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 of selection criteria. Here we only consider well-sampled events with timescales of 1 d < t fwhm < 20 d, high amplitude, and low χ 2 of the microlensing fit. The two-color photometry (R, I) shows that the events are achromatic and that giant stars with colors of (R − I) ≈ 1.1 mag in the bulge of M31 have been lensed. The magnification factors are 64 and 10 which are obtained for typical giant luminosities of M I = −2.5 mag. Both lensing events lasted for only a few days (t GL1 fwhm = 1.7 d and t GL2 fwhm = 5.4 d). The event GL1 is likely identical with PA-00-S3 reported by the POINT-AGAPE project. Our calculations favor in both cases the possibility that MACHOs in the halo of M31 caused the lensing events. The most probable masses, 0.08 M ⊙ for GL1 and 0.02 M ⊙ for GL2, are in the range of the brown dwarf limit of hydrogen burning. Solar mass objects are a factor of two less likely.

Abstract. 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 MI = 0.

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We present light curves from the novae detected in the long-term, M 31-monitoring WeCAPP project. The goal of WeCAPP is to constrain the compact dark matter fraction of the M 31 halo with microlensing observations. As a by product we detected 91 novae benefiting from the high cadence and highly sensitive difference imaging technique required for pixel-lensing. We thus can now present the largest sample of optical/CCD nova lightcurves towards M 31 to date. We also obtained thorough coverage of the light curve before and after the eruption thanks to the long-term monitoring. We apply a nova taxonomy to our nova candidates and found 29 S-class novae, 10 C-class novae, 2 O-class novae, and 1 J-class nova. We investigated a universal decline law 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 counterparts of the super soft X-ray sources detected in M 31. Optical surveys like WeCAPP, when coordinated with multi-wavelength observation, will continue to shed light on the underlying physical mechanism of novae in the future.

The Wendelstein Observatory of Ludwig Maximilians University of Munich has recently been upgraded with a modern 2m robotic telescope. One Nasmyth port of the telescope has been equipped with a wide-field corrector which preserves the excellent image quality (< 0.8" median seeing) of the site (Hopp et al. 2008) over a field of view of 0.7 degrees diameter. The available field is imaged by an optical imager (WWFI, the Wendelstein Wide Field Imager) built around a customized 2 × 2 mosaic of 4k × 4k 15 µm e2v CCDs from Spectral Instruments. This paper provides an overview of the design and the WWFI's performance. We summarize the system mechanics (including a structural analysis), the electronics (and its electromagnetic interference (EMI) protection) and the control software. We discuss in detail detector system parameters, i.e. gain and readout noise, quantum efficiency as well as charge transfer efficiency (CTE) and persistent charges. First on sky tests yield overall good predictability of system throughput based on lab measurements.