If you have the free time I strongly recommend Graham Farmelo's new book The Universe Speaks in Numbers. My review is here.
I'd guess for most of us only the last chapter will be new, but the book is well written and entertaining even when it's covering ancient history like Dirac and Einstein :-)
Interface and colloid science is an interdisciplinary intersection of branches of chemistry, physics, nanoscience and other fields dealing with colloids, heterogeneous systems consisting of a mechanical mixture of particles between 1 nm and 1000 nm dispersed in a continuous medium. A colloidal solution is a heterogeneous mixture in which the particle size of the substance is intermediate between a true solution and a suspension, i.e. between 1–1000 nm. Smoke from a fire is an example of a colloidal system in which tiny particles of solid float in air. Just like true solutions, colloidal particles...
Just a quick doubt. What would happen if we perform the double slit expermient but instead of the screen used to obtain the interference patter we used a metal instead
I guess there would be photoelectrons, but they wouldn't affect the diffraction pattern. Light would still go through the slits and interfere to form the pattern on the screen.
As a general rule light behaves as a wave when it's propagating through space and it behaves like a particle when it is exchanging energy with something.
A photon that passes through the slits behaves like a wave when it is travelling between the slits ad the screen. Then when it hits the screen it transfers its energy to the screen and behaves like a particle.
The interference pattern is created in the region between the slits and screen where the photon is behaving like a wave.
Suppose the screen is a photographic plate. Photons interact with the plate like a particle, so one photon will create one spot on the plate i.e. it behaves like a tiny particle hitting the point at the plate and leaving a mark at the impact point.
But when you send lots of photons you find the dots build up to form the diffraction pattern.
What is a wave? From sound and water waves we come to an association with sine and cosine variational behavior. Wave equations are differential equations whose elementary solutions are sinusoidal .
In water waves and sound waves and even electromagnetic waves what is "waving", i.e. has a sinuso...
That's for electrons not photons, but the principle is the same.
"There is obviously interference, yet each particle also collapses to a single point when it hits the film. Which means that when the interference occurs each particle is travelling alone thus not being interfered with by anything else. Each particle, in essence, interferes with itself.
Every so often people would come up with new interpretations of this phenomena. It used to be said that each electron's probability distribution act as a wave thus interfere with itself. Now it is said that electrons are just excitations in the electric field "
Particles are described by quantum field theory, where they are excitations in a field. In some circumstances it is a good approximation to describe as particles and in other circumstances it is a good approximation to describe them as waves. But both of these are just approximations.
It is important to understand that an electron or photon isn't sometimes a particle and sometimes a wave. It is a quantum field that sometimes behaves like a particle and sometimes behaves like a wave.
I mean a LOT of chemistry is explained by thinking of electrons as particles(basicity of compounds,electronegativity and so on). How would we able to explain these effects by thinking of electrons as waves(even approximately)
I'd say the novelty was that these objects were discrete. Your detector could catch/eat/consume a discrete quantum of the field, it would also seemingly "disappear" from the other detector, something that classical fields don't do. Hence the "mechanics" of "quanta".
Also the vacuum noise, which leads to a lot of fun things like the Casmir effect, or the less well known tendency for light in a vacuum to experience chromatic dispersion because it hits stuff.
You need Quantum Electrodynamics (QED) to understand vacuum polarization. In a nut shell, imagine that the vacuum is filled with virtual electron-positron pairs, and as the high-energy light propagates it interacts with these pairs and they separate creating a polarization-like effect. In some ...
I hope this is the right place to ask. If not I will delete and ask somexhere else (where though?). I noticed there is a star I can click next to vote arrows close to questions title. So I thought I could bookmark them this way, but I cannot see any effect, nor can I find a list where those marke...
I really like to think quantum fields are neither waves nor particles. It just when given a correct circumstances, it interacts in a way that is similar to how particle or waves interact with something, but it is always a quanutm field, never suddenly becoming something else
The thing that makes QFT much less straightforward is there isn't really much place one can build an ontology from the mathematical formulism without risk overinterpreting with classical intuition
e.g. as Acuriousmind once reminded me, that the quantum field is really an infinite dimensional generalisation of e.g. momentum operator, thus nothing is actually physically produced when we operate a quantum field onto a quantum state in the mathematics. It is only the expectation value that has physical meaning
I mean, a computer program which to the question of the form "Does x exist?" or "Does x not exist," returns the answer "x both exists and does not exist." is computable. That "phrase" or answer can be computed. Even though the answer itself is computable, it expresses something that is not computable (we cannot simulate a universe where x both is and is not). @Wolphramjonny — nielsbohrden13 mins ago
This reminds me a lot of the person trying to push the idea that if they could get a computer program to print X = X and X =/= X it proved we were a simulation or something
The rarest thing in our universe is not antimatter
It's dialetheia
In fact, I will bet that given unbounded amount of time, the probability of having a physical infinity is much much closer to certainty than the probability of obtaining a dialetheia object
@JMac not sure how a device built under the principle that the LNC is absolute could violate said LNC...not sure how a potential violation would also indicate anything more than a broke computer...
@KyleKanos That was what all the comments on the question had tried to explain, but the OP kept insisting that it "represented something physical" and therefore for some convoluted reason had to be describing something physical because he could make a program output seemingly contradictory statements
the worst part IMO was he basically just made it print out "A = True; A = False" and conclude that it necessarily meant the program considered it both true and false. From my limited understanding of code, it seemed more like they were changing A from true to false and printing both results
@JMac seems like that's the equivalent of treating whether a coin is heads/tails as an immutable fact of the universe, and then acting shocked when it changes
@ACuriousMind Yeah, they basically did that, but added in a step where it printed based off the status of a variable, and then just changed that variable between calls so that it was true, then false. I might be remembering wrong, but I'm pretty sure it was that trivial
Interpreting the challenge too literally
That is, if the challenge says "write a function that, given a number n, returns the n-th prime", posting something equivalent to:
function f($n) {
return "the $n-th prime";
}
I am working with a 4-bar linkage system that i'm modeling in sympy. I've got the equations worked out for how the system behaves, but i have some questions about how dynamical systems work
Specifically, suppose I have like a pendulum with a spring.
I can plot a graph of the position of the mass at the end through time.
But let's suppose I change one of the parameters, like the length of the rod or the size of the mass or the spring constant.
Then the paths it would sweep out would be different.
@KyleKanos When I studied mechanisms, we definitely didn't learn one. The process basically worked out to "play around with parameters until you get the desired motion", except for a couple specific mechanisms that were a bit more studied. Designing a 6-bar mechanism for example was just a mess of excel spreadsheets that related how each input would change the output, and we just adjusted the lengths and stuff
You could try a minimization technique to get the parameter space down, but it's basically going to be getting the trajectory for each possible input, comparing the computed to the given & adjusting
@StanShunpike You mention you're modelling a 4-bar mechanism, are you modelling them as rigid members? If so, I'm not sure how related this spring pendulum example will be (unless you only intended that to show what you wanted to plot)
Yeah, I would just work it the other way around with your code, make a code that can plot the trajectory based on your inputs, then just play around until you get the desired trajectory
Ok, that makes a lot of sense. Do you know what kind of algorithms are used to like try to make a system like a pendulum match a particular trajectory?
@KyleKanos like make a program that generates the output based on input, and then use a numerical method that adjusts the parameters until the desired output is approximately right? Even if that's not specifically what you meant, I've never thought of it like that before but that makes a lot of sense
Yeah, that method makes a ton of sense. I don't know if I'll ever be in a position to apply it, but I need to try to remember that one. Almost tempted to bust out some old textbooks and try it out
@KyleKanos I could see it being complicated to actually get a good implementation... but compared to trying to figure out an analytical method that can start with desired trajectory and output the mechanism requirements, that method seems pretty simple
@Stan hi havent seen you in ages. did analyze something vaguely similar in college mechatronics class, we used fourier analysis to find 1 out of 2 motors with messed up bearings.
@vzn nice to see you guys too! well, i completed my undergrad in econ and decided i didn't like econ, and am going back to doing physics related things. currently taking a robotics class.
@StanShunpike amazing that was going to be my next question! congrats on your new degree + return! robotics is such a great field too. for your problem my question is, its not clear what the motors are doing on the pendulums...?
Well, I haven't worked that out specifically yet the mechanics. I'm envisioning a robot where a motor fails but a situation where we have no sensors and need to make inference.
Currently, this is my first robotics course and the professor emphasizes probabilistic graphical models, with little consideration for use in actual mechanical settings
His emphasis is more on topics like Kalman filters and SLAM
So I don't have a specific example off hand of what the motors are doing yet.
@StanShunpike if the motors are doing something rhythmic and not random, then fourier analysis probably would do a lot. my "application" was maybe from control system theory or monitoring, mechanical engineering, mechatronics etc, not sure the exact subfield... also it sounds a lot like machine learning might be applicable to your general idea. its making a lot of new inroads into physics & many science areas these days...
@StanShunpike statistics, great choice! and ML is very strongly connected to statistics these days, aka "data science". yes "low sample sizes" can be a difficult aspect of robotics + ML... is this a masters project? simulations are increasingly acceptable/ applied in robotics... eg google is going a lot in that direction... its basically an ML classification problem...
:) the idea is you have a lot of physical inputs into the ML system and it classifies as ok vs broken etc... via training... the time series aspect of this makes it harder for ML which is maybe better suited to "instantaneous" physical classifications...
@StanShunpike the ML has to monitor a timerange of data before it can make a decision, a single sample in time probably isnt enough to differentiate. yes the way to feed the time series data would be part of the analysis/ decomposition. you could maybe feed a fixed set of points/ samples over n seconds as the training vector etc.
@StanShunpike yes, in Reinforcement Learning the Bellman equation is a Fredholm equation of the second kind. So you can do, e.g. light transport using reinforcement learning algorithms
@enumaris yes ML is really taking off in cosmology! almost a killer (science) app for physics ML so to speak. but think it will have wideranging impact on many areas of physics & we're seeing early days.
@enumaris maybe heard some about that. ML is going to be Very Big in scene generation in near future. reminds me, did you ever see this site? extraordinary, it was announced earlier this year thispersondoesnotexist.com
@enumaris thats wild. it's amazing. because the examples in ML classes tend to ignore physics, which is actually a shame now that im thinking about it because its so useful for robotics systems as well as other things in physics
@StanShunpike ML is finally really starting to take off Bigtime in robotics, paradigm shift in play, have seen a few refs on that recently... am expecting really big breakthroughs in "motion planning" etc... you guys have seen boston dynamics spotmini havent you? very smooth/ lifelike/ biological-looking motions, basically all ML afaik... (would like to learn more about their algorithms)
@StanShunpike billions of dollars are riding on "artificial scene generation" in video games and movies. ML is starting to make inroads as in the nvidia research. it can create more than just scenes, it can create artificial worlds...
@enumaris am very excited by it too lately its a huge "gamechanger" o_O think its way cool that youre doing it on a pro level, the field is very vibrant/ dynamic these days, very long dreaming of working in it, but itd be a tricky "lateral" move for me at this point...
@StanShunpike my current area of research is kinda like conversational AI...natural language understanding, human dialogue understanding...that kind of stuff
if I had to put my "expertise" into topics, I would say Physics, Deep Learning, and NLU
the 3-D rendering interest comes from my interest in deep learning
@StanShunpike my day job is java + database + ui, but like to/ enjoy tracking cutting edge stuff from CS for yrs etc... recently researched/ blogged quite a bit on AGI...
My most recent question (Why do we assume fundamental properties like charge or mass do not consume anything?) was put on hold given the following reason:
"We deal with mainstream physics here. Questions about the general correctness of unpublished personal theories are off topic, although specif...
In Einstein's book about relativity, he says that his theory predicts that the shape of the universe would be finite but unbounded.
But how is this possible?
What's the difference between an infinite and an unbounded universe?
Therefore, what does it mean for a universe to be "finite but unbo...
This may sound like a silly question but I believe it is not. I recently deleted a question in order to rewrite it, as there were (a lot of) concerns regarding the definitions used and more generally its tone and clarity. But the system has no way to tell if I intend to undelete at some point or ...