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We analyze the data of the gravitational microlensing survey carried out byby the MOA group during 2000 towards the Galactic Bulge (GB). Our observationsare designed to detect efficiently high magnification events with faint sourcestars and short timescale events, by increasing the the sampling rate up to 6times per night and using Difference Image Analysis (DIA). We detect 28microlensing candidates in 12 GB fields corresponding to 16 deg^2. We use MonteCarlo simulations to estimate our microlensing event detection efficiency,where we construct the I-band extinction map of our GB fields in order to finddereddened magnitudes. We find a systematic bias and large uncertainty in themeasured value of the timescale $t_{\rm Eout}$ in our simulations. They areassociated with blending and unresolved sources, and are allowed for in ourmeasurements. We compute an optical depth tau = 2.59_{-0.64}^{+0.84} \times10^{-6} towards the GB for events with timescales 0.3<t_E<200 days. We considerdisk-disk lensing, and obtain an optical depth tau_{bulge} =3.36_{-0.81}^{+1.11} \times 10^{-6}[0.77/(1-f_{disk})] for the bulge componentassuming a 23% stellar contribution from disk stars. These observed opticaldepths are consistent with previous measurements by the MACHO and OGLE groups,and still higher than those predicted by existing Galactic models. We presentthe timescale distribution of the observed events, and find there are nosignificant short events of a few days, in spite of our high detectionefficiency for short timescale events down to t_E = 0.3 days. We find that halfof all our detected events have high magnification (>10). These events areuseful for studies of extra-solar planets.Comment: 65 pages and 30 figures, accepted for publication in ApJ. A  systematic bias and uncertainty in the optical depth measurement has been  quantified by simulation

astrophysical journal/the astrophysical journal

Microlensing Optical Depth toward the Galactic Bulge from Microlensing Observations in Astrophysics Group Observations during 2000 with Difference Image Analysis