# GLOW: A Unified Particle Flow Transformer

## TL;DR

GLOW is a transformer-based model that unifies particle flow reconstruction tasks, achieving state-of-the-art results in particle physics simulations by integrating incidence matrix supervision with a MaskFormer architecture.

## Contribution

The paper introduces GLOW, a novel unified transformer architecture that combines incidence matrix supervision and MaskFormer design for particle flow reconstruction.

## Key findings

- Achieves state-of-the-art performance on CLIC detector simulations.
- Demonstrates effectiveness of a single unified transformer for diverse tasks.
- Validates the approach with competitive results in particle physics reconstruction.

## Abstract

We present GLOW, a transformer-based particle flow model that combines incidence matrix supervision from HGPflow with a MaskFormer architecture. Evaluated on CLIC detector simulations, GLOW achieves state-of-the-art performance and, together with prior work, demonstrates that a single unified transformer architecture can effectively address diverse reconstruction tasks in particle physics.