About 25-50% of observed white dwarfs atmospheres are polluted
by elements heavier than Helium, even though these elements are expected
to sink quickly. Previous work show that accretion of materials
over the course of several billions years is needed to match observations.
Current consensus is that the white dwarf accretes from the remnant
planets and planetesimals, which are tidally disrupted as they get close to the
star. Two important questions arise:
What are the potential reservoirs in an evolved planetary system?
Which mechanisms excite
these bodies' eccentricity so that they may be able to get close to the
white dwarf?
I am broadly interested in answering these two questions using numerical and analytical methods.
These projects seek to understand the long-term evolution of planetary systems
and connect them to observations of polluted white dwarfs.
I have modeled the dynamics (Pham & Rein, 2024)
and chemical composition of comets over time,
and have developed numerical models to study these processes.
Exoplanet Obliquity & Dynamics
The obliquity (tilt) of exoplanets important factor for
climate and habitability. In the last few years,
we have begun to measure obliquity. I am interested in understanding
the dynamics of exoplanet obliquity, and predicting their obliquity evolution
over time. I have modeled obliquity evolution through secular
spin-orbit coupling with a distant exomoon (Poon, Rein & Pham, 2024).
Numerical Methods
Many problems require numerical simulations. I am interested in
improving numerical methods and ensuring their accuracy.
I have worked in developing a new adaptive timestepping criterion
(Pham, Rein, & Spiegel, 2024),
a fast dynamical integration technique for small bodies around binary systems
(Pham & Rein, 2024),
and a new long-term comet evolution code that fully couples dynamical,
stellar, thermal, and volatiles evolution.
Statistical Methods
I am interested in applying statistical methods and machine learning
to astrophysical problems. I have recently applied Bayesian inference
on the current ensemble of observed exoplanet obliquity to understand
formation mechanisms (Poon et al., 2025). I have also used machine learning methods, supervised
and unsupervised, together with statistical techniques to
characterize exoplanets from photometric observations
(Pham & Kaltenegger 2021,
Pham & Kaltenegger 2022,
Li et al., 2024), and to cluster
planet types from planet formation simulations
(Schlecker, Pham, Burns et al., 2021).
Small Bodies & Fast Radio Bursts
Fast radio bursts (FRBs) are millisecond radio events.
Their physical origin remains unknown. I am interested in the possibility
that these FRBs are caused by small bodies (asteroids, comets) impacting neutron stars.
I have modeled the dynamics of these small bodies around neutron stars,
and their collision rates, and made some observational predictions for this scenario
(Pham, Hopkins et al., 2024).
Simulation & Atmosphere Removal for the TIME Collaboration
TIME (Tomographic Ionized Carbon Intensity Mapping Experiment)
is an [CII]/CO line-intensity mapping instrument seeking
to understand the epoch of reionization.
Having an understanding of the epoch of reionization remains a
central task in building a complete picture of the Universe's evolution,
early galaxies formation, and star formation history. In this project,
I am mostly involved in building a simulation pipeline and perform
atmosphere removal for TIME observations
(Butler et al., 2024, Yang et al., 2025).