most citedEstimating the Redshift Distribution of Faint Galaxy Samples

207 citations · 368 across the 2 of their papers we have counts for

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astro-ph2008252 cited

Non-linear Evolution of f(R) Cosmologies III: Halo Statistics

Fabian Schmidt, Marcos Lima, Hiroaki Oyaizu +1

The statistical properties of dark matter halos, the building blocks of cosmological observables associated with structure in the universe, offer many opportunities to test models…

astro-ph2008208 cited

Non-linear evolution of f(R) cosmologies II: power spectrum

Hiroaki Oyaizu, Marcos Lima, Wayne Hu

We carry out a suite of cosmological simulations of modified action f(R) models where cosmic acceleration arises from an alteration of gravity instead of dark energy. These models…

astro-ph2008178 cited

Non-linear evolution of f(R) cosmologies I: methodology

Hiroaki Oyaizu

We introduce the method and the implementation of a cosmological simulation of a class of metric-variation f(R) models that accelerate the cosmological expansion without a cosmolog…

astro-ph2008207 cited

Estimating the Redshift Distribution of Faint Galaxy Samples

Marcos Lima, Carlos E. Cunha, Hiroaki Oyaizu +3

We present an empirical method for estimating the underlying redshift distribution N(z) of galaxy photometric samples from photometric observables. The method does not rely on phot…

astro-ph2007128 cited

Cross-correlation Weak Lensing of SDSS Galaxy Clusters I: Measurements

Erin S. Sheldon, David E. Johnston, Ryan Scranton +12

This is the first in a series of papers on the weak lensing effect caused by clusters of galaxies in Sloan Digital Sky Survey. The photometrically selected cluster sample, known as…

astro-ph2007161 cited

A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6

Hiroaki Oyaizu, Marcos Lima, Carlos E. Cunha +3

We present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6). We use the Artificial Neural Network (AN…