Veselra & LumenFrost
LumenFrost LumenFrost
Hey Veselra, quick thought: what if a photon behaved like a glitch in a video stream—splitting into a burst of light and a random pixel pattern? I'd love to dissect how that would break or reinforce interference. Care to jam on that?
Veselra Veselra
Whoa, a glitch‑photon! Picture a single photon hitting a screen, then splattering into a burst of clean light plus a chaotic pixel burst—like a glitchy GIF. The interference pattern would go haywire: the coherent wavefront that builds the classic double‑slit pattern would get scrambled by the random pixel clatter, so the usual bright-dark fringes would blur or vanish. But if that pixel burst somehow kept a hidden phase lock, you might get a weird new interference pattern—maybe a super‑cooled, pixelated Moiré effect. Either way, it’d be a wild, fractal‑like interference dance. Want to run a simulation and see how the pixel noise corrupts the fringe visibility? Let's crank up the chaos!
LumenFrost LumenFrost
Sure, let’s set up a quick Monte‑Carlo run. I’ll add a stochastic noise term to the phase field and see how the contrast degrades. It’ll be fun to watch the fringes wobble like a badly edited GIF. Want me to drop the parameters into a script and watch the chaos unfold?
Veselra Veselra
Absolutely, drop those parameters! I’ll keep the playlist of random phase jitters ready—let’s see the interference groove get all wobbly. Bring the code, and let’s watch the pattern get glitch‑fied, like a VHS tape on loop. Go!
LumenFrost LumenFrost
import numpy as np import matplotlib.pyplot as plt # Grid parameters x = np.linspace(-5, 5, 2000) y = np.linspace(-5, 5, 2000) X, Y = np.meshgrid(x, y) # Double‑slit geometry slit_width = 0.5 slit_spacing = 1.0 slit1 = np.abs(Y + slit_spacing/2) < slit_width/2 slit2 = np.abs(Y - slit_spacing/2) < slit_width/2 slits = slit1 | slit2 # Baseline wavefront (plane wave) wave = np.ones_like(X, dtype=complex) # Apply random phase jitter per pixel (gaussian noise) noise_std = 0.2 # adjust for more or less chaos phase_noise = np.random.normal(0, noise_std, size=X.shape) wave *= np.exp(1j * phase_noise) # Propagate to screen with Fresnel kernel (simple approximation) k = 2*np.pi # wavenumber (units arbitrary) z = 10.0 # distance to screen fresnel = np.exp(1j * k * (X**2 + Y**2) / (2*z)) field = wave * fresnel # Intensity pattern intensity = np.abs(field)**2 # Plot plt.figure(figsize=(8,4)) plt.imshow(intensity, extent=(-5,5,-5,5), cmap='inferno') plt.title('Glitch‑fied double‑slit interference') plt.xlabel('x') plt.ylabel('y') plt.colorbar(label='Intensity') plt.show()