1. LSST: From Science Drivers to Reference Design and Anticipated Data Products
- Author
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Ivezić, Ž, Ivezić, Ž, Kahn, SM, Tyson, JA, Abel, B, Acosta, E, Allsman, R, Alonso, D, Alsayyad, Y, Anderson, SF, Andrew, J, Angel, JRP, Angeli, GZ, Ansari, R, Antilogus, P, Araujo, C, Armstrong, R, Arndt, KT, Astier, P, Aubourg, E, Auza, N, Axelrod, TS, Bard, DJ, Barr, JD, Barrau, A, Bartlett, JG, Bauer, AE, Bauman, BJ, Baumont, S, Bechtol, E, Bechtol, K, Becker, AC, Becla, J, Beldica, C, Bellavia, S, Bianco, FB, Biswas, R, Blanc, G, Blazek, J, Blandford, RD, Bloom, JS, Bogart, J, Bond, TW, Booth, MT, Borgland, AW, Borne, K, Bosch, JF, Boutigny, D, Brackett, CA, Bradshaw, A, Brandt, WN, Brown, ME, Bullock, JS, Burchat, P, Burke, DL, Cagnoli, G, Calabrese, D, Callahan, S, Callen, AL, Carlin, JL, Carlson, EL, Chandrasekharan, S, Charles-Emerson, G, Chesley, S, Cheu, EC, Chiang, HF, Chiang, J, Chirino, C, Chow, D, Ciardi, DR, Claver, CF, Cohen-Tanugi, J, Cockrum, JJ, Coles, R, Connolly, AJ, Cook, KH, Cooray, A, Covey, KR, Cribbs, C, Cui, W, Cutri, R, Daly, PN, Daniel, SF, Daruich, F, Daubard, G, Daues, G, Dawson, W, Delgado, F, Dellapenna, A, Peyster, RD, Val-Borro, MD, Digel, SW, Doherty, P, Dubois, R, Dubois-Felsmann, GP, Durech, J, Economou, F, Eifler, T, Eracleous, M, Emmons, BL, Neto, AF, Ivezić, Ž, Ivezić, Ž, Kahn, SM, Tyson, JA, Abel, B, Acosta, E, Allsman, R, Alonso, D, Alsayyad, Y, Anderson, SF, Andrew, J, Angel, JRP, Angeli, GZ, Ansari, R, Antilogus, P, Araujo, C, Armstrong, R, Arndt, KT, Astier, P, Aubourg, E, Auza, N, Axelrod, TS, Bard, DJ, Barr, JD, Barrau, A, Bartlett, JG, Bauer, AE, Bauman, BJ, Baumont, S, Bechtol, E, Bechtol, K, Becker, AC, Becla, J, Beldica, C, Bellavia, S, Bianco, FB, Biswas, R, Blanc, G, Blazek, J, Blandford, RD, Bloom, JS, Bogart, J, Bond, TW, Booth, MT, Borgland, AW, Borne, K, Bosch, JF, Boutigny, D, Brackett, CA, Bradshaw, A, Brandt, WN, Brown, ME, Bullock, JS, Burchat, P, Burke, DL, Cagnoli, G, Calabrese, D, Callahan, S, Callen, AL, Carlin, JL, Carlson, EL, Chandrasekharan, S, Charles-Emerson, G, Chesley, S, Cheu, EC, Chiang, HF, Chiang, J, Chirino, C, Chow, D, Ciardi, DR, Claver, CF, Cohen-Tanugi, J, Cockrum, JJ, Coles, R, Connolly, AJ, Cook, KH, Cooray, A, Covey, KR, Cribbs, C, Cui, W, Cutri, R, Daly, PN, Daniel, SF, Daruich, F, Daubard, G, Daues, G, Dawson, W, Delgado, F, Dellapenna, A, Peyster, RD, Val-Borro, MD, Digel, SW, Doherty, P, Dubois, R, Dubois-Felsmann, GP, Durech, J, Economou, F, Eifler, T, Eracleous, M, Emmons, BL, and Neto, AF
- Abstract
We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg 2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg 2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r ∼27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.
- Published
- 2019