Computational Modeling Quotes

I've always been very interested in the question of how computation can fundamentally advance the things that we can see. This led me to have a fascination with medical imaging, especially things like MRI and scanning, and eventually computer graphics.

Over the centuries, monumental upheavals in science have emerged time and again from following the leads set out by mathematics.

We think that computer models represent reality especially if we developed the models.

My laboratory uses evolution to design new enzymes. No one really knows how to design them - they are tremendously complicated. But we are learning how to use evolution to make new ones, just as nature does.

There was a project at Lawrence Livermore National Labs where many years ago they went down this path for scripting and controlling very large numerical calculations.

The question you raise, 'How can such a formulation lead to computations?' doesn't bother me in the least! Throughout my whole life as a mathematician, the possibility of making explicit, elegant computations has always come out by itself, as a byproduct of a thorough conceptual understanding of what was going on. Thus I never bothered about whether what would come out would be suitable for this or that, but just tried to understand - and it always turned out that understanding was all that mattered.

The computer takes up where psychoanalysis left off. It takes the ideas of a decentered self and makes it more concrete by modeling mind as a multiprocessing machine.

If we suppose that many natural phenomena are in effect computations, the study of computer science can tell us about the kinds of natural phenomena that can occur.

Because of recent improvements in the accuracy of theoretical predictions based on large scale ab initio quantum mechanical calculations, meaningful comparisons between theoretical and experimental findings have become possible.

In a biological system, the software builds its own hardware, but design is critical, and if you start with digital information, it has to be really accurate.

The methods of theoretical physics should be applicable to all those branches of thought in which the essential features are expressible with numbers.

One day I discovered that one could get the barrier to internal rotation in ethane approximately right using this method. This was the beginning of my work on organic molecules.

The eventual goal is to marry all of my work together to make a high-speed, high-resolution, low-impact tool that can look deep inside biological systems.

That's the new way - with computers, computers, computers. That's the way we can have the cell survive and get some new information in high resolution. We started about five years ago and, today, I think we have reached the target.

All physical systems can be thought of as registering and processing information, and how one wishes to define computation will determine your view of what computation consists of.

I can only speak for particle physics. But it has become obvious that on the experimental side, there has been a huge evolution in the number of people who have to collaborate because of the gigantic size of the instruments used, but also because of the enormous task that is data analysis.

The thing that got me started on the science that I've been building now for about 20 years or so was the question of okay, if mathematical equations can't make progress in understanding complex phenomena in the natural world, how might we make progress?

We have the ability, at such high fidelity, to simulate the physical world through computers. But when the spiritual world or human behavior comes into play, we don't have a very good model for that at all.

I realized that you could formulate theories about human and social phenomena in language and pictures and whatever you wanted on the computer, and you didn't have to go through this straitjacket, adding a lot of numbers.