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Rachel Bean

Professor of Astronomy

Research

While the last century has seen revolutionary developments in our understanding of the matter we find on Earth, my research focuses on improving our understanding of types of matter, and physical laws, whose existence and properties have been inferred purely from astronomical measurements.

My work focuses on extracting information about cosmological theories, of dark energy, the properties of gravity on cosmic scales and primordial inflation, using observations such as the cosmic microwave background (CMB) and large scale structure data (galaxies and clusters of galaxies).

Dark Energy is the name given to the unknown quantity responsible for the accelerated expansion of the universe we observe today. This acceleration runs counter to the deceleration predicted by General Relativity and a universe populated with Standard Model matter. Dark energy could be a strange new type of matter or it could be evidence that we don’t fully understand how gravity behaves on cosmic scales. I am interested in how can we use different types of astrophysical measurements to distinguish  between competing theories.

My research also looks into methods to test high energy theories of cosmic inflation – a period of rapid expansion during the first moments after the universe was conceived. Inflation occurred at energies inaccessible to terrestrial particle physics experiments, however cosmic large scale structure (galaxies and clusters of galaxies) contains fossil imprints of quantum fluctuations during inflation.  Large scale structure observations, therefore,  provide an unparalleled window into quantum physics at these high energy scales.

I am a member of the LSST Dark Energy Science Collaboration (and led the collaboration from 2015-17), the Dark Energy Spectroscopic Instrument (DESI) science team, the NASA Euclid science team and the NASA WFIRST High Latitude Survey Science Investigation Team. I am also involved in a Cornell-led facility, CCAT-prime.

These surveys will create meticulously detailed maps of the images and/or spectral properties of galaxies and galaxy clusters over volumes of space billions of light-years across. Extracting the cosmological information from these surveys is a challenging enterprise, requiring computational infrastructure and algorithms to manage the massive datasets (e.g. LSST will create datasets of hundreds of TBs each night, and tens of petabytes over its lifetime).

My group is interested in the development and implementation of cosmological tests of the properties of dark energy, gravity and inflation, from combining, contrasting and cross-correlating datasets from the various surveys.

See the INSPIRES catalog for access to a full list of my published papers.

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