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  2. Color wheel - Wikipedia

    en.wikipedia.org/wiki/Color_wheel

    A color wheel or color circle [1] is an abstract illustrative organization of color hues around a circle, which shows the relationships between primary colors, secondary colors, tertiary colors etc. Some sources use the terms color wheel and color circle interchangeably; [ 2 ] [ 3 ] however, one term or the other may be more prevalent in ...

  3. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated.

  4. List of mathematical constants - Wikipedia

    en.wikipedia.org/wiki/List_of_mathematical_constants

    A mathematical constant is a key number whose value is fixed by an unambiguous definition, often referred to by a symbol (e.g., an alphabet letter), or by mathematicians' names to facilitate using it across multiple mathematical problems. [1]

  5. Domain coloring - Wikipedia

    en.wikipedia.org/wiki/Domain_coloring

    Domain coloring plot of the function f(x) = ⁠ (x 2 − 1)(x − 2 − i) 2 / x 2 + 2 + 2i ⁠, using the structured color function described below. In complex analysis, domain coloring or a color wheel graph is a technique for visualizing complex functions by assigning a color to each point of the complex plane. By assigning points on the ...

  6. A New Formula for Pi Is Here. And It’s Pushing Scientific ...

    www.aol.com/lifestyle/formula-pi-pushing...

    The digits of pi extend into infinity, and pi is itself an irrational number, meaning it can’t be truly represented by an integer fraction (the one we often learn in school, 22/7, is not very ...

  7. Box–Muller transform - Wikipedia

    en.wikipedia.org/wiki/Box–Muller_transform

    It discards 1 − π /4 ≈ 21.46% of the total input uniformly distributed random number pairs generated, i.e. discards 4/ π − 1 ≈ 27.32% uniformly distributed random number pairs per Gaussian random number pair generated, requiring 4/ π ≈ 1.2732 input random numbers per output random number.

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