Statistics – Computation
Scientific paper
Dec 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aspc..413..135m&link_type=abstract
2nd Crisis in Cosmology Conference, CCC-2. ASP Conference Series, Vol. 413, Proceedings of the conference held 7-11 September 20
Statistics
Computation
Scientific paper
The rapid convergence of advancing sensor technology, computational power, and knowledge discovery techniques over the past decade has brought unprecedented volumes of astronomical data together with unprecedented capabilities of data assimilation and analysis. A key result is that a new, data-driven "observational-inductive'' framework for scientific inquiry is taking shape and proving viable. The anticipated rise in data flow and processing power will have profound effects, e.g., confirmations and disconfirmations of existing theoretical claims both for and against the big bang model. But beyond enabling new discoveries can new data-driven frameworks of scientific inquiry reshape the epistemic ideals of science? The history of physics offers a comparison. The Bohr-Einstein debate over the "completeness'' of quantum mechanics centered on a question of ideals: what counts as science? We briefly examine lessons from that episode and pose questions about their applicability to cosmology. If the history of 20th century physics is any indication, the abandonment of absolutes (e.g., space, time, simultaneity, continuity, determinacy) can produce fundamental changes in understanding. The classical ideal of science, operative in both physics and cosmology, descends from the European Enlightenment. This ideal has for over 200 years guided science to seek the ultimate order of nature, to pursue the absolute theory, the "theory of everything.'' But now that we have new models of scientific inquiry powered by new technologies and driven more by data than by theory, it is time, finally, to relinquish dreams of a "final'' theory.
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