# Search for Highly Ionizing Particles with the Pixel Detector at Belle II

## TL;DR

This paper explores the detection of Highly Ionizing Particles at Belle II using the Pixel Detector and neural networks, aiming to identify particles like anti-deuterons and magnetic monopoles that do not leave signals in outer detectors.

## Contribution

It introduces a novel method for identifying HIPs solely with Pixel Detector data using neural network algorithms, bypassing the need for outer detector signals.

## Key findings

- Neural network algorithms can effectively identify HIPs from PXD data.
- The method enables detection of particles that do not trigger outer sub-detectors.
- Potential to discover new physics phenomena involving HIPs.

## Abstract

The Belle II experiment, located at the SuperKEKB collider at the high-energy research facility KEK in Tsukuba, Japan, started operation in 2018. Compared to the predecessor experiment Belle, Belle II plans to increase the peak luminosity by a factor of about 40, by employing nano-beam technology in the interaction region. In particular the new, innermost sub-detector of Belle II - the Pixel Vertex Detector (PXD) - is in close proximity to the interaction point. This allows for the detection of particles, which do not leave a signal in the outer sub-detectors. Among these, Highly Ionizing Particles (HIPs) encounter a characteristically high energy loss, limiting their penetration depth into the detector. Anti-deuterons and magnetic monopoles as possible HIPs are considered. Without a signal in the outer sub-detectors, no track trigger is issued, resulting in possible information loss. The possibility of identifying HIPs solely with information provided by the PXD is presented, by using neural network algorithms operating in a multidimensional parameter space of PXD cluster data.