[Physics-grads-open] Dissertation Defense, Ming-Feng Ho, 8/12 (Mon) at 1 PM

[Ming-Feng Ho]

Hi all!

I'd like to update my defense location to: *MRB 1110*.

Updated information:

*Date/Time: 8/12 (Monday) at 1 PM or after Niusha's defense*

*Place: MRB 1110 Seminar Room*

So we can have two astro defenses in the same room. :)

Zoom link for remote join:
https://ucr.zoom.us/j/92505382183?pwd=Fqi6yZXr7jTzVXb3HZLytH1WIqtMao.1

ID: 925 0538 2183
Password: 1216

Thanks!
Ming-Feng


On Tue, Aug 6, 2024 at 4:30 PM Ming-Feng Ho <mingfeng.ho at email.ucr.edu>
wrote:

> Hi all!
>
> I’d like to advertise my PhD thesis defense! Everyone is welcome to join.
> P.S., the location is in MRB, not Physics building.
>
> Date/Time: *8/12 (Monday) at 1 PM*
> Place: *4th floor, Conference Room, Multidisciplinary Research Building
> <https://maps.app.goo.gl/w4Jt6MDZg3Wce9eS6> (MRB)*
>
> Zoom link for remote join:
> https://ucr.zoom.us/j/92505382183?pwd=Fqi6yZXr7jTzVXb3HZLytH1WIqtMao.1
>
> ID: 925 0538 2183
> Password: 1216
>
> *Title: Model-Driven Cosmology with Bayesian Machine Learning & Population
> Inference*
>
> *Abstract*:
> In this talk, I will present two research projects during my PhD. In the
> first part, I will introduce the concept of “emulation,” a fast-to-compute
> regression model that helps researchers utilize slow-to-compute simulations
> in data analysis tasks. Emulators have been widely used in cosmology since
> the 2010s. During that time, cosmologists began relying on expensive N-body
> simulations to explain the observed distributions of galaxies or gases. A
> typical Bayesian data analysis for cosmology requires millions of
> simulations; however, only hundreds of N-body simulations are computable.
> Emulators act as a “surrogate” model for simulations in data analyses by
> using a Bayesian interpolator trained on simulations’ inputs and outputs.
> Emulators make cosmology data analysis possible for current observations.
> However, the curse of dimensionality restricts the development of emulators
> from expanding to higher dimensions, which is crucial for exploring beyond
> ΛCDM parameters or astrophysical feedback effects, the science goals for
> future Stage-V cosmological surveys. To address this problem, we developed
> the “multi-fidelity emulation.” Multi-fidelity emulation uses
> cheaply-obtained simulations to fill the high-dimensional parameter space
> and only a few expensive-and-slow simulations to correct the resolution
> differences. I will explain how effective multi-fidelity emulation is
> applied in cosmology and discuss potential future improvements by using it.
> Then, I will present two applications of multi-fidelity simulations from
> Bird’s group: Goku simulations for beyond ΛCDM and PRIYA simulations for
> the Lyα forest.
>
> In the second part of the talk, I will discuss gravitational wave
> astronomy. LIGO-Virgo’s first detection of gravitational waves from binary
> black holes (BBHs) dates back to 2016. By 2021, the number of detected BBH
> events had increased to approximately 90. With this number of events,
> astronomers can study the formation origins of these BBHs by fitting
> Bayesian hierarchical models and inferring the population statistics. The
> recent LIGO-Virgo-KAGRA (LVK) population analysis reveals a Gaussian bump
> substructure at ~35 M⊙ in the primary mass spectrum, while the rest of the
> black holes are mostly distributed in a power-law distribution from ~5 M⊙
> to ~80 M⊙. An interesting question is whether this ~35 M⊙ Gaussian
> population of black holes is mixed with the power-law distribution or if
> they remain separate due to distinct formation channels. We designed a
> Bayesian hierarchical model to measure the co-location and separation of
> the power-law and Gaussian populations in the LVK catalog using a mixture
> model approach. We found that the posterior suggests that the Gaussian bump
> black holes prefer to merge within their cohort, indicating a preference
> for these two populations to be separate. Current formation channels for
> producing the Gaussian bump might also need to consider the separation of
> this population.
>
> Thank you and look forward to seeing you!
> Ming-Feng
>
> ---
> Ming-Feng Ho
> PhD Candidate (NASA FINESST FI)
> Physics and Astronomy
> University of California, Riverside
> Bird's group
> jibancat.github.io
>
>
>
>
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