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تسجيل مستخدم جديدThe Wendelstein Calar Alto Pixellensing Project (WeCAPP): the M31 Nova catalogue
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We present light curves from the novae detected in the long-term, M31 monitoring WeCAPP project. The goal of WeCAPP is to constrain the compact dark matter fraction of the M31 halo with microlensing observations. As a by product we have detected 91 novae benefiting from the high cadence and highly sensitive difference imaging technique required for pixellensing. We thus can now present the largest CCD and optical filters based nova light curve sample up-to-date towards M31. We also obtained thorough coverage of the light curve before and after the eruption thanks to the long-term monitoring. We apply the nova taxonomy proposed by Strope et al. (2010) to our nova candidates and found 29 S-class novae, 10 C-class novae, 2 O-class novae and 1 J-class nova. We have investigated the universal decline law advocated by Hachichu and Kato (2006) on the S-class novae. In addition, we correlated our catalogue with the literature and found 4 potential recurrent novae. Part of our catalogue has been used to search for optical counter-parts of the super soft X-ray sources detected in M31 (Pietsch et al. 2005). Optical surveys like WeCAPP, and coordinated with multi-wavelength observation, will continue to shed light on the underlying physical mechanism of novae in the future.
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We report the detection of the first 2 microlensing candidates from the Wendelstein Calar Alto Pixellensing Project (WeCAPP). Both are detected with a high signal-to-noise-ratio and were filtered out from 4.5 mill. pixel light curves using a variety
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We present WeCAPP, a long term monitoring project searching for microlensing events towards M 31. Since 1997 the bulge of M 31 was monitored in two different wavebands with the Wendelstein 0.8 m telescope. In 1999 we extended our observations to the
Calar Alto 1.23 m telescope. Observing simultaneously at these two sites we obtained a time coverage of 53 % during the observability of M 31. To check thousands of frames for variability of unresolved sources, we used the optimal image subtraction method (OIS) by Alard & Lupton (1998) This enabled us to minimize the residuals in the difference image analysis (DIA) and to detect variable sources with amplitudes at the photon noise level. Thus we can detect microlensing events with corresponding amplifications A > 10 of red clump giants with M_I = 0.
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