> (1) From Ken Tatematsu In order to investigate how molecular clouds form in galaxies, one will propose to map extragalactic, early-phase molecular clouds in the nearby galaxy, e.g., M51, in the 492 GHz CI 3P1-3P0 line, For the single-dish sampling, one should know contribution of the CI emission in the error pattern (about 30 % of the total). In addition to the accurate knowledge of the beam pattern, we may need to know the CI distribution (with velocity infomation) outside of the area of interest, to obtain well-calibrated line-strength. (2) From Chris Wilson and Brenda Matthews. Polarization "normal" -measure polarization morphology in an isolated protostar or circumstellar disk; similar requirements apply to measuring the polarization of Sgr A* in the mm/submm - polarization percentage 0.5-5% - S/N 5-10 (to get 11-6 degrees uncertainty on position angle) - continuum mode - frequency ~300 GHz (whatever combination of dust emissivity and receiver sensitivity gives the best overall sensitivity is what would be prefered) "demanding" -same experiment as above but in a region with extended and complex emission so that Single Dish polarization data must be included with the same overall requirements "demanding" -use the dispersion in the polarization angle to measure the magnetic field strength in the plane of the sky versus radius in an extended star forming region like a massive protostar - polarization percentage: down to 0.1% (to get low polarization in the extended envelope) - S/N = 10 (for 6 degree uncertainty in polarization angle) - continuum mode as in previous examples "demanding" - measure polarization pattern at several frequency to use the spectrum of polarizations to constrain dust grain properties; could also be interesting to measure Sgr A* polarization at several frequencies - polarization percentage 0.5-5% (but maybe lower in some cases) - S/N 5-10 - continuum mode - range of frequencies i.e. 100 GHz, 300 GHz, 800 GHz with matched angular resolution "demanding" ? - use the linearly polarized emission from CO lines to probe magnetic field geometries in protostellar outflows. (other lines, i.e., HCN, are also possible). At high resolution (10s of AU in nearby regions), these data could test mechanisms for generation of outflows (i.e. X-winds vs. disks, if the theorists will make testable predictions); in more distant sources, the magnetic field geoemetries of the outflows can be determined using data coupled with the Goldreich-Kylafis effect to interpret the polarization angles. Different configurations are predicted for dipolar and quadrupolar outflows. - polarization percentage expected to decrease with J transitions - CO 3-2 typically 1-2% in single dish observations - need S/N 5-10 to nail down position angle with uncertainty of 10 degrees or better - CO 2-1 also doable, and possibly 4-3 if lower transitions are strong (3) From Geoff Blake and Ewine van Dishoeck Example 1: Consider a protostellar envelope around a young stellar object with a power-law density profile n ~ r^p. How accurate can the slope p be determined with a few % absolute calibration accuracy between different bands? The accompanying figure shows modeling results for the case of L723 with a CS abundance of 1E-9, i.e., not too optically thick (see Joergensen et al. 2002, A&A). The best fitting model to the current data has a slope p=-1.50. Models have been run with p varying from -1.30 to -1.70, and CS line fluxes and ratios have been computed averaged over different beams. The top figure shows the CS 7-6/5-4 ratio (Band 7/Band 6) for an ALMA resolution of 1"; the lower plot is for the current JCMT beams of 14" and 20", respectively. It is seen that if the uncertainty in the ratio ~5%, the power-law slope p can be determined to better than +- 0.05. Thus, one could certainly distinguish between a pure power-law and an inside-out collapse type model with such high accuracy. This analysis of course assumes that the CS abundance does not vary in the gas probed by these beams and that the (relative) collisional rate coefficients are known to this accuracy, both of which may be larger sources of error. Example 2: Accurate isotopic ratios from emission lines (rather than the absorption line case discussed by Stephane). The isotopic lines may be sufficiently far apart that they cannot be obtained in a single setting. Intensities of the relevant isotopic lines may differ by a factor of 20 or more. Accurate absolute calibration down to a few % across an entire receiver band would allow such ratios to be determined to a few % accuracy, which in turn gives accurate elemental abundance gradients across our galaxy and other galaxies. (example needs to be worked out more quantitatively) Example 3: Full spectral survey at 650 GHz in DSB mode. Deconvolution of the sidebands requires accurate relative calibration of the two sidebands. For interferometer data, this is likely not a problem, but the single-dish data used to fill in the zero-spacings may be the limiting factor. This can be quantified with Peter Schilke's software. (4) From Munetake Momose bandpass calibration: It is expected that accurate passband calibration will be required when one observes an astronomical object with a small (line)/(continuum) ratio. We believe the observations of line features associated with nearby AGNs (e.g., CenA or 3C84) would offer good examples for such cases. The continuum emission of an AGN is quite strong while the line emission components from its surrounding dense gas have a wide velocity width (~ 500 km/s for CenA, see Eckart et al. 1990a & b) but lower brightness compared to the AGN continuum. In the case of CO(J=1-0) observations toward the nucleus of the radio loud AGN 3C84, line to continuum ratio is about 1 : 50 to 100, and the accuracy of CO line images seems to be limited by the passband calibration (Inoue et al. 1996). With ALMA, much weaker lines other than 12CO transitions must be observed, where line to continuum ratios could be 1: a few 100 to 1000, or larger. In addition to the emissions, narrow (< 0.5km/s) absorption features that will allow us to make ``pencil beam'' measurements of the physical condition of outer molecular clouds are also detected in some objects (e.g., CenA, see Eckart et al. 1990a & b). To correctly separate the contribution of each featrue, precise determination of passband characterisitics will be essential. (references) Eckart et al. (1990a) ApJ, vol. 363 451-463 Eckart et al. (1990b) ApJ, vol. 365 522-531 Inoue et al. (1996) AJ, vol.111, 1852-1859 (5) From Mark Gurwell Science Example --------------- Temperature, Water Vapor, and Winds from the atmosphere of Mars Observations in the 230 GHz band that cover the 225.9 GHz HDO line and the 230.5 GHz CO(2-1) line, can be used to simultaneously measure the temperature structure (from CO) and water vapor distribution (from HDO). The CO line is strong in absorption, so relatively easy to see. The HDO line, on the other hand, is an extremely weak feature in emission on the limbs, and even weaker in absorption on the disk (maybe 1% in emission, 0.2% in absorption) over 200 MHz or so. This must be measured against the strong continuum of Mars, making it a challenging project. An additional component to this science example is that the surface continuum of Mars will show radial polarization (due to the brewster angle effect) which could be used to measure the surface dielectric properties. The CO line emission, of course is unpolarized and can be used as a calibration check. P.S. In my haste to send out the Science example, I failed to include (though it was in the title) that winds on Mars would be derived from doppler shifts in the 12CO(2-1) spectra. The line of sight velocities relative to the Mars center of reference will be maximum of about 200 - 300 m/s, most of which is just Mars rotation, which will have to be removed after processing. The winds themselves will be in the +/- 0-100 m/s range, which is quite small relative to the voigt lineshape of the core. The way to measure the small doppler shifts is to fit the lineshape (which is symmetric) over many channels. This does require a good knowledge of the bandpass, primarily at the channel level (e.g. the large scale RX bandpass doesn't have a strong effect on determining the bandpass). However, standing waves, depending on their frequency and strength, might be an important source of error.