks so cool!

#Physics #Chemistry #Quasicrystal

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F. Diacu "The Solution of the n-body Problem"
Math. Intell. 18, 66 (1996)
https://doi.org/10.1007/BF03024313

In Physics we are often guilty of cutting corners when it comes to Mathematics (to be honest, we are in very good company). One example is in Chaos theory, where statements like "the 3-body problem is unsolvable" are common but misleading.
The author of this paper actually complains about his fellow Mathematicians colleagues (not about Physicists), and then explain in a very understandable way how the sentence "the 3-body problem is unsolvable" must be understood (spoiler: it just means we have fewer conserved quantities than degrees of freedom), how a full solution to the n-body problem in terms of an infinite but convergent series had been found already in 1991 by a Chinese student, and how this solution (albeit correct) is completely useless for any practical purpose, as it converges horribly slow.

An easy and very interesting reading if you know just a little bit about classical mechanics.

#Chaos #3bodyProblem

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Today a paper I contributed to!

S. Kendall et al. "Dynamically reconfigurable 2D polarization-agnostic image edge-detection using nonvolatile phase-change metasurfaces"

Optics Express 33, 8971 (2025)
https://doi.org/10.1364/OE.543602

Phase-change materials are media with two metastable solid phases (usually an amorphous and a crystalline phase) with different optical properties. They are commonly used in CD/DVDs where you can use a laser to melt a small volume of the material and let it solidify in the phase you prefer (depending on how fast you let it cool down), creating a binary pattern in the refractive index which encode whatever data you wanted to write.

Beside their use in data storage, phase-changing materials can be used to create structures with two different optical responses, that can be switched at will*.

In this paper we show (simulations only so far, but the experimental results are coming) how to design a structure that is either transparent, or highlight the edges of any image passing through it.

* Caveats apply.

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"Three-dimensional holographic imaging of incoherent objects through scattering media"
by Y. Baek, H. de Aguiar and @sylvaingigan
https://arxiv.org/abs/2502.01475
#optics #physics #imaging

As you daily experience anytime you look at anything, light scattering severely impairs your ability to image (mild scattering like mist makes things in a distance fuzzy, strong scattering like your own body makes it completely impossible to see what is happening inside or behind it). On one hand this is good, as it allows us to see where (e.g.) trees are so we don't bump into them. On the other hand there are a LOT of situations where you would really like to see what is going on behind a scattering medium (surely it would save a lot of exploratory surgeries).
The problem of imaging through a scattering medium is largely unsolvable in its most general form, but there are a lot of special cases where you can go surprisingly far, and people (me included) have spent a lot of time checking exactly how far.

In this paper the authors consider a set of small fluorescent objects behind a not-too-thick scattering medium, and look for a way to retrieve their 3D arrangement.
Problem: fluorescent emission means incoherent emission, so the phase information (which encodes a lot of information about position) is lost. Still, we can rely on the assumption that there is a finite (ideally not too large) amount of point emitters. Since each emitter is point-like, if we only measure the light that reaches us through the scattering medium at a single frequency (to be more realistic, a small bandwidth), we will see the incoherent sum of a speckle pattern per fluorescent emitter.
1/2

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"Emergence of collective oscillations in massive human crowds"
by Francois Gu et al.
Nature 638, 112 (2025)
https://doi.org/10.1038/s41586-024-08514-6

The flow of granular media (think nuts or sand in a pipe) is a notoriously difficult system to deal with, with a smooth flow suddenly turning into a jam that completely prevents any movement.
People moving is even harder, because most of us (not all) look where we go and make some sort of informed decision about how to move next depending on our surrounding. If there is a lot of space things tend to go smoothly, but what if there is a LOT of people?

In the paper the authors record and analyse people movement at the San Fermín festival in Pamplona (Spain). Before the beginning of the run, there is a lot of people pressed in a not too big square. When the density passes 4 people per m² they observe the spontaneous creation of localized group movement along circles ("vortices") for no apparent reason. The paper contains a lot of discussion on how one can model this.

Do I understand the deep reason for this? NO.
Is this utterly fascinating? Yes.
Do I wish I could replicate this at Saint Ubaldo day in Gubbio (https://en.wikipedia.org/wiki/Saint_Ubaldo_Day)? Totally YES!!! 😀

#PhysicsJournalClub "Emergence of collective oscillations in massive human crowds" by Francois Gu et al. Nature 638, 112 (2025) a (short) 🧵 1/ 🧪🎢⚛️

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"The Tumultuous Birth of Quantum Mechanics"
by Philip Ball

https://physics.aps.org/articles/v18/24

"quantum mechanics wasn’t created all at once. It took several decades and was a messy, confused process, during most of which the true nature of this revolution was obscure. In some ways it still is."

#QuantumMechanics #HistoryOfScience #Physics

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"Anderson Transition for Light in a Three-Dimensional Random Medium"
by A. Yamilov, H. Cao, and S. Skipetrov
Phys. Rev. Lett. 134, 046302 (2025)

Anderson localization is a phenomenon where wave interference in a disordered scattering medium results in the wave being unable to propagate. It is a fascinating, complex, and VERY niche topic.
It is also the centre of never-ending arguments.

Anderson localization was originally proposed as a mechanism to explain why certain spin states in metals full of impurities would take longer to relax than expected (the answer was: their quantum state could not propagate due to the disorder). [https://www.nobelprize.org/uploads/2018/06/anderson-lecture-1.pdf]
It was soon realized that electron-electron interaction would dominate over a pure "Anderson localization" in most solid state systems, where a similar effect ("Mott insulation") would dominate.

The topic had a resurgence when it became clear that Anderson localization was a general wave phenomenon, and it wasn't restricted to electrons, but could in principle happen to any wave, e.g. sound or light. [https://doi.org/10.1103/PhysRevLett.58.2486]
Due to its nature, Anderson localization is easier to achieve the lower the dimensionality of the system is. Anderson localization of (ultra)sound in 1D and 2D were quickly discovered, with light coming a few years later.

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"Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks"
by S. Sunada et. al.
Phys. Rev. Lett. 134, 017301 (2025)

I am not a big fan of generative AI, especially in the form it is sold and advertised today, bvut I think that there is a lot of cool and potentially useful research been done in the field of Machine Learning. In particular I am very interested in approaches where most of the heavy lifting is left to Physics, i.e. the Physical system naturally does stuff, and you exploit it for Machine learning, instead of spending a ton of resources and energy to create and manipulate the whole neural network.
In this paper the authors borrow ideas from different sub-fields to put together a training method that doesn't really need to know much about what the Physical system is actually doing, and doesn't need an accurate control of the Physical system either.
I admit I understand no more than 10% of what they say (Machine Learning is definitively not my field), but it looks interesting and promising!
https://doi.org/10.1103/PhysRevLett.134.017301
#MachineLearning #Physics

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"Testing the necessity of complex numbers in traditional quantum theory with quantum computers"
by Jarrett L. Lancaster and Nicholas M. Palladino
Am. J. Phys. 93, 110 (2025)

In classical electrodynamics the use of complex numbers is only due to to its convenience for calculations. Nobody wants to remember all those pesky trigonometric identities, so we use complex numbers to simplify calculations and take the real part at the end. You need to be a bit careful when calculating stuff like the Poynting vector, but this is well addressed ion any half-decent undergrad-level textbook.
But for quantum mechanics the problem is less obvious. On one hand we only ever measure real quantities, but on the other hand the imaginary unit appears explicitly in the Schrödinger equation, and no textbook I am aware of ever even mention the possibility that quantum numbers might be just a calculation convenience like it is in classical electrodynamics.
The question is subtle enough that you are going to find no shortage of well-read Physicists claiming that it is "obvious" that complex numbers are necessary for quantum mechanics, or that it is "obvious" that you could just use real numbers if you wanted.
This paper makes a pretty good job at explaining the problem, going through some of the history and explicit calculations, up to constructing explicitly a real-valued version of QM.
The second part, where they make an "experiment" on a IBM cloud quantum computer is (imho) less interesting, and their conclusion that you need indeed complex numbers not really supported by the evidence, but your mileage might vary 🙂
https://pubs.aip.org/aapt/ajp/article/93/1/110/3327097/Testing-the-necessity-of-complex-numbers-in

#Physics #QuantumMechanics #ITeachPhysics