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  2. Cauchy–Schwarz inequality - Wikipedia

    en.wikipedia.org/wiki/CauchySchwarz_inequality

    CauchySchwarz inequality (Modified Schwarz inequality for 2-positive maps [27]) — For a 2-positive map between C*-algebras, for all , in its domain, () ‖ ‖ (), ‖ ‖ ‖ ‖ ‖ ‖. Another generalization is a refinement obtained by interpolating between both sides of the CauchySchwarz inequality:

  3. QM-AM-GM-HM inequalities - Wikipedia

    en.wikipedia.org/wiki/QM-AM-GM-HM_Inequalities

    There are three inequalities between means to prove. There are various methods to prove the inequalities, including mathematical induction, the CauchySchwarz inequality, Lagrange multipliers, and Jensen's inequality. For several proofs that GM ≤ AM, see Inequality of arithmetic and geometric means.

  4. Uncertainty principle - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_principle

    The CauchySchwarz inequality asserts that ... changes by an amount equal to one standard deviation. [48] Examples: The time a free quantum ...

  5. AM–GM inequality - Wikipedia

    en.wikipedia.org/wiki/AM–GM_inequality

    In this case, their geometric mean t 0 has the same value, Hence, unless x 1, . . . , x n, x n+1 are all equal, we have f(x n+1) > 0. This completes the proof. This completes the proof. This technique can be used in the same manner to prove the generalized AM–GM inequality and CauchySchwarz inequality in Euclidean space R n .

  6. Welch bounds - Wikipedia

    en.wikipedia.org/wiki/Welch_bounds

    The CauchySchwarz inequality is met with equality when the two vectors involved are collinear. In the way it is used in the above proof, this occurs when all the non-zero eigenvalues of the Gram matrix G {\displaystyle G} are equal, which happens precisely when the vectors { x 1 , … , x m } {\displaystyle \{x_{1},\ldots ,x_{m ...

  7. Positive linear functional - Wikipedia

    en.wikipedia.org/wiki/Positive_linear_functional

    CauchySchwarz inequality [ edit ] If ρ {\displaystyle \rho } is a positive linear functional on a C*-algebra A , {\displaystyle A,} then one may define a semidefinite sesquilinear form on A {\displaystyle A} by a , b = ρ ( b ∗ a ) . {\displaystyle \langle a,b\rangle =\rho (b^{\ast }a).}

  8. Law (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Law_(mathematics)

    CauchySchwarz inequality: An upper bound on the inner product between two vectors in an inner product space in terms of the product of the vector norms. It is considered one of the most important and widely used inequalities in mathematics. [8]

  9. Nesbitt's inequality - Wikipedia

    en.wikipedia.org/wiki/Nesbitt's_inequality

    There is no corresponding upper bound as any of the 3 fractions in the inequality can be made arbitrarily large. It is the three-variable case of the rather more difficult Shapiro inequality, and was published at least 50 years earlier.