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From Science to Computational Sciences

Studies in the History of Computing and its Influence on Today‘s Sciences

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.

240 pages | 6 x 9 | © 2011

Mathematics and Statistics

Physical Sciences: Physics and Astronomy


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Table of Contents

I. INTRODUCTION

Gabriele Gramelsberger
A Brief Introduction to the Volume
From Science to Computational Sciences - A Science History and Philosophy Overview


II. ORIGINS OF SIMULATION AND RATIONAL PROGNOSIS

Sybille Krämer
Roots and Media of Computational Power. Some Remarks on the Genesis and Genius of Quantification in Early European Modernity

David Alan Grier
The Early Progress of Scientific Simulation

Thomas Brandstetter
Mimetic Experiments before the Invention of the Computer

Thomas Lange
Computer Simulation in the V2 Rocket Development

Peter Galison
Computer Simulations and the Trading Zone

Gabriele Gramelsberger
From Computation with Experiments to Experiments with Computation


III. REVERSE ENGINEERING OF NATURE BY NUMBERS

David Alan Grier
Towards A Definition of Simulation

Sergio Sismondo
Simulation as a New Style of Research: Iteration, Integration, and Instability

Johannes Lenhard
Artificial, False, and Performing Well

Erika Mansnerus
Explanatory and Predictive Functions of Simulation Modelling. Case: Haemophilus Influenzae type b Dynamic Transmission Models

Renate Mayntz
Research Technology, the Computer and Scientific Advance

Johann Feichter
The Earth System

Peter Bexte
Uncertainty in Grammar / The Grammar of Uncertainty. Some Remarks on the Future Perfect


IV. APPENDIX

Authors

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