Ultrafast Spectroscopy Analyzer

Ultrafast Spectroscopy Analyzer is a comprehensive, open-source software suite designed for the advanced processing and analysis of ultrafast spectroscopy data. It provides an intuitive graphical environment to transform raw experimental data into publication-quality results.

Read the docs: https://ultrafast-spectroscopy-analyzer.readthedocs.io/en/latest/index.html# (Work in progress)

---

Install the required dependencies (run this command in the folder containing the script):

pip install -r requirements.txt

Run the application by typing the following in your terminal (inside the script folder):

python "UltrafastSpectroscopyAnalyzer.py"

Create a Standalone Executable (.exe) (Run by typing in your terminal inside the script folder):

pyinstaller --onefile --noconsole --icon=icon.ico --exclude-module PyQt6 "Ultrafast Spectroscopy Analyzer.py"

---

Supported Techniques

The application is optimized for two main experimental methods:

• TAS — Transient Absorption Spectroscopy
• FLUPS — Fluorescence Up-Conversion Spectroscopy

Mathematical Models

The software fits the experimental signal $\Delta A(t, \lambda)$ using three main approaches, all convolved with the Instrument Response Function (IRF).

---

1. Parallel Model: Decay-Associated Spectra (DAS)

Assumes that the components decay independently, which is ideal for mixtures of uncoupled species.

$$\Delta A(t, \lambda) = IRF(t) \otimes \sum_{i=1}^{n} A_i(\lambda) e^{-t/\tau_i}$$

Where each $A_i(\lambda)$ represents the DAS of the component with lifetime $\tau_i$.

---

2. Sequential Model: Species-Associated Spectra (SAS)

Describes an energy cascade or consecutive reaction: $1 \xrightarrow{k_1} 2 \xrightarrow{k_2} \dots \xrightarrow{k_n} n$.
The populations of each species are governed by the Bateman Equations.

For a decay chain where $k_i = 1/\tau_i$, the concentration $C_n(t)$ of species $n$ is defined as:

$$C_n(t) = \left( \prod_{j=1}^{n-1} k_j \right) \sum_{j=1}^{n} \frac{e^{-k_j t}}{\prod_{p=1, p \neq j}^{n} (k_p - k_j)}$$

The total signal is the sum of the contributions of each excited state (SAS):

$$\Delta A(t, \lambda) = IRF(t) \otimes \sum_{i=1}^{n} SAS_i(\lambda) C_i(t)$$

---

3. Damped Oscillation Model

Suitable for systems exhibiting coherent dynamics (e.g., vibrational wavepackets) alongside population relaxation. The total signal is modeled as a superposition of standard parallel decays and a damped oscillatory component.

$$ \Delta A(t, \lambda) = \left( IRF(t) \otimes \sum_{i=1}^{n} A_i(\lambda) e^{-t/\tau_i} \right) + B(\lambda) \cdot S_{osc}(t) $$

Where:

• $A_i(\lambda)$ are the decay amplitudes (DAS).
• $B(\lambda)$ is the Spectrum of the Oscillation Amplitude.

The oscillatory term $S_{osc}(t)$ incorporates a "Soft Step" function (using the error function erf) to simulate the convolution of the oscillation onset with the Gaussian IRF:

$$ S_{osc}(t) = \frac{1}{2} \left[ 1 + \text{erf}\left( \frac{t - t_0}{\sqrt{2}w} \right) \right] \cdot e^{-\alpha (t - t_0)} \cdot \sin\big(\omega (t - t_0) + \phi \big) $$

Key Parameters:

• $\alpha$: Damping rate.
• $\omega$: Angular frequency.
• $\phi$: Phase shift.
• $w$: Width of the IRF (controls the smoothness of the oscillation "turn-on").

Instrument Response Function (IRF)

The time resolution is modeled using a Gaussian of width $w$ (FWHM) centered at $t_0$:

$$IRF(t) = \frac{1}{w \sqrt{\pi}} \exp\left( -\left( \frac{t - t_0}{w} \right)^2 \right)$$

---

Main Features

Multi-Technique Support

• Dual Analysis: Fully compatible with TAS (Transient Absorption Spectroscopy) and FLUP (Fluorescence Upconversion) data.
• TCSPC Ready: Support for Time-Correlated Single Photon Counting data processing.

Advanced Pre-processing

• Chirp Correction: Automated and manual $t_0$ adjustment per wavelength to correct Group Velocity Dispersion (GVD).
• Data Cleaning: Integrated tools for baseline subtraction, spectral/temporal binning, and dynamic data cropping.
• Flexible Scaling: Support for Linear and SymLog (Symmetric Logarithmic) time axes for better visualization of ultrafast dynamics.

Advanced Mathematical Analysis

• SVD Diagnosis: Built-in Singular Value Decomposition to determine the number of photo-active species (matrix rank) and spectral components.
• Global Fitting: Multiexponential analysis (up to 6 components) using two physical models:
  • Parallel Model (DAS): Extraction of Decay Associated Spectra.
  • Sequential Model (SAS): Species Associated Spectra modeling for successive population transfer.
• Error Estimation: Reliability analysis using covariance matrices and Jacobian-based confidence intervals.

Scientific Visualization

• 3D Surface Explorer: Interactive 3D rendering of data surfaces to identify global trends.
• Trace Checker: Real-time inspection of individual wavelength kinetics with dual Linear/Log views.
• Residual Mapping: Automated generation of 2D error maps to evaluate fit quality across the entire dataset.

Export & Integration

• Publication-Ready: Export high-resolution plots (300 DPI) in PNG/PDF formats.
• Open Data Formats: Save results as .txt (compatible with Origin, Excel, or Python) and binary .npy files for fast reloading.

---

See also: Supported Data Formats →

Screenshots

MAIN MENU

GUI FLUPS

GUI TAS

GUI Global Fit

SVD Analysis

Species Associated Spectra

Kinetics Fit