Seminars

 

  • September 18, 2020, 2:30 p.m. - MIfA Colloquim 

    • Speaker: Salvatore Vitale

    • Title: The first 5 years of gravitational-wave astrophysics
    • Zoom link: https://umn.zoom.us/j/92030995506?pwd=bWlGV0g5V2ZQSmxYam1hS2ZITkFTUT09, Meeting ID:920 3099 5506, Passcode: [email protected]
    • Professor Vitale is also available for some meetings on Friday, 9/18 morning.  You can sign up for a time at  this link. Please enter your name and e-mail in the spaces provided and a zoom link will be created and sent to everyone who signs up.  
    • Abstract: In 2015 the LIGO observatories discovered gravitational waves. Five years later, signals from tens of binary black holes and two binary neutron stars have been detected. With a detection rate of roughly one source a week, it is now possible to start inferring the properties of the underlying population of black holes in binaries. Meanwhile, new groundbreaking discoveries have been made, such as the observation of an intermediate-mass black hole and of a compact object that could be either the lightest black hole or heaviest neutron star ever detected. In this talk I will present an overview of what we have learned in these first five years, and a summary of what comes next.
  • October 9, 2020, 2:30 p.m. - MIfA Colloquium 

    • David Spergel, Astrophysics, Flatiron Institute

    • Title: Determining the Universe’s Initial Conditions
    • Zoom link: https://www.google.com/url?q=https%3A%2F%2Fumn.zoom.us%2Fj%2F98636692905&sa=D&ust=1604512724069000&usg=AOvVaw05M2MkyTJkyrfgL7EH5nRW
    • Abstract: Observations of the cosmic microwave background and measurements of the large-scale structure of the universe have revealed the initial fluctuations that grew to form galaxies. I will review measurements showing that these fluctuations were Gaussian random phase and that the basic properties of the universe appear to be described by the Lambda Cold Dark Matter model.I will report recent results from the Atacama Cosmology Telescope that probe not only the initial conditions but also map the integrated matter density, integrated pressure and integrated electron monentum through gravitational lensing and the Sunyaev-Zel’dovich Effects. I will then discuss the use of machine learning techniques to enable rapid forward modeling of the universe and discuss how these can be used in the coming years to recover the initial conditions from observations of large-scale structure
  • November 10, 2020, 4:00 p.m.- Seagate Presentation

  • Nicholas Propes, Addishiwot Woldesenbet, Seagate

    • Title: Applied Data Science in Seagate Manufacturing
    • Presentation Slides
    • Zoom Link: https://umn.zoom.us/j/91859416813?pwd=bzN3S3F6NnlXSDNwZ3NkSUZsTkdldz09 Meeting ID: 918 5941 6813 Passcode: JXN6TJ
    • Abstract: Seagate Technology manufacturers world-class, precision-engineered data storage solutions.  Data science offers many opportunities to optimize manufacturing operations.  In this presentation, we provide an overview of Seagate manufacturing and highlight some example use cases of applied machine learning to various systems.  We discuss some of the associated challenges that machine learning presents in manufacturing and internship opportunities at Seagate.
  • December 11, 2020, 2:30 p.m. - MIfA Colloquium

    • Roberto Trotta, Imperial College London 

    • Title: New Statistical Tools Improve Supernova Type Ia Cosmology
    • Zoom link: https://umn.zoom.us/j/98636692905
    • Abstract: One of the observational pillars of the accelerating expansion of the universe attributed to dark energy is the measurement of the redshift-distance relation with type Ia supernovae (SNIa), thermonuclear explosions of CO white dwarfs. While the original discovery of acceleration in 1998 relied on just ~40 SNIas, current samples of over 1,000 spectroscopically confirmed SNIas require a more sophisticated statistical approach to account for systematics, selection effects and intrinsic variability of the SNIas' properties. In the near future, the Vera Rubin Observatory will deliver ~10,000 candidates per year -- too many for complete spectroscopic typing: SNIa cosmology will have to rely on photometric data only, and thus contend with the possibility of non-Ia interlopers which could bias cosmological constraints. In this talk, I will present in a pedagogic fashion the basics of supernova type Ia cosmology. I will then focus on three open questions that need resolving in order to achieve precise and accurate constraints on dark energy in the coming decade: the problem of selection bias in the training set used for machine learning classification of photometric candidates; the question of accurate modeling of selection effects; and the investigation of the dependency of SNIa's brightness on their environment.
  • April 16, 2021, 2:30 p.m. - MIfA Colloquium

    • Zeljko Ivezic, University of Washington

    • Title:
    • Zoom link:
    • Abstract: