Recent content by Ax_xiom

The context here is that Mark continues to choke Conquest for several minutes after, so time shouldn't be much of an issue here. If Mark is providing a constant force over a constant distance, surely his kinetic energy in both cases is the same, right?

True, didn't consider that. But what if we neglect aerodynamic drag? What is the case then?

The former. Mark & Conquest were both flying before he gets slammed So how much energy does Mark need to output to do this and who is correct?

So in the comic Invincible, Mark Grayson (a character who can fly and has super strength) slams Conquest (another character with the same powers) into the ground while fighting him. And on impact they create a crater about this large. Conquest doesn't do anything while being slammed So I had...

Thank you, I think this gives me more intuition on the definition of temperature. Out of curiosity, is it possible to see how this original expression is derived? And is the ##TdS ## term energy input into the system, and the ##-PdV## term work done by the system?

So, temperature is formally defined as the inverse of the rate of change of entropy in respect to internal energy. I'm fine working with this mathematically but I don't get it intuitively. Does anyone have some intuition as to why temperature is defined this way?

Apologies That's probably what I was looking for. Thanks for your help

I think the issue is that, for reasons I am not smart enough to understand, the computed diffraction pattern is usually different to the actual diffraction pattern. Compare an airy disk that was computed with a computer: And one observed in real life: The second-order maxima seem to be nearly...

I haven't tried it because I decided to just use Excel's built-in solver. I subsequently abandoned the project when the solver kept on giving solutions that made no physical sense

I'm taking the square root so the image looks brighter compare the regular image to the image when the values are squarerooted The squarerooted version is the closest to what I'm trying to do, but my target image has the centre much brighter and the edges much darker

I'll create a new image with the centre at 0,0 so no shifting is required. Here it is: # fourier_synthesis.py import numpy as np import matplotlib.pyplot as plt image_filename = "HubbleOutline10.jpg" def calculate_2dft(input): ft = np.fft.ifftshift(input) ft = np.fft.fft2(ft)...

I tried it and I get this: Which does have the same general structure as what I'm aiming for, but doesn't "glow" as much Here is the code I'm using, I'm not sure if it uses block swapping

So I'm using python to compute the fourier transform of a black and white image and the images I've been getting have been different to what I expected. Input image: Output FFT: What I expected: Image from MinutePhysics's video Why are Stars Star-Shaped? So why is there a difference?

Not really, but I'll mess around with it as I don't think there is any other reasonable way to solve my problem

After some thinking, I don't think this is possible. For an arbitrary stage i, the expression for the mass ratio will be this $$N_i = \frac{m_i + \alpha_i p + U}{s m_i + \alpha_i p + U}$$ where U is the mass of all upper stages. And we (ideally) want to find ##\frac{m_i + \alpha_i p + U}{U}## in...