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Sascha VongehrRSS Feed of this column.

Dr. Sascha Vongehr [风洒沙], physicist and philosopher, studied phil/math/chem/phys in Germany, obtained a BSc in theoretical physics (electro-mag) & MSc (stringtheory) at Sussex University... Read More »

We already must deal with computers too much rather than too little, and there is already lots of advanced computing done also for example in materials science and nanotechnology, for example molecular dynamics (MD) and Monte Carlo simulations.[2] The molecular biologist’s programs for predicting protein folding can also count as nanotechnology. Nevertheless, all of our previous articles* concluded that we need more computing, and several mentioned statistics. This would sound predictable if coming from a statistical physicist with a background in computing, advertising his skills. However, we mean a more efficient computing rather than simply more.
The (Pre-)Neanderthals were the first, you see:

When optimizing in multi-dimensional parameter spaces, local maximums are not as much of a problem as being misguided by maximums that are constrained on a lower dimensional subspace. Therefore, so called ‘walk-in’ methods are necessary. They must explore all directions of the high dimensional space. Apart from such details, we are more interested in complexity as such in order to allow complex reactions and properties/behaviors in the first place (before optimizing), and to further research how proxy-measures of complexity compare to performance.

Long Title: "Galactic Random-Genocide from Quantum-Relativistic Plenitude Principled Multiversial Many-Minds Ethics under the Doctrine of Diversity or Donald Trump"

Alternative Title: The 1 CC = 50 FF or FFF Theorem or One Concealed Carry saves Fifty Feely Faggots in a parallel universe under Donaldo Trumpovich.


Higher dimensional spaces allow configurations that are unexpected from lower dimensions. For example, four-dimensional topology escapes full classification. Since complexity is related to dimensionality, there is a certain “magic” to it. Increasing complexity is advantageous generally for adaptation. We can give examples from nanotechnology. With catalysts, starting with mono-metallic ones, the desired catalytic prowess increases almost geometrically with the number of different substances involved.[2] Bimetallic catalysts multiply the catalytic rate constants of mono metallic compounds.