Frequently asked questions
The questions below are the ones we hear most often — from a first installation to the quiet details that matter once an experiment is running.
Installation and platforms
Which operating systems are supported? Quatm uses Qt 6/PySide6; supported platforms follow the Qt 6.11 matrix: Windows 10 (1809+) and Windows 11 on x86-64, macOS 13 or newer, and Linux x86-64 (Ubuntu 22.04/24.04, Debian 12, or equivalent). ARM64 desktop support is limited; see the Qt 6.11 supported-platform matrix. Python 3.9 or newer is required.
What are the minimum requirements? A machine with at least 8 GB of memory and 4 CPU cores is recommended for the full GUI and data services. Real-time control requires an FPGA-class controller.
Devices and drivers
Do I need specific hardware? No single vendor is required, but a real-time controller with TTL/DAC outputs is needed for timed sequences. Instruments using standard protocols can be integrated by selecting or writing a driver; the effort depends on the protocol and vendor SDK.
How do I integrate a custom device?
Write a driver class and register it in device_db.py as type: local (or map channels with attr / generic_attr). See Device drivers.
Which cameras are supported? Andor, FLIR/BlackFly and other scientific cameras are covered by the driver catalogue; custom cameras can be added through project-local drivers.
Data
What format is used? Experiment data is archived as HDF5, with optional streaming/export services.
How large are the files? A typical absorption-imaging run is on the order of 10–50 MB, depending on image count and resolution. Plan disk capacity and retention for long campaigns.
Updating
How do I upgrade? Update the Python environment and reinstall the package, or pull the repository and rerun the bootstrap. Check the changelog for incompatible changes.
Will my experiment scripts break? Quatm follows semantic versioning for public interfaces; major changes are documented with migration notes. Verify in simulation before a campaign.