Stellar Wakes from Dark Matter Subhalos

We propose a novel method utilizing stellar kinematic data to detect low-mass substructure in the Milky Way's dark matter halo. By probing characteristic wakes that a passing dark matter subhalo leaves in the phase space distribution of ambient halo stars, we estimate sensitivities down to subhalo masses $\sim 10^7\,M_\odot$ or below. The detection of such subhalos would have implications for dark-matter and cosmological models that predict modifications to the halo-mass function at low halo masses. We develop an analytic formalism for describing the perturbed stellar phase-space distributions, and we demonstrate through simulations the ability to detect subhalos using the phase-space model and a likelihood framework. Our method complements existing methods for low-mass subhalo searches, such as searches for gaps in stellar streams, in that we can localize the positions and velocities of the subhalos today.Comment: 6 + 3 pages, 1 + 2 figures, code available at: https://github.com/bsafdi/stellarWake

Pilk Richard Viidalepa perekonnaloole

Richard Viidalepp (Widebaum before Estonianising his name, and later Viidebaum; Jan. 23, 1904 - June 3, 1986), the famous Estonian folklorist, was born in the Jalapuu farm in the village of Nurmsi in Central Estonia. The same farm was the home of Urve Buschmann, the author of the article and R. Viidalepp's niece. On the basis of the 1722 list of inhabitants in the Särgavere estate and the registers of the Järva Peetri congregation, the documented genealogy of Viidalepp's family starts with Jüri Jalapuu and his wife Els (?1730-?1761). In more recent registers their son Jüri (?1771-1843) already appears under the name Widebaum. The family was a typical Estonian family, including farmers, handicraftsmen, inventive technicians, later also intellectuals and artists. Some emigrated (the Finnish and American branches of the Viidebaums) and some were deported to Siberia. The fate of family members and descriptions of family history are illustrated by Richard Viidalepp's letters and family photographs. The last Viidalepps born in the Jalapuu farm moved to Tallinn in 1950

Der natürliche Fluß und seine Veränderung durch den Menschen : dargestellt am Beispiel Oberweser

Am Beispiel der Oberweser zwischen Beverungen und Holzminden wird die weitestgehende Zerstörung eines natürlichen Flußsystems durch den Menschen aufgezeigt. Die für den Naturzustand typischen Gewässerstrukturen wie Stromspaltungen, Uferabbrüche, Kolke und Flachwasserstellen werden eingehend charakterisiert und die Geschichte ihrer Beseitigung beschrieben. Ein Vergleich zwischen ursprünglicher und heutiger Flußlandschaft verdeutlicht die durch das Wirken des Menschen verursachten tiefgreifenden Veränderungen im "Ökosystem Fluß". Es zeigt sich, daß der wesentliche Eingriff des Menschen auf den Fluß heute darin besteht, daß sich die Wirkungen nacheinander folgender Hochwasser nicht mehr summieren können

Collider constraints and new tests of color octet vectors

We analyze the collider sensitivity for new colored resonances in $t\bar{t}$, $b \bar{b}$, and $jj$ final states. While searches in the single production channel are model-dependent, the pair production rate is model independent and the existing $(JJ)(JJ)$ and $4t$ searches impose strong constraints on the relevant branching fractions, where $J = j$ or $b$. We point out the missing, complementary searches in the mixed decay modes, $t\bar{t}(jj)$, $t\bar{t}(b\bar{b})$, and $(b\bar{b})(jj)$. We propose analysis strategies for the $t\bar{t}(jj)$ and $t\bar{t}(b\bar{b})$ decays and find their sensivity surpasses that of existing searches when the decay widths to tops and light jets are comparable. If no other decays are present, collective lower limits on the resonance mass can be set at 1.5~TeV using 37~fb$^{-1}$ of 13~TeV data.Comment: 22 pages, 3 figures, 2 table

Task-related edge density (TED) - a new method for revealing large-scale network formation in fMRI data of the human brain

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges in a brain network that differentially respond in unison to a task onset and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.Comment: 21 pages, 11 figure