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ScotDIST annual research conference 2019

15 November 2019
8 University Gardens, U of Glasgow
Europe/London timezone

Session

Talks

15 Nov 2019, 11:00
101 (8 University Gardens, U of Glasgow)

101

8 University Gardens, U of Glasgow

University of Glasgow University Place GLASGOW G12 8QQ

Presentation materials

There are no materials yet.

  1. 21. Earth Object Detection on-board CubeSats Using Deep Learning
    John Armstrong (University of Glasgow)
    15/11/2019, 11:00
  2. 22. Doubly charmed baryon searches at LHCb
    Dana Bobulska (University of Glasgow), Dana Seman Bobulska (University of Glasgow (GB))
    15/11/2019, 11:10

    The main focus of my research work - search for the doubly charmed baryon Xicc+ in two different decay channels using data recorded by the LHCb experiment, will be discussed.

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  3. 24. Constraining Astronomy with Nuclear Physics and vice versa
    Samuel Lloyd (University of Edinburgh)
    15/11/2019, 11:20

    Nuclear physics, through computational models, provides the opportunity to constrain astronomy. Little is known about the oldest stars, but through observations of there successors and nucleosynthetic models, we can begin to predict the conditions they produced and their properties.

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  4. 23. The highs and lows of an industry placement
    Teri Love (University of St Andrews)
    15/11/2019, 11:30

    I will discuss my first industry placement which took place over the summer at the Heineken UK HQ in Edinburgh. A brief insight will be given into working in industry. (It's not all about Beer!)

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  5. 25. Gamma-Ray Burst Jet Structure Modelling
    Fergus John Hayes
    15/11/2019, 11:40

    The angular distribution of energy from gamma-ray bursts is unknown, but it is believed their could be a common structure among all these astrophysical events. I combine gravitational wave and electromagnetic data to perform model comparison between different existing jet structure models and infer model parameters. I also perform a non-parametric approach to determine the structure using...

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  6. 26. GW propagation through the clumpy universe
    Marios Kalomenopoulos (University of Edinburgh)
    15/11/2019, 11:50
  7. 27. Craft prospect placement
    Gennaro Di Pietro (University of Edinburgh)
    15/11/2019, 13:30

    I will discuss my time with Craft Prospect giving details on some of the work completed and my personal experience from the placement.

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  8. 28. Using MCMC techniques in a scattering amplitude analysis
    Robert Wishart (University of Glasgow)
    15/11/2019, 13:40

    In addition to more classic parameter estimation techniques, MCMC techniques can be implemented to compliment these methods as a further analysis tool. These tools become especially useful when the dimensionality of parameter spaces become high, as is the case with the three pion production channel that will be a focus of this analysis.

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  9. 29. (Machine) learning the structure of BSM matrix element corrections
    Abhijeet Gangan (University of Glasgow)
    15/11/2019, 13:50
  10. 30. Placement: Spotting Bad Kegs on a Production Line
    Adam Thornton (University of Edinburgh)
    15/11/2019, 14:00
  11. 31. Hyper-fast gravitational wave parameter estimation using machine learning
    Hunter Gabbard (University of Glasgow)
    15/11/2019, 14:10

    Gravitational wave detection is now commonplace and as the sensitivity of the global network of GW detectors improves, we will observe O(100)s of transient GW events per year. The current methods used to estimate their source parameters employ optimally sensitive but computationally costly Bayesian inference approaches where typical analyses have taken between 6 hours and 5 days. Here we show...

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  12. 32. Improving B meson form factor calculations in lattice QCD
    Esther Pertinez (University of Glasgow)
    15/11/2019, 14:20
  13. 33. LIGO fellowship experience
    Laurence Datrier (University of Glasgow)
    15/11/2019, 15:00
  14. 34. Information production in homogeneous isotropic turbulence
    Daniel Clark (University of Edinburgh)
    15/11/2019, 15:10

    One of the most striking features of turbulent fluid flows is their seemingly random and unpredictable nature. However, since such fluids are described by the Navier-Stokes equations, which are entirely deterministic in nature, their motion cannot be truly random. In reality, turbulent flows exhibit what is commonly referred to as deterministic chaos. The time evolution of such systems is...

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  15. 35. Combining collider analysis data for global BSM bounds-setting
    Stephen Brown (University of Glasgow), Stephen Brown (University of Glasgow), Stephen Brown (University of Glasgow)
    15/11/2019, 15:20
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