The Standard Model is Intuitive | Feynman Diagrams, Gauge Symmetries, and more

What actually is the Standard Model, and what does symmetry have to do with it? By following the theoretical arguments of Feynman, concepts like Quantum Field Theory and Feynman diagrams become surprisingly accessible.
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Timestamps:
0:00 - Intro
1:17 - Global vs Local waves
3:17 - Quantum Fields
4:20 - Feynman Diagrams
7:12 - KE, Mass, and interaction terms
11:19 - Adding symmetries
13:05 - Minimal Subsitution
15:03 - SU(3) and the Strong Force
18:31 - Beyond the concepts
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Music: Mark Tyner - Close To You

[@lexinwonderland5741]

great work as always, m8! it's such a shame there's not more likes and viewers -- your content is fantastic and connects the gap that i find so frustrating!! it's always either dry lectures or cutesy conceptuals for laymen. god BLESS you for actually explaining some of the math and why this happens the way it does!!!!! please please please please PLEASE keep up the good work!!

[@mindmaster107]

Thank you so much for your kind words!

[@lexinwonderland5741]

@@mindmaster107 thank you so much for your great work! Thank us by making more content!

[@meek6173]

Great video!! I'm currently doing a directed reading program at my university on QFT and never really understood the real intuition behind a vertex Feynman diagram and how it relates to the evolution of coupled fields. I'd love to watch more content on QFT if you ever decide to pursue that

[@user-xk9lg6xe5z]

have been waiting for the next upload and coincidentally, I'm taking nuclear and particle physics course this semester, so this really helps! Thank you XD

[@Jaylooker]

Gauges having symmetries sound like groups. Gauges describe the interactions using something that looks like a generating function at 11:10. Groups have associated generating functions by Molien’s theorem.

[@michael_v2624]

this was an amazing summary on quantum mechanics and standard model particle physics. I was making my way struggling through my computer science math courses. linear algebra and spent some time studying quantum computing, qiskit by IBM. Eigenchris's videos on the fundementals of physics really helped me grasp the matrices, tensors, and basics of QFT and history of wave interferience, entanglement, and mathematical techniques. Although most of the physics equations are out of my reach (complex & real analysis, calculus 3 manifolds), various fluid dynamics and astrophysics. I have a deeper understanding of the mathematical fields underlying encryption algorithms, shor's algorithm for polynomial NP problems, grover's alogirthm & galois theory for determining solutions are possible for 5 root polynomials. Linear algebra vector and matrices transformations was useful but had a hard time grasping. Now onto study rational root theorems, Fourier transforms (Karatsuba multiplication), primes equations & derivations, group & set theory. Math and computer science here we come. Honestly electromagnetism fields and circuits in electrical engineerings still scare me. Even the reimman einstein stuff is intimidating, but always had an interest in space-time and this was an amzing overview as were your other videos. Zap, eigenchris & mindmaster107. there's a few others but you guys were my self-education in QFT. + various history and mathematical concepts from other channels. thanks to 3B1B for the youtube math community!

[@mindmaster107]

Thank you so much for your detailed reply! It’s great to know I was of help learning such a large and important topic. It’s a lucky coincidence that you mentioned riemannian einstein stuff as being intimidating, because those were the first 2 videos I’ve ever made! I have a video on riemannian curvature that should be quite nice. The special relativity video also goes over special relativity + basic general relativity in as much detail as it needs without the super high difficulty mathematics. I hope I can continue to make good videos and to inspire more people into university level physics!

[@chapaj3000]

Thank you for this simple and understandable video! 😊

[@muscovado09]

Aw lawd the bear guy uploaded 😄

[@shreyashdwived8178]

I am very glad you came back, love your videos

[@mindmaster107]

I'm making them between projects, so I'll not gone. I'll make quite a few more when holidays roll around, so just keep an eye on that :D

[@cycklist]

This is wonderful. Thank you.

[@Leo-if5tn]

Great video!

[@FlavioLanfranconi]

Great work.

[@amritawasthi7030]

Damn this is impressive idk why there are so less views. Thank you for the video

[@mindmaster107]

It’s not the most accessible of topics, being a 4th year physics module, so KZbin’s algorithm isn’t sure who exactly to send it to. If you know anyone else who might enjoy this video, send it their way and thats the most I can ask for!

[@amritawasthi7030]

@@mindmaster107 for sure, I'll send it to all my phys friends. Keep up the good work.

[@满地走]

PHYSICS BEAR JUMPSCARE !!!! awesome video it has been a while since u last uploaded lol. i have learned a lot during this time, the most tragic of which was “”””””physical chemistry”””””” (real subject) where i essentially got tricked into learning the entirety of thermodynamics

[@torrentails]

Great take on the standard model. Love the video, and your videos in general! I do have a request though, I have poor eyesight and it's difficult to read the text with the background, so I'm hoping you might consider increasing the font weight for future videos? My stressed eyes will absolutely be thankful :D

[@mindmaster107]

I should make it more clear in the future, but the text on the screen is more for background reading and additional context. Even if you don’t read it, you shouldn’t be missing out on much, but I will use a better font in the future!

[@torrentails]

@@mindmaster107 Thanks, I'd appreciate it! I'm one of those people who pause the video to read everything, it's an autistic thing 😅

[@mindmaster107]

:D

[@ES-qe1nh]

Great video! Only thing that I noticed is that sometimes you wrote Albelian not Abelian

[@mindmaster107]

The l was move elsewhere in the video by commutability

[@ES-qe1nh]

@@mindmaster107 that's a fucking good one I love it I will steal this

[@KrasBadan]

Cool video physics bear

[@Nylspider]

lfg new Bearable Explanations video

[@fluffy_tail4365]

wow this was very good, it made me click some concepts that I knew in words but couldn't understand in the lagrangians, and why gauge fields are so useful. BTW this makes me wonder, we maybe can't make sense of gravity in the standard model because we're trying to make a gauge field for it, it might be possible that there is no such thing and gravity arises from some direct coupling between fields? I measn probably someone thought of it

[@mindmaster107]

Interestingly, any massless spin-2 automatically reproduces gravity. It’s just that due to how perturbation theory works, we can’t use it on gravity. This is why quantum gravity is taking so long, as it isn’t a theoretical limit, but developing a mathematical method that actually gives usable results with the mathematics.

[@fluffy_tail4365]

@@mindmaster107 oh you're right, I remember reading something similar. I imagine that there is some hairy stuff also in integrating general relativity's curvature in the standard model since if I recall correctly it's basically defined in Minkowsky flat space, but I definitely don't know enough yet to understand this on a deep level

[@docopoper]

Fantastic video. I've been keen to understand how fields interact for a long time. So, in my attempts to understand QFT I'm coding a basic wave simulator using a discrete grid (in 2D to keep visualisation easy). In my simulator I have a big 2D array where each cell has a value. This represents a scalar field. I also store an acceleration and speed value for each cell in the array. At each simulation step I add the acceleration variable to the speed variable and then add the speed variable to the cell's scalar value. During each step I set the acceleration of each cell so that the cell's value accelerates towards the mean value of the neighbouring cells. This is a discrete implementation of the wave equation and works to create wave simulations as one would expect. I haven't known how to have more than one field so far. If I understood the first part of this video correctly, are you saying that I would implement a second field by having the cells in that field be considered adjacent to the original field as if they were spatially adjacent on a new axis? That is to say cell (x, y) on field 1 is considered adjacent to cell (x, y) on field 2 in the same way that cell (x, y) and cell (x+1, y) are adjacent? I just need to provide a coupling strength? And that I can do something with powers? Like, when considering the values of each field for the other's calculations I might square field 2? So field 1 would consider the value of field 2's adjacent cell to be the square of its actual value, and field 2 would consider field 1's value to be the square root of its actual value? Apologies if that didn't make sense. I'm essentially trying to re-encode the maths in this video into a different format.

[@mindmaster107]

For a simple model, all you need to do is have a variable in each cell, which takes a weighted average of neighbouring cells. I’ve made something in excel before lol, so I guess that would be a good start since it seems like your questions are more about how to implement it in code rather than a conceptual misunderstanding.

[@docopoper]

@@mindmaster107 Well, my question is about how to represent multiple fields. When you say "takes a weighted average of neighbouring cells". Is it really just that cell (x, y) in the electron field is a neighbouring cell of cell (x, y) in the electromagnetic field? In the exact same was as if the cells were spatially adjacent? I think I'm honestly just very surprised that the logic of how fields interact would be so simple. They're effectively just spatially adjacent to each other? I keep thinking there must be some kind of catch.

[@mindmaster107]

The real physical interpretation depends on who you ask, but the mathematics is literally treated as such. Technically, a particle’s mass is how much a particle wants to couple to the space it already on (a mass term is A^2, so is the vertex of staying the same). This is balanced against the KE term which wants to move the particle elsewhere. The Mass term is literally how much a particle wants to stay still. Everything makes sense under the same logic.

[@docopoper]

@@mindmaster107 Ohhhhh. That's honestly incredible to find out. It also really reminds me of compactification from string theory. That's really neat. Thank you for the explanation. I must admit I find it surprising that mass is part of the equation of QFT. I was under the impression that mass was an emergent property stemming from light speed particles rapidly changing direction and thus staying in one area.

[@mindmaster107]

It is just possible for a particle to couple to itself. I didn’t explicitly mention this in the video, but a particle which doesn’t have a mass term doesn’t know itself exists, due to that self-interaction being absent. Therefore, it is impossible for the massless particle to decay, or do anything probabilistically on its own. Time doesn’t pass for it. You might have seen this as speed-of-light particles having no centre of mass reference frame, or how neutrinos oscillating implies they have mass.

[@dwighte5482]

'Promo sm'

[@krysz4536]

awesome video!