What is computational science and why is it important?

Computational science is the study of using computers to solve complex theories and problems. In the past, computation was an auxiliary tool, but with the development of computers, it has become an important factor. It has a wide range of applications, and developed countries are investing heavily in it.

 

Nowadays, you’ll often hear the term computational science used to refer to computational physics, computational chemistry, computational biology, etc. Even if you don’t use the term computational science, there are many important studies that utilize it. The detection of gravitational waves on February 11, 2016, which made headlines around the world, can also be attributed to computational science. However, many people are still unfamiliar with the term computational science. So what are the new implications of “computational science” for those of us who know “computation” and “science,” and why is it important?
According to the Korea Institute of Advanced Study (KIAS), a research institute under the Ministry of Science, ICT and Future Planning, computational science is “an academic field that systematically solves problems involving complex theories and massive computations in various fields of science and technology using pure basic science theories and computers.” In the past, science consisted of two elements: theory (hypothesis) and experiment. If the experimental results supported the hypothesis, it became a theory. This is not to say that computation hasn’t been used in the past, but the role of computation has changed dramatically. “Science used to run on two wheels: theory and experiment, but now it has added computation and simulation.
Advances in computers have played a big role in this change. The advent and development of computers has made it possible to perform astronomical calculations that were previously impossible, allowing us to build virtual laboratories (simulations) that allow us to achieve the desired results with much less investment (e.g., time and money) than actual experiments. In addition, nanoscale research at the atomic and molecular levels, or macroscale research at the cosmic level, has been difficult to achieve through classical experiments and observations, but computational science allows us to overcome these limitations. Computational science also allows us to perform experiments that would otherwise be prohibited for ethical reasons. For example, in the real world, a researcher might not be able to marry two men and women and have them produce children at will, but in a computer, there is no problem combining and analyzing the genetic information of two specific individuals.
Computational science takes on many different forms in real-world applications depending on the field in which it is applied, making it inherently multidisciplinary. Regardless of the field, computational science requires basic knowledge of numerical analysis from mathematics, computer algorithms from computer science, and statistical processing of information, as well as tools such as ultra-fast and large-scale computation, simulation, modeling, visualization, and data analysis, represented by parallel supercomputing. When these computational scientific methodologies are combined with the principles and knowledge of the field to which they are applied, a new field called computational science is born.
So, what fields can computational science be applied to? It can be applied to any field where computation is possible. It can be applied in engineering, finance, and economics, as well as in the natural sciences. Let’s take the example of computational biology, which is a branch of computational science, and computational neuroscience. Neuroscience is the study of the nervous system, including the human brain, and computational neuroscience focuses on studying the workings of the brain as it relates to cognition, experience, and behavior. With more than 100 billion neurons in the human brain, the computational capacity of the human brain is far from astronomical at this point, but the nematode Caenorhabditis elegans, which has about 300 neurons, can be programmed on a computer, and the same behaviors can be replicated by a real creature and a programmed robot.
As such, computational science is not only at the core of 21st century academia, but also at the core of high-value industries, which is why developed countries are investing heavily in computational science. As early as the 50s and 60s, research institutes in the United States began to establish computational science departments (the genesis of computational science was nuclear weapons development), followed by the United Kingdom, Germany, and Japan. In Korea, the Cooperative Program in Computational Science at Seoul National University was established in 2004. Despite the fact that many of the research that captures our attention, such as the discovery of gravitational waves, utilizes computational science, many people are not familiar with it. More attention needs to be paid to computational science, which is becoming an important methodology across a wide range of disciplines.