mirror of https://github.com/E-Almqvist/hsf
parent
cc12437725
commit
02e3548c6b
@ -1,4 +1,4 @@ |
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from phys.func import * |
from phys.func import * |
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from phys.const import * |
from phys.const import * |
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from phys.box import box |
from phys.quantum_systems import * |
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from phys.particle import particle |
from phys.particle import particle |
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from phys.particle import particle |
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class box: |
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def __init__(self, length: float): |
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self.length = length |
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def add_particle(pobj: particle): |
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pass |
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from phys.func import psi, prob, E |
from phys.func import psi, prob |
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from phys.const import energy, psi_k |
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from phys.quantum_systems import * |
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import numpy as np |
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import cmath |
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from scipy.constants import Planck |
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class particle: |
class particle: |
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def __init__(self, mass: float, n_state: int): |
def __init__(self, mass: float, system: infbox, n_state: int=1): |
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self.mass = mass |
if n_state < 1: |
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self.n_state = n_state |
print(f"Particle energy state index must be 1 or more! {n_state=}") |
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return |
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self.mass = mass # particle mass |
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self.n_state = n_state # energy state index |
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self.system = system # quantum system |
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self.energy = |
self.energy = energy(self.n_state) # total energy "for" the particle |
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self.psi_k = psi_k(self.n_state) # wave function coeff- |
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self.system.add_particle(self) |
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def psi(self, x: float): |
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return self.system.norm_factor * np.sin(self.psi_k * x) |
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def wave(self, x: float, time: float) -> complex: |
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z_coef = -( (2*np.pi*self.energy*time)/Planck ) # exponent coef |
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z = complex(0, z_coef) # full coef (complex) |
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time_factor = cmath.exp(z) # TODO: cmath.exp is weird, verify... |
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psi = self.system.norm_factor * np.sin(self.psi_k * x) |
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return psi * time_factor |
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from phys.particle import particle |
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import numpy as np |
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class quantum_system: |
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def __init__(self, name: str): |
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self.name = name |
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self.particles = [] |
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def add_particle(particle: particle): |
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self.particles.append(particle) |
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print(f"Added particle {particle} to quantum system '{self.name}'") |
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class infbox(quantum_system): |
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def __init__(self, length: float): |
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super |
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self.name = "Inf Box" |
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self.length = length |
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self.norm_factor = np.sqrt(2/self.length) |
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