‘Impossible’ particle discovery adds key piece to the strong force puzzle
quantamagazine.org
quantamagazine.org
So in these situations how do you tell apart electrons from one source compared to another? In the article they mention how the LHC collides particles at a rate of "40 million times each second". I can imagine there are a lot of electrons and other particles flying around from other collisions. What makes an electron discernible between one type of particle and another?
The point is, we cannot tell which pair of electrons/muons come from the decay of a specific particle, but we can tell how many extra occurred beyond what we would expect from all other known processes.
If you don't mind my asking, what are you doing now after spending years studying such a specific area of particle physics?
Some of the best data for branching ratios comes from e+e- (electon-positron) colliders such as LEP (literally, the Large Electron-Positron collider). In these colliders, we can fine-tune the energy to produce massive amounts of particles we care about. From that, we can see how they decay. Mostly, Upsilons decay into massive sprays of hadrons and leptons (called jets in particle physics). These can come from decaying Tau particles (the much much heavier cousins of muons and electons) or from quarks/hadrons decaying over and over and over again into things like Kaons, pions, muons, electrons, photons, and other lightish particles. In the relatively clean environment of a e+e- collider, we can reconstruct these jets and determine which may have come from Upsilons. Combining this with a whole bunch of other measurements (and some theory) lets us determine the branching ratio (how often a particle decays into certain things).
The scattering matrix is calculated by including all the possible interactions you expect. So a matrix including some intermediate C will be different from one that does not.
Then you can line up what you actually observe and select the matrix that most accurately describes it.
The extra path does not necessarily raise the probability. The interactions are more complex than that. The simplest thing to say is that it affects the distribution.
It's 511 keV at rest, and you are sensing a 4.73 GeV electron coming out of the decaying Upsilon. E=m and c=1 in the units you are using.
https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampli...
This answer simplifies alot and of course,one only gains a stop-motion picture show of the observed phenomena, but none the less..
That depends on what you mean by "complicated". Conceptually they are not too bad, it's basically just quantum field theory (which some might consider "incredibly complicated" so YMMV). But the devil is in the details. From the article:
"While physicists know the exact equation that defines the strong force — the fundamental force that binds quarks together to make the protons and neutrons in the hearts of atoms, as well as other composite particles like tetraquarks — they can rarely solve this strange, endlessly iterative equation, so they struggle to predict the strong force’s effects."
> Are there open source implementations of these models
That I don't know.
> and if so, would the code make any sense to a non-physicist programmer?
Having seen code written by scientists, I can confidently answer this with: almost certainly not.
Got a kick out of that, thanks. I think there is a kind of compartmentalization of environments going on when one engages in scientific programming. It seems to often be structured more akin to math than code. I once worked with a brilliant multitalented individual who held a PhD in a specific field of physics that I cannot recall. In one instance they ported the orchestration software for a supercomputer from python into java, in a week. It was beautiful to read. This same person used single letter variables in their ML models and had virtually zero comments which made it somewhat difficult for me to follow their updates after a week of having not seen the code.
Physical engineers, especially, have a very formalized, standardized way of looking at the world. They all share it, and so their code follows from that.
Physicists, biologists, software developers all have different ways of looking at the world (some more standardized, some less). Our code follows from that.
So while we may gripe they don't leverage (insert language arcana / convention), my intuition is our code would still look very different even if they did. Biggest example, as you point out: math-structured code, from math-heavy disciplines.
But the OP didn't ask if the code was good (or "solid"), they asked if it would make any sense to a non-physicist programmer. And the answer to that question, I'm guessing, is most likely not. But I would be very happy if I turned out to be wrong about that.
There are a variety of open-source implementations; I’ll just point to a few. The one funded by the Department of Energy through the SciDAC program is the USQCD software stack [0]. There’s also the GPU library quda, which is maintained by Nvidia employees (and others in the community). There’s Grid [2], development led by Edinburgh in close collaboration with intel (to make sure it compiles down to sensible high-performance primatives). There’s openQCD [3], coordinated by CERN researchers.
As to whether it’ll be readable to you—-maybe? How transparent each library is differs. The most important parts are typically (1) the generation of gauge configurations (typically by HMC, which was discovered by the LQCD community [4]), which are MCMC samples and (2) the calculation of observable on each sample. Both rely on highly optimized (and preconditioned, and maybe multigrid-ed) linear solves—-the most important kernel.
Some libraries are written to be as transparent as possible; some to be as portable as possible. All are written to handle massive data parallelism across hundreds of high-performance nodes with some mixture of OpenMP, MPI, #pragma acceleration, etc.
Finally, the code will only “make (big picture) sense” to you if you understand lattice quantum field theory.
[0] http://usqcd-software.github.io/ [1] http://lattice.github.io/quda/ [2] https://github.com/paboyle/Grid [3] https://luscher.web.cern.ch/luscher/openQCD/ [4] https://www.sciencedirect.com/science/article/abs/pii/037026...
The three body problem can generally be acceptably approximated for a reasonable period of time. But that problem only involves inverse squaring of distances. Strong forces decay much faster than that, which makes them more sensitive to errors. Plus you end up with one of the fundamental problems we have trying to understand our universe, which is just how monstrously enormous and monstrously slow we humans are. We operate at "meter" scales and "second" time frames, and particle physics operates at somewhere around 30 and 40 orders of magnitude smaller, respectively. (Not quite all the way down to the Planck sizes, but closer to those than to the macroscopic world.) So when you try to numerically approximate the differential equations, you don't get very far in time or space before your approximations have critically diverged from reality.
It's like we're trying to work out the fundamentals of chemistry and our primary tool is smashing planets together.
However, it's very misleading to call quintic equations unsolvable, because we know where the solutions are, and we can use various numeric methods to calculate the solution with arbitrary precision. Any time we can calculate the answer with as much precision as we want, I'd like to say that the problem is "solved" in a very real and meaningful way.
The problem is worse with quantum mechanics. With quantum mechanics, not only do we lack analytic solutions to many of the equations used in QM, but we also lack good numeric solutions (using real hardware, at least).
Is it that we haven't discovered the solution generating algorithms? That the state/probabilities of quantum mechanics are fundamentally untenable to similar calculation? Or something else entirely?
Electrodynamics is like that. There is a number, the fine structure constant, about 1/137, that gives the natural scale for how big the next step in the approximation is, compared to the size of the current step. So, if I need to know the answer to 1 part in 10^9, I’m going to need to do 4 or 5 steps of fixing up the approximation (each fix, of course, being a great deal more arduous).
QCD, and other “strongly coupled” or “non-perturbative” problems are not like that. If you make the dumbest approximation (flat-earth) and then fix it up a bit (sphere earth), answers don’t change just a little. They change completely. In QCD the number that characterizes the “obvious” approximation (the Feynman diagram approach)—-the number that’s 1/137 for electrodynamics—-is about 1.5. That’s a disaster! The approximation scheme is obviously no good—-you learn that you can never stop improving your approximation, because if you only worked “a little harder” your answer could change completely.
Other approaches are required.
There is no known way to simulate a quantum computer, using a classical computer, in polynomial time. A quantum computer is just a kind of quantum system, so we know that some quantum systems cannot be efficiently modeled (barring revolutionary advances in simulation algorithms).
When your simulations take superpolynomial time, it tends to be easy to find problems which you simply do not have the computational resources to solve, and you may not be able to solve interesting versions of the problem. There are lots of examples of problems like this. However, I don't consider this to be a fundamental difference.
For example, satellite navigation systems are just fine calculating directions for driving all the way across the continental US, even though that's a very "large" instance of the problem that they are solving. But if you try to find the fastest route for a delivery driver to make a hundred deliveries within one city, good luck. This is just an analogy, and I'd like to emphasize that "no KNOWN algorithm" efficiently solves these problems, and that we haven't proven whether such an algorithm exists.
If your computer doesn't have that capability, you can simulate it to arbitrary precision with ~2^n bits.
there are some open source packages for lattice QCD. e.g. https://jeffersonlab.github.io/chroma/
Not my field of expertise though, I am in experimental gamma-ray astronomy
Poetic and informative. What a sentence.
This seems to be discovery within standard model. A new composite particle.
Sabine's blog exists in an interesting superposition of comforting and existential dread =]
If this is about Sabine Hossenfelder, she has opinions and she has arguments. Sometimes she’s right, sometimes she’s wrong. Like everyone. Sometimes her opinions are well supported, sometimes I think not. Some of her explanations are sound, others contain mistakes.
However, life is about trusting other people and adopting their opinions. I do not have the time or energy to be an expert on every subject, so naturally I will have to read the opinions of other people who have spent time in that particular subject.
Someone's previous record of factual accuracy as well as considering reasonable opposition to their points obviously will affect how much I trust them to influence my worldview, and how likely I am to believe what they say is true.
[1] https://www.sciencedirect.com/science/article/abs/pii/S13552...
"To those who still cling to a single-universe world-view, I issue this challenge: explain how Shor’s algorithm works. I do not merely mean predict that it will work, which is merely a matter of solving a few uncontroversial equations. I mean provide an explanation. When Shor’s algorithm has factorized a number, using 10^500 or so times the computational resources than can be seen to be present, where was the number factorized? There are only about 10^80 atoms in the entire visible universe, an utterly minuscule number compared with 10^500. So if the visible universe were the extent of physical reality, physical reality would not even remotely contain the resources required to factorize such a large number. Who did factorize it, then? How, and where, was the computation performed?"
Computation is real - it requires matter and energy. If Shor's algorithm can factor a number so large that it would require more matter than there is available in the universe: _where is the computation occurring_? I have never seen this plainly addressed. I'm a layman, of course, which I why I would hope she'd break this argument down in her MWI video.
The author doesn't have to answer that question to dispute Deutsch's alleged answer.
Secondly, Deutsch's challenge of explaining Shor's algorithm presupposes that quantum computation requires an explanation in terms of classical computation. While I'm sympathetic to that view, this assumption is easily rejected by people who don't view reality as fundamentally classical or local. So for these people, there is no challenge to meet.
Thirdly, while you can speculate that Shor's algorithm will scale to factoring numbers so large they require more atoms than are in the universe, no one has demonstrated that this is the case. Just because our current models describe this happening, that doesn't mean the model corresponds to what will actually happen in reality. It could easily be the case that the model is not accounting for noise or other factors that will prevent entanglement from scaling to the levels you describe. This is the position of some determinists, in which case Deutsch's challenge is also neutered.
Finally, other interpretations of QM can also provide explanations for speedups. For instance, any interpretation of QM that accepts its non-locality has an escape hatch via relativity: non-locality is effectively time travel in GR, but in a form that cannot be exploited for superluminal signalling. There are many other possible answers given by other interpretations of QM.
I personally think it's an interesting question, but it's not a compelling argument for many worlds, not least because the "many worlds as parallel computations" doesn't actually work beyond trivial examples.
> Computation is real - it requires matter and energy.
Yes, classical bits require a certain amount of matter and energy, but qubits do not have the same matter and energy requirements, which seems to be what you're expecting. If you expect there to be an answer of this sort, then I think you must give up believing that quantum computation will scale. Basically, you are expecting reality to actually be classical, and so have some deterministic classical computation happening behind the scenes (hidden variables), and these hidden variables will more than likely disrupt scaling quantum computations.
Should this be read as 10^80? The way it's written is confusing.
Those sentences should be like this: "When Shor’s algorithm has factorized a number, using 10^500 or so times the computational resources than can be seen to be present, where was the number factorized? There are only about 10^80 atoms in the entire visible universe, an utterly minuscule number compared with 10^500."
So, I get the drift of the article. Do I have enough knowledge to make any reasonable assumptions about the validity of the findings it presents? Nope, not at all.
That's why I cherish Sabine. She's down to earth and has an understanding of science that suits me. She's definitely more than enough physics under her belt[0] to be qualified to talk about these topics. Go away with your 'She not an expert'. Have you seen her qualifications?
"Naw," I hear you say "she's a theoretical physicist, not a particle physicist."
Yeah, well. I'm a Software Engineer. I can still tell if a Network Engineer tells bullshit.
I do understand why some people hate on her; she's abrasive and irreverent. Some people don't like their ivory towers to be besmirched.
[0] https://portal.dnb.de/opac/simpleSearch?reset=true&cqlMode=t...