70 citations · 447 across the 15 of their papers we have counts for
10 papers · 1 filter
Constraining cosmology with machine learning and galaxy clustering: the CAMELS-SAM suite
Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro +5
As the next generation of large galaxy surveys come online, it is becoming increasingly important to develop and understand the machine learning tools that analyze big astronomical…
New spectroscopic confirmations of Lyman- emitters at z 7 from the LAGER survey
Santosh Harish, Isak G. B. Wold, Sangeeta Malhotra +14
We report spectroscopic confirmations of 15 Lyman-alpha galaxies at , implying a spectroscopic confirmation rate of 80% on candidates selected from LAGER (Lyman-Alpha…
LAGER Ly Luminosity Function at , Implications for Reionization
Isak G. B. Wold, Sangeeta Malhotra, James Rhoads +17
We present a new measurement of the Ly luminosity function at redshift , finding moderate evolution from that is consistent with a fully or largely ionized $z\sim…
Correlations between H Equivalent Width and Galaxy Properties at : Physical or Selection-driven?
Ali Ahmad Khostovan, Sangeeta Malhotra, James E. Rhoads +13
The H equivalent width (EW) is an observational proxy for specific star formation rate (sSFR) and a tracer of episodic star-formation activity. Previous assessments show that EW…
A Lyman-α protocluster at redshift 6.9
Weida Hu, Junxian Wang, Leopoldo Infante +21
Protoclusters, the progenitors of the most massive structures in the Universe, have been identified at redshifts of up to 6.6. Besides exploring early structure formation, searchin…
Void Probability Function of Simulated Surveys of high-redshift Lyman-Alpha Emitters
Lucia A. Perez, Sangeeta Malhotra, James E. Rhoads +1
We calculate the void probability function (VPF) in simulations of Lyman- emitters (LAEs) across a wide redshift range (). The VPF measures the zero-poi…