Solution

ID: past-exam-of-the-mathematics-course-of-the-university-of-cambridge/2003/iii/paper-10/2/solution

We use independent symmetric Rademacher random variables , the intended meaning of the Bernoulli variables in this context. Without this convention the assertion need not hold: for one Bernoulli variable of success probability and one nonzero vector, the proposed inequality would be , which is false.
Let with the uniform probability measure, put , and set . We prove the sharp estimate rather than assuming the Kahane-Khintchine inequality. If denotes with its th sign reversed, define
The Walsh characters form an orthonormal basis of scalar functions on this finite cube, and . Since , its coefficients for odd vanish. Every nonconstant remaining character has . Expanding in this orthonormal basis gives the even-function spectral gap on a hypercube
At each , the Hahn-Banach theorem supplies a real norming linear functional with and . For a complex Banach space use its underlying real space. Since ,
Adding gives . Multiplying by the nonnegative yields . Therefore
The constant is sharp: take and in the scalar field. The random norm is or , each with probability one half.
A Banach space has cotype 2 if a constant , independent of the length of the family, satisfies
For , the triangle inequality for the Euclidean norm gives
For real or complex scalars , independence gives . The proved sharp Rademacher second-moment inequality, applied pointwise to , and Fubini theorem now yield
Thus has cotype 2, with .

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