Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces

arXiv:2607.05127v1 Announce Type: cross Abstract: Understanding the physics of many-body complex dynamical systems is typically non-trivial. High-dimensional analysis approaches are often deemed necessary to prevent losing important information. Typically, these use order parameters or descriptors capturing information related to, e.g., relative positions, symmetries, etc., of the units in the studied system. However, in many cases, gaining information related to the relative positions (or velocities) of the constitutive units alone may be insufficient, and to reach a more complete physical kn

Source: arXiv cs.LG — read the full report at the original publisher.

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