Original Math Notes
All Seasons
Episode 406: In Security--Explore the Math
Episode 406: In Security
Interactive Computations
Use the free Wolfram Mathematica Player to interact with the math behind NUMB3RS.
Scene 10:
Charlie enters, sees Don.

          Hey.  What's up?

          There was a murder last night in Van
          Nuys and I'm hoping you can do that
          thing with the radius.

          An escape radius?  Don, after this
          many hours, calculating the max
          travel distance won't give us --

          I need something.

Think Big, Really Big! »

Think Big, Really Big!
As a radius increases, the search space increases by the radius squared. This Demonstration of the planets illustrates just how much larger an object can become with an increase in radius.
Scene 12:
          I'm starting to suspect that I can no
          more live within the norms of their
          singular convention than light can
          escape the event horizon of a black

Schwarzschild Space-Time Embedding Diagram »

Schwarzschild Space-Time Embedding Diagram
This Demonstration shows a two-dimensional analog of four-dimensional spacetime curvature. This curvature is most extreme around black holes.
Scene 12:

A Rat travels through a maze.

                     CHARLIE (V.O.) (cont'd)
          Like a rat in a maze, we have a set
          of known variables.  We know the rat
          wants to escape the maze.

Interactive Maze »

Interactive Maze
Create a customized maze.
Scene 51:
           I can use a simple Morphological
           Image Cleaning Algorithm to find the
           hidden message.

                     CHARLIE (cont'd)
           The algorithm was originally intended
           to save corrupted images, but it's
           also useful to smooth out the grayscale
           image, removing the camouflage
           while revealing the thin features
           where a hidden message resides.

           How long will it take?

           Get a cup of coffee.

Image Restoration for Degraded Images »

Image Restoration for Degraded Images
This Demonstration applies various deconvolution techniques to restore original images from blurred images. Mathematically, a linearly degraded (blurred) image is defined as the convolution of the pristine image with a kernel function with additive noise. The problem is to find a best estimate of the pristine image from the noisy blurred data when the noise function is unknown.
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