Time-Resolved Fluorescence Wiki

start - [Data Acquisition and Analysis Software]

admin (admin@undisclosed.example.com) — 2026-03-23T07:40:50+00:00

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	===== Data Acquisition and Analysis Software=====		===== Data Acquisition and Analysis Software=====

-	[[Software#Commercial \| PicoQuant SymPhoTime Software (SPT32/SPT64)]]	+	[[https://helpdesk.picoquant.com/help/en-us/30-faq/65-open-source-software-for-picoquant-data-analysis-and-acquisition\|Open-Source Software for PicoQuant Data Analysis and Acquisition]]
-		+
-	[[Software#Commercial \| Phasor Analysis]]	+
-		+
-	[[Software#Open Source Software]]	+
	===== Fluorophores and Samples =====		===== Fluorophores and Samples =====

software

admin (admin@undisclosed.example.com) — 2026-03-23T07:38:40+00:00

2025/05/28 07:18		current
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	{{tag> software acquisition analysis}}		{{tag> software acquisition analysis}}

-	~~TOC~~

	====== Software ======		====== Software ======
-		+	[[https://helpdesk.picoquant.com/help/en-us/30-faq/65-open-source-software-for-picoquant-data-analysis-and-acquisition\|Open-source software for PicoQuant data analysis and acquisition]]
-	===== Commercial =====	+
-	==== Microscopy ====	+
-		+
-		+
-	[[software:SymPhoTime64]] \\	+
-	A complete software suite for acquisition and analysis of time resolved fluorescence data. SymPhoTime features a powerful scripting language that allows customisation of existing analysis and even implementation of novel analysis techniques.	+
-		+
-		+
-	[[howto:Phasor Analysis]]	+
-	Phasor Analysis is currently included in [[products:NovaFLIM]]. It is not included in [[products:SymPhoTime]] However, you can use [[http://www.lfd.uci.edu/globals/\|Globals]] developed by the [[http://www.lfd.uci.edu\|Laboratory for Fluorescence Dynamics]] to analyse FLIM data via the Phasor approach. Another option would be [[https://www.phasorpy.org]].	+
-		+
-	==== Spectroscopy ====	+
-		+
-		+
-	[[software:EasyTau]] \\	+
-	EasyTau is the systems software of PicoQuants time resolved spectrometer [[products:FluoTime 300]].	+
-	EasyTau features a scripting language to automate more complex experiments. Examples of EasyTau scripts can be found on github: https://github.com/PicoQuant/EasyTau-Scripts	+
-		+
-	[[software:FluoFit]] \\	+
-	Decay curve analysis software	+
-	===== Open Source =====	+
-		+
-	Please note that these are external projects for which PicoQuant takes no responsibility and provides no support. In case of problems please contact the respective authors. Also note that such projects may not be	+
-	maintained continuously. In particular, please check if they use current versions of file formats and/or programming libraries before you invest in larger development work based on such projects.	+
-		+
-	If you develop improved or new code, please consider contributing your code back to the community.	+
-		+
-	The compilation below is probably not complete. If you are the maintainer of a software that deals with TCSPC data please edit this page and add your software listing. Alternatively you can also use [[https://support.picoquant.com]] to contact PicoQuant support to submit your software project.	+
-		+
-		+
-	==== Data Analysis ====	+
-		+
-		+
-		+
-		+
-	* snAPI is a powerful Python wrapper which enables seamless communication and configuration with PicoQuant Time Correlated Single Photon Counting Instruments (TCSPC devices). It harnesses the advantages of C++ for optimal speed and performance and bridges the gap between the high-speed capabilities of your PicoQuant TCSPC device and the ease of use and versatility of Python. [[https://github.com/PicoQuant/snAPI]]	+
-	* PhasorPy is an open-source Python library for the analysis of fluorescence lifetime and hyperspectral images using the phasor approach. [[https://www.phasorpy.org]]	+
-	* FLUTE is a Python GUI for interactive phasor analysis of Fluorescence Lifetime Microscopy (FLIM) data [[https://github.com/LaboratoryOpticsBiosciences/FLUTE]].	+
-	* FLIMPA is an open-source software designed for the phasor plot analysis of raw Time-Correlated Single Photon Counting (TCSPC) Fluorescence Lifetime Imaging Microscopy (FLIM) data. Developed in Python, it offers an intuitive graphical user interface (GUI) for the analysis and visualisation of FLIM data. [[https://github.com/SofiaKapsiani/FLIMPA]]	+
-	* PAM is a software package for quantitative analysis of fluorescence microscopy and spectroscopy data, with a focus on experiments using pulsed interleaved excitation.[[http://pam.readthedocs.io\|]]	+
-	* [[https://www.mpc.hhu.de/software/3-software-package-for-mfd-fcs-and-mfis\|Software Package for Multiparameter Fluorescence Spectroscopy and Imaging by research group Seidel, HHU]]: A collection of independent sotftware packages which enable the user to perfrom the analysis workflow put forward by the group.Please note that a trial version is available.	+
-	* [[https://github.com/OpenSMFS\|Open Tools for Solution-Based Single-Molecule Fluorescence Spectroscopy]]	+
-	* FRETBursts: software for burst analysis of freely-diffusing single-molecule FRET (smFRET) measurements including μs-ALEX. [[http://tritemio.github.io/FRETBursts/\|FRETBursts Homepage]] and [[http://dx.doi.org/10.1101/039198\|paper]].	+
-	* PyBroMo [[https://github.com/tritemio/PyBroMo\|simulator for single molecule FRET experiments of freely diffusing particles.]]	+
-	* [[https://www.researchgate.net/project/Open-Computational-Tools-for-Single-Molecule-Spectroscopy\|Researchgate group Open Computational Tools for Single-Molecule Spectroscopy]]	+
-		+
-	* [[software:PyCorrFit]] is a general-purpose FCS evaluation software that, amongst other formats, supports the established Zeiss ConfoCor3 ~.fcs file format. PyCorrFit comes with several built-in model functions, covering a wide range of applications in standard confocal FCS. In addition, it contains equations dealing with different excitation geometries like total internal reflection (TIR).	+
-		+
-	*[[https://github.com/khemmen/katcorr/\|Katherinas correlator]] is a collection of scripts and correlators that are inspired by the paper Ries...Schwille 2010 Optics Express "Automated suppression of sample-related artifacts in FCS".	+
-	These scripts have different scopes and use the library [[https://github.com/Fluorescence-Tools/tttrlib\|tttrlib]] to read and correlate time-tagged time resolved (TTTR) files.	+
-		+
-	* [[http://flim-analyzer.ip-korea.org/\|FLIM-FRET analyzer]]: open source software for automation of lifetime-based FRET analysis. This is a Microsoft Windows application originally developed in C#. The main goal of this application is to provide the FLIM community a user-friendly application.	+
-		+
-	/* * [[https://www.tu-ilmenau.de/bmti/forschung/ophthalmologische-technik/flimx/\|FLIMX]]:A Software Package to / /Determine and Analyze the Fluorescence Lifetime in Time-Resolved Fluorescence Data from the Human Eye*/	+
-		+
-	* [[http://www.fluortools.com/software\|Fluortools]].Fluorescence Decay and Anisotropy Analysis.	+
-		+
-		+
-	* [[http://pycorrelate.readthedocs.io/en/latest/ \| PyCorrelate]]:Pycorrelate computes fast and accurate cross-correlation over arbitrary time lags. Cross-correlations can be calculated on “uniformly-sampled” signals or on “point-processes”, such as photon timestamps. Pycorrelate allows computing cross-correlation at log-spaced lags covering several orders of magnitude. This type of cross-correlation is commonly used in physics or biophysics for techniques such as fluorescence correlation spectroscopy (FCS) or dynamic light scattering (DLS).	+
-		+
-	* [[http://www.dkfz.de/Macromol/quickfit\|QuickFit 3.0]]: QuickFit 3 is our open-source data evaluation software for FCS and imagingFCS (imFCS) measurement. Actually QuickFit 3 itself is a project manager and all functionality is added as plugins. A set of tested plugins is supplied together with the software.	+
-		+
-		+
-	*/ * [[software:FCS viewer]] ..This became redundant as its developer released Pycorrfit/*	+
-		+
-	* [[https://github.com/dwaithe/FCS_point_correlator\| FCS Point Correlator]] FCS Bulk Correlation Software accepting pt3 and ptu files. for fitting see https://dwaithe.github.io/FCSfitJS/	+
-	[[https://dwaithe.github.io/FCSfitJS/\| FCS fit JS]]	+
-		+
-	* [[software:FLIMFit]]. FLIMfit is an open source package for rapid analysis of large FLIM datasets.	+
-		+
-	* [[https://github.com/zhengkaiyu/FIMAS]] Fluorescent Imaging Analysis Software	+
-		+
-	* [[https://timetag.github.io\|Extensible Time-tag Analyzer]]. 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.[[https://eta.readthedocs.io/en/latest/intro.html\|More info.]]	+
-		+
-	* [[https://pals3d.readthedocs.io/en/latest/\|Pals3D]] is a graphical application to support the use of a Time-Correlated Single Photon Counting system for application to Positron Annihilation Lifetime Spectroscopy. [[https://github.com/avancra/Pals3D]].	+
-		+
-	* [[https://github.com/SarthakJariwala/Python_GUI_apps]] Graphical User Interface (GUI) Python apps written in python using qt and pyqtgrpah for quick analysis of scientific data. It also includes the ability to convert data to H5 if needed.	+
-		+
-	* [[https://lifefit.readthedocs.io/en/latest/]] LifeFit is a Python package to analyze time-correlated single-photon counting (TCSPC) data sets, namely fluorescence lifetime and time-resolve anisotropy decays.	+
-	* [[https://github.com/ryoheiyasuda/FLIMage_public]] FLIMage allows for controlling TCSPC hardware and generate fluorescence lifetime images in real time. The main part of the source code is free for academic and educational uses. It is used and tested in the Yasuda lab (Max Planck Florida Institute for Neuroscience) on Windows 10 and NationalInstruments DAQmx 18.6. The software is updated frequently.	+
-		+
-	=== Libraries/scripts/readers ===	+
-	* [[https://github.com/PicoQuant/PicoQuant-Time-Tagged-File-Format-Demos\| Demo Code for reading PicoQuants PTU File format]]	+
-		+
-	* [[https://github.com/Brinkslab/ptu_flim_tools/]] Tools for reading, converting and analysing ptu flim data.	+
-		+
-	* [[https://github.com/ChrisHal/PTU2BIN]] Tool to convert PicoQuant PTU filesto BIN files or IgorPro binary wave files (IBW)	+
-		+
-	* [[https://de.mathworks.com/matlabcentral/fileexchange/61789-ptu-to-matlab-converter?focused=7307670&tab=function\|Reading PicoQuants PTU File formats to MatLab - 100x faster than the Demo Code]]	+
-	* libpicoquant: Tools for reading PicoQuant file formats: [[https://github.com/tsbischof/libpicoquant]]	+
-		+
-		+
-	* Open Microscopy's BioFormat supports PicoQuant bin files ([[glossary:pre-histogrammed_image\|pre-histogrammed Image Data File]]) [[https://www.openmicroscopy.org/site/support/bio-formats5/formats/picoquant-bin.html]]	+
-		+
-	* ImageJ data readers-	+
-	* Import Filter for pt3 files: [[http://imagejdocu.tudor.lu/doku.php?id=plugin:inputoutput:picoquant_.pt3_image_reader:start]]	+
-	* Import of ptu/pt3 image files (+intensity/average lifetime stacks): [[https://github.com/ekatrukha/PTU_Reader]]	+
-		+
-		+
-	* [[https://github.com/QuantumPhotonicsLab/readPTU]] readPTU: a Python Library to Analyse Time Tagged Time Resolved Data [[http://qpl.eps.hw.ac.uk/]], [[https://arxiv.org/pdf/1903.07112.pdf]]	+
-		+
-		+
-		+
-	* [[https://github.com/trevhull/ptuT3toT2\|ptuT3toT2 - a program that converts ptu files from picoquant from T3 mode to T2 mode]]	+
-		+
-	* Photon-Tools Python utilities for working with photon timestamp data from fluorescence spectroscopy experiments [[https://github.com/bgamari/photon-tools]]	+
-		+
-	* Photon Correlation A suite of command-line tools for performing calculations on photon arrival data, as produced by hardware such as the PicoQuant PicoHarp and HydraHarp: [[https://github.com/tsbischof/photon_correlation]]	+
-		+
-		+
-		+
-		+
-		+
-	* dspFRET: Matlab code for analyzing TTTR data from PicoQuant. Typical application is analysis of single pair FRET measurements with pulsed interleaved excitation (PIE-FRET). \\ https://github.com/RobinsonLab/dspFRET	+
-		+
-		+
-	* [[https://github.com/hammer-wang/exciton_diffusion\|exciton diffusion (Matlab)]]	+
-		+
-	*/ * [[https://github.com/PicoQuant/Notebooks]] Jupyter Notebooks reading the tiff files exported by SymPhoTime /*	+
-		+
-		+
-		+
-		+
-		+
-		+
-		+
-	* FoCuS-point: FoCuS-point utilises advanced time-correlated single-photon counting (TCSPC) correlation algorithms along with time-gated filtering and innovative data visualisation. [[https://github.com/dwaithe/FCS_point_correlator \| FoCuS Homepage]] and [[http://dx.doi.org/10.1093/bioinformatics/btv687 \| paper ]]	+
-		+
-	* [[https://github.com/skyjur/picoharp300-curvefit-ui\|TCSPC curve fitting for phd files (Python)]]	+
-		+
-	* [[ https://github.com/SumeetRohilla/readPTU_FLIM \| readPTU_FLIM]] Library for reading PTU files (works for MultiHarp, HydraHarp, PicoHarp, TimeHarp acquisition) as well as converting raw TTTR data to FLIM image data stack.	+
-		+
-	* [[https://github.com/RobertMolenaar-UT/PicoQuant-multi_channel_screen]] The main purpose of the MultiChannel script is one can proccess multiple PTU files or a folder with PTU files and get a series Fluorescent multicolor images with minimal user input. Usefull for screening results during imaging and to be used in presentations.	+
-	* [[https://github.com/RobertMolenaar-UT/Lifetime_fit]] With this script you can fit TCSPC lifetime histograms to single, double or triple order exponential fit with reconvolution method Minimalization method are NLLS / MLE-Nelder-Mead minimalisation methods.	+
-		+
-	* [[https://github.com/Fluorescence-Tools/tttrlib\| tttrlib]] tttrlib is a low level, high performance API to read and process time-tagged-time resolved (TTTR) data	+
-		+
-	* [[https://github.com/GCBallesteros/trattoria\| Trattoria]] Trattoria delivers you the fastest streaming algorithms to analyze your TTTR data	+
-		+
-	* [[https://picoquantio.readthedocs.io/en/latest/\| picoquantio]] is a Python library for reading file formats generated by PicoQuant hardware.	+
-	* [[https://github.com/cgohlke/ptufile]] Ptufile is a Python library to read image and metadata from PicoQuant PTU and related files: PHU, PCK, PCO, PFS, PUS, and PQRES. PTU files contain time correlated single photon counting (TCSPC) measurement data and instrumentation parameters.	+
-		+
-		+
-	==== Data Acquisition ====	+
-	* snAPI is a powerful Python wrapper which enables seamless communication and configuration with PicoQuant Time Correlated Single Photon Counting Instruments (TCSPC devices). It harnesses the advantages of C++ for optimal speed and performance and bridges the gap between the high-speed capabilities of your PicoQuant TCSPC device and the ease of use and versatility of Python. [[https://github.com/PicoQuant/snAPI]]	+
-		+
-	* qudi: A modular laboratory experiment management suite which supports PicoHarp300. [[https://github.com/Ulm-IQO/qudi]]	+
-	* pyPL: wxpython integration of software and hardware for micro-photoluminescence measurements: WinSpec, PicoHarp, and Thorlabs/APT piezos and stepper motors. \\ https://github.com/kaseyrussell/pyPL	+
-	* PicoHarp Multiscan with Prior Stage: [[https://bitbucket.org/ywsong2/uky_ptu_convert]]	+
-	* Python interface to communicate with TimeHarp 260: [[https://github.com/impact27/th260]]	+
-	* LabView based Fluorescence lifetime activated droplet sorting software[[https://github.com/SadatHasan/EasyFlux]]	+
-	* [[https://github.com/scopefoundry/]] A Python platform for controlling custom laboratory experiments and visualizing scientific data	+
-		+
-		+
-	* [[https://github.com/CEMES-CNRS/pymodaq_plugins_picoquant]] [[http://pymodaq.cnrs.fr/en/latest/index.html\|PyMoDAQ]] plugin for Picoquant instruments (TimeHarp260, ...)	+
-		+
-		+
-		+
-	=== Demos about Controlling PicoQuant Devices ===	+
-	== Sepia II and Solea ==	+
-	* [[https://github.com/PicoQuant/SepiaWrapper \| SepiaWrapper ]] is an experimental Python Wrapper to control PicoQuants Sepia PDL828	+
-	* [[https://github.com/PicoQuant/PQLaserDrv]]	+
-	* [[https://github.com/crisbour/pq-laser-triad \| PicoQuant Sepia2 API Bundle]]	+
-		+
-	== TimeHarp 260 ==	+
-	* https://github.com/PicoQuant/TH260-Demos	+
-		+
-	== PicoHarp 300 ==	+
-	* [[https://github.com/ScopeFoundry/HW_picoharp\|PicoHarp 300 TCSPC system hardware plug-in for ScopeFoundry (Python)]]	+
-	* [[https://github.com/srgblnch/PicoHarp300\|Python binding, Tango device server and Taurus gui to access the PicoHarp300 photon counter]]	+
-	* https://github.com/PicoQuant/PH300-v2.x-Demos	+
-	* https://github.com/PicoQuant/PH300-v3.x-Demos	+
-		+
-		+
-	== HydraHarp 400 ==	+
-	* [[https://github.com/ColinBrosseau/Hydraharp400 \| Control HydraHarp400 (python)]]	+
-	* https://github.com/PicoQuant/HH400-v1.x-Demos	+
-	* https://github.com/PicoQuant/HH400-v3.x-Demos	+
-		+
-	== MultiHarp 150 ==	+
-	* [[https://github.com/PicoQuant/MH150-Demos]]	+
-		+
-	=== Other ===	+
-		+
-	* PicoHarp Library in Python \\ https://github.com/srgblnch/PicoHarp300	+
-		+
-		+
-		+
-	GitHub repositories mentioning PicoQuant and supporting the PicoQuant t3r data file format: [[https://github.com/search?&q=picoquant+OR+picoharp+OR+hydraharp+OR+TimeHarp]]	+

start - [NovaFLIM / Analysis]

oschulz (oschulz@undisclosed.example.com) — 2026-02-11T14:19:03+00:00

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	{{topic>howto -FT300 -sample -analysis -draft &nodate&nouser}}		{{topic>howto -FT300 -sample -analysis -draft &nodate&nouser}}

-	===== NovaFLIM / Analysis =====

-	{{topic>howto +tutorial +novaflim}}
	===== SymPhoTime64 / Analysis =====		===== SymPhoTime64 / Analysis =====

start - removed

oschulz (oschulz@undisclosed.example.com) — 2026-02-11T14:18:23+00:00

2026/02/11 14:17		current
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-	{{tag> howto tutorial NovaFLIM}}
-

tutotial1 - removed

oschulz (oschulz@undisclosed.example.com) — 2026-02-11T14:18:00+00:00

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-	m a Batch Analysis Over Many Frames]( {{ :howto:novaflim:02_how_to_perform_a_batch_analysis_over_many_frames.pdf \| }}). {{ :howto:novaflim:02_how_to_perform_a_batch_analysis_over_many_frames.pdf \|}}	+

burst_duration_and_fcs_diffusion_time - [References]

doerr (doerr@undisclosed.example.com) — 2026-01-12T14:58:02+00:00

2026/01/12 10:06		current
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	~~NOTOC~~		~~NOTOC~~

-	====== Burst Duration and FCS Diffusion Time ======	+	====== Burst duration and FCS diffusion time ======
		+	Diffusion, flow, burst selection, and photobleaching in confocal single-molecule fluorescence

-	===== Overview =====	+	===== 1. Introduction =====

-	In single-molecule fluorescence experiments, two closely related time scales are commonly discussed:	+	In confocal single-molecule fluorescence experiments, molecular transport through the detection volume is commonly characterized using two different observables: the diffusion time extracted from fluorescence correlation spectroscopy (FCS) and the burst duration obtained from single-molecule detection (SMD) or burst analysis. Both quantities probe molecular motion through the same optical volume, yet they originate from fundamentally different experimental procedures and statistical definitions.

-	* the burst duration obtained from single-molecule burst analysis	+	The apparent similarity of their numerical values often suggests a direct equivalence. However, this impression can be misleading, because each observable responds differently to transport mechanisms, detection geometry, selection criteria, and photophysical processes. As a consequence, diffusion time and burst duration must be treated as distinct quantities whose relationship depends on the underlying physical assumptions and on how the experiment is performed.
-	* the diffusion time extracted from fluorescence correlation spectroscopy (FCS)	+

-	Although both quantities probe molecular transport through the same confocal detection volume and often have comparable numerical values, they differ fundamentally in their physical meaning, statistical definition, and sensitivity to experimental parameters.	+	In this article, we develop a unified theoretical framework to analyze the diffusion time and burst duration within a three-dimensional Gaussian detection model. We first derive both quantities independently using their full mathematical formalism. We then compare the two observables and establish their relationship under ideal diffusion conditions. Finally, we investigate how burst-selection procedures, directed flow, and photobleaching modify each observable and how these effects alter their mutual relation.

-	This article summarizes their relationship within the framework of a three-dimensional Gaussian detection model, explains the origin of the frequently cited relation between the two time scales, and discusses the influence of burst-selection thresholds and directed flow.	+	===== 2. Three-dimensional Gaussian detection model =====
-		+
-	===== Three-dimensional Gaussian detection model =====	+

	Both FCS and burst-based single-molecule experiments rely on a confocal detection volume that is well approximated by a three-dimensional Gaussian molecular detection function (MDF):		Both FCS and burst-based single-molecule experiments rely on a confocal detection volume that is well approximated by a three-dimensional Gaussian molecular detection function (MDF):

	$$		$$
-	\mathrm{MDF}(x,y,z) \propto	+	W(\mathbf r)
-	\exp\left(-2\frac{x^2+y^2}{w_0^2}\right)	+	=
-	\exp\left(-2\frac{z^2}{z_0^2}\right)	+
		+	\exp\left(
		+	-\frac{2(x^2+y^2)}{w_0^2}
		+	-\frac{2z^2}{z_0^2}
		+	\right)
	$$		$$

-	Here, $w_0$ and $z_0$ denote the lateral and axial $1/e^2$ radii of the detection volume.	+	where $w_0$ and $z_0$ denote the lateral and axial $1/e^2$ radii of the detection volume.

-	This model forms the basis of classical FCS theory and has been validated extensively in both theoretical and experimental studies.	+	This Gaussian MDF constitutes the standard model underlying classical FCS theory and most analytical treatments of single-molecule residence times. It provides a consistent geometric framework for comparing correlation-based and trajectory-based observables.

-	===== Diffusion and transit-time distributions =====	+	===== 3. Diffusive transport and transit-time distributions =====

-	For freely diffusing molecules, transport is governed by the three-dimensional diffusion propagator:	+	For freely diffusing molecules, transport is governed by the three-dimensional diffusion propagator

	$$		$$
-	P(\mathbf{r},t) = (4\pi D t)^{-3/2}	+	G(\mathbf r,t \mid \mathbf r_0,0)
-	\exp\left(-\frac{\|\mathbf{r}\|^2}{4Dt}\right)	+	=
		+	\frac{1}{(4\pi Dt)^{3/2}}
		+	\exp\left(
		+	-\frac{\|\mathbf r-\mathbf r_0\|^2}{4Dt}
		+	\right)
	$$		$$

-	A crucial point is that the transit time through the confocal volume is not a single well-defined quantity, but a random variable with a broad distribution.	+	where $D$ is the diffusion coefficient.

-	This distribution depends on the diffusion coefficient $D$, the molecular entry position, and the spatial weighting imposed by the MDF.	+	A crucial point is that the time a molecule spends in the detection volume is not a single well-defined quantity but a stochastic variable with a broad distribution. This distribution depends on the diffusion coefficient, the entry position of the molecule, and the spatial weighting imposed by the MDF. Any experimentally extracted time scale therefore corresponds to a specific statistical functional of this distribution rather than to a unique physical residence time.

-	===== FCS diffusion time $t_D$ =====	+	===== 4. FCS diffusion time $t_D$ =====

-	==== Definition ====	+	==== 4.1 Definition ====

-	In FCS, the fluorescence intensity autocorrelation function for pure diffusion can be written as:	+	In FCS, the normalized fluorescence intensity autocorrelation function is defined as

	$$		$$
-	G(\tau) =	+	G(\tau)
		+	=
		+
		+	\frac{\langle \delta I(t)\,\delta I(t+\tau)\rangle}{\langle I\rangle^2}
		+	$$
		+
		+	For pure diffusion, this can be expressed as
		+
		+	$$
		+	G(\tau)
		+	\propto
		+	\int d^3r \int d^3r_0\,
		+	W(\mathbf r)\,W(\mathbf r_0)\,
		+	G(\mathbf r,\tau \mid \mathbf r_0,0)
		+	$$
		+
		+	For a three-dimensional Gaussian MDF, this integral yields
		+
		+	$$
		+	G(\tau)
		+	=
	\frac{1}{N}		\frac{1}{N}
-	\frac{1}{(1+\tau/t_D)\sqrt{1+\tau/(S^2 t_D)}}	+	\frac{1}{(1+\tau/t_D)\sqrt{1+\tau/(\kappa^2 t_D)}}
	$$		$$

-	where $S = z_0 / w_0$.	+	with

-	==== Physical meaning ====	+	$$
		+	t_D = \frac{w_0^2}{4D},\qquad
		+	\kappa = \frac{z_0}{w_0}
		+	$$

-	The diffusion time $t_D$ is not the mean residence time of an individual molecule.	+	==== 4.2 Physical interpretation ====

-	Instead, it is a correlation-derived time scale determined by the spatial extent of the detection function. Formally, it can be related to the second spatial moment of the MDF.	+	The diffusion time $t_D$ is not the mean residence time of an individual molecule. Instead, it is a correlation-derived geometry time scale governed by the quadratic spatial weighting of the MDF in the autocorrelation function.

-	Thus, $t_D$ reflects ensemble-averaged transport properties rather than individual molecular trajectories.	+	Formally,

-	===== Burst duration $t_B$ =====	+	$$
		+	t_D
		+	\approx
		+	\frac{\langle r^2\rangle_{W^2}}{6D},\qquad
		+	\langle r^2\rangle_{W^2}
		+	=

-	==== Definition ====	+	\frac{\int r^2 W(\mathbf r)^2\,d^3r}
		+	{\int W(\mathbf r)^2\,d^3r}
		+	$$

-	In burst analysis, individual molecular events are identified by applying an intensity threshold.	+	For a Gaussian MDF, the lateral contribution evaluates to

-	A burst is defined as the time interval during which the detected signal remains above this threshold.	+	$$
		+	\langle r^2\rangle_{W^2} = \frac{3}{4}w_0^2
		+	$$

-	As a consequence, bursts begin and end on iso-intensity surfaces of the MDF rather than at the geometric boundary of the confocal detection volume.	+	which directly leads to the expression $t_D = w_0^2/(4D)$.

-	For a Gaussian detection function, this surface is an ellipsoid whose effective radius depends on the chosen threshold.	+	===== 5. Burst duration $t_B$ =====

-	==== Statistical meaning ====	+	==== 5.1 Definition ====

-	The mean burst duration is defined as:	+	In burst analysis, individual molecular events are identified by applying an intensity threshold $W_{th}$. A burst is defined as

	$$		$$
-	\langle t_B \rangle = \int_0^\infty t\,p_B(t)\,dt	+	t_B = t_{exit} - t_{entry},\qquad
		+	W[\mathbf r(t)] > W_{th}
	$$		$$

-	Because short, peripheral trajectories often remain below threshold, the burst-time distribution differs from the full transit-time distribution.	+	Bursts therefore begin and end on iso-intensity surfaces of the MDF rather than at a geometric boundary of the confocal volume.

-	Burst analysis therefore yields a threshold-selected first moment of molecular residence times.	+	For a Gaussian detection function, the effective threshold radius scales as

-	===== Relation between diffusion time and burst duration =====	+	$$
		+	r_{th}
		+	\propto
		+	w_0\sqrt{\ln(1/W_{th})}
		+	$$

-	For a three-dimensional Gaussian detection volume, pure diffusion, and moderate threshold conditions, analytical treatments show:	+	==== 5.2 Statistical interpretation ====
		+
		+	The mean burst duration is

	$$		$$
-	\langle t_B \rangle \approx \frac{4}{3}\,t_D	+	\langle t_B\rangle
		+	=
		+
		+	\int_0^\infty t\,p_{burst}(t)\,dt
	$$		$$

-	===== Origin of the factor 4/3 =====	+	where $p_{burst}(t)$ denotes the threshold-conditioned residence-time distribution.
		+
		+	Burst analysis measures a first moment of residence times with linear spatial weighting, modified by explicit event selection. Short, peripheral trajectories often do not exceed the detection threshold and therefore do not contribute to the measured distribution.

-	The appearance of this constant factor reflects the fundamentally different nature of the two observables:	+	==== 5.3 Burst selection procedure ====

-	* the FCS diffusion time is obtained from an autocorrelation function and therefore involves a quadratic weighting of the MDF	+	In practice, burst detection is a multi-step selection process.
-	* the mean burst duration corresponds to a linearly weighted residence time conditioned on being above a detection threshold	+

-	For a Gaussian detection profile, this mismatch in statistical weighting leads, under ideal conditions, to the universal ratio:	+	Intensity thresholding.
		+	Photon arrival times are binned into short intervals $\Delta t$ or processed using a sliding window. A burst is initiated when the photon count rate exceeds a predefined threshold

	$$		$$
-	\frac{\langle t_B \rangle}{t_D} = \frac{4}{3}	+	R(t)=\frac{N_\gamma(t,\Delta t)}{\Delta t}>R_{th}
	$$		$$

-	This interpretation is consistent with theoretical treatments of single-molecule photon trajectories and residence-time statistics and with early analyses of diffusion in confocal volumes.	+	which is equivalent, up to proportionality factors, to $W[\mathbf r(t)]>W_{th}$.

-	===== Influence of burst-selection thresholds =====	+	Temporal continuity and photon-number criteria.
		+	To suppress spurious threshold crossings due to shot noise, bursts are often required to satisfy

-	In experimental practice, the ratio $\langle t_B \rangle / t_D$ is not universal.	+	$$
		+	t_B \ge t_{min},\qquad
		+	N_\gamma \ge N_{\gamma,min}
		+	$$

-	Increasing the burst-selection threshold preferentially selects long, central trajectories, thereby increasing the mean burst duration relative to the FCS diffusion time.	+	Selection functional.
		+	The burst-selection procedure can be written formally as

-	Conversely, photophysical effects such as blinking or inappropriate binning can shorten apparent burst durations without significantly affecting the FCS diffusion time, provided these effects are properly modeled in the correlation analysis.	+	$$
		+	\mathcal S[\mathbf r(t)]
		+	=
		+	\Theta(W[\mathbf r(t)]-W_{th})\,
		+	\Theta(t_B-t_{min})\,
		+	\Theta(N_\gamma-N_{\gamma,min})
		+	$$

-	===== Flow effects: decoupling of burst duration and FCS diffusion time =====	+	leading to an observed distribution

-	==== Physical background ====	+	$$
		+	p_{burst}(t)
		+	\propto
		+	\left\langle
		+	\delta(t-t_B)\,
		+	\mathcal S[\mathbf r(t)]
		+	\right\rangle
		+	$$

-	In the presence of flow, molecular transport through the confocal detection volume is no longer governed by diffusion alone.	+	==== 5.4 Consequences of burst selection ====

-	Directed motion introduces an additional transport mechanism that modifies single-molecule trajectories.	+	Burst selection introduces intrinsic and controllable biases. The mean burst duration depends explicitly on the chosen thresholds, increasing thresholds bias toward central trajectories and increase $\langle t_B\rangle$, and bursts are defined by iso-intensity surfaces rather than geometric boundaries. Burst statistics are also sensitive to photophysical processes such as blinking and photobleaching.

-	==== Effect on burst duration ====	+	===== 6. Comparison of diffusion time and burst duration =====

-	Burst analysis directly reflects single-molecule residence times.	+	Although both observables probe molecular motion through the same confocal detection volume, their statistical definitions differ fundamentally. The FCS diffusion time $t_D$ is determined by quadratic spatial weighting of the MDF and reflects the decay of concentration correlations. In contrast, the mean burst duration $\langle t_B\rangle$ is governed by linear spatial weighting combined with explicit selection rules.

-	Directed flow shortens these residence times by accelerating molecular passage through the detection volume.	+	Because of burst-selection thresholds, $\langle t_B\rangle$ can be smaller than, comparable to, or larger than $t_D$. There is no universal ordering between the two quantities, whereas $t_D$ is largely insensitive to burst-selection parameters.

-	Consequently, burst duration distributions shift toward shorter times even when the diffusion coefficient and optical geometry remain unchanged.	+	===== 7. Mathematical comparison and conditions for a fixed ratio =====

-	==== Effect on FCS diffusion time ====	+	Under the assumptions of pure diffusion, Gaussian detection geometry, moderate burst-selection thresholds, and negligible photophysical interruptions, a closed analytical relation can be derived.

-	In contrast, the FCS diffusion time remains essentially constant under moderate flow, as it is primarily determined by the optical geometry and diffusion coefficient.	+	For a Gaussian MDF,

-	==== Relation to the 4/3 factor under flow ====	+	$$
		+	\langle r^2\rangle_{W^2} = \frac{3}{4}w_0^2,\qquad
		+	\langle r^2\rangle_W = w_0^2
		+	$$

-	The relation above is derived under the assumption of pure diffusion.	+	Using $\langle r^2\rangle \approx 6Dt$,

-	The presence of flow violates these assumptions by introducing directed transport.	+	$$
		+	t_D = \frac{w_0^2}{4D},\qquad
		+	\langle t_B\rangle = \frac{w_0^2}{3D}
		+	$$

-	Deviations from the 4/3 ratio under flow conditions therefore reflect the fundamentally different sensitivity of burst-based and correlation-based observables rather than a breakdown of the Gaussian detection model.	+	Thus,

-	===== Summary =====	+	$$
		+	\frac{\langle t_B\rangle}{t_D} = \frac{4}{3}
		+	$$

-	Although burst duration and FCS diffusion time often appear numerically similar, they represent fundamentally different quantities.	+	This ratio represents a diffusion-limited reference case and is not universal.

-	The diffusion time is a correlation-derived, geometry-dependent time scale linked to the second spatial moment of the detection function, whereas the mean burst duration is a threshold-selected first moment of individual molecular residence times.	+	===== 8. Flow: advection--diffusion effects =====

-	Under ideal diffusion conditions, this distinction naturally leads to:	+	==== 8.1 Transport equation and time scales ====

	$$		$$
-	\langle t_B \rangle \approx \frac{4}{3}\,t_D	+	\frac{\partial c}{\partial t}
		+	+
		+	\mathbf v\cdot\nabla c
		+	=
		+
		+	D\nabla^2 c,\qquad
		+	\tau_v=\frac{w_0}{v},\qquad
		+	\mathrm{Pe}=\frac{vw_0}{D}
	$$		$$

-	Threshold selection and directed flow introduce systematic deviations from this relation, further emphasizing the conceptual difference between burst-based and correlation-based observables.	+	==== 8.2 Effect of flow on FCS ====
		+
		+	With advection--diffusion propagator
		+
		+	$$
		+	G(\mathbf r,\tau\mid\mathbf r_0,0)
		+	=
		+
		+	\frac{1}{(4\pi D\tau)^{3/2}}
		+	\exp\left(
		+	-\frac{\|\mathbf r-\mathbf r_0-\mathbf v\tau\|^2}{4D\tau}
		+	\right)
		+	$$
		+
		+	The autocorrelation function factorizes as
		+
		+	$$
		+	G(\tau)
		+	=
		+
		+	G_{diff}(\tau)
		+	\exp\left(
		+	-\frac{(v\tau)^2}{w_0^2(1+\tau/t_D)}
		+	\right)
		+	$$
		+
		+	When flow is modeled explicitly, $t_D$ remains unchanged.
		+
		+	==== 8.3 Effect of flow on burst duration ====
		+
		+	Burst durations scale approximately as
		+
		+	$$
		+	\langle t_B\rangle \sim \frac{L_{eff}}{v}
		+	\qquad (\mathrm{Pe}\gg1)
		+	$$
		+
		+	and therefore decrease continuously with increasing flow velocity.
		+
		+	==== 8.4 Consequences ====
		+
		+	Flow selectively affects burst durations while leaving the FCS diffusion time invariant when modeled correctly.
		+
		+	===== 9. Photobleaching effects =====
		+
		+	==== 9.1 General model ====
		+
		+	$$
		+	P_{survival}(t)=e^{-k_{bl}t},\qquad
		+	\tau_{bl}=\frac{1}{k_{bl}}
		+	$$
		+
		+	==== 9.2 Effect on FCS ====
		+
		+	$$
		+	G(\tau)=G_{diff}(\tau)e^{-\tau/\tau_{bl}},\qquad
		+	\tau_{bl}\gg t_D
		+	$$
		+
		+	Bleaching primarily affects amplitude and long-delay behavior.
		+
		+	==== 9.3 Effect on burst duration ====
		+
		+	$$
		+	t_{B,obs}=\min(t_{transport},t_{bleach}),\qquad
		+	p_{obs}(t)=p_{trans}(t)e^{-k_{bl}t}
		+	$$
		+
		+	Burst durations are systematically shortened.
		+
		+	===== 10. Conclusion =====
		+
		+	The diffusion time extracted from fluorescence correlation spectroscopy and the burst duration obtained from single-molecule detection probe molecular transport through the same confocal detection volume, yet they represent fundamentally different observables.
		+
		+	The FCS diffusion time $t_D$ is a correlation-derived geometry time scale governed by quadratic spatial weighting of the molecular detection function, whereas the mean burst duration $\langle t_B\rangle$ is a residence-time observable governed by linear weighting and explicit burst-selection criteria.
		+
		+	Because of these differences, there is no general reason for $t_D$ and $\langle t_B\rangle$ to coincide. Depending on burst-selection thresholds, the mean burst duration can be smaller than, comparable to, or larger than the diffusion time.
		+
		+	Under ideal diffusion conditions--Gaussian detection geometry, moderate thresholding, and negligible photophysical interruptions--a fixed relation can be derived,
		+
		+	$$
		+	\frac{\langle t_B\rangle}{t_D}=\frac{4}{3}
		+	$$
		+
		+	This factor is a geometric consequence of Gaussian detection combined with diffusion statistics and specific selection conditions. It is not universal.
		+
		+	Directed flow and photobleaching systematically break this reference relation. Flow introduces an additional transport time scale that leaves the FCS diffusion time unchanged when modeled explicitly, while directly shortening burst durations. Photobleaching truncates bursts and biases burst statistics strongly, whereas its influence on FCS is largely confined to slow non-stationarity.
		+
		+	Diffusion time and burst duration should therefore be regarded as complementary rather than interchangeable observables. Deviations from the diffusion-limited reference ratio provide direct physical insight into burst-selection effects, directed transport, and photophysical limitations in confocal single-molecule fluorescence experiments.

	===== References =====		===== References =====

-	* Elson, E. L.; Magde, D. Biopolymers 1974, 13, 1--27.	+	Elson, E. L.; Magde, D. Biopolymers 1974, 13, 1--27.
-	* Rigler, R.; Elson, E. L. (eds.) Fluorescence Correlation Spectroscopy, Springer.	+
-	* Rigler, R.; Widengren, J. Bioscience Reports 1990, 10, 395--403.	+	Rigler, R.; Elson, E. L. (eds.) Fluorescence Correlation Spectroscopy, Springer.
-	* Gopich, I. V.; Szabo, A. Journal of Chemical Physics 2005, 122, 014707.	+
-	* Rüttinger, S. Dissertation, 2006.	+	Rigler, R.; Widengren, J. Bioscience Reports 1990, 10, 395--403.
-	* Dörr, D. Dissertation, 2014.	+
		+	Widengren, J.; Rigler, R. Bioimaging 1996, 4, 149--157.
		+
		+	Gopich, I. V.; Szabo, A. Journal of Chemical Physics 2005, 122, 014707.
		+
		+	Ruettinger, S. Dissertation, 2006.
		+
		+	Doerr, D. Dissertation, 2014.

applications

doerr (doerr@undisclosed.example.com) — 2026-01-12T10:25:53+00:00

2023/02/23 06:35		current
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	[[howto:roi_fitting_using_the_flim_script\|ROI fitting using FLIM analysis software]]		[[howto:roi_fitting_using_the_flim_script\|ROI fitting using FLIM analysis software]]
-
-	[[howto:roi_fitting_using_the_flim_script\|ROI fitting using FLIM analysis software (updated for SymPhoTime v2.5)]]

	[[howto:flim-fret_calculation_for_single_exponential_donors\|FLIM-FRET Calculation for Single Exponential Donors]]		[[howto:flim-fret_calculation_for_single_exponential_donors\|FLIM-FRET Calculation for Single Exponential Donors]]
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	[[howto:antibunching_measurements\|Photon antibunching measurements]]		[[howto:antibunching_measurements\|Photon antibunching measurements]]
		+
		+	[[howto:burst_duration_and_fcs_diffusion_time:burst_duration_and_fcs_diffusion_time\|Burst Duration and FCS Diffusion Time]]


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	[[howto:calculate_ratiometric_single_pair_fret_distributions\|Calculate ratiometric single pair FRET distributions]]		[[howto:calculate_ratiometric_single_pair_fret_distributions\|Calculate ratiometric single pair FRET distributions]]
		+
		+	[[howto:burst_duration_and_fcs_diffusion_time:burst_duration_and_fcs_diffusion_time\|Burst Duration and FCS Diffusion Time]]

howto

doerr (doerr@undisclosed.example.com) — 2026-01-12T10:03:28+00:00

2025/06/16 08:31		current
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	[[howto:phasor_plot_structure_separation:phasor_plot_structure_separation\|Phasor-Based Structural Separation Using FLIM]]		[[howto:phasor_plot_structure_separation:phasor_plot_structure_separation\|Phasor-Based Structural Separation Using FLIM]]
		+
		+	[[howto:AX_FLIM_Examples:AX_FLIM_Examples\|NIS_Element_based_FLIM_Measurement_Examples]]
		+
		+	[[howto:Burst Duration and FCS Diffusion Time:Burst Duration and FCS Diffusion Time\|Burst Duration and FCS Diffusion Time]]
		+

ax_flim_examples

lan (lan@undisclosed.example.com) — 2025-06-16T08:53:39+00:00

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	1. How to automatically acquire both confocal and FLIM channels		1. How to automatically acquire both confocal and FLIM channels
		+
		+	{{ :howto:ax_flim_examples:nis-twochannel_publish.mp4?1000 \|}}

	2. How to perform FLIM stitching to visualize a large sample		2. How to perform FLIM stitching to visualize a large sample
		+
		+	{{ :howto:ax_flim_examples:nis_stiching_publish.mp4?1000 \|}}
		+
		+

nis_stiching_publish.mp4 - created

lan (lan@undisclosed.example.com) — 2025-06-16T08:50:33+00:00

	current

nis-twochannel_publish.mp4 - created

lan (lan@undisclosed.example.com) — 2025-06-16T08:48:51+00:00

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phasor_plot_structure_separation

lan (lan@undisclosed.example.com) — 2025-06-16T08:36:34+00:00

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	{{tag> FLIM acquisition Nikon AX Phasor video LSM_upgrade howto}}		{{tag> FLIM acquisition Nikon AX Phasor video LSM_upgrade howto}}
		+
		+	====== Nikon AX: Phasor-Based Structural Separation Using FLIM ======

	Introduction		Introduction

nis_phasor_publish.mp4 - created

lan (lan@undisclosed.example.com) — 2025-06-16T06:52:08+00:00

	current

01_how_to_select_rois_in_novaflim_based_on_parameter-histogram.pdf - created

lan (lan@undisclosed.example.com) — 2024-12-20T14:02:34+00:00

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02_how_to_perform_a_batch_analysis_over_many_frames.pdf - created

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	current

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	[[howto:roi_fitting_using_the_flim_script\|ROI fitting using FLIM analysis software]]		[[howto:roi_fitting_using_the_flim_script\|ROI fitting using FLIM analysis software]]
-
-	[[howto:roi_fitting_using_the_flim_script\|ROI fitting using FLIM analysis software (updated for SymPhoTime v2.5)]]

	[[howto:flim-fret_calculation_for_single_exponential_donors\|FLIM-FRET Calculation for Single Exponential Donors]]		[[howto:flim-fret_calculation_for_single_exponential_donors\|FLIM-FRET Calculation for Single Exponential Donors]]
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	[[howto:antibunching_measurements\|Photon antibunching measurements]]		[[howto:antibunching_measurements\|Photon antibunching measurements]]
		+
		+	[[howto:burst_duration_and_fcs_diffusion_time:burst_duration_and_fcs_diffusion_time\|Burst Duration and FCS Diffusion Time]]


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	[[howto:calculate_ratiometric_single_pair_fret_distributions\|Calculate ratiometric single pair FRET distributions]]		[[howto:calculate_ratiometric_single_pair_fret_distributions\|Calculate ratiometric single pair FRET distributions]]
		+
		+	[[howto:burst_duration_and_fcs_diffusion_time:burst_duration_and_fcs_diffusion_time\|Burst Duration and FCS Diffusion Time]]

2025/06/16 08:48		current
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	1. How to automatically acquire both confocal and FLIM channels		1. How to automatically acquire both confocal and FLIM channels
		+
		+	{{ :howto:ax_flim_examples:nis-twochannel_publish.mp4?1000 \|}}

	2. How to perform FLIM stitching to visualize a large sample		2. How to perform FLIM stitching to visualize a large sample
		+
		+	{{ :howto:ax_flim_examples:nis_stiching_publish.mp4?1000 \|}}
		+
		+