Date & Time: Tuesday 25 September, 13:30 – 15:00
Organisers: Nick Fontaine and Roland Ryf, Nokia Bell Labs, USA; Jochen Schröder, Chalmers University of Technology Sweden; Binbin Guan, Acacia Communications USA
Have you ever wanted to automate your lab, get better/quicker at processing your data, make beautiful plots and figures and at the same time meet a bunch of cool scientists? Well, you are in luck! We have 8 demos for various common lab automation tasks, ranging from simple remote control of optical instrumentation, data processing and photonic design simulations, all the way to full lab automation. Students, professionals of all levels are welcome to learn and share their secret tips and tricks developed over the years.
Lab automation is becoming more and more important as lab equipment is growing more capable and optical experiments more complex. Especially experiments performed over longer time periods or requiring the acquisition of massive amount of data can significantly benefit from automation and allows researchers to concentrate on the more fun part of the experimental work.
Open source software, which is widely available, can offer significant advantages over standard commercial software in terms of flexibility, modularity and compatibility.
Low-cost system-on-chip controller running Linux (like the Raspberry Pi for example) can provide local controls and interfaces for instrumentation and coordinated using a local area network using Python as rapid prototyping programming language. Python is fun to learn and useful for lab automation as it runs on almost any computer and the functionality can be easily extended based on a comprehensive set of modules with good support for scientific applications.
In this hackathon we will provide 8 stations/demos, each staffed with a researcher experienced in lab automation, which will cover the following topics:
-Installing python on your computer (beginners)
-Introduction to the Python programming language (beginners)
-Python programming environment and web based tools (beginners)
-Plots and graphics in Python (beginners)
-Instrumentation control in Python
-Remote control and coordination of multiple computer for lab automation (advanced)
-Data processing on multicore and GPU based systems (advanced)
-Python software for photonic design
Bring a laptop to participate in the exercise. There will be plenty of time for mingling and discussion. Food and drinks sponsored by the IEEE Photonics Society