PyLDM

PyLDM performs lifetime density analysis of time-resolved ultrafast spectroscopic data, extracting semi-continuous distributions of lifetimes to characterize dynamic energy and charge transfer processes in systems such as photosynthetic complexes.

Key Features:

• Lifetime Density Analysis (LDA): Implements LDA using a semi-continuous distribution of 100 lifetimes as an alternative to approximating data with a small number of exponential decays.
• Dynamic Motion Resolution: Resolves dynamic motion and non-linear decay behavior that conventional global analysis, based on linear combinations of exponentials, cannot describe.
• Complex Chromophore Systems: Enables elucidation of lifetime distributions in systems with multiple chromophores such as photosystems.
• Comparison with Global and Target Analysis: Provides direct comparison of LDA results with global analysis and target analysis approaches.
• Statistical Regularization: Incorporates statistical methods to regularize noisy time-resolved data and stabilize inferred lifetime distributions.
• Implementation: Implemented in Python (version 2.7).

Scientific Applications:

• Photosynthetic complexes: Characterizes energy transfer and charge separation dynamics in photosystems and other photosynthetic assemblies.
• Photoactive compounds: Analyzes ultrafast energy and charge transfer processes in multi-chromophore photoactive molecules.
• Transient species analysis: Identifies and characterizes transient states and their interactions in time-resolved spectroscopic experiments.
• Complementary analysis: Serves as a complementary method to global and target analysis for interpreting complex ultrafast spectroscopic data.

Methodology:

Implements lifetime density analysis on a semi-continuous grid of 100 lifetimes, compares LDA outputs with global and target analysis, and applies statistical regularization to noisy data; implemented in Python 2.7.