Sunday, December 15, 2013

Scientific Computing


There are a million uses for a computer in the field of science. A million. So as you may be able to guess there are about a million ways in which I could tell you scientific computing happens. But instead of boring you with endless lists of ways things happen in the lab I will just tell you a few ways that computers are useful to specific types of scientists.

The first is computational science. It is the science of constructing mathematical models and quantitative techniques to analyze scientific problems. Scientists write programs that model systems being studied and then use these programs on different sets of input parameters. The next is numerical analysis. Numerical analysis is defined as studying algorithms which use numerical approximation for mathematical analysis. Modern numerical analysis does not attempt to find exact answers, but instead to obtain approximate solutions while at the same time maintaining a certain small margin of error.  Symbolic computation is another branch of scientific computing. It specifically focuses on studying and developing algorithms and software for manipulating mathematical expressions or objects. These objects could be calculated to exact or inexact values.

Computational physics/biology/chemistry are the study and development of algorithms to solve problems in physics, biology, or chemistry. Computational physics was the first of the three to use computers to solve problems. An example of a problem solved in physics is the matrix eigenvalue problem, which finds eigenvalues and their corresponding eigenvectors for matrices very large in size. Lastly, computational neuroscience is the science of studying the information processing properties of the brain and nervous system. It is a way of modeling the essential features of a biological system in many ways. It generally deals with single-neuron modeling, development, axonal patterning, guidance, sensory processing, memory, cognition, discrimination, and learning.


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