/Modeling Physical Systems With Large Language Machine-learned Models
Abstract

A predictive system may access a set of physical structures corresponding to a molecule. Each physical structure is representative of a configuration. The predictive system may encode the accessed physical structures to produce a set of encoded physical structures by encoding, for each accessed physical structure, a position of each constituent unit of the molecule within the accessed physical structure. The predictive system may train a machine-learned model using the encoded physical structures. The predictive system may retrain the machine-learned model by iteratively: accessing a set of two or more candidate physical structures, determining a first energy difference among the set of candidate physical structures, obtaining a second energy difference between a set of physical structures corresponding to the set of candidate physical structures using a method to calculate reference energy values.

Full Text

What is claimed is:

A predictive system may access a set of physical structures corresponding to a molecule. Each physical structure is representative of a configuration. The predictive system may encode the accessed physical structures to produce a set of encoded physical structures by encoding, for each accessed physical structure, a position of each constituent unit of the molecule within the accessed physical structure. The predictive system may train a machine-learned model using the encoded physical structures. The predictive system may retrain the machine-learned model by iteratively: accessing a set of two or more candidate physical structures, determining a first energy difference among the set of candidate physical structures, obtaining a second energy difference between a set of physical structures corresponding to the set of candidate physical structures using a method to calculate reference energy values.
Timeline
Filed
04/24/2026
Published
09/03/2026
Granted
Not Available
IPC Codes(2)
G06F 30/27:using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
G06N 3/084:Backpropagation, e.g. using gradient descent