In 1946 John von Neumann stated that science is stagnant along the entire front of complex problems, proposing the use of largescale computing machines to overcome this stagnation. In other words, Neumann advocated replacing analytical methods with numerical ones. The invention of the computer in the 1940s allowed scientists to realise numerical simulations of increasingly complex problems like weather forecasting, and climate and molecular modelling. Today, computers are widely used as computational laboratories, shifting science toward the computational sciences. By replacing analytical methods with numerical ones, they have expanded theory and experimentation by simulation.
During the last decades hundreds of computational departments have been established all over the world and countless computer-based simulations have been conducted. This volume explores the epoch-making influence of automatic computing machines on science, in particular as simulation tools.
Author(s): Gabriele Gramelsberger (ed.)
Publisher: Diaphanes
Year: 2011
Language: English
Pages: 240
City: Zürich
Tags: History of Computing; History of Scientific Computing; Computational Sciences
Cover
Table of Contents
I. INTRODUCTION
A Brief Introduction to the Volume / Gabriele Gramelsberger
From Science to Computational Sciences: A Science History and Philosophy Overview / Gabriele Gramelsberger
II. ORIGINS OF SIMULATION AND RATIONAL PROGNOSIS
Roots and Media of Computational Power: Some Remarks on the Genesis and Genius of Quantification in Early European Modernity / Sybille Krämer
The Early Progress of Scientific Simulation / David Alan Grier
Mimetic Experiments before the Invention of the Computer / Thomas Brandstetter
Computer Simulation in the V2 Rocket Development / Thomas Lange
Computer Simulations and the Trading Zone / Peter Galison
From Computation with Experiments to Experiments on Computation / Gabriele Gramelsberger
III. REVERSE ENGINEERING OF NATURE BY NUMBERS
Towards A Definition of Simulation / David Alan Grier
Simulation as a New Style of Research: Iteration, Integration, and Instability / Sergio Sismondo
Artificial, False, and Performing Well / Johannes Lenhard
Explanatory and Predictive Functions of Simulation Modelling Case: Haemophilus Influenzae Type b Dynamic Transmission Models / Erika Mansnerus
Research Technology, the Computer, and Scientific Advance / Renate Mayntz
Shaping Reality with Algorithms: The Earth System / Johann Feichter
Uncertainty in Grammar / The Grammar of Uncertainty: Some Remarks on the Future Perfect / Peter Bexte
IV. APPENDIX
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