Write , and use the second modulus of smoothness . The Jackson kernel is even, nonnegative and has unit integral. Pairing the two halves of its convolution therefore givesWe need a weighted moment estimate rather than just concentration of the Jackson kernel. For , the bounds and implyConsequently, splitting the integral at givesThe second modulus of smoothness satisfies for . To see this, choose when , put , and factor the function translation difference . Squaring gives at most translated second differences of step . Each function translation is an isometry in the supremum norm, and centered and forward second differences have the same supremum norm. This proves the stated scaling bound.
Taking , using , and integrating against the Jackson kernel now provesThus the Jackson operator estimate is uniform in both and .
For the requested degree- best uniform approximation, note that the Jackson kernel, and hence , has trigonometric polynomial degree at most . Indeed the fourth power in the Jackson kernel is the squared modulus of a squared sum of consecutive complex exponentials. Choose , so and . The second-difference integral formula givesApplying the Jackson operator estimate with this yields the concise answerThe change of index is essential: itself generally has degree , exceeding the permitted degree.
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