L2LFlows: generating high-fidelity 3D calorimeter images

IF 1.3 4区工程技术 Q3 INSTRUMENTS & INSTRUMENTATION

Journal of Instrumentation Pub Date : 2023-10-01 DOI:10.1088/1748-0221/18/10/p10017

Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Claudius Krause, Imahn Shekhzadeh, David Shih

引用次数: 17

Abstract

Abstract We explore the use of normalizing flows to emulate Monte Carlo detector simulations of photon showers in a high-granularity electromagnetic calorimeter prototype for the International Large Detector (ILD). Our proposed method — which we refer to as “Layer-to-Layer Flows” ( L2LFlows ) — is an evolution of the CaloFlow architecture adapted to a higher-dimensional setting (30 layers of 10× 10 voxels each). The main innovation of L2LFlows consists of introducing 30 separate normalizing flows, one for each layer of the calorimeter, where each flow is conditioned on the previous five layers in order to learn the layer-to-layer correlations. We compare our results to the BIB-AE, a state-of-the-art generative network trained on the same dataset and find our model has a significantly improved fidelity.

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L2LFlows:生成高保真3D量热仪图像

摘要:我们探索了在国际大型探测器(ILD)的高粒度电磁量热计原型中使用归一化流来模拟蒙特卡罗探测器对光子雨的模拟。我们提出的方法——我们称之为“层到层流”(L2LFlows)——是CaloFlow架构的一种进化，适合于更高维度的设置(30层，每层10× 10体素)。L2LFlows的主要创新包括引入30个独立的归一化流，每个归一化流对应于量热计的每一层，其中每个流都以前五层为条件，以便学习层与层之间的相关性。我们将我们的结果与BIB-AE(在相同数据集上训练的最先进的生成网络)进行比较，发现我们的模型具有显着提高的保真度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Instrumentation 工程技术-仪器仪表

CiteScore

2.40

自引率

15.40%

发文量

827

审稿时长

7.5 months

期刊介绍： Journal of Instrumentation (JINST) covers major areas related to concepts and instrumentation in detector physics, accelerator science and associated experimental methods and techniques, theory, modelling and simulations. The main subject areas include. -Accelerators: concepts, modelling, simulations and sources- Instrumentation and hardware for accelerators: particles, synchrotron radiation, neutrons- Detector physics: concepts, processes, methods, modelling and simulations- Detectors, apparatus and methods for particle, astroparticle, nuclear, atomic, and molecular physics- Instrumentation and methods for plasma research- Methods and apparatus for astronomy and astrophysics- Detectors, methods and apparatus for biomedical applications, life sciences and material research- Instrumentation and techniques for medical imaging, diagnostics and therapy- Instrumentation and techniques for dosimetry, monitoring and radiation damage- Detectors, instrumentation and methods for non-destructive tests (NDT)- Detector readout concepts, electronics and data acquisition methods- Algorithms, software and data reduction methods- Materials and associated technologies, etc.- Engineering and technical issues. JINST also includes a section dedicated to technical reports and instrumentation theses.