Physic Labs

Frontier physics

Fractals in physics

Vary the spectral exponent and amplitude of a synthetic fractal surface, observe the effective roughness across scales, then compare with the log M–log R plot to estimate the fractal dimension.

Advanced

Equipment

  • “Spectral exponent” β slider
  • “Amplitude” slider of the ripples
  • Rotatable self-similar 3D terrain mesh
  • log M vs log R plot whose slope gauges the fractal dimension

Procedure

  1. Change the spectral exponent and inspect roughness

    Raise the “Spectral exponent” β slider: short-wavelength ripples lose amplitude faster, so the surface looks smoother at fine detail. Drag the figure to rotate it and note that self-similarity holds only over a finite range of scales.

  2. Estimate the fractal dimension on the plot

    Move to the log M–log R figure: measure the slope of the straight segment inside the observation window to read off the mass dimension DD via M∝RDM \propto R^D. Change “Amplitude” and check that the slope — the power law — does not depend on the overall amplitude.

  3. State the limits of the power law

    For two different β values, predict which surface is rougher at small scales, then verify on the figure. Explain why the model “does not represent a specific sample”: real materials are fractal only over a band of scales between atomic and sample sizes.

Simulation

Experiment history

In the 1960s Lewis Fry Richardson measured coastlines with dividers of different spacings and found the length grows as a power law — the first empirical evidence of nature's non-smooth geometry. Benoît Mandelbrot used this in his celebrated 1967 paper “How long is the coast of Britain?” and coined “fractal” in 1975, building on the Hausdorff dimension (1918). In physics the fractal viewpoint was soon applied to diffusion-limited aggregates, fracture surfaces, galaxy clustering and turbulent fluctuations — where Kolmogorov had described the scale-by-scale energy cascade in 1941. The common lesson: a power law is only meaningful inside the observed scaling window, exactly as the simulation stresses.

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