Introduction I am an astrophysicist and recent graduate from the department of Astronomy and Astrophysics at the University of Chicago (Ph.D. 2014, advisor Joshua A. Frieman), with a passion for astronomy, science communication and data visualization.
For my professional website please visit alanzablocki.com.
My Ph.D. thesis work involved analysis of very large data sets from galaxy surveys to constrain aspects of fundamental physics, such as the nature of dark energy and the masses of neutrinos. In particular, I studied how the measurements of the spatial clustering of galaxies on the sky can be used to determine neutrino masses.
My research involves numerical computation, data analysis and uses sophisticated statistical methods such as Bayesian statistics and Monte Carlo techniques.
I have developed a likelihood analysis pipeline to test how well the Dark Energy Survey will be able to constrain the neutrino masses. This includes testing the pipeline on simulated datasets and measuring any bias in the estimates of the model parameters due to various astrophysical and theoretical uncertainties.
I am interested in Cosmology and General Relativity, and more specifically in:
- Neutrino effects on Structure Formation
- Lossless data compression algorithms
- CMB Physics
- Nature of Dark Matter and Dark Energy
- Primordial Gravitational Waves as signatures of Inflation
- Cosmic Reionization in the 21cm