FAQs

Optimal PC Requirements for Time Tagger

Time Tagger supports Windows (10 or higher) and Linux (Ubuntu 18.04+, CentOS 8). The high-performance GUI Time Tagger Lab is exclusive to Windows. Linux users can access a deprecated web application. macOS is unsupported, but solutions exist. CPU performance is crucial; optimal CPUs with high single-core performance ensure the best data streaming and preprocessing. Multi-threading is essential for simultaneous measurements.

Connecting Time Tagger via USB Port

Time Tagger supports Windows and Linux but not macOS. Workarounds include running Windows on a virtual machine on macOS to use the USB-connected Time Tagger, or using TimeTaggerRPC to control the Time Tagger with macOS via a Windows or Linux machine.

Downloading the Time Tagger Software

Download Swabian Instruments Software

Resolving License Acquisition Errors

Learn how to resolve common issues with automatic license acquisition for Time Tagger software

Fixing Python ModuleNotFound Error for Time Tagger

resolve compatibility issues between Time Tagger and Numpy 2.0.0 or higher by updating to the latest Time Tagger software version

Using Time Tagger on macOS

Time Tagger supports Windows and Linux but not macOS. Workarounds include running Windows on a virtual machine on macOS to use the USB-connected Time Tagger, or using TimeTaggerRPC to control the Time Tagger with macOS via a Windows or Linux machine.

Connecting Time Tagger to an external FPGA

Discover the advanced capabilities of the Time Tagger X with its QSFP+ interface, allowing high-speed, low-latency signal output to a secondary FPGA.

Fixing Numpy 2.0.0 Import Error in Time Tagger

Troubleshoot Python module import issues for Time Tagger by ensuring the installation path is correctly added to the PYTHONPATH

Importing Time Tagger in Spyder IDE

Fix the ImportError DLL load failed’ in Spyder by manually adding the Time Tagger Python module to Spyder’s custom PYTHONPATH

Recommended SMA Cables for Time Taggers

SMA cables are ideal for Time Tagger connections. Use double-shielded cables under 5 meters for optimal signal quality and minimal jitter.

Suitable Pulse Shapes for Time Tagger Measurements

The Time Tagger precisely detects electrical signals across various waveforms with 1 ps resolution, ensuring accurate edge detection for signals with sufficient slew rates, like those in the Time Tagger Ultra model.

Detecting Negative Signals with Time Tagger 20

Pulse inverters compatibility with Time Tagger 20

Setting the Appropriate Trigger Level

What trigger level to set for Time Tagger

Maximum Input Voltage Amplitude

Each Time Tagger model has specific input signal ranges, with slight tolerance beyond limits. For signals outside these ranges, using SMA attenuators is recommended. Refer to our brochure for details.

Minimum Pulse Amplitude and Duration Requirements

Time Tagger models require a minimum input amplitude of 100 mV and specific pulse durations. Shorter or smaller pulses may reduce count rate or increase jitter.

Compensating for Channel Delays

This page explains how to compensate the delays between channels depending on the signal

Detecting Falling Edges of Pulses

In the Time Tagger Lab, rising and falling edges are separate channels, with falling edges marked as negative numbers.

Analyzing Timestamps from Other Time Tagger Devices

our Software is designed to work with our Time Tagger products

Choosing an Appropriate Bin Width for Histograms

With our Time Tagger, you can select any binwidth from 1 ps to over a day, in 1 ps steps, offering flexibility to match your experiment’s needs.

Exporting Data and Saving Plots

Our Time Tagger API supports saving raw data and performing analyses in Python. Use TimeTagStream for saving data in text format or FileWriter for ttbin files. For plotting, integrate with libraries like Matplotlib

Maximum Time Span Window for Measurements

Measuring the Average Count Rate

the paage describes how to measure average countrate using a Time Tagger

Single vs. Multiple Start/Stop in Time Histograms

This page describes how time histograms work

Using the Same Channel in Multiple Measurements

Our API allows multiple measurement classes to use the same channel, enabling simultaneous measurements.

CPU Performance Impact on Transfer Rate

Results of the test on determining the maximum transfer rate that can be achieved with different CPUs using a Time Tagger X

Effects of USB Hubs and Docking Stations on Transfer Rate

this page explains how USB hubs or docking stations affect the overall maximum transfer rate from time Taggers

Impact of Registered Channels on Transfer Rate

Registered channels cannot affect the overall maximum transfer rate of a Time tagger

Low Count Rate Due to CPU Overload

This page explains low countrate even if the USB interface is properly set up

Transfer Rate Limits for Each Time Tagger Model

The maximum data transfer rates of different Time Taggers

Transfer Rate Using Time Tagger Network

Transfer rate using Time Tagger Network is limited to the transmission speed of your local network

USB Extenders and Their Impact on Transfer Rate

This page lists USB extenders which can be used with Time Taggers without degrading the transfer performance

Fixing Broken Wires Due to .NET Assembly Mismatch

Getting Started with Time Tagger in NI LabVIEW

Updating LabVIEW Code for New Time Tagger Software

Accessing the Web Application Server from Another PC

This page explains how to access Web Application server from another PC"

Difference Between TimeTaggerNetwork and Pyro Control

This page explains difference between TimeTaggerNetwork and Remote Control with Pyro

Scanning for Time Tagger Servers on Different Subnetworks

This page explains ScanTimeTaggerServers function

How to Cite Swabian Instruments