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  2. Exponentiation - Wikipedia

    en.wikipedia.org/wiki/Exponentiation

    Otherwise, the cyclic group is finite (it has a finite number of elements), and its number of elements is the order of x. If the order of x is n , then x n = x 0 = 1 , {\displaystyle x^{n}=x^{0}=1,} and the cyclic group generated by x consists of the n first powers of x (starting indifferently from the exponent 0 or 1 ).

  3. Exponentiation by squaring - Wikipedia

    en.wikipedia.org/wiki/Exponentiation_by_squaring

    In mathematics and computer programming, exponentiating by squaring is a general method for fast computation of large positive integer powers of a number, or more generally of an element of a semigroup, like a polynomial or a square matrix. Some variants are commonly referred to as square-and-multiply algorithms or binary exponentiation.

  4. Modular exponentiation - Wikipedia

    en.wikipedia.org/wiki/Modular_exponentiation

    A third method drastically reduces the number of operations to perform modular exponentiation, while keeping the same memory footprint as in the previous method. It is a combination of the previous method and a more general principle called exponentiation by squaring (also known as binary exponentiation).

  5. Matrix exponential - Wikipedia

    en.wikipedia.org/wiki/Matrix_exponential

    This is analogous to the fact that the exponential of a complex number is always nonzero. The matrix exponential then gives us a map exp : M n ( C ) → G L ( n , C ) {\displaystyle \exp \colon M_{n}(\mathbb {C} )\to \mathrm {GL} (n,\mathbb {C} )} from the space of all n × n matrices to the general linear group of degree n , i.e. the group of ...

  6. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Graphs of functions commonly used in the analysis of algorithms, showing the number of operations versus input size for each function. The following tables list the computational complexity of various algorithms for common mathematical operations.

  7. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python uses the ** operator for exponentiation. Python uses the + operator for string concatenation. Python uses the * operator for duplicating a string a specified number of times. The @ infix operator is intended to be used by libraries such as NumPy for matrix multiplication. [104] [105]

  8. Knuth's up-arrow notation - Wikipedia

    en.wikipedia.org/wiki/Knuth's_up-arrow_notation

    In expressions such as , the notation for exponentiation is usually to write the exponent as a superscript to the base number .But many environments — such as programming languages and plain-text e-mail — do not support superscript typesetting.

  9. Finite field arithmetic - Wikipedia

    en.wikipedia.org/wiki/Finite_field_arithmetic

    The multiplicative inverse for an element a of a finite field can be calculated a number of different ways: By multiplying a by every number in the field until the product is one. This is a brute-force search. Since the nonzero elements of GF(p n) form a finite group with respect to multiplication, a p n −1 = 1 (for a ≠ 0), thus the inverse ...