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Full-Text Articles in Physical Sciences and Mathematics
The Discovery Of A Gravitationally Lensed Supernova Ia At Redshift 2.22, David Rubin, Brian Hayden, Xiaosheng Huang, Greg Aldering, R Amanullah, K Barbary, K Boone, M Brodwin, S E. Deustua, S Dixon, P Eisenhardt, A S. Fruchter, A H. Gonzalez, A Goobar, R R. Gupta, I Hook, M. James Jee, A G. Kim, M Kowalski, C Lidman, E V. Linder, K Luther, J Nordin, R Pain, Saul Perlmutter, Z Raha, M Rigault, P Ruiz-Lapuente, C Saunders, C Sofiatti, A L. Spadafora, S A. Stanford, D Stern, N Suzuki, S C. Williams
The Discovery Of A Gravitationally Lensed Supernova Ia At Redshift 2.22, David Rubin, Brian Hayden, Xiaosheng Huang, Greg Aldering, R Amanullah, K Barbary, K Boone, M Brodwin, S E. Deustua, S Dixon, P Eisenhardt, A S. Fruchter, A H. Gonzalez, A Goobar, R R. Gupta, I Hook, M. James Jee, A G. Kim, M Kowalski, C Lidman, E V. Linder, K Luther, J Nordin, R Pain, Saul Perlmutter, Z Raha, M Rigault, P Ruiz-Lapuente, C Saunders, C Sofiatti, A L. Spadafora, S A. Stanford, D Stern, N Suzuki, S C. Williams
Physics and Astronomy
We present the discovery and measurements of a gravitationally lensed supernova (SN) behind the galaxy cluster MOO J1014+0038. Based on multi-band Hubble Space Telescope and Very Large Telescope (VLT) photometry of the supernova, and VLT spectroscopy of the host galaxy, we find a 97.5% probability that this SN is a SN Ia, and a 2.5% chance of a CC SN. Our typing algorithm combines the shape and color of the light curve with the expected rates of each SN type in the host galaxy. With a redshift of 2.2216, this is the highest redshift SN Ia discovered with a spectroscopic …
Using Monte Carlo Simulation To Derive Electron Energy Distribution Functions In Argon Plasma, Ivan Sepulveda
Using Monte Carlo Simulation To Derive Electron Energy Distribution Functions In Argon Plasma, Ivan Sepulveda
Creative Activity and Research Day - CARD
A two-dimensional Monte-Carlo simulation is used to obtain distribution of electron energies inside low temperature argon plasma. The simulation written using a python script propagates an electron inside plasma by checking whether an electron collides with an argon atom and checking whether an elastic or inelastic collision occurred. Low temperature plasmas are commonly used for plasma etching in the semiconductor and medical fields.