Unification of Physics, Chemistry and Biology by Computation.

The Nobel Prizes 2024 in Physics and Chemistry were given to the booming industry of AI/machine learning developed mainly outside traditional academic disciplines by big actors like Google and Microsoft. 

Machine learning consist of training networks on large data sets using general computational tools from linear algebra and optimisation, which are not application specific.  

The Prize in Chemistry was given to AlphaFold2 by Google Deep Mind as an important step towards simulation/prediction of protein folding as the outstanding open problem of biology and medicine in two forms: 

• Given DNA sequence, find protein geometry.
• Given protein geometry, find DNA sequence. 

A protein is a big molecule consisting of a collection of atomic kernels kept together by electrons and as such can be described by Schrödinger's equation and folding simulated by molecular dynamics. This connects physics (atoms), chemistry (small molecules) and biology (big molecules) with their traditional roles from fundamental to composite. 

Protein folding thus connects disciplines from fundamental physics over chemistry to biology and medicine including functions of proteins as carriers of life. 

But there is one caveat: The Schrödinger equation of Standard Quantum Mechanics StdQM of standard physics involves 3N spatial dimensions for N electrons, which makes the computational cost grow exponentially making even 10 electrons beyond the capacity of any thinkable computer. 

Direct simulation of protein from first principles is thus viewed to be impossible. It is here AI comes in as way to get around this road block by starting from experimental data instead of first principles and using machine learning to train a network to predict folding of a new protein from old ones. This is what AlphaFold2 does and so was awarded the Nobel Prize in Chemistry. 

But it is possible to formulate a different Schrödinger equation as first principle  Real Quantum Mechanics RealQM, which acts in 3 space dimensions like classical continuum mechanics, for which the computational work grows linearly with the number of electrons. 

It is thus possible that protein folding can be simulated by RealQM. If true, this forms a new unification of physics, chemistry and biology based on computation as mathematics, which can be viewed as an ultimate dream of science.  

The basic code reads

• $n=n+1$

which to a given number $n$ assigns the new value $n+1$. The same code for all disciplines.This the essence of The World as Computation.

Compare with Unity of Science by Toumas Thako with Summary:

• Unity of science was once a very popular idea among both philosophers and scientists. But it has fallen out of fashion, largely because of its association with reductionism and the challenge from multiple realisation. Pluralism and the disunity of science are the new norm, and higher-level natural kinds and special science laws are considered to have an important role in scientific practice. What kind of reductionism does multiple realisability challenge? What does it take to reduce one phenomenon to another? How do we determine which kinds are natural? What is the ontological basis of unity?

Nobel Prize in Physics 2024 by AI to AI

Because of the deepening crisis of modern physics, the Nobel Committee in Physics, apparently unable to find awardees within physics, seemingly in deep despair turned to AI for help. 

No wonder: The 2024 Nobel Prize in Physics was given to AI, more precisely to computer scientist Geoffrey Hinton and scientist/higher education teacher John Hopfield, who are not really physicists.  

The Nobel Prize in Physics can thus now be given to non-physicists, if physicist candidates are missing. This would open to give the Physics Prize to mathematicians, which would resolve a controversy (between Nobel and mathematician Mittag-Leffler) from start banning mathematicians.   

PS Compare with Sabine Hossenfelder's reaction.