اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدSpectroscopic identification of a redshift 1.55 supernova host galaxy from the Subaru Deep Field Supernova Survey
139
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Context: The Subaru Deep Field (SDF) Supernova Survey discovered 10 Type Ia supernovae (SNe Ia) in the redshift range 1.5<z<2.0, as determined solely from photometric redshifts of the host galaxies. However, photometric redshifts might be biased, and the SN sample could be contaminated by active galactic nuclei (AGNs). Aims: We aim to obtain the first robust redshift measurement and classification of a z > 1.5 SDF SN Ia host galaxy candidate Methods: We use the X-shooter (U-to-K-band) spectrograph on the Very Large Telescope to allow the detection of different emission lines in a wide spectral range. Results: We measure a spectroscopic redshift of 1.54563 +/- 0.00027 of hSDF0705.25, consistent with its photometric redshift of 1.552 +/- 0.018. From the strong emission-line spectrum we rule out AGN activity, thereby confirming the optical transient as a SN. The host galaxy follows the fundamental metallicity relation defined in Mannucci et al. (2010, 2011) showing that the properties of this high-redshift SN Ia host galaxy is similar to other field galaxies. Conclusions: Spectroscopic confirmation of additional SDF SN hosts would be required to confirm the cosmic SN rate evolution measured in the SDF.
قيم البحث
اقرأ أيضاً
Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in t
he absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate hostless SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey.
Using data from the Sloan Digital Sky Supernova Survey-II, we measure the rate of Type Ia Supernovae (SNe Ia) as a function of galaxy properties at intermediate redshift. A sample of 342 SNe Ia with 0.05<z<0.25 is constructed. Using broad-band photom
etry we use the PEGASE spectral energy distributions (SEDs) to estimate host galaxy stellar masses and recent star-formation rates. We find that the rate of SNe Ia per unit stellar mass is significantly higher (by a factor of ~30) in highly star-forming galaxies compared to passive galaxies. When parameterizing the SN Ia rate (SNR_Ia) based on host galaxy properties, we find that the rate of SNe Ia in passive galaxies is not linearly proportional to the stellar mass, instead a SNR_Ia proportional to M^0.68 is favored. However, such a parameterization does not describe the observed SN Ia rate in star-forming galaxies. The SN Ia rate in star-forming galaxies is well fit by SNR_Ia = 1.05pm0.16x10^{-10} M ^{0.68pm0.01} + 1.01pm0.09x10^{-3} SFR^{1.00pm0.05} (statistical errors only), where M is the host galaxy mass and SFR is the star-formation rate. These results are insensitive to the selection criteria used, redshift limit considered and the inclusion of non-spectroscopically confirmed SNe Ia. We also show there is a dependence between the distribution of the MLCS light-curve decline rate parameter, Delta, and host galaxy type. Passive galaxies host less luminous SNe Ia than seen in moderately and highly star-forming galaxies, although a population of luminous SNe is observed in passive galaxies, contradicting previous assertions that these SNe Ia are only observed in younger stellar systems. The MLCS extinction parameter, A_V, is similar in passive and moderately star-forming galaxies, but we find indications that it is smaller, on average, in highly star-forming galaxies. We confirm these results using the SALT2 light-curve fitter.
Supernova rates are directly coupled to high mass stellar birth and evolution. As such, they are one of the few direct measures of the history of cosmic stellar evolution. In this paper we describe an probabilistic technique for identifying supernova
e within spectroscopic samples of galaxies. We present a study of 52 type Ia supernovae ranging in age from -14 days to +40 days extracted from a parent sample of simeq 50,000 spectra from the SDSS DR5. We find a Supernova Rate (SNR) of 0.472^{+0.048}_{-0.039}(Systematic)^{+0.081}_{-0.071}(Statistical)SNu at a redshift of <z> = 0.1. This value is higher than other values at low redshift at the 1{sigma}, but is consistent at the 3{sigma} level. The 52 supernova candidates used in this study comprise the third largest sample of supernovae used in a type Ia rate determination to date. In this paper we demonstrate the potential for the described approach for detecting supernovae in future spectroscopic surveys.
The IfA Deep survey uncovered ~130 thermonuclear supernovae (TNSNe, i.e. Type Ia) candidates at redshifts from z=0.1 out to beyond z=1. The TNSN explosion rates derived from these data have been controversial, conflicting with evidence emerging from
other surveys. This work revisits the IfA Deep survey to re-evaluate the photometric evidence. Applying the SOFT program to the light curves of all SN candidates, we derive new classification grades and redshift estimates. We find a volumetric rate for z~0.5 that is substantially smaller than the originally published values, bringing the revised IfA Deep rate into good agreement with other surveys. With our improved photometric analysis techniques, we are able to confidently extend the rate measurements to higher redshifts, and we find a steadily increasing TNSN rate, with no indication of a peak out to z=1.05.
We report a measurement of the Type Ia supernova (SN Ia) rate in galaxy clusters at 0.9 < z < 1.45 from the Hubble Space Telescope (HST) Cluster Supernova Survey. This is the first cluster SN Ia rate measurement with detected z > 0.9 SNe. Finding 8 +
/- 1 cluster SNe Ia, we determine a SN Ia rate of 0.50 +0.23-0.19 (stat) +0.10-0.09 (sys) SNuB (SNuB = 10^-12 SNe L_{sun,B}^-1 yr^-1). In units of stellar mass, this translates to 0.36 +0.16-0.13 (stat) +0.07-0.06 (sys) SNuM (SNuM = 10^-12 SNe M_sun^-1 yr^-1). This represents a factor of approximately 5 +/- 2 increase over measurements of the cluster rate at z < 0.2. We parameterize the late-time SN Ia delay time distribution with a power law (proportional to t^s). Under the assumption of a cluster formation redshift of z_f = 3, our rate measurement in combination with lower-redshift cluster SN Ia rates constrains s = -1.41 +0.47/-0.40, consistent with measurements of the delay time distribution in the field. This measurement is generally consistent with expectations for the double degenerate scenario and inconsistent with some models for the single degenerate scenario predicting a steeper delay time distribution at large delay times. We check for environmental dependence and the influence of younger stellar populations by calculating the rate specifically in cluster red-sequence galaxies and in morphologically early-type galaxies, finding results similar to the full cluster rate. Finally, the upper limit of one host-less cluster SN Ia detected in the survey implies that the fraction of stars in the intra-cluster medium is less than 0.47 (95% confidence), consistent with measurements at lower redshifts.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
