Computer Simulations and Their Importance

In summary, a computer simulation can lead to a scientific discovery from an epistemic point of view.
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radoo
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Can a computer simulation lead to a scientific discovery from an epistemic point of view?
Do you know any of such discoveries throughout the history of physics?
 
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http://sciencefocus.com/qa/can-computers-make-discoveries

Computers have certainly helped make lots of discoveries in areas ranging from mathematics and astronomy to biochemistry. But during the 1950s, some computer scientists believed that their machines might one day make discoveries by themselves. The prediction appeared to come to pass in 1982, when a logic-based program named the Automated Mathematician (AM), developed by Douglas Lenat at Stanford University, announced its belief that every even integer greater than two might be expressed as the sum of two primes. Admittedly, humans had got there first: the German mathematician Christian Goldbach made the same claim in 1742, though neither he nor anyone else has ever been able to prove conclusively that all integers obey this rule. Even so, ‘Goldbach’s Conjecture’ is widely believed to be the first ever (re-)discovery made by a computer without overt human intervention.
 
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This is an interesting question. It begs the question, what is a scientific "discovery"?

Chaos theory is almost a legitimate "discovery," because until Edward Lorenz tried to repeat a Navier-Stokes simulation with initial conditions he rounded to three decimal places instead of the six the computer stored, people were not totally convinced of such "sensitivity to initial conditions." So that really is a place where the computer simulation really allowed a new phenomenon in the theory to be observed.

Not quite science, but pure math has some "discoveries" that come from computers. Was the Mandelbrot Set "discovered" when it was simulated, or was it discovered when the defining equation was written down? It gets hazy.

Simulations are used all the time in physics to get numerical estimates. For example, a lot of computational power has been devoted to simulating the equations of GR, such as estimating the magnitude of gravitational waves from colliding black holes. But there's really no "discovery" here unless you're very impressed with numerical values. Similar things are often done in quantum theory, e.g. simulations are often done to find variational solutions to many-body wavefunctions, and perturbative QFT calculations involving Feynman diagrams are often calculated on computer. Still not really a "discovery" though.

Then again there are some actual nontrivial hypotheses that people were only able to arrive at using computers. I don't think any good ones have been verified yet but they've been proposed, so that's why I call them hypotheses. For example, astronomers simulated the history of the solar system, and the simulations seem to indicate that both Neptune and Uranus actually originated inside the orbit of Saturn, and subsequently moved into their current position. See here: http://arxiv.org/abs/astro-ph/0111290. There's even a paper on arXiv which says that similar solar system simulations indicate there was an extra gas giant in our early solar system! http://arxiv.org/pdf/1109.2949v1.pdf

Other simulations that give nontrivial facts are models of climate-changing ocean flows and how they led to ice ages. I have heard (no reference though) that someone performed a simulation of the oceans over the next few years, incorporating global warming, which led to the prediction that global warming would divert the gulf stream, and then (counterintuitively) as a result of the gulf stream being diverted, the polar ice caps would grow super rapidly sending us into another ice age! I don't know how you could cook that up without a simulation. (Here's a sort of related reference on ocean modeling and climate change http://www.psc.edu/science/OKeefe/OKeefe.html )
 
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Computer simulations are an essential tool in modern scientific research. They allow scientists to create virtual models of complex systems and phenomena, which can be studied and manipulated in ways that would not be possible in the physical world. This allows for a deeper understanding of the underlying mechanisms and behaviors of these systems, and can lead to new discoveries and insights.

From an epistemic point of view, computer simulations can certainly lead to scientific discoveries. By providing a platform for testing and refining hypotheses, simulations can help scientists to make sense of complex data and to identify patterns and relationships that may not be immediately apparent. In some cases, simulations can even suggest new hypotheses or avenues of research that may not have been considered before.

One example of a scientific discovery made possible by computer simulations is the discovery of the Higgs boson, a fundamental particle that was predicted by the Standard Model of particle physics but had not been observed until 2012. The Large Hadron Collider, a massive particle accelerator, was used to generate and analyze data from high-energy collisions, which were then compared to simulations of the expected outcomes. This ultimately led to the discovery of the Higgs boson and confirmed the validity of the Standard Model.

Another example is the discovery of gravitational waves, which were predicted by Einstein's theory of general relativity but had not been directly observed until 2015. The Laser Interferometer Gravitational-Wave Observatory (LIGO) used computer simulations to model and analyze the data from the gravitational wave signals detected from the collision of two black holes. These simulations were crucial in verifying the existence of gravitational waves and opened up a new field of study in astrophysics.

In conclusion, computer simulations are a powerful tool in scientific research and have been instrumental in many significant discoveries throughout the history of physics. They allow for a deeper understanding of complex systems and phenomena and can lead to new insights and discoveries. However, it is important to note that simulations should always be used in conjunction with other methods and should not be seen as a replacement for real-world experiments and observations.
 

FAQ: Computer Simulations and Their Importance

What are computer simulations and why are they important?

Computer simulations are digital models or representations of real-world systems or phenomena. They use mathematical algorithms and data to mimic the behavior of the system being studied. They are important because they allow scientists to study complex systems that are difficult or impossible to observe in real life, and can provide insights and predictions that are crucial for scientific advancement.

What types of systems can be simulated using computers?

Almost any system can be simulated using computers, including physical systems (e.g. climate, fluid dynamics, and atomic interactions), biological systems (e.g. protein folding and evolution), and social systems (e.g. economics and population dynamics).

What are some benefits of using computer simulations?

Computer simulations have numerous benefits, including providing a safe and cost-effective way to study complex systems, allowing for the manipulation of variables and conditions to observe their effects, and reducing the need for expensive and time-consuming experiments.

What are some limitations of computer simulations?

While computer simulations have many advantages, they also have limitations. They are only as accurate as the data and assumptions used in the model, and they cannot account for all the complexities and uncertainties of real-world systems. Additionally, simulations may not be able to capture rare or unexpected events that could occur in the real world.

How are computer simulations validated and verified?

Validation and verification are crucial steps in ensuring the accuracy and reliability of computer simulations. Validation involves comparing the simulation results to real-world data and experiments to ensure that the model accurately represents the system being studied. Verification involves testing the code and algorithms used in the simulation to ensure they are correctly implemented. These processes help to improve the confidence in the simulation results and their usefulness for scientific research.

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