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Kolmogorov gliding hump series converges in lone
Statement
Assume AC. For one can choose analytic polynomials of degree with and , where . Set , , and . Their positive frequency intervals are pairwise disjoint and increasing. The series converges in complex to f, with and . Moreover almost everywhere, and its pointwise sum represents f.
Facts & Assumptions
Analytic norm-one blocks can have arbitrarily large partial-sum maxima outside a set of prescribed small measure Kolmogorov block polynomial with large partial sums.
Modulation translates frequency support and preserves pointwise magnitude up to the scalar amplitude Separated frequency blocks do not disturb earlier partial sum maxima.
Complex is complete under countable choice Complex Lp completeness and almost-everywhere subsequences.
Nonnegative increasing measurable functions satisfy monotone convergence Monotone convergence for the integral.
Assume AC The Axiom of Choice.
Proof
Given: AC and the block supplier F1.
Apply F1 for each with and . AC selects one polynomial from each nonempty set of possible polynomials. Its degree can be taken as its greatest nonzero coefficient index, which exists because its norm is one. The stated exceptional sets are measurable because the maxima are finite continuous maxima. The recursion for is explicit; it gives and . F2 therefore places each in the claimed disjoint positive interval and gives .
For partial sums and , the triangle inequality gives . They are Cauchy, so F3 supplies an limit f. Passing K to infinity in the norm inequality gives , and . AC includes the countable choice required by F3.
Apply F4 to . Its increasing limit G is measurable and has integral . For every positive integer M, , so off a null set. There the numerical series converges absolutely; set its sum h to zero on that measurable exceptional set. The resulting function is measurable, a.e., and a.e. A further application of F4 to the nonnegative tail gives . Consequently , so h represents f. No smallness of completed blocks is attributed to their frequency shifts.
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Sources
- Grafakos, Classical Fourier Analysis, third edition (standard reference, not scraped)