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Memos

EPIC Memo Series

List of memos

  1. A Roadmap for Efficient Direct Imaging with Large Radio Interferometer Arrays (Astro2020 APC White Paper - White paper submitted to Decadal Survey outlining state of direct imaging and future directions.
  2. Searching for Crab Giant Pulses with EPIC - First steps toward searching EPIC data for Crab Giant Pulses. Includes some sensitivity considerations and several examples of data artifacts.
  3. Romein Optimization - Modifications to Romein Kernel - Includes a GPU primer that gives and introduction to GPU specific terminologies; Compares Timing of original to modified romein; Commands to perform code profiling
  4. 1D Omniscope/EPIC Hybrid - An exploration of an Omniscope/EPIC framework. Includes math theory, description of algorithm to fit a grid to an array, and a few examples. Main punchline is that it's not as efficient as hoped.
  5. Cross-Correlator Module / Romein bug fix - Briefly describes the xCorr module and explains a bug-fix to enable illumination pattern > 1 in romein gridding
  6. FRB Detectability with EPIC - Describes the projected dispersive delay and pulse broadening for FRBs at LWA frequencies. We also have a sensitivity curve for integrations at EPIC timescales
  7. EPIC Data Assessment - Describes the issues dealt with while processing EPIC images offline to produce dynamic spectra or light curves for sources
  8. EPIC vs Beam : Data Comparison - Describes our understanding of the differences between EPIC and beam-formed data taken simultaneously. Steps to address these is also mentioned.
  9. EPIC Code Optimizations - Describes profiling of GPU code and various optimizations that lead to high bandwidth and full polarization capability.
  10. EPIC Imager Data Management - Summarizes data rates and storage requirements, and describes schemes for data transfer between imager and post-processing systems.
  11. Float vs Half Precision Accumulation for EPIC Images - Evaluates the uncertainies in pixel values when using half (16-bit) and float (32-bit) precision for image accumulations.
  12. EPIC Imaging & Source Localization Comparisons - Performs direct image comparisons between EPIC system and "Off-the-shelf" imagers such as WSClean. Also describes and characterizes outstanding problems within the python EPIC deployment.
  13. Searching for FRBs with EPIC - A first look at data recorded and dedispersed following CHIME-FRB alerts. No low-frequency FRBs were found.

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant Number AST-2108115 (ATI).

Disclaimer

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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