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3: Determinants and Diagonalization

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    With each square matrix we can calculate a number, called the determinant of the matrix, which tells us whether or not the matrix is invertible. In fact, determinants can be used to give a formula for the inverse of a matrix. They also arise in calculating certain numbers (called eigenvalues) associated with the matrix. These eigenvalues are essential to a technique called diagonalization that is used in many applications where it is desired to predict the future behaviour of a system. For example, we use it to predict whether a species will become extinct.

    Determinants were first studied by Leibnitz in 1696, and the term “determinant” was first used in 1801 by Gauss is his Disquisitiones Arithmeticae. Determinants are much older than matrices (which were introduced by Cayley in 1878) and were used extensively in the eighteenth and nineteenth centuries, primarily because of their significance in geometry (see Section [sec:4_4]). Although they are somewhat less important today, determinants still play a role in the theory and application of matrix algebra.


    This page titled 3: Determinants and Diagonalization is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by W. Keith Nicholson (Lyryx Learning Inc.) via source content that was edited to the style and standards of the LibreTexts platform.