Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Development of High-Granularity Dual-Readout Calorimetry with psec Timing

View through CrossRef
Dual-readout and particle flow algorithm (PFA) are technologies proposed for precise jet energy measurement in future colliders. While PFA requires highly granular calorimeters, dual-readout has mainly been used with fiber-based calorimeters that do not have highly segmented capabilities. It is still non-trivial to combine these two technologies in one calorimeter system because of the use of fibers in most of the dualreadout calorimeters, which is not compatible with the high granularity requirement of PFA technologies. The aim of this study is to develop a novel calorimetry that combines dual-readout and PFA by adopting a highly segmented tile-based configuration. This paper compares the improvement of energy resolution using dual-readout approach across several configurations of highly granular hadron calorimeters through simulation. Results indicate that setups with fine sampling and close placement of scintillators and Cherenkov detectors improve dual-readout performance.
Title: Development of High-Granularity Dual-Readout Calorimetry with psec Timing
Description:
Dual-readout and particle flow algorithm (PFA) are technologies proposed for precise jet energy measurement in future colliders.
While PFA requires highly granular calorimeters, dual-readout has mainly been used with fiber-based calorimeters that do not have highly segmented capabilities.
It is still non-trivial to combine these two technologies in one calorimeter system because of the use of fibers in most of the dualreadout calorimeters, which is not compatible with the high granularity requirement of PFA technologies.
The aim of this study is to develop a novel calorimetry that combines dual-readout and PFA by adopting a highly segmented tile-based configuration.
This paper compares the improvement of energy resolution using dual-readout approach across several configurations of highly granular hadron calorimeters through simulation.
Results indicate that setups with fine sampling and close placement of scintillators and Cherenkov detectors improve dual-readout performance.

Related Results

When Does a Dual Matrix Have a Dual Generalized Inverse?
When Does a Dual Matrix Have a Dual Generalized Inverse?
This paper deals with the existence of various types of dual generalized inverses of dual matrices. New and foundational results on the necessary and sufficient conditions for vari...
Strip-based Scintillation Detector for Dual-readout High-granularity Calorimetry
Strip-based Scintillation Detector for Dual-readout High-granularity Calorimetry
New calorimeter technology is being developed for future collider experiments. We are developing a calorimeter that integrates two technologies, a high-granularity calorimeter and ...
Collaborative Promotion:A New Path for the Development of Dual-Innovation Education in Colleges and Universities in Ethnic Minority Area
Collaborative Promotion:A New Path for the Development of Dual-Innovation Education in Colleges and Universities in Ethnic Minority Area
In the context of the new era, talent is the first resource and innovation is the first driving force, and it is more and more important to emphasize the dual-creation education in...
Spatial resolution improvement of PICOSEC Micromegas precise timing detectors
Spatial resolution improvement of PICOSEC Micromegas precise timing detectors
Abstract The combination of a Cherenkov radiator with a semi transparent photocathode and a Micromegas based amplification stage allows P...
Excellent Timing Cherenkov Light Detection for Dual-readout High-granularity Calorimetry
Excellent Timing Cherenkov Light Detection for Dual-readout High-granularity Calorimetry
We are developing a Cherenkov detector aiming for applications in the next-generation calorimetry. It is a calorimetry that combines dual-readout and high-granularity with excellen...
Self-Supervised Multi-Level Generative Adversarial Network Data Imputation Algorithm
Self-Supervised Multi-Level Generative Adversarial Network Data Imputation Algorithm
Abstract Data missing has always been a challenging problem in machine learning. The Generative Adversarial Imputation Networks (GAIN) have been shown to outperform many ex...
Circadian meal timing is heritable and associated with insulin sensitivity
Circadian meal timing is heritable and associated with insulin sensitivity
Abstract Background Although the contribution of the circadian clock to metabolic regulation is widely recognized, the role of ...

Back to Top