Re: Next version of abstract -- probably needs more work.

From: Marc Postman (postman@stsci.edu)
Date: Thu Jan 26 2006 - 13:34:42 PST

  • Next message: Henk Hoekstra: "Re: Next version of abstract -- probably needs more work."

    0. "and we propose here to (continue to??) capitalize on ..."

    1. Do you want to note the higher weighting of 1 dust-free elliptical = 9 field SNe somewhere?

    2. If you are refering to the overdensity of z>1 ellipticals, then I would say the factor is AT LEAST 5x and can be as high as 10 - 15x.

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    ---- Original message ----
    >Date: Thu, 26 Jan 2006 13:10:09 -0800
    >From: Saul Perlmutter <saul@lbl.gov>
    >Subject: Next version of abstract -- probably needs more work.
    >To: Kyle Dawson <KDawson@lbl.gov>
    >Cc: hstclustersn@lbl.gov
    >
    >Our Cycle 14 program has now proven a new extremely efficient approach
    >to obtain z>1 dust-free Type Ia supernovae, and we here propose to
    >capitalize on this new technique . We will collect a total sample of
    >~20 z>1 SNe Ia in cluster ellipticals, yielding dark energy measurements
    >that do not suffer from the major systematic uncertainty at these
    >redshifts, that of the extinction correction with a prior. By targeting
    >massive galaxy clusters at z>1, we obtain a five-times [CHECK] higher
    >efficiency in detection of Type Ia supernovae in elliptical galaxies,
    >and provide a well-understood host galaxy environment. These same deep
    >cluster images then also yield fundamental calibrations required for
    >future weak lensing and Sunyaev-Zel'dovich measurements of dark energy,
    >as well as an entire program of cluster studies. The data will make
    >possible a factor of two improvement on supernova constraints on dark
    >energy time variation, and much larger improvement in systematic
    >uncertainty, taking advantage of the uniquely well-controlled host
    >environment that clusters provide. They will provide both a cluster
    >dataset and a SN Ia data set that will be a longstanding scientific
    >resource.
    >



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