Find a job you love and you will realize you actually love only a small fraction of it, while most of your time is spent doing the parts you don't like at all.
It is PhD application time in the UK!
Are you interested in doing a PhD with me to work on light scattering, imaging, and/or optical computing?
Then take a look at the link below and contact me!
These are fully funded PhD positions, but if you are not used to the UK system the way they work can be a bit puzzling.
In practice there is a limited number of positions to be distributed around the faculty. Prospective PhD students contact a potential supervisor and agree on a project. The faculty then shortlist the people with the best grades, there is a round of interviews, people are ranked and the top N are offered a position.
The (potential) supervisor can help with the application, but has no power to offer the position.
Haven't seen much discussion on the recent room-temperature superconductivity claims here on Mastodon (am I following the wrong people?), but before the hype hits you, here is the current state of affairs:
One numerical result shows that the suggested material should have flat eletron bands, which are consistent with (but do not prove) superconductivity (https://t.co/2m0ojMOTLr).
Until we have independent experimental replication, any hype is premature.
Just made this (as a variation on an old animation) for a talk, so why not show it here?
(hand-coded) finite element simulation of a pulse hitting a disordered medium and being scattered around. #PhysicsFactlet#ITeachPhysics#Physics#Optics
@j_bertolotti Oh this is absolutely beautiful, thank you for sharing! Are you willing to share the code for this? EDIT: whoops, I saw you linked it. Thanks!
@mattkenworthy Apart from a couple of minor changes to the way I display things (to make the scatterers more visible), the code is the same as in https://commons.wikimedia.org/wiki/File:Multiple_Scattering02.gif
which I released into the #PublicDomain a long time ago, so you are more than welcome to use it however you like 😃
#PhysicsFactlet
Common misunderstanding about #Entropy: the two configurations below have exactly the same entropy, and in both cases the entropy is zero (as you know exactly where each dot is, so there is only one possible microstate they can be in).
@j_bertolotti I like this demonstration! Is there a perspective from which the entropy of the second system is lower? Maybe if we knew something like the minimum distance between points in the box instead of the whole configuration?
@franco_vazza Let me try to be less confusing: the usual definition of entropy as being propprtional to the log of the number of microstates is not meant to be used when you can't take a statistical ensemble (e.g. the case N=1 like here). On the other hand the Kolmogorov complexity can be applied to this case too.
#PhysicsFactlet
A quantum simple pendulum.
The pendulum position is spread out, with opacity here being proportional to the probability that the pendulum is at that position at a given time. The average position of the quantum dynamics is the same as the classical pendulum dynamics (Ehrenfest theorem).
Technicalities: I used the Crank-Nicholson method to evolve the system in time. This is a 1D problem, and the only variable I considered was the angle, with the initial state being a Gaussian.
@j_bertolotti By the way, this is a fun example, thanks for sharing! Especially as it behaves differently to a harmonic oscillator. I don't have Mathematica though, so have had to try to reproduce your code using Python.
I seem to have passed the 2k followers, so I will do what I used to do on the birdsite, and make a brief (and invariably incomplete) list of people I follow, who have less than half of my follower count, and who I think you should follow. (I will exclude people who are not really active here on Mastodon)
@robinhouston Mathematical thoughts and musing. @sfera314 Visualizations of Math and Physics @lana AI, but mostly follow for the dog 😉 @DrMLHarris Science news @narain Computer science @UnsolvedMrE Recreational Math @thosgood Math, usually above my level @RobJLow Musings about Math&co @ben Making videogames @testtubegames Making educational videogames about Physics @BrunoLevy01 Computing and computational Physics
#PhysicsFactlet
If you sample N points uniformly on the unit sphere, take for each the halfway point to the north pole of the sphere, and then project is on the x-y plane, you obtain N points sampled uniformly on the unit disk.
There is no age limit to study at Uni, or to do a PhD. Actually, very often the "mature students" do much better than the young ones.
The problem is not age per se, the problem is that to study you need time and (depending on the country you are in) money. And especially time is hard to come by when you are older.
But don't let age be what stops you from studying, if you want to study.
There are many situations in the real world where small initial differences can easily grow into very large differences just out of pure chance.
Since we are on a social network, let's create a toy model* where a number of posts all have the same probability to be reposted/shared/boosted by any person seeing them. Since the more people see a post, the more people have a chance of boosting it, the posts with more visibility are also the ones that are likely to gain more visibility. So small initial fluctuations (just one or two extra boosts at the beginning) can lead a post to skyrocket in popularity, even though it is not intrinsically "better" than any of the other.
If we simulate this process numerically and make a histogram of the result, we see that the distribution of how many boosts a post had rapidly grows a tail, with most posts having no visibility whatsoever, and a few having a LOT more than the average. #ITeachPhysics#ProbabilityTheory#ToyModel
In the #Physics jargon, a "toy model" is a very simple (often unrealistic) model, which nevertheless capture the essence of the problem, without being burdened by all the real world complications. If you ever heard about spherical cows in vacuum, that is a toy model!
@mattmcirvin The normal rule of thumb is that you need data over at least two full decades before you can make any claim about power laws.
But I think it is well accepted that social networks are scale invariant graphs.
Every time I see a "xyz explained without Math" kindnof post, I always wish more people wrote explainers WITH the Math, without skipping 90% of it, so that the explanation is actually understandable without having to rely on leaps of faith.