E
Edmund Bertschinger
Researcher at Massachusetts Institute of Technology
Publications - 143
Citations - 12080
Edmund Bertschinger is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Dark matter & Cold dark matter. The author has an hindex of 49, co-authored 143 publications receiving 11425 citations. Previous affiliations of Edmund Bertschinger include University of California, Santa Barbara & Institute for Advanced Study.
Papers
More filters
Journal ArticleDOI
Cosmological Perturbation Theory in the Synchronous and Conformal Newtonian Gauges
Chung-Pei Ma,Edmund Bertschinger +1 more
TL;DR: In this paper, the authors present a systematic treatment of the linear theory of scalar gravitational perturbations in the synchronous gauge and the conformal Newtonian (or longitudinal) gauge.
Journal ArticleDOI
Cosmological Perturbation Theory in the Synchronous and Conformal Newtonian Gauges
Chung-Pei Ma,Edmund Bertschinger +1 more
TL;DR: In this article, the authors present a systematic treatment of the linear theory of scalar gravitational perturbations in the synchronous gauge and the conformal Newtonian (or longitudinal) gauge.
Journal ArticleDOI
Self-similar secondary infall and accretion in an Einstein-de Sitter universe
TL;DR: Similarity solutions have been found for secondary infall and accretion onto an initially overdense perturbation in an Einstein-de Sitter (..cap omega.. = 1) universe.
Journal ArticleDOI
Dynamics of radiative supernova remnants
TL;DR: In this paper, a high-resolution numerical simulation is used to study the evolution of a SNR evolving in a homogeneous uniform medium, focusing on the transition from the adiabatic stage to the radiative pressure-driven snowplow stage, along with the possible further establishment of a momentum-conserving SNR state.
Journal ArticleDOI
Multiscale Gaussian Random Fields and Their Application to Cosmological Simulations
TL;DR: In this paper, the authors describe the generation of Gaussian random fields with multiple levels of resolution and present the theory of adaptive mesh refinement of Gaussian random fields followed by the implementation and testing of a computer code package performing this refinement called GRAFIC2.