GGrantIndex
← Search

CAREER: Gravitational Wave Detection Using Pulsars

$654,917FY2008MPSNSF

Franklin And Marshall College, Lancaster PA

Investigators

Abstract

Dr. Andrea Lommen (Franklin and Marshall College) will conduct a focused effort toward detecting burst sources of gravitational radiation as well as continuing work in the area of stochastic gravitational wave background detection. Burst sources of gravitational waves include eccentric black hole binaries, cosmic strings, and production of super massive black holes. The activities Dr. Lommen will undertake to address these primary goals will yield a number of additional scientific results. These include increased understanding of the interstellar medium, increased understanding of constraints on populations of various gravitational wave sources such as binary massive black holes and cosmic strings, increased number of known pulsars, increased precision in timing pulsars, improved solar system ephemerides, and improved limits on the energy density of the stochastic gravitational wave background. In conjunction with her research, Dr. Lommen will engage undergraduates through modeling of binary systems, computing their waveforms, and performing weekly monitoring of the pulsar data as it comes in from telescopes located all over the world. Because this work will be done in conjunction with a number of international collaborators, it will serve to introduce Franklin and Marshall undergraduates to astronomy and to a global network of astronomers in general, and to gravitational wave detection in particular. There will also be a liaison between US and Australian high schools in a program where the high school students from both countries will learn to conduct remote observations in their classrooms on an on-going basis at the Charles Sturt University Observatory in Bathurst, NSW, Australia. The program will also host a research/teaching postdoctoral fellow.

View original record on NSF Award Search →
CAREER: Gravitational Wave Detection Using Pulsars · GrantIndex