Brownian Motion¤
BrownianMotion
¤
Brownian motion describes motion of small particles with stochastic forces applied to them. The math of Brownian motion can be modeled with Wiener process.
For consistency, we always use \(\mathbf x\) for displacement, and \(t\) for steps. The model we are using is
References:
- Brownian motion and random walks. [cited 13 Mar 2024]. Available: https://web.mit.edu/8.334/www/grades/projects/projects17/OscarMickelin/brownian.html
- Contributors to Wikimedia projects. Brownian motion. In: Wikipedia [Internet]. 22 Jan 2024 [cited 13 Mar 2024]. Available: https://en.wikipedia.org/wiki/Brownian_motion
1D Brownian Motion
The dimsion of our Brownian motion is specified by the dimension of the initial condition.
To simulate a 1D Browian motion, we define the system and initial condition:
system = {
"sigma": 1,
"delta_t": 1,
}
initial_condition = {
"x0": 0
}
The Brownian motion can be simulated using
bm = BrownianMotion(system=system, initial_condition=initial_condition)
bm(n_steps=100)
2D Brownian Motion
To simulate a 2D Browian motion,
system = {
"sigma": 1,
"delta_t": 1,
}
initial_condition = {
"x0": [0, 0]
}
bm = BrownianMotion(system=system, initial_condition=initial_condition)
bm(n_steps=100)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
system |
dict[str, float]
|
the Brownian motion system definition |
required |
initial_condition |
dict[str, float] | None
|
the initial condition for the simulation |
None
|
Source code in hamilflow/models/brownian_motion.py
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|
dim: int
property
¤
Dimension of the Brownian motion
BrownianMotionIC
¤
Bases: BaseModel
The initial condition for a Brownian motion
Attributes:
Name | Type | Description |
---|---|---|
x0 |
float | int | list[float | int]
|
initial displacement of the particle, the diminsion of this initial condition determines the dimension of the model too. |
Source code in hamilflow/models/brownian_motion.py
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|
BrownianMotionSystem
¤
Bases: BaseModel
Definition of the Brownian Motion system
For consistency, we always use \(\mathbf x\) for displacement, and \(t\) for steps. The model we are using is
References:
- Brownian motion and random walks. [cited 13 Mar 2024]. Available: https://web.mit.edu/8.334/www/grades/projects/projects17/OscarMickelin/brownian.html
- Contributors to Wikimedia projects. Brownian motion. In: Wikipedia [Internet]. 22 Jan 2024 [cited 13 Mar 2024]. Available: https://en.wikipedia.org/wiki/Brownian_motion
Attributes:
Name | Type | Description |
---|---|---|
sigma |
float
|
base standard deviation to be used to compute the variance |
delta_t |
float
|
time granunality of the motion |
Source code in hamilflow/models/brownian_motion.py
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|
gaussian_scale: float
cached
property
¤
The scale (standard deviation) of the Gaussian term in Brownian motion