The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy
The world in a grain of sand: condensing the string vacuum degeneracy

World in a grain of sand

AI algorithm of few-shot learning finds that the vast string landscape could be reduced by only seeing a tiny fraction to predict the rest.

The world in a grain of sand: condensing the string vacuum degeneracy

Submitted to Proceedings of the National Academy of Sciences of the USA (2022)

Y. He, S. Lal, M. Zaid Zaz

Submitted to Proceedings of the National Academy of Sciences of the USA (2022)

Y. He, S. Lal, M. Zaid Zaz