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Scaling law: Difference between revisions
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* make performance comparisons between devices | * make performance comparisons between devices | ||
* make educated guesses at local transport mechanisms | * make educated guesses at local transport mechanisms | ||
The typical scaling law expression for an (output) variable ''y'' as a function of some system variables ''x<sub>1</sub>'', ''x<sub>2</sub>'',... is: | |||
:<math>y = \alpha_0 x_1^{\alpha_1} x_2^{\alpha_1} ...</math> | |||
Here, the α<sub>i</sub> are the scaling parameters. | |||
By taking the logarithm of this expression, it becomes linear and simple (multivariate) linear regression tools can be used. | |||
However, a proper analysis requires: | |||
* using ''dimensionless'' variables (easily achieved by normalizing all quantities appropriately) | |||
* using (linearly) ''statistically independent'' variables (applying, e.g., Principal Component Analysis) | |||
== Confinement time scaling == | == Confinement time scaling == | ||