Multi channel time-to-digital converter
- Jitter Measurement
- Use cases
- Coding Examples
quTAG MC – Multi Channel Variants
The quTAG MC is designed for a high number of simultaneous measurements with up to 32 channels in one device and the ability of synchronizing multiple devices.
These time taggers of the quTAG family are available with a wide range of channel numbers and timing resolution. Enhanced timing jitter values can be achieved by interconnecting input channels via software.
The table below shows all quTAG MC variants with number of input channels and varying timing RMS jitter by interconnectiong channels in picoseconds.
|Time correlated single photon counting|
|Digital resolution 1 ps|
|Up to 32 stop channels in one device|
|Synchronization of multiple devices|
|Timing jitter <20 ps RMS|
|Cost-sensitive, modular versions available|
quTAG MC Variants
|8 Input Channels|
|16 Input Channels|
|32 Input Channels|
quTAG MC Features
|+ Clock Input|
The quTAG can be synchronized to an external clock to allow more precise long-term accuracy.
|+ Synchronization of devices|
This extension allows to synchronize up to 10 quTAGs. Up to 320 equal stop channels of MC version are offered – all sharing the same clock.
|+ Virtual channels & filters|
|+ Marker inputs – optional|
|+ Output channels – optional|
Software features for quTAG MC
|Histograms||Create start-stop & start-multistop histograms|
|Lifetime||The software enables analyzing lifetime measurements on the fly.
It calculates histograms and fits exponential decreases.
|Correlations||This software extension is intended for calculating the correlation function, as needed for example in Hanbury Brown-Twiss experiments or FCS.|
|Virtual channels & filters||The device allows to enable virtual channels or user-defined filters. The filtering is based on hardware and happens inside the device to save USB bandwidth.|
|GUI||Web-application on the PC or via WIFI from quTAG,
Daisy – generic Data Analysis and Imaging System
|User interfaces||command line & libraries in C, Python, Matlab, LabVIEW|
In order to measure the jitter, we generate an electrical pulse with steep edges. This pulse gets split into two by a power splitter and sent into two different inputs of the quTAG (i.e. start and stop-X or stop-X and stop-Y).
Then we use the quTAG software to generate a startstop-histogram. We fit a Gaussian function to this histogram and determine RMS and FWHM. The single channel jitter corresponds to σ / √2 from this two-channel measurement, assuming equal Gaussian contributions from both signals. The FWHM can be obtained by the standard deviation with the relation FWHM = 2 √2 ln 2 σ ≈ 2.35 σ.
- Performance Optimization and Real-Time Security Monitoring for Single-Photon Quantum Key Distribution
T. Kupko et al., arXiv preprint (2019)
- Hong-Ou-Mandel interference between independent III-V on silicon waveguide integrated lasers
C. Agnesi, et al., arXiv preprint (2019)
- Sub-ns timing accuracy for satellite quantum communications
C. Agnesi et al., arXiv preprint (2019)
- Experimental demonstration of quantum advantage for one-waycommunication complexity
N. Kumar et al., arXiv preprint (2018)
- A photonic quantum walk with a four-dimensional Coin
L. Lorz et al., arXiv preprint (2018)
- Towards quantum communication from global navigation satellite system
L. Calderaro et al., IOP Publishing (2018)
Laser trigger as Start, Single Quantum SNSPD as Stop
We measured a time difference histogram between the trigger pulse from the laser as start and the SQ detector signal as stop.
This is basically the setup for a Fluorescence Lifetime Imaging (FLIM) measurement..
Whole system response function (blue, measured with quTAG): Timing jitter 17.8 ps RMS, 35.9 ps FWHM
For comparison: Detector response function (red, measured with fast oscilloscope): Timing jitter 14.5 ps RMS, 26.1 ps FWHM.
One SQ Detector as Start, another one as Stop
Here, we measured the time difference histogram between one of the two SQ SNSPDs as Start and the other one as Stop pulse.
Timing jitter of 2 SQ SNSPDs measured with the quTAG (blue): 21.6 ps RMS, 45.6 ps FWHM.
Overview of quick and easy Python Coding Examples
Python is a popular coding language for labs and institutes. Therefore, qutools created a Python file to wrap all the DLL or SO (Win/Linux) functions to gain quick and easy control of the hardware.
The following list shows the different examples using this wrapper. An explanation is added to each code.
- Retrieve Countrates and Coincidences
- Live Plotting of Countrates with matplotlib
- Create and retrieve a histogram of two channels
- Live Plotting of the histogram with a changing channel delay
- Retrieve timestamps
- Write timestamps to a file on the PC
- Change different settings of the quTAG
|Download quTAG MC Python Examples||04/2021||0.4 MB||zip|
|quTAG software manual V1.5.0 – Example explanation||10/2019||0.3 MB|
First Coding Example: How to retrieve Countrates
The following codes show how to quickly connect to the quTAG via Python. The quTAG.py file wraps all DLL functions to get simple access via your own code.
In the first example qutag-GetCoincCounter-starter_example.py we are retrieving countrates and coincidences of the quTAG and its input channels.
Datasheet & Manuals
|quTAG MC datasheet||01/2021||0.3 MB|
|quTAG MC quickstart manual V1.0.0||05/2019||0.2 MB|
|quTAG MC manual V1.0.0||01/2021||0.9 MB|
|quTAG software manual V1.5.0||10/2019||0.3 MB|
|quTAG brochure||03/2019||2.4 MB|
|quTAG & Matlab technical note||01/2021||0.3 MB|
Software quTAG MC
|quTAG MC software V1.0.5||02/2021||20.0 MB||exe|
|quTAG MC software V1.0.5||02/2021||15.8 MB||zip|
|quTAG MC 64bit library win V1.0.5||02/2021||0.4 MB||zip|
|quTAG MC 64bit software linux V1.0.5||02/2021||5.5 MB||tgz|
|Python examples||04/2021||0.4 MB||zip|