Abstract

Given a Boolean function f:{ -1,1} ^{n}→ { -1,1, define the Fourier distribution to be the distribution on subsets of [n], where each S ⊆ [n] is sampled with probability f ˆ (S) 2 . The Fourier Entropy-influence (FEI) conjecture of Friedgut and Kalai [28] seeks to relate two fundamental measures associated with the Fourier distribution: does there exist a universal constant C > 0 such that H(f ˆ2 ) ≤ C ⋅ Inf (f), where H (fˆ2) is the Shannon entropy of the Fourier distribution of f and Inf(f) is the total influence of f In this article, we present three new contributions toward the FEI conjecture: (1) Our first contribution shows that H(f ˆ2 ) ≤ 2 ⋅ aUC ⊕ (f), where aUC ⊕ (f) is the average unambiguous parity-certificate complexity of f . This improves upon several bounds shown by Chakraborty et al. [20]. We further improve this bound for unambiguous DNFs. We also discuss how our work makes Mansour's conjecture for DNFs a natural next step toward resolution of the FEI conjecture. (2) We next consider the weaker Fourier Min-entropy-influence (FMEI) conjecture posed by O'Donnell and others [50, 53], which asks if H ∞ fˆ2) ≤ C ⋅ Inf(f), where H ∞ fˆ2) is the min-entropy of the Fourier distribution. We show H ∞ (fˆ2) ≤ 2⋅C min ⊕ (f), where C min ⊕ (f) is the minimum parity-certificate complexity of f . We also show that for all ε≥0, we have H ∞ (fˆ2) ≤2 log⁡(∥f ˆ ∥1,ε/(1−ε)), where ∥f ˆ ∥1,ε is the approximate spectral norm of f . As a corollary, we verify the FMEI conjecture for the class of read- k DNFs (for constant k ). (3) Our third contribution is to better understand implications of the FEI conjecture for the structure of polynomials that 1/3-approximate a Boolean function on the Boolean cube. We pose a conjecture: no flat polynomial (whose non-zero Fourier coefficients have the same magnitude) of degree d and sparsity 2 ω(d) can 1/3-approximate a Boolean function. This conjecture is known to be true assuming FEI, and we prove the conjecture unconditionally (i.e., without assuming the FEI conjecture) for a class of polynomials. We discuss an intriguing connection between our conjecture and the constant for the Bohnenblust-Hille inequality, which has been extensively studied in functional analysis.

Highlights

  • One of the dominant uncertainties in current climate projections is the estimation of cloud feedback; whereas it is certain that clouds play a crucial role in the development of the Earth’s albedo and climate sensitivity, our global circulation models (GCM) do not yet possess the resolution to represent realistically boundary layer turbulence and convection that determine cloud fields and emerging mesoscale organization [5]

  • We have given a detailed description of the various factors that determine the performance of a SP of OpenIFS by a large number of independent large eddy simulations (LES) instances

  • The scaling of the application has been improved by optimizing single-threaded performance of Dutch Atmospheric Large Eddy Simulation (DALES) and increasing parallelism in the coupling routines

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Summary

Introduction

One of the dominant uncertainties in current climate projections is the estimation of cloud feedback; whereas it is certain that clouds play a crucial role in the development of the Earth’s albedo and climate sensitivity, our global circulation models (GCM) do not yet possess the resolution to represent realistically boundary layer turbulence and convection that determine cloud fields and emerging mesoscale organization [5]. Resolving the turbulent overturning motion of air and humidity within the atmospheric boundary layer requires grid resolutions typically of the order of 100 m, which is still orders of magnitude beyond state-of-the art GCM’s and non-hydrostatic regional weather models. These models rely on a complex system of process parametrizations, which gives rise to model uncertainties and biases [6]. On the other end of the spectrum of model resolutions, the large eddy simulations (LES) reside At these scales, turbulence is well represented due to self-similarity in the inertial sub-range, convective up- and downdrafts arise from explicitly resolved dynamics and mesoscale phenomena such as cold pools emerge naturally. Computationally not feasible to cover the globe with a single LES

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