Introduction

Time resolved measurements are widely used for many research field, including

  • Time correlated photon counting
  • Fluorescence lifetime imaging
  • Anti-bunching
  • Linear optics quantum computing
  • Quantum process tomography
  • Scanning fluorescence microscopy
  • Photo-activated localization microscopy (PALM)
  • Stochastic optical reconstruction microscopy (STORM)
  • Stimulated emission depletion (STED) microscopy

Depending on the duration of the experiments and frequency of events, time resolved measurements can easily generate huge amounts of data, which is overwhelming for common data analysis software.

We attempt to extract the useful information form data generated from time-resolved measurements by introducing a new kind of time-tag analysis software.

ETA, the extensible time tag analyzer, is an event driven programming language with graphical user interface for analyzing, plotting, and fitting of time tagged data.

Why use ETA?

Fast
In order to make ETA fast, our approach is twofold. First, we try to find the fastest algorithm for time tag processing. On the other hand, ETA utilizes LLVM, a state-of-the- art low-level code optimizer, to perform assembly code transformation. This way we generate fast target-specific code for Intel x64 and other processors. ETA allows fast processing of large amounts of time-tagged data, with a scalability from personal computers to super computers.
Flexible
ETA allows user defined analysis which is suitable for most of the existing analysis methods, which previously required using different software. ETA is also prepared for upcoming tasks.
User-Friendly
ETA provides an easy-to-understand graphical user interface (GUI), with a novel programming paradigm dedicated to simplifying time tag processing.