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  1. Buch ; Online: Topological descriptors of spatial coherence in a convective boundary layer

    Licón-Saláiz, José / Ansorge, Cedrick

    2019  

    Abstract: The interaction between a turbulent convective boundary layer (CBL) and the underlying land surface is an important research problem in the geosciences. In order to model this interaction adequately, it is necessary to develop tools which can describe it ...

    Abstract The interaction between a turbulent convective boundary layer (CBL) and the underlying land surface is an important research problem in the geosciences. In order to model this interaction adequately, it is necessary to develop tools which can describe it quantitatively. Commonly employed methods, such as bulk flow statistics, are known to be insufficient for this task, especially when land surfaces with equal aggregate statistics but different spatial patterns are involved. While geometrical properties of the surface forcing have a strong influence on flow structure, it is precisely those properties that get neglected when computing bulk statistics. Here, we present a set of descriptors based on low-level topological information (i.\,e. connectivity), and show how these can be used both in the structural analysis of the CBL and in modeling its response to differences in surface forcing. The topological property of connectivity is not only easier to compute than its higher-dimensional homological counterparts, but also has a natural relation to the physical concept of a coherent structure.

    Comment: 16 pages, 9 figures
    Schlagwörter Physics - Data Analysis ; Statistics and Probability ; Computer Science - Machine Learning ; Physics - Atmospheric and Oceanic Physics
    Erscheinungsdatum 2019-06-07
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Buch ; Online: Metrics for Learning in Topological Persistence

    Riihimäki, Henri / Licón-Saláiz, José

    2019  

    Abstract: Persistent homology analysis provides means to capture the connectivity structure of data sets in various dimensions. On the mathematical level, by defining a metric between the objects that persistence attaches to data sets, we can stabilize invariants ... ...

    Abstract Persistent homology analysis provides means to capture the connectivity structure of data sets in various dimensions. On the mathematical level, by defining a metric between the objects that persistence attaches to data sets, we can stabilize invariants characterizing these objects. We outline how so called contour functions induce relevant metrics for stabilizing the rank invariant. On the practical level, the stable ranks are used as fingerprints for data. Different choices of contour lead to different stable ranks and the topological learning is then the question of finding the optimal contour. We outline our analysis pipeline and show how it can enhance classification of physical activities data. As our main application we study how stable ranks and contours provide robust descriptors of spatial patterns of atmospheric cloud fields.

    Comment: 16 pages, 8 figures
    Schlagwörter Computer Science - Machine Learning ; Physics - Data Analysis ; Statistics and Probability ; Statistics - Machine Learning
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2019-06-11
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Buch ; Online ; Dissertation / Habilitation: Topological Aspects of Turbulence in the Planetary Boundary Layer

    Licon-Salaiz, Jose [Verfasser] / Kunoth, Angela [Gutachter]

    2020  

    Verfasserangabe Jose Licon-Salaiz ; Gutachter: Angela Kunoth
    Schlagwörter Naturwissenschaften ; Science
    Thema/Rubrik (Code) sg500
    Sprache Englisch
    Verlag Universitäts- und Stadtbibliothek Köln
    Erscheinungsort Köln
    Dokumenttyp Buch ; Online ; Dissertation / Habilitation
    Datenquelle Digitale Dissertationen im Internet

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  4. Artikel: The Structure of the Convective Boundary Layer as Deduced from Topological Invariants

    Licón-Saláiz, José / Ansorge, Cedrick / Shao, Yaping / Kunoth, Angela

    Boundary-layer meteorology. 2020 July, v. 176, no. 1

    2020  

    Abstract: We study the convective boundary layer (CBL) through low-order topological properties of updrafts and downdrafts, that is, based solely on the sign of the vertical velocity. The geometric representation of the CBL as a pair of two-dimensional cubical ... ...

    Abstract We study the convective boundary layer (CBL) through low-order topological properties of updrafts and downdrafts, that is, based solely on the sign of the vertical velocity. The geometric representation of the CBL as a pair of two-dimensional cubical complexes, one each for updrafts and downdrafts, is exemplarily obtained from two simulations of the CBL, a realistic daily cycle and an idealized quasi-steady CBL growing into linear stratification. Each cubical complex is defined as a set of grid cells that have the same sign of vertical velocity, either positive or negative. Low-order topological invariants, namely the Betti numbers of the cubical complexes, are found to capture key aspects of the boundary-layer organization and evolution over the diurnal cycle. An unsupervised-learning algorithm is trained using the topological invariants in order to classify the spatio–temporal evolution of convection over a whole day. The successful classification of the CBL by using this approach illustrates the potential of such simplified representation of turbulent flow for data reduction and boundary-layer parametrization approaches.
    Schlagwörter algorithms ; convection ; evolution ; geometry ; meteorology ; topology ; turbulent flow
    Sprache Englisch
    Erscheinungsverlauf 2020-07
    Umfang p. 1-12.
    Erscheinungsort Springer Netherlands
    Dokumenttyp Artikel
    Anmerkung NAL-AP-2-clean ; Letter
    ZDB-ID 1477639-X
    ISSN 1573-1472 ; 0006-8314
    ISSN (online) 1573-1472
    ISSN 0006-8314
    DOI 10.1007/s10546-020-00517-w
    Datenquelle NAL Katalog (AGRICOLA)

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  5. Artikel: Kilohertz droplet-on-demand serial femtosecond crystallography at the European XFEL station FXE.

    Perrett, Samuel / Fadini, Alisia / Hutchison, Christopher D M / Bhattacharya, Sayantan / Morrison, Cade / Turkot, Oleksii / Jakobsen, Mads Bregenholt / Größler, Michael / Licón-Saláiz, José / Griese, Florian / Flewett, Samuel / Valerio, Joana / Schulz, Joachim / Biednov, Mykola / Jiang, Yifeng / Han, Huijong / Yousef, Hazem / Khakhulin, Dmitry / Milne, Christopher /
    Barty, Anton / van Thor, Jasper J

    Structural dynamics (Melville, N.Y.)

    2024  Band 11, Heft 2, Seite(n) 24310

    Abstract: X-ray Free Electron Lasers (XFELs) allow the collection of high-quality serial femtosecond crystallography data. The next generation of megahertz superconducting FELs promises to drastically reduce data collection times, enabling the capture of more ... ...

    Abstract X-ray Free Electron Lasers (XFELs) allow the collection of high-quality serial femtosecond crystallography data. The next generation of megahertz superconducting FELs promises to drastically reduce data collection times, enabling the capture of more structures with higher signal-to-noise ratios and facilitating more complex experiments. Currently, gas dynamic virtual nozzles (GDVNs) stand as the sole delivery method capable of best utilizing the repetition rate of megahertz sources for crystallography. However, their substantial sample consumption renders their use impractical for many protein targets in serial crystallography experiments. Here, we present a novel application of a droplet-on-demand injection method, which allowed operation at 47 kHz at the European XFEL (EuXFEL) by tailoring a multi-droplet injection scheme for each macro-pulse. We demonstrate a collection rate of 150 000 indexed patterns per hour. We show that the performance and effective data collection rate are comparable to GDVN, with a sample consumption reduction of two orders of magnitude. We present lysozyme crystallographic data using the Large Pixel Detector at the femtosecond x-ray experiment endstation. Significant improvement of the crystallographic statistics was made by correcting for a systematic drift of the photon energy in the EuXFEL macro-pulse train, which was characterized from indexing the individual frames in the pulse train. This is the highest resolution protein structure collected and reported at the EuXFEL at 1.38 Å resolution.
    Sprache Englisch
    Erscheinungsdatum 2024-04-17
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2758684-4
    ISSN 2329-7778
    ISSN 2329-7778
    DOI 10.1063/4.0000248
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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