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Register a new userThe Supremum Norm of the Discrepancy Function: Recent Results and Connections
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A great challenge in the analysis of the discrepancy function D_N is to obtain universal lower bounds on the L-infty norm of D_N in dimensions d geq 3. It follows from the average case bound of Klaus Roth that the L-infty norm of D_N is at least (log N) ^{(d-1)/2}. It is conjectured that the L-infty bound is significantly larger, but the only definitive result is that of Wolfgang Schmidt in dimension d=2. Partial improvements of the Roth exponent (d-1)/2 in higher dimensions have been established by the authors and Armen Vagharshakyan. We survey these results, the underlying methods, and some of their connections to other subjects in probability, approximation theory, and analysis.
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It is a well-known conjecture in the theory of irregularities of distribution that the L1 norm of the discrepancy function of an N-point set satisfies the same asymptotic lower bounds as its L^2 norm. In dimension d=2 this fact has been established by Halasz, while in higher dimensions the problem is wide open. In this note, we establish a series of dichotomy-type results which state that if the L^1 norm of the discrepancy function is too small (smaller than the conjectural bound), then the discrepancy function has to be large in some other function space.
The paper proposes a novel event-triggered control scheme for nonlinear systems based on the input-delay method. Specifically, the closed-loop system is associated with a pair of auxiliary input and output. The auxiliary output is defined as the derivative of the continuous-time input function, while the auxiliary input is defined as the input disturbance caused by the sampling or equivalently the integral of the auxiliary output over the sampling period. As a result, a cyclic mapping forms from the input to the output via the system dynamics and back from the output to the input via the integral. The event-triggering law is constructed to make the mapping contractive such that the stabilization is achieved and an easy-to-check Zeno-free condition is provided. With this idea, we develop a theorem for the event-triggered control of interconnected nonlinear systems which is employed to solve the event-triggered control for lower-triangular systems with dynamic uncertainties.
A new structure function analysis of CCFR deep inelastic nu-N and nubar-N scattering data is presented for previously unexplored kinematic regions down to Bjorken x=0.0045 and Q^2=0.3 GeV^2. Comparisons to charged lepton scattering data from NMC and E665 experiments are made and the behavior of the structure function F2_nu is studied in the limit Q^2 -> 0
The purpose of this paper is to extend the result of arXiv:1810.00823 to mixed Holder functions on $[0,1]^d$ for all $d ge 1$. In particular, we prove that by sampling an $alpha$-mixed Holder function $f : [0,1]^d rightarrow mathbb{R}$ at $sim frac{1}{varepsilon} left(log frac{1}{varepsilon} right)^d$ independent uniformly random points from $[0,1]^d$, we can construct an approximation $tilde{f}$ such that $$ |f - tilde{f}|_{L^2} lesssim varepsilon^alpha left(log textstyle{frac{1}{varepsilon}} right)^{d-1/2}, $$ with high probability.
Given $n$ polynomials $p_1, dots, p_n$ of degree at most $n$ with $|p_i|_infty le 1$ for $i in [n]$, we show there exist signs $x_1, dots, x_n in {-1,1}$ so that [Big|sum_{i=1}^n x_i p_iBig|_infty < 30sqrt{n}, ] where $|p|_infty := sup_{|x| le 1} |p(x)|$. This result extends the Rudin-Shapiro sequence, which gives an upper bound of $O(sqrt{n})$ for the Chebyshev polynomials $T_1, dots, T_n$, and can be seen as a polynomial analogue of Spencers six standard deviations theorem.
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