Large deviation for slow-fast McKean-Vlasov stochastic differential equations driven by fractional Brownian motions and Brownian motions

In this article, we consider slow-fast McKean-Vlasov stochastic differential equations driven by Brownian motions and fractional Brownian motions. We give a definition of the large deviation principle (LDP) on the product space related to Brownian motion and fractional Brownian motion, which is different from the traditional definition for LDP. Under some proper assumptions on coefficients, LDP is investigated for this type of equations by using the weak convergence method

Crystal Structure of ethyl (E)-3,4-dimethyl-5-((2-(4-methylbenzoyl)hydrazono)methyl)-1H-pyrrole-2-carboxylate — water — ethanol (1/1/1), C20H29N3O5

Abstract C20H29N3O5, triclinic, P1̅ (no. 2), a = 9.1571(18) Å, b = 10.505(2) Å, c = 11.576(2) Å, α = 94.509(4)°, β = 92.570(4)°, γ = 102.312(3)°, V = 1082.4(4)) Å3, Z = 2, R gt(F) = 0.0543, wR ref(F 2) = 0.1704, T = 296(2) K

Halo-to-Halo Similarity and Scatter in the Velocity Distribution of Dark Matter

We examine the Velocity Distribution Function (VDF) in dark matter halos from Milky Way to cluster mass scales. We identify an empirical model for the VDF with a wider peak and a steeper tail than a Maxwell--Boltzmann distribution, and discuss physical explanations. We quantify sources of scatter in the VDF of cosmological halos and their implication for direct detection of dark matter. Given modern simulations and observations, we find that the most significant uncertainty in the VDF of the Milky Way arises from the unknown radial position of the solar system relative to the dark matter halo scale radius.Comment: Accepted to ApJ. Figure 3 and 5 and Section 4 newly added. 6 pages, 6 figures, typeset using emulateap

Decoding working memory and perceptual choice during tactile information processing

Working memory and decision-making are two building blocks of human cog-nition that are involved in most goal-directed behaviors. Exposing the neural underpinnings of these mental functions has been a central goal of cognitive and systems neuroscience. Critically, most models and theories have emerged from empirical findings in the visual domain, leaving open the question of whether they hold for other sensory domains. In this dissertation, I aimed at studying the neural correlates of working memory and decision-making during tactile information processing. In particular, I con-ducted four fMRI studies to address the question of which brain regions repre-sent the contents of working memory and perceptual choices. We found para-metric working memory representation of vibrotactile frequencies distributed across sensory, posterior parietal, and frontal cortices. This finding was also replicated in the visual and auditory modalities. Perceptual choices are repre-sented in the prefrontal and oculomotor regions, even when decoupled from saccade plans. These results support the view that the loci of mental representations depend critically on task requirements and content types