CIRCLE WITH A DOT

This #CMSPaper investigates different #AI #machinelearning methods that aim to find jets that are inconsistent with the standard model. It shows that a new method called #Wasserstein normalized autoencodes works much better than other neural networks arxiv.org/abs/2510.02168

@ftranschel @Thcoudreau @johncarlosbaez @pluralistic this has nothing to do with "society as a whole" and just so it is clear:

it was for YEARS possible to support arxiv via donations. My group always did. The number of groups that did so worldwide was in the few hundred.

So, now we will get a shitty arXiv instead. Own fault. Academic institutions are happy to shell out 20k+ publishing fees to Nature/Science for one paper but not a few 1000 for one of the essential open science tools in our field. And so we will get what we pay for.

@ftranschel @Thcoudreau @johncarlosbaez @pluralistic agree completely. But then it's our own fault. I've been fighting in various university/academic board of directors to reserve budget for things like arxiv. Those are the line items that get cut first

In quantum physics, the decay width is a fundamental parameter that quantifies a particle's instability. Measuring the decay width is also a way to check if a particle is decaying to undiscovered particles. This #CMSPaper measures the decay width of the Higgs boson in a single signature, which involves a trick comparing Higgs bosons in their on-shell and off-shell production, which means this paper isolates these separately using machine learning https://arxiv.org/abs/2601.05168