Scientific Computing: An Intro

Scientific Computing is nothing but mathematical and informatical basis of numerical simulation. It can be used for reconstruction or prediction of phenomena and processes, esp. from science and engineering, on supercomputers

It is often known as the third-way to obtain knowledge apart from theory and experiment. It is 

transdisciplinary: mathematics + informatics + field of application.

Objectives may include,

• Reconstruct and understand known scenarios (natural disasters)
• Optimize known scenarios (technical processes)
• Predict unknown scenarios (like the weather)

One would wonder why would we need Numerical Analysis ? Well, there can be many possible reasons for it,

1. Since experiments are sometimes impossible like,

      - Predicting the life cycle of galaxies

galaxy

      - Weather forecast

      - Predicting stock market, or predicting           economic effects

2. Since experiments can be unwelcome sometimes, these would include

      - Tests of nuclear weapons

      - Stability of buildings

stability test

      - propagation of harmful substances

3. Sometimes experiments can be costly

      - Car crash

Crash test

      - Aerodynamics

      - Analysis & study of proteins

What's interesting is that you have people master one particular tool, and then work on that to solve some complex problem  of their discipline. Let's look at some particularly famous tools that most of the researchers use for this.

Mathematica logo.

Mathematica is a computational software used in many disciplines such as scientific, engineering etc, developed by Wolfram Research. It has all the features that MATLAB includes but can also be extends to 2D, 3D processing, parallel           programming.

Matlab logo.

MATLAB short for MATrix LABoratory is a numerical computing environmnt, sometimes also called fourth-generation programming language. It is allows plotting of functions and data, implementation of

algorithm, creation of UI, and interfacing with other languages, including C, C++, Java and Fortran.

With all of the technological innovation happening today, this field of computation will only be more  helpful as complex problems become much more complex to solve. It will be great to see what all problems can be solved with the ongoing technological advancement.