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  2. Exponentiation - Wikipedia

    en.wikipedia.org/wiki/Exponentiation

    This definition of exponentiation with negative exponents is the only one that allows extending the identity + = to negative exponents (consider the case =). The same definition applies to invertible elements in a multiplicative monoid , that is, an algebraic structure , with an associative multiplication and a multiplicative identity denoted 1 ...

  3. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    Python supports normal floating point numbers, which are created when a dot is used in a literal (e.g. 1.1), when an integer and a floating point number are used in an expression, or as a result of some mathematical operations ("true division" via the / operator, or exponentiation with a negative exponent). Python also supports complex numbers ...

  4. Euler's totient function - Wikipedia

    en.wikipedia.org/wiki/Euler's_totient_function

    The first thousand values of φ(n).The points on the top line represent φ(p) when p is a prime number, which is p − 1. [1]In number theory, Euler's totient function counts the positive integers up to a given integer n that are relatively prime to n.

  5. Exponentiation by squaring - Wikipedia

    en.wikipedia.org/wiki/Exponentiation_by_squaring

    If the exponent n is zero then the answer is 1. If the exponent is negative then we can reuse the previous formula by rewriting the value using a positive exponent. That is, = (). Together, these may be implemented directly as the following recursive algorithm:

  6. Tetration - Wikipedia

    en.wikipedia.org/wiki/Tetration

    of the infinitely iterated exponential converges for the bases () The function | (⁡) ⁡ | on the complex plane, showing the real-valued infinitely iterated exponential function (black curve) Tetration can be extended to infinite heights; i.e., for certain a and n values in n a {\displaystyle {}^{n}a} , there exists a well defined result for ...

  7. Half-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Half-precision_floating...

    The half-precision binary floating-point exponent is encoded using an offset-binary representation, with the zero offset being 15; also known as exponent bias in the IEEE 754 standard. [9] E min = 00001 2 − 01111 2 = −14; E max = 11110 2 − 01111 2 = 15; Exponent bias = 01111 2 = 15

  8. Modular exponentiation - Wikipedia

    en.wikipedia.org/wiki/Modular_exponentiation

    For example, given b = 5, e = 3 and m = 13, dividing 5 3 = 125 by 13 leaves a remainder of c = 8. Modular exponentiation can be performed with a negative exponent e by finding the modular multiplicative inverse d of b modulo m using the extended Euclidean algorithm. That is: c = b e mod m = d −e mod m, where e < 0 and b ⋅ d ≡ 1 (mod m).

  9. Integer overflow - Wikipedia

    en.wikipedia.org/wiki/Integer_overflow

    The register width of a processor determines the range of values that can be represented in its registers. Though the vast majority of computers can perform multiple-precision arithmetic on operands in memory, allowing numbers to be arbitrarily long and overflow to be avoided, the register width limits the sizes of numbers that can be operated on (e.g., added or subtracted) using a single ...

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