کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1833023 | 1027531 | 2006 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Energy reconstruction for a hadronic calorimeter using neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
ابزار دقیق
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Energy reconstruction for a hadronic calorimeter using neural networks Energy reconstruction for a hadronic calorimeter using neural networks](/preview/png/1833023.png)
چکیده انگلیسی
Often calorimeters have a non-compensating response (e/hâ 1). Non-compensation degrades both resolution and linearity figures. To improve on this, weighting techniques are frequently applied. These techniques normally use linear combination of the energy deposited in the calorimeter cells or longitudinal samples. For the hadronic calorimeter of ATLAS, Tilecal, the use of a neural network is proposed to perform the energy reconstruction for pions, taking into account both linearity and energy resolution. Experimental data from testbeam periods were used to perform neural reconstruction.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 559, Issue 1, 1 April 2006, Pages 124-128
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 559, Issue 1, 1 April 2006, Pages 124-128
نویسندگان
P.V.M. da Silva, J.M. de Seixas,