scholarly journals A search for supernova light echoes in NGC 6946 with SITELLE

2020 ◽  
Vol 497 (3) ◽  
pp. 3297-3305
Author(s):  
M C Radica ◽  
D L Welch ◽  
L Rousseau-Nepton

ABSTRACT We present the analysis of 4 h of spectroscopic observations of NGC 6946 with the SITELLE Imaging Fourier Transform Spectrometer on the Canada–France–Hawaii Telescope, acquired to search for supernova light echoes from its 10 modern supernovae. We develop a novel spectroscopic search method: identifying negatively sloped continua in the narrow-band SN3 filter as candidate highly broadened P-Cygni profiles in the H α line, which would be characteristic of the spectra of supernova ejecta. We test our methodology by looking for light echoes from any of the 10 supernovae observed in NGC 6946 in the past 100 yr. We find no evidence of light echoes above the survey surface brightness limit of 1 × 10−15 erg s−1 cm−2arcsec−2.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lila Lovergne ◽  
Dhruba Ghosh ◽  
Renaud Schuck ◽  
Aris A. Polyzos ◽  
Andrew D. Chen ◽  
...  

AbstractAlthough some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.


1994 ◽  
Vol 15 (9) ◽  
pp. 1481-1496 ◽  
Author(s):  
D. Boucher ◽  
R. Bocquet ◽  
D. Petitprez ◽  
L. Aime

2010 ◽  
Author(s):  
Huandong Wei ◽  
Jianwen Hua ◽  
Zuoxiao Dai ◽  
Ren Chen ◽  
Xiaojie Sun

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