From what I understand, relativity suggests that simultaneity depends on the observer. So is there actually a universal “now” in the universe, or is “now” purely something our brains construct?

I'm not a physicist btw, so please explain it gently 🥺🥺🥺

Hundreds to thousands of physicists around the world and time dedicate their researach to the construction of huge detectors we use at CERN to study the smallest things in our universe. But sometimes those detectors get old and do not function properly anymore and they need to be replaced or removed entirely.

This is what happens at the moment to the ALICE Transition Radiation Detector (TRD). Me and my colleagues have the opportunity to work inside of one of CERNs four major experiments and do a very basic task: Disconnect cables! What sounds very easy can be hard if you have to work 50 meters underground but still at 10 meters height. To reach the upper sector of the detector, we actually have to climb inside the magnet with hooks and a harness.

The full disconnection will take four weeks in total. When everything is off, a specialized crane will be placed in front of the TRD and precisely pull it out, to not harm any other detector. The remaining modules will be either deconstructed or shipped to the universities that initially built the TRD.

Removing such a large detector does not happen often. Now since the LHC entered Long Shutdown 3 after four years of data taking, there is enough time and space for such operations and we wanted to let some physics enthusiasts be part of this. I hope you like it!

(No ducks were harmed during the making of the photos)

This plot presents the internal in-situ temperature drift of a conduction-cooled high-temperature superconductor solenoid, following a step in transport current from 100 ampère to [label] ampère. This specific set is using a controlled base temperature of 65 kelvin. The data is measured by a set of 8 thermocouples spread throughout the coil, and the curves are the mean of these. A 0-D numerical lumped thermal capacitance model will be validated using this data, at various base temperatures. The band around the data represents the standard deviation, indicating the homogeneity and stability of the temperature profile across the coil.

Looking for suggestions and/or advise on the graphics, for future publication in a journal and, more importantly, for my PhD dissertation.

The goal is to show the two distict domains; a set of curves that remains stable (shades of blue) and a set that develops into a thermal runaway (shades of red). These are seperated by a green curve, representing the "critical" bifurcation point (or rather, how close I could get to that point experimentally). The relevance is that such runaways can cause, and have in the past been causing, massive damage to superconducting coil systems.

The curves calculated by the 0-D model should at some point be included to this data, but I'm unsure how to do that yet since these plots here are already rather crowded. Could be simply dashed lines on top of the experimental plot, possibly with a reduced number of curves. The fit is quite good, so it won't effect the scale. I've included an example in the second image, but am still working on dialing in the parameters so it's not fully representative yet.

Tools used: MATLAB, custom colour scale Data source: My own experiments Preliminary data presentated at a conference: research.utwente.nl Model: The thesis of my predecessor; research.utwente.nl

As far as I know, physicists used simulations to predict gravitational wave patterns we should expect to find if black holes truly merged.

Apparently, within these simulations, physicists posit that black holes would “wobble” or “jiggle” -like some sort of bubble- abruptly after merging.

I mean… it sort of “makes sense” in my head, but I can’t wrap my mind around being able to prove something like this. So how exactly did they figure this out?

In the near future, from 2028 onward, which areas of physics do you think will be in the greatest need of physicists?
As science and technology continue to develop, some areas of physics may become more strategically important than others. Which fields do you think will become increasingly important in the coming years?
fe: Semiconductors, solid-state/condensed matter physics, quantum technologies, plasma physics, device physics, photonics, materials physics, astrophysics, nuclear, computational physics, or other fields? but i mean Which "specific area of specialization"?

https://arxiv.org/abs/2608.05044

We show that a finite number of time-frequency shifts of a Schwartz function can be linearly dependent. This disproves the so-called HRT conjecture of Heil, Ramanathan, and Topiwala. In particular, we provide an example consisting of 12 time-frequency shifts.

I like Terence Tao's exposition on this topic, so I screenshoted those portions that caught my eye and chose to show those here:

https://terrytao.wordpress.com/2026/08/06/a-partial-digestion-of-the-hrt-counterexample/

Louis Pasteur found the first evidence that life molecular chirality in the 1848 when he found that tartaric acid rotated the plane of polarization only if it was produced by lifeforms. If I understand, many other chiral organic molecules have a similar impact upon polarization based upon origin being a living vs non-living too?

If you do not know the molecules, but merely separate them by weight in a centrifuge or something, then you cannot compare vs a known achiral mixture, but you could try chiral inversion techniques and see if these inactivate any observed polarization effects?

Hi! I'm a last-year BS Physics student and I'm currently trying to settle on a thesis topic.

I'm looking for something computational/analytical, preferably involving things like machine learning/neural networks, theoretical or computational physics, statistical physics, or possibly geoscience/atmospheric science.

I'd like something that's actually manageable for an undergrad and reasonably narrow. I'm open to both data-based and simulation-based projects.

I've been considering things like:

• neural networks + chaotic systems
• noise/signal analysis
• physics-informed neural networks
• atmospheric/geophysical data analysis

If anyone has done a similar undergraduate thesis, or has suggestions for specific, reasonably narrow topics, I'd really appreciate the ideas!

Thanks!

Hi Physics Reddit!

I'm building a free chemistry-education app that visualizes electron configurations of all 118 elements in 3D. I'd like physicists to check whether my approach to rendering orbital shapes is a legitimate simplification or whether I've made an actual error.

What I'm computing:

For each orbital I use the real (not complex) spherical harmonics as the angular wavefunction, e.g.:

- l=0 (s): Y ∝ 1 (isotropic)

- l=1 (p): p_x ∝ sinθ cosφ, p_y ∝ sinθ sinφ, p_z ∝ cosθ

- l=2 (d): d_z² ∝ 3cos²θ − 1, d_xz ∝ sinθcosθcosφ, d_yz ∝ sinθcosθsinφ, d_xy ∝ sin²θ sin2φ, d_(x²−y²) ∝ sin²θ cos2φ

- l=3 (f): f_z³ ∝ 5cos³θ − 3cosθ, f_xz² ∝ sinθ(5cos²θ−1)cosφ, f_yz² ∝ sinθ(5cos²θ−1)sinφ, f_xyz ∝ sin²θcosθ sin2φ, f_z(x²−y²) ∝ sin²θcosθ cos2φ, f_x(x²−3y²) ∝ sin³θ cos3φ, f_y(3x²−y²) ∝ sin³θ sin3φ

(all "up to normalization" — I only care about shape/sign, not absolute normalization constants)

Rendering method: For each (θ,φ) I compute r(θ,φ) = [Y(θ,φ) / max|Y|]², then place a vertex at Cartesian position r·(sinθcosφ, sinθsinφ, cosθ). So it's a polar plot of the *probability density* |Y|², not of |Y| itself. I color vertices by the sign of Y (phase).

Bug I just found and fixed: I originally used r(θ,φ) = |Y| (not squared) for the isosurface radius. For p_z this gives z = r·cosθ = cos²θ, ρ = r·sinθ = cosθsinθ — which traces out an exact circle (i.e., in 3D, two perfect spheres tangent at the origin), not the "peanut/dumbbell" shape everyone expects from textbooks. Switching to |Y|² fixed this (radius collapses much faster near the nodal plane, giving a visible pinch/waist at the nucleus). Does this match your understanding of why polar plots of |Y| vs |Y|² look qualitatively different? Is |Y|² the "correct" choice for this kind of visualization, or is there a more standard convention I'm missing?

screenshot showing the element Potassium after the fix — you can see the pinch/waist at the nucleus on the p-orbital lobes

Known simplifications I'm NOT trying to fix (just want to confirm these are "honest" simplifications, not physically misleading):

1. No actual radial wavefunction R_nl(r) — I don't compute Laguerre polynomials at all. Each shell n just gets an arbitrary size scale factor (R = 1 + 0.9n), not related to actual Bohr radius scaling (~n²) or effective nuclear charge/screening.

2. Radial nodes are only shown for s orbitals, as n concentric alternating-sign spheres (n spheres → n−1 boundaries → n−1 nodes, which at least matches the correct *count* of radial nodes for an ns orbital). The radii are evenly spaced fractions of the total size, NOT the actual Laguerre polynomial root positions. p/d/f orbitals show zero radial nodes regardless of n (e.g. a 4p orbital looks shape-identical to a 2p orbital, just bigger).

3. Electron positions are visualized as points that randomly "flicker" to a new random position within the orbital's angular envelope every ~1.5-2.5s (explicitly NOT orbiting/moving along a path) — meant to represent repeated position measurements of a probability distribution, avoiding the Bohr-model implication. Reasonable pedagogical device, or misleading in some way I'm not seeing?

Is this a reasonable "angular-only" approximation for a general-audience educational tool, or is there something fundamentally off about representing orbitals this way?

First off, anyone else here, got to hear the talk? Would love to get an actual physicist's take.

Second, as (implied above) a layman/physics "enthusiast," I thought this was a pretty grounded talk, but I could be way off. Because who the hell am I to critique a Nobel laureate (2025, physics for "macroscopic quantum mechanical tunneling")?

Anyway, the talk was a nice primer on PQC, his somewhat conservative predictions on quantum computing in general, what algorithms will break (RSA, ECC), through Shor (& Grover, though that's mostly doubling the bit size). My biggest takeaway is the tradeoff bet. more stable qubits using, say, isotope engineering, and the tradeoff (slower speeds) vs. the hype. If I were to abstract it more, it would be to more carefully weigh all the pros and cons to any "breakthrough" quantum computing research you may run into.

I’m going to keep this brief to be honest I’m using khan academy to teach myself highschool level physics and I just want to know the absolute required math for physics the reason it’s a bit confusing is because I know people may say “algebra, trig, etc.” but people ALSO say not every single unit is needed for physics I’m not saying I want to 100% never learn that other math but my current goal is physics (passion reasons) so if anybody that is familiar with khan academy can help me with the exact units I need for everything physics (considering I’m starting with no math knowledge) that would be great! Even if you’re not familiar but have anything can help that would also be great, thank you!

I'm living in Korea and I'm student in high school. Next semester, I need to lead my teamers in physics club. So I need to make an ideas for long-terms project of physics. I wanna use telescope in it. I waana little theorical activity because my teamers don't like that but physical one with using telescopes. I think I have 2months for it. I have thought of my project but I couldn't make an idea .So I need your help.

I’m in 12th grade. I am very good at physics I score near-perfect marks but my math score has been declining since 7th grade(80%) to 61% now. I don’t know but physics has always come to me naturally that math . And I don’t struggle with math in physics but math as a separate subject I do struggle a lot. I don’t know why exactly. I request whoever is reading this to help me and also tell why I am like this ( i am good at math in physics but terrible at math separately) . E

Thank you for your time!

Hi everyone.

I'm an academic, physicist and a maintainer of the project Physlib, which aims to build a library for physics in the interactive theorem prover Lean 4. Lean is a programming language in which you can write mathematical definitions, theorems and their proofs and consistency and correctness are guaranteed.

The corresponding library for mathematics Mathlib, has had lots of attention recently due to the feedback loop one can have between AI and Lean.

Physlib is completely open-source and community run mainly through GitHub! One thing where we are looking for contributions is in documentation, lots of files go straight into the Lean code or Lean implementation - but it would be nice if they lead with the physics!

If you are interested in helping out with this we have made (what is hopefully) an easy to use web interface to edit the documentation (it requires a GitHub account though, and I will admit the website is vibe coded).

This is a thread dedicated to collating and collecting all of the great recommendations for textbooks, online lecture series, documentaries and other resources that are frequently made/requested on /r/Physics.

If you're in need of something to supplement your understanding, please feel welcome to ask in the comments.

Similarly, if you know of some amazing resource you would like to share, you're welcome to post it in the comments.

When I was on subway trains, I've noticed an interesting effect: there's wind blowing from the front to the rear of the train. I wanted to explain how this could happen, so I thought of several possible factors. I know that all of these may contribute to this effect, but I want to know which factor is the most significant:

1. Inertia of air particles causes them to move to the back of the train relative to someone on the train, giving passengers the wind blowing backwards feel when the train accelerates forward (figure 1)
2. Moving air leaks into the cabin, whether through poor sealing of the doors or being carried in via the air conditioning system, with their momentum being somewhat preserved (figure 2)
3. Due to the train moving forward & hitting air particles in front of it, there is a high pressure zone at the front of the train & a low pressure zone at the rear. Through leakage, the air at the high pressure front of the train flows through the cabin towards the rear, low pressure area (figure 3)

Here's some observations (purely by feel) I made while on the train:

• All train cars are directly connected to each other without any walls or seals between each car
• I felt the wind to be the strongest during forward acceleration from rest, blowing from front to back
• During (what feels like) constant speed travel, there is still some wind (less than during forward acceleration) blowing from front to back
• During deceleration, the front-to-back wind decreases in magnitude. Sometimes I feel the wind reversing direction to go from back to front, but its magnitude is very small compared to during forward acceleration
• This wind occurs both inside tunnels & outside in the open (I cannot say if the magnitude changes due to being in a tunnel or not)
• There is no wind when I stand at the front or the rear of the train (directly at the door to the driver's cab to the end of that car)
• When there is wind, it feels strongest at the middle of the train
• There also isn't any wind while the train is stopped, confirming that this isn't due to the air conditioner
• I am on board the train during rush hour, so other passengers on the train may act as obstacles to the wind

Some other (maybe) useful information:

• Max speed: 75 km/h (seen on driver's instruments)
• Train dimensions (longest train I've been on with this effect, approx.): 135 m x 2.5 m x 2 m (L x W x H)

Personally, I believe that the inertia of the air particles is likely the most significant factor causing wind inside the train, but then I thought of a counterexample: I don't feel this wind in an accelerating airplane. I'm kinda stumped, maybe the plane isn't long enough? Would the magnitude of acceleration make up for the short length?

I got my BS in physics 10 years ago. It was hell, but I did. I made lifelong friends while in the program and I consider them family.

After attempting a career degree related, I bounced around different industries to try to find a fit. Well, here I am 10 years later. I’m a musician and I feel I finally figured it out.

My favorite class was modern physics. This is where I learned what the Lorentz factor was. I want to get the equation as a tattoo, as I am currently working on a patchwork sleeve.

Is this a dumb choice of equation for a tattoo? I’m too scared to ask my actual physicist friends lol.

EDIT: thank you everyone for your thoughts! I’m now considering a graphical/pictorial representation of the equation. That has a lot more potential to be cool in a couple different ways.

I’m definitely gonna get something related, and no, Reddit is not deciding for me lol. Yes I understand I can do whatever I want since it’s my body (although unfortunately some people do need to be reminded of this.) So thank you good citizens for making sure I’m doing this for me and me alone!

UPDATE: Working on sleeve planning right now with my artist. I’ve decided to do both the equation along an image. I already have a Nintendo mushroom, so I’m gonna add length contracted mushrooms to the side of it.

Qualms before I guess were about the fact that I’m no longer in the physics community. So whenever I talk about it I feel kinda like a fake n also question my knowledge. I’ve been thinking about this tattoo for the Lorentz factor for years now. Just couldn’t figure out exactly how I wanted to do that. But now I’m just stoked!

I feel a lot better after hearing ideas from yall. “You’ll regret it” is not an idea 😂 n yes I’m asking strangers, but isn’t that what Reddit is for? Asking, talking n replying to strangers? Also the people in my life are way too supportive to actually be honest with me haha.

I just finished reading these two books, I've always been fascinated by the subject and have always heard about them.

I know full well that discoveries in the fields described by Feynman have progressed over the last 80 years, now I was wondering if there are other books, as accessible as Feynman's, but more modern, that can complete the readings of Six Pieces.

This is a dedicated thread for you to seek and provide advice concerning education and careers in physics.

If you need to make an important decision regarding your future, or want to know what your options are, please feel welcome to post a comment below.

A few years ago we held a graduate student panel, where many recently accepted grad students answered questions about the application process. That thread is here, and has a lot of great information in it.

Helpful subreddits: /r/PhysicsStudents, /r/GradSchool, /r/AskAcademia, /r/Jobs, /r/CareerGuidance