Advancements in Long-Lived Particle Detection at ATLAS

The search for new physics beyond the Standard Model is a major goal for scientists working at particle colliders like the Large Hadron Collider (LHC). A major area of research involves finding Long-Lived Particles (LLPs). These particles can be challenging to detect because they often travel a significant distance from where they were produced before they decay. This paper discusses improvements made to the ATLAS detector's ability to find and reconstruct the paths of charged particles, particularly those resulting from the decay of LLPs.

#The ATLAS Detector

The ATLAS detector is a large device located at the LHC, designed for a variety of experiments. It has a cylindrical shape and covers almost the entire area around the point where protons collide. The detector is made up of several components, including the inner detector, electromagnetic calorimeter, hadronic calorimeter, and muon spectrometer. Each component plays a role in measuring particles produced during collisions.

#Inner Detector

The inner detector is crucial for tracking the paths of charged particles. It consists of three main types of detectors: silicon pixel detectors, silicon strip detectors, and straw drift tubes. These detectors work together to provide precise measurements of where charged particles travel within the detector.

• Silicon Pixel Detectors: These are highly sensitive and provide detailed information about the position of particles.
• Silicon Strip Detectors: They help track particles over slightly longer distances within the detector.
• Straw Drift Tubes: These are used for tracking particles that may travel farther out, adding points to the reconstructed paths of the particles.

#Energy Measurement

The calorimeters measure the energy of the particles. The electromagnetic calorimeter is designed to capture the energy from particles like photons and electrons, while the hadronic calorimeter is focused on measuring energy from particles like protons and neutrons.

#Long-Lived Particles and Challenges

Long-lived particles can take longer to decay compared to other particles. When searching for these particles, scientists face challenges because the traditional methods of detecting particles are often focused on those that decay very close to where they were produced. In cases where LLPs are involved, the decay may occur far from the initial point of interaction, making it harder to identify them.

#Challenges in Detection

The standard detection methods often require particles to be relatively close to the primary interaction point. However, LLPs may travel several millimeters or even centimeters away before they decay. This distance can lead to difficulties in accurately reconstructing their paths and identifying them among the many particles produced in collisions.

#Large-Radius Tracking

To address the challenges posed by LLPs, the ATLAS collaboration developed a special tracking method called Large-Radius Tracking (LRT). This approach uses a different set of criteria to search for and reconstruct the paths of particles that decay farther away from the interaction point.

#Improvements for Run 3

In preparation for the upcoming data collection period, known as Run 3, significant improvements have been made to the LRT method. These enhancements allow the detection system to run LRT on all recorded events, rather than just a small subset. The goal is to increase the chance of detecting LLPs and to improve the efficiency of the overall detection system.

#How The Tracking Works

#Track Reconstruction Process

The process of tracking involves multiple steps. Initially, the system looks for "seeds," which are points where the system believes a particle may have passed through. Once these seeds are identified, the tracking algorithms use them to estimate the paths of particles through the inner detector.

1. Seed Identification: The process begins by identifying candidate points in the detectors that indicate the presence of a charged particle.
2. Combining Measurements: Measurements from the silicon pixel and strip detectors are combined to form potential particle paths.
3. Ambiguity Resolution: The system evaluates different possible paths to determine the most likely trajectory of the particle.
4. Final Tracking: The confirmed paths are finalized, taking into account any additional measurements from the other detector components.

#Large-Radius Tracking Features

LRT differs from traditional tracking methods. It relaxes the strict requirements for particle position, allowing it to include tracks that originate farther away from the primary interaction area. This is particularly important for detecting LLPs, which may produce decay products that are more distant.

#Simulation and Performance Testing

Before applying these methods to actual data, simulations are performed. These simulations help researchers understand how well the tracking algorithms will perform under different conditions.

#Benchmark Scenarios

Several theoretical scenarios are used to simulate how LLPs might behave. Each scenario is based on different models of particle physics, providing diverse conditions for the tracking algorithms to test against. These scenarios help fine-tune the system and ensure it is effective in real-world applications.

1. Supersymmetric Models: In these scenarios, particles called gluinos decay into multiple quarks, allowing researchers to study how the tracking system identifies complex decay patterns.
2. Higgs Portal Models: These models explore how Higgs particles could decay into neutral particles, providing insights into the tracking of less common decay products.
3. Heavy Neutral Leptons: This scenario focuses on interactions between standard model neutrinos and heavier theoretical particles, allowing researchers to test the system's performance with isolated tracks.

#Results from Simulation

#Reconstruction Efficiency

The efficiency of the tracking system is analyzed by comparing the simulated conditions with the expected behavior of particles. The results indicate how well the algorithms can identify and reconstruct the pathways of charged particles.

• Efficiency Factors: The efficiency of LRT is measured against traditional methods, showing that LRT can recover paths for LLPs that traditional methods might miss.
• Facts about Displaced Tracks: As the distance from the primary interaction increases, traditional tracking becomes less efficient, while LRT maintains a higher efficiency for longer distances.

#Robustness Against Background Events

As the number of collisions in a given time period increases, the environment becomes more crowded. This can lead to confusion in detecting tracks since many particles are produced simultaneously. The new LRT method has been designed to handle this increased complexity effectively.

#Improved Secondary Vertex Reconstruction

Another area of focus has been the reconstruction of secondary vertices. When LLPs decay, they can create secondary vertices that researchers want to identify. The improved LRT method helps accurately pinpoint these vertices, translating to better identification of LLPs.

#Vertex Reconstruction Algorithms

Two main algorithms are used for reconstructing secondary vertices:

1. Inclusive Vertexing Algorithm: This method aims to find decays from heavier LLPs, forming vertices from pairings of tracks.
2. Two-Body Decay Algorithm: This algorithm is specifically tailored to reconstruct two-body decays, focusing on pairs of particles that are oppositely charged.

#Comparing Data and Simulation

To validate the performance of LRT, scientists compare the reconstructed tracks and vertices from real data collected during experiments with simulated events. This process helps ensure that the models accurately represent the conditions observed during actual collisions.

#Understanding Discrepancies

When there are differences between the simulated data and the actual results, these discrepancies are carefully analyzed. Factors such as the material composition within the detector can impact how well tracks are reconstructed. Researchers adjust simulations to account for these variables, ensuring the models reflect reality as closely as possible.

#Conclusion

The ATLAS Collaboration has made significant strides in improving track reconstruction methods for detecting long-lived particles. The integration of LRT into the standard tracking process will enhance the detection of new physics beyond the Standard Model. These advancements not only streamline the workflows for LLP analyses but also improve the overall efficiency of particle detection at the Large Hadron Collider. The results from simulation and real data verification demonstrate that the updated methods will increase the sensitivity and effectiveness of future searches for new particle phenomena. This work sets the stage for exciting discoveries in the field of particle physics.