Hostname: page-component-77c89778f8-n9wrp Total loading time: 0 Render date: 2024-07-19T00:24:13.487Z Has data issue: false hasContentIssue false
  • English
  • Français

Exploration of the local solar neighbourhood I: Fixed number of probes

Published online by Cambridge University Press:  10 April 2013

Daniel Cartin
Daniel Cartin*
Affiliation:
Naval Academy Preparatory School, 440 Meyerkord Ave Newport, RI (USA) 02841-1519
Get access Rights & Permissions [Opens in a new window]

Abstract

Previous work in studying interstellar exploration by one or several probes has focused primarily either on engineering models for a spacecraft targeting a single star system, or large-scale simulations to ascertain the time required for a civilization to completely explore the Milky Way Galaxy. In this paper, a simulated annealing algorithm is used to numerically model the exploration of the local interstellar neighbourhood (i.e. of the order of ten parsecs of the Solar System) by a fixed number of probes launched from the Solar System; these simulations use the observed masses, positions and spectral classes of targeted stars. Each probe visits a pre-determined list of target systems, maintains a constant cruise speed, and only changes the direction from gravitational deflection at each target. From these simulations, it is examined how varying design choices – differing the maximum cruise speed, number of probes launched, number of target stars to be explored, and probability of avoiding catastrophic system failure per parsec – change the completion time of the exploration programme and the expected number of stars successfully visited. In addition, it is shown that improving this success probability per parsec has diminishing returns beyond a certain point. Future improvements to the model and possible implications are discussed.

Keywords

interstellar explorationnumerical simulationssimulated annealingSETI
Type
Research Article
Information
International Journal of Astrobiology , Volume 12 , Issue 4 , October 2013 , pp. 271 - 281
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Beals, K.A., Beaulieu, M., Dembia, F.J., Kerstiens, J., Kramer, D.L., West, J.R. & Zito, J.A. (1988). U S Naval Academy. NASA-CR-184718.Google Scholar
Bjørk, R. (2007). Int. J. Astrobiol. 6, 89–93; arXiv: astro-ph/0701238.Google Scholar
Bond, A., et al. (1978). J. Br. Interplanet. Soc. 31 (Supplement), S37–S42.Google Scholar
Bruntt, H., Bedding, T.R., Quirion, P.-O., Lo Curto, G., Carrier, F., Smalley, B., Dall, T.H., Arentoft, T., Bazot, M. & Butler, R.P. (2010). Mon. Not. R. Astron. Soc. 405, 1907–1923; arXiv:1002.4268.Google Scholar
Burleigh, M.R. et al. (2008). Mon. Not. R. Astron. Soc.: Lett. 386, L5–L9; arXiv:0801.2917.CrossRefGoogle Scholar
Cartin, D. (2012). Developing routes for interstellar exploration probes, Presented at the Anacapa Society Meeting, May 2012.Google Scholar
Cerný, V. (1985). J. Optim. Theory Appl. 45, 41–51.Google Scholar
Cotta, C. & Morales, Á. (2009). J. Br. Interplanet. Soc. 62, 82–88; arXiv:0907.0345.Google Scholar
Dasgupta, S., Papadimitriou, C.H. & Vazirani, U.V. (2008). Algorithms, McGraw-Hill Higher Education, Boston.Google Scholar
Dawson, P.C. & De Robertis, M.M. (2004). Astron. J. 127, 2909–2914.Google Scholar
Demory, B.-O., Segransan, D., Forveille, T., Queloz, D., Beuzit, J.-L., Delfosse, X., Di Folco, E., Kervella, P., Le Bouquin, J.-B., & Perrier, C. (2009). Astron. Astrophys. 505, 205–215; arXiv:0906.0602v2.Google Scholar
Forgan, D.H., Papadogiannakis, S. & Kitching, T. (2012). J. Br. Interplanet. Socy., to be published; arXiv:1212.2371.Google Scholar
Forward, R.L. (1985). J. Spacecr. Rockets, 22, 345–350.Google Scholar
Gatewood, G. & Russell, J. (1974). Astron. J. 79, 815–818.Google Scholar
Holberg, J.B., Barstow, M.A., Bruhweiler, F.C., Cruise, A.M. & Penny, A.J. (1998). Astrophys. J. 497, 935–942.Google Scholar
King, R.R., McCaughrean, M.J., Homeier, D., Allard, F., Scholz, R.-D., & Lodieu, N. (2009). Astron. Astrophys. 510, A99; arXiv:0911.3143.Google Scholar
Kirkpatrick, S., Gelatt, C.D. Jr. & Vecchi, M.P. (1983). Science, 220, 671–680.Google Scholar
Landis, G.A. (1999). Advanced Solar- and laser-pushed Lightsail Concepts, Final Report for NASA Institute for Advanced Concepts, May 31.Google Scholar
Lang, K.R. (1999). Astrophysical Formulae, Volume II: Space, Time, Matter and Cosmology, 3rd edn, Springer-Verlag, Berlin.CrossRefGoogle Scholar
Liebert, J., Young, P.A., Arnett, D., Holberg, J.B. & Williams, K.A. (2005). Astrophys. J. Lett. 630, L69–L72; arXiv:astro-ph/0507523.CrossRefGoogle Scholar
Long, K. F., Obousy, R.K., Tziolas, A.C., Mann, A., Osborne, R., Presby, A. & Fogg, M. (2009). J. Br. Interplanet. Soc. 62, 403–414.Google Scholar
Mamajek, E.E., (2012). Astrophys. J. Lett. 754, L20; arXiv: 1206.6353v2.CrossRefGoogle Scholar
Marion, J.B. & Thornton, S.T. (1988). Classical Dynamics of Particles & Systems, 3rd edn, Academic Press, San Diego.Google Scholar
Matthews, R.A.J. (1994). Quarter. J. R. Astron. Soc. 35, 1–9.Google Scholar
Millis, M.G. (2011). Energy, incessant obsolescence, and the first interstellar missions, in 61st International Astronautical Congress, International Astronautical Federation, Prague, Czech Republic; arXiv: 1101.1066.Google Scholar
Moir, R.W. & Barr, W.L. (2005). J. Br. Interplanet. Soc. 58, 332–341.Google Scholar
Newman, W.I. & Sagan, C. (1985). Nonlinear Diffusion and Population Dynamics. In Interstellar Migration and the Human Experience, eds Finney, B.R. & Jones, E.M., University of California Press, Berkeley, pp. 302–312.Google Scholar
Provencal, J.L., Shipman, H.L., Koester, D., Wesemael, D. & Bergeron, P. (2002), Astrophys. J. 568, 324–334.Google Scholar
Research Consortium on Nearby Stars. (2012) “List of the Nearest 100 Stellar Systems,” available at www.recons.org (accessed 6 January 2013).Google Scholar