skip to main content

Title: Implications of CMS analysis of photon-photon interactions for photon PDFs
Award ID(s):
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Chinese Physics C
Page Range / eLocation ID:
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Gregor, Ingo ; Erdmann, Rainer ; Koberling, Felix (Ed.)
    Photon-HDF5 is an open-source and open file format for storing photon-counting data from single molecule microscopy experiments, introduced to simplify data exchange and increase the reproducibility of data analysis. Part of the Photon-HDF5 ecosystem, is phconvert, an extensible python library that allows converting proprietary formats into Photon-HDF5 files. However, its use requires some proficiency with command line instructions, the python programming language, and the YAML markup format. This creates a significant barrier for potential users without that expertise, but who want to benefit from the advantages of releasing their files in an open format. In this work, we present a GUI that lowers this barrier, thus simplifying the use of Photon-HDF5. This tool uses the phconvert python library to convert data files originally saved in proprietary data formats to Photon-HDF5 files, without users having to write a single line of code. Because reproducible analyses depend on essential experimental information, such as laser power or sample description, the GUI also includes (currently limited) functionality to associate valid metadata with the converted file, without having to write any YAML. Finally, the GUI includes several productivity-enhancing features such as whole-directory batch conversion and the ability to re-run a failed batch, only converting the files that could not be converted in the previous run. 
    more » « less
  2. Abstract

    Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

    more » « less