Katherine Whitaker

Associate Professor of Astronomy University of Massachusetts Amherst

  • Amherst MA

Kate Whitaker is an observational extragalactic astronomer who studies galaxy formation and evolution at the very edges of the universe.

Contact

University of Massachusetts Amherst

View more experts managed by University of Massachusetts Amherst

Expertise

Detection of Dead Galaxies
Galaxy formation and evolution
Astronomy

Biography

Kate Whitaker is an observational extragalactic astronomer who studies galaxy formation and evolution over the past twelve billion years of cosmic time.

Working with the Cosmic Dawn Center in Copenhagen, Denmark, Whitaker and her team are working towards pushing our detection of quiescent “red and dead” galaxies even earlier in time (within a billion years of the Big Bang itself!) with a goal understand the detailed physics of the structures and underlying stellar populations of these early massive galaxies.

In 2019, Whitaker gained international attention for her work on a team that discovered a new monster galaxy hiding behind a cloud of stardust.

Social Media

Video

Education

Yale University

Ph.D.

Astronomy

Yale University

M.Phil.

Astronomy

Yale University

M.Sc.

Astronomy

Show All +

Select Recent Media Coverage

The James Webb Space Telescope prompts a rethink of how galaxies form

PNAS  

2023-08-02

Katherine Whitaker talks about the first pictures from the ultra-powerful James Webb Space Telescope. “We would zoom in and be like, ‘Oh wow,’ and ‘What the heck is that?’ It was joy—pure joy.” JWST’s initial results may suggest that stars and galaxies were forming far faster than anyone expected.

View More

New image from Webb Telescope, processed by UMass astronomers, reveals the deepest parts of space in Pandora’s Cluster

The Boston Globe  

2023-02-16

“These galaxies are some of the very first galaxies in the universe,” Katherine Whitaker, an assistant professor of astronomy at UMass Amherst, said in a phone interview. “Webb is like a time machine.”

View More

UMass Amherst astronomers help uncover new details deep in space

WWLP  online

2023-02-15

“With these pictures, we’re looking back in time, 97% of the way to the Big Bang,” says Kate Whitaker, professor of astronomy at UMass Amherst. “The James Webb Space Telescope is fundamentally changing our understanding of our cosmic origins.”

View More

Show All +

Select Publications

JWST UNCOVER: Extremely Red and Compact Object at z phot≃ 7.6 Triply Imaged by A2744

The Astrophysical Journal

2023

Recent JWST/NIRCam imaging taken for the ultra-deep UNCOVER program reveals a very red dropout object at z phot≃ 7.6, triply imaged by the galaxy cluster A2744 (z d= 0.308). All three images are very compact, ie, unresolved, with a delensed size upper limit of r e≲ 35 pc. The images have apparent magnitudes of m F444W∼ 25− 26 AB, and the magnification-corrected absolute UV magnitude of the source is M UV, 1450=− 16.81±0.09. From the sum of observed fluxes and from a spectral energy distribution (SED) analysis, we obtain estimates of the bolometric luminosities of the source of L bol≳ 10 43 erg s− 1 and L bol∼ 10 44–10 46 erg s− 1, respectively.

View more

UNCOVERing the extended strong lensing structures of Abell 2744 with the deepest JWST imaging

Monthly Notices of the Royal Astronomical Society

2023

We present a new parametric lens model for the massive galaxy cluster Abell 2744 based on new ultra-deep JWST imaging taken in the framework of the UNCOVER program. These observations constitute the deepest JWST images of a lensing cluster to date, adding to existing deep Hubble Space Telescope (HST) images and the recent JWST Early Release Science and Director’s Discretionary Time data taken for this field. The wide field of view of UNCOVER (∼45 arcmin2) extends beyond the cluster’s well-studied central core and reveals a spectacular wealth of prominent lensed features around two massive cluster sub-structures in the north and north-west, where no multiple images were previously known.

View more

As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting

The Astrophysical Journal

2023

IOP Publishing
Description
Artificial neural network emulators have been demonstrated to be a very computationally efficient method to rapidly generate galaxy spectral energy distributions, for parameter inference or otherwise. Using a highly flexible and fast mathematical structure, they can learn the nontrivial relationship between input galaxy parameters and output observables. However, they do so imperfectly, and small errors in flux prediction can yield large differences in recovered parameters. In this work, we investigate the relationship between an emulator's execution time, uncertainties, correlated errors, and ability to recover accurate posteriors.

View more

Show All +