We present our first results from 130 ks of X–ray observations obtained with the Advanced CCD Imaging Spectrometer on the Chandra X–ray Observatory . The field of the two combined exposures is 0.096 square degrees and the detection limit is to a S / N ratio of 2 ( corresponding to \sim 7 net counts ) . We reach a flux of 2 \times 10 ^ { -16 } erg s ^ { -1 } cm ^ { -2 } in the 0.5–2 keV soft band and 2 \times 10 ^ { -15 } erg s ^ { -1 } cm ^ { -2 } in the 2–10 keV hard band . Our combined sample has 144 soft sources and 91 hard sources respectively for a total of 159 sources . Fifteen sources are detected only in the hard band , and 68 only in the soft band . For the optical identification we carried out a survey in VRI with the FORS–1 imaging-spectrometer on the ANTU telescope ( UT–1 at VLT ) complete to R \leq 26 . This dataset was complemented with data from the ESO Imaging Survey ( EIS ) in the UBJK bands and the ESO Wide Field Imager Survey ( WFI ) in the B band . The positional accuracy of the X–ray detections is of order of 1 ” in the central 6 ’ . Optical identifications are found for \simeq 90 % of the sources . Optical spectra have been obtained for 12 objects . We obtain the cumulative spectra of the faint and bright X–ray sources in the sample and also the hardness ratios of individual sources . A power law fit in the range 2–10 keV using the galactic value of N _ { H } \simeq 8 \times 10 ^ { 19 } cm ^ { -2 } , yields a photon index of \Gamma = 1.70 \pm 0.12 and 1.35 \pm 0.20 ( errors at 90 % c.l . ) for the bright and faint sample respectively , showing a flattening of the spectrum at lower fluxes . Hardness ratio is given as a function of X–ray flux and confirms this result . The spectrum of our sources is approaching the spectrum of the XRB in the hard band , which has an effective \Gamma = 1.4 . Correlation function analysis for the angular distribution of the sources indicates that they are significantly clustered on scales as large as 100 arcsec . The scale-dependence of the correlation function is a power law with index \gamma \sim 2 , consistent with that of the galaxy distribution in the local Universe . Consequently , the discrete sources detected by deep Chandra pointed observations can be used as powerful tracers of the large-scale structure at high redshift . We discuss the LogN–LogS relationship and the discrete source contribution to the integrated X–ray sky flux . In the soft band , the sources detected in the field at fluxes below 10 ^ { -15 } erg s ^ { -1 } cm ^ { -2 } contribute ( 4.0 \pm 0.3 ) \times 10 ^ { -12 } erg cm ^ { -2 } s ^ { -1 } deg ^ { -2 } to the total XRB . The flux resolved in the hard band down to the flux limit of 2 \times 10 ^ { -15 } erg s ^ { -1 } cm ^ { -2 } , contributes ( 1.05 \pm 0.2 ) \times 10 ^ { -11 } erg cm ^ { -2 } s ^ { -1 } deg ^ { -2 } . Once the contribution from the bright counts resolved by ASCA is included , the total resolved XRB amounts to 1.3 \times 10 ^ { -11 } erg cm ^ { -2 } s ^ { -1 } deg ^ { -2 } which is a fraction of 60–80 % of the total measured background . This result confirms that the XRB is due to the integrated contribution of discrete sources , but shows that there is still a relevant fraction ( at least 20 % ) of the hard XRB to be resolved at fluxes below 10 ^ { -15 } erg s ^ { -1 } cm ^ { -2 } . We discuss the X–ray flux versus R magnitude relation for the identified sources . We find that \simeq 10 \% of the sources in our sample are not immediately identifiable at R > 26 . For these sources S _ { X } / S _ { opt } > 15 , whereas most of the ROSAT and Chandra sources have S _ { X } / S _ { opt } < 10 . We have found also a population of objects with unusually low S _ { X } / S _ { opt } that are identified as galaxies . The R–K vs R color diagram shows that the Chandra sources continue the trend seen by ROSAT . For our 12 spectroscopically studied objects with redshifts , we observe 4 QSOs , 5 Sy2 galaxies , 1 elliptical and 2 interacting galaxies . We compare the L _ { X } vs z obtained with these measurements and show that Chandra is achieving the predicted sensitivity .