David Hendriks

PhD Student Astrophysics

University of Surrey

Biography

My name is David Hendriks, and I’m a final year PhD student at the university of Surrey. My PhD is on binary star interactions and how accretion disks outflows affect their orbital evolution, as well as which of these binary star systems evolve in to binary black hole systems that merge through gravitational wave emission. I make use of ballistic orbit integration codes to study the behaviour of particles in a gravitational potential, binary population synthesis to evolve large populations of binary stars (using the package that I wrote called binary_c-python), as well as detailed accretion disk evolution codes to study the behaviour of accretion disks in detail.

Interests

Stellar evolution
Compact object formation
Planetary formation
Bayesian sampling methods
Notetaking and organising thoughts
Physics informed neural networks

Education

PhD Astrophysics, 2018 - Now

University of Surrey
Msc Astronomy (GRAPPA), 2015 - 2018

University of Amsterdam
Bsc Physics and astronomy, 2011 - 2015

University of Amsterdam

Publications

R. M. Yates, David Hendriks, A. P. Vijayan, R. G. Izzard, P. A. Thomas, P. Das (2023). The Impact of Binary Stars on the Dust and Metal Evolution of Galaxies.

Cite URL Zenodo

G. M. Mirouh, David Hendriks, S. Dykes, M. Moe, R. G. Izzard (2023). Detailed Equilibrium and Dynamical Tides: Impact on Circularization and Synchronization in Open Clusters. Published in MNRAS.

David Hendriks, L. A. C. van Son, M. Renzo, R. G. Izzard, R. Farmer (2023). Pulsational Pair-Instability Supernovae in Gravitational-Wave and Electromagnetic Transients. MNRAS.

Cite DOI Blogpost URL Zenodo

David Hendriks, R. G. Izzard (2023). Mass-Stream Trajectories with Non-Synchronously Rotating Donors. Published in MNRAS.

Cite DOI Blogpost URL Zenodo

David Hendriks, R. G. Izzard (2023). Binary_c-Python: A Python-based Stellar Population Synthesis Tool and Interface to Binary_c. published in JOSS.

Cite DOI URL Gitlab repo Documentation

See all publications

Recent Posts

binary_c-python

For my research during my masters and PhD I’ve made us of the rapid (binary) stellar evolution code binary_c, to simulate (binary) star systems. The population-synthesis wrapper that enabled running many of these systems was written in Perl but I decided to rewrite this into a Python based code. The code is well documented and automatically generated based on docstrings, and is available on Gitlab and Pypi. We provide tutorial and example notebooks on how to use the code technically, and how to actually calculate useful things with it on documentation page.

Nov 6, 2023

Astrotalks

Table of Contents astrotalks and where to find them ## astrotalks and where to find them aaa

Nov 6, 2023

Mass-stream trajectories in binary systems

While working on my project on the role of disk mass-transfer in systems with main-sequence accretors I found that in many cases mass transfer occurred with a donor that rotated sub-synchronously (slower than the orbit), although the torques and other properties of the mass-transfer were calculated to occur from synchronous donors. It is important to properly account for this because my goal is to make a correct concensus of how important disk mass-transfer is in these systems, and using the wrong stream properties strongly affects whether disks will form.

Oct 29, 2023

My workflow and setup

Table of Contents ZSH + oh-my-ZSH FZF TODO TMUX + addons pyenv & pyenv-virtualenv Git pre-commit hooks Emacs + Org In my day to day life as an Astrophysics PhD student I make heavy use of linux systems and spend many hours within terminal environments and running things on servers. Over the years I’ve created a nice workflow and setup to make things a bit easier, and below is a bit of a write up of this.

Nov 20, 2022

Acceleration Hamiltonian Monte Carlo through neural symplectic transformations and action angle sampling

During the last phase of my PhD I worked together with Dr. Payel Das, Dr. Simon Hadfield and Dr. Yunpeng Li, on a project aimed at accelerating Hamiltonian Monte-Carlo. This project was quite a cross-disciplinary effort, as we had to combine ideas from (astro)physics together with computer science and probabilistic mathematics. Hamiltonian Monte-Carlo is a Monte-Carlo sampling/inference technique which uses techniques from classical mechanics to guide the sampling through the posterior.

Oct 11, 2022