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The first phase of the Carnegie Supernova Project (CSP-I) was a dedicated supernova follow-up program based at the Las Campanas Observatory that collected science data of young, low-redshift supernovae between 2004 and 2009. Presented in this paper is the CSP-I photometric data release of low-redshift stripped-envelope core-collapse supernovae. The data consist of optical (uBgVri) photometry of 34 objects, with a subset of 26 having near-infrared (YJH) photometry. Twenty objects have optical pre-maximum coverage with a subset of 12 beginning at least five days prior to the epoch of B-band maximum brightness. In the near-infrared, 17 objects have pre-maximum observations with a subset of 14 beginning at least five days prior to the epoch of J-band maximum brightness. Analysis of this photometric data release is presented in companion papers focusing on techniques to estimate host-galaxy extinction (Stritzinger et al., submitted) and the light-curve and progenitor star properties of the sample (Taddia et al., submitted). The analysis of an accompanying visual-wavelength spectroscopy sample of ~150 spectra will be the subject of a future paper.
Stripped-envelope (SE) supernovae (SNe) include H-poor (Type IIb), H-free (Type Ib) and He-free (Type Ic) events thought to be associated with the deaths of massive stars. The exact nature of their progenitors is a matter of debate. Here we present t
The Carnegie Supernova Project (CSP) is a five-year survey being carried out at the Las Campanas Observatory to obtain high-quality light curves of ~100 low-redshift Type Ia supernovae in a well-defined photometric system. Here we present the first r
We use the spectroscopy and homogeneous photometry of 97 Type Ia supernovae obtained by the emph{Carnegie Supernova Project} as well as a subset of 36 Type Ia supernovae presented by Zheng et al. (2018) to examine maximum-light correlations in a four
We present $81$ near-infrared (NIR) spectra of $30$ Type II supernovae (SNe II) from the Carnegie Supernova Project-II (CSP-II), the largest such dataset published to date. We identify a number of NIR features and characterize their evolution over ti
Supernovae are essential to understanding the chemical evolution of the Universe. Type Ia supernovae also provide the most powerful observational tool currently available for studying the expansion history of the Universe and the nature of dark energ