ePix: a class of architectures for second generation LCLS cameras
Abstract
ePix is a novel class of ASIC architectures, based on a common platform, optimized to build modular scalable detectors for LCLS. The platform architecture is composed of a random access analog matrix of pixel with global shutter, fast parallel column readout, and dedicated sigma-delta analog-to-digital converters per column. It also implements a dedicated control interface and all the required support electronics to perform configuration, calibration and readout of the matrix. Based on this platform a class of front-end ASICs and several camera modules, meeting different requirements, can be developed by designing specific pixel architectures. This approach reduces development time and expands the possibility of integration of detector modules with different size, shape or functionality in the same camera. The ePix platform is currently under development together with the first two integrating pixel architectures: ePix100 dedicated to ultra low noise applications and ePix10k for high dynamic range applications.
- Authors:
-
- SLAC National Accelerator Laboratory, Menlo Park, CA (United States)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1187988
- Grant/Contract Number:
- AC02-76SF00515
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physics. Conference Series (Online)
- Additional Journal Information:
- Journal Name: Journal of Physics. Conference Series (Online); Journal Volume: 493; Journal Issue: 96; Journal ID: ISSN 1742-6596
- Publisher:
- Institute of Physics (IOP)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Dragone, A., Caragiulo, P., Markovic, B., Herbst, R., Reese, B., Herrmann, S. C., Hart, P. A., Segal, J., Carini, G. A., Kenney, C. J., and Haller, G. ePix: a class of architectures for second generation LCLS cameras. United States: N. p., 2014.
Web. doi:10.1088/1742-6596/493/1/012012.
Dragone, A., Caragiulo, P., Markovic, B., Herbst, R., Reese, B., Herrmann, S. C., Hart, P. A., Segal, J., Carini, G. A., Kenney, C. J., & Haller, G. ePix: a class of architectures for second generation LCLS cameras. United States. https://doi.org/10.1088/1742-6596/493/1/012012
Dragone, A., Caragiulo, P., Markovic, B., Herbst, R., Reese, B., Herrmann, S. C., Hart, P. A., Segal, J., Carini, G. A., Kenney, C. J., and Haller, G. Mon .
"ePix: a class of architectures for second generation LCLS cameras". United States. https://doi.org/10.1088/1742-6596/493/1/012012. https://www.osti.gov/servlets/purl/1187988.
@article{osti_1187988,
title = {ePix: a class of architectures for second generation LCLS cameras},
author = {Dragone, A. and Caragiulo, P. and Markovic, B. and Herbst, R. and Reese, B. and Herrmann, S. C. and Hart, P. A. and Segal, J. and Carini, G. A. and Kenney, C. J. and Haller, G.},
abstractNote = {ePix is a novel class of ASIC architectures, based on a common platform, optimized to build modular scalable detectors for LCLS. The platform architecture is composed of a random access analog matrix of pixel with global shutter, fast parallel column readout, and dedicated sigma-delta analog-to-digital converters per column. It also implements a dedicated control interface and all the required support electronics to perform configuration, calibration and readout of the matrix. Based on this platform a class of front-end ASICs and several camera modules, meeting different requirements, can be developed by designing specific pixel architectures. This approach reduces development time and expands the possibility of integration of detector modules with different size, shape or functionality in the same camera. The ePix platform is currently under development together with the first two integrating pixel architectures: ePix100 dedicated to ultra low noise applications and ePix10k for high dynamic range applications.},
doi = {10.1088/1742-6596/493/1/012012},
journal = {Journal of Physics. Conference Series (Online)},
number = 96,
volume = 493,
place = {United States},
year = {Mon Mar 31 00:00:00 EDT 2014},
month = {Mon Mar 31 00:00:00 EDT 2014}
}
Web of Science
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