In the present paper, we introduce and study two new subclasses of analytic $m$-fold symmetric bi-univalent functions defined in open unit disk $U$. Furthermore, for each introduced here, obtain upper bounds initial coefficients $\left| a_{m+1}\right|$ a_{2m+1}\right|$. Also, indicate certain special cases our results.

are known as Lieb-Thirring bounds and hold true with finite constants Lγ,d if and only if γ ≥ 1/2 for d = 1, γ > 0 for d = 2 and γ ≥ 0 for d ≥ 3. Here and in the following, A± = (|A| ± A)/2 denote the positive and negative parts of a self-adjoint operator A. The case γ > (1 − d/2)+ was shown by Lieb and Thirring in [21]. The critical case γ = 0, d ≥ 3 is known as the Cwikel-Lieb-Rozenblum inequ...

Consider the Schrödinger operators H± = −d/dx ± V (x). We present a method for estimating the potential in terms of the negative eigenvalues of these operators. Among the applications are inverse Lieb-Thirring inequalities and several sharp results concerning the spectral properties of H±.

In this article, we derive a new covariance estimate. The estimate has a similar structure as the Brascamp-Lieb inequality and is optimal for ferromagnetic Gaussian measures. It can be naturally applied to deduce decay of correlations of lattice systems of continuous spins. We also discuss the relation of the new estimate with known estimates like a weighted estimate due to Helffer & Ledoux. Th...

So far we have talked about the expectation of random variables, and moved on to the variance or the second moment. However, neither of these methods is strong enough to produce the tight bounds needed for some applications. We have already stated that if all you are given is the variance of a r.v., then Chebyshev’s Inequality is essentially the best you can do. Thus, more information is needed...

We consider a process given as the solution of a stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. Explicit and optimal bounds for the Lebesgue density of that process at any given time are derived. The bounds and their optimality is shown by identifying the worst case stochastic differential equation. Then we generalise...