Streamlining Archer’s quantum measurements, instrument control and data analysis

Angela Tanesha, Archer Nanofabrication Engineer and University of Melbourne Alumni, explains how the company is streamlining its quantum device measurements, instrument control, and performing insightful data analysis.

Archer’s development of a qubit processor involves the nanofabrication and measurement of chip-based quantum electronic devices, or QEDs. Some important measurements of QEDs centres around the movement of electrons. The information collected from these measurements are used to characterise the QEDs, and rely on sophisticated instruments like multiple programmable voltage source and current measurement units. The instruments are typically controlled by an external computer to facilitate data acquisition and analysis.

Archer implements an instrument control and data acquisition system that allows its researchers to collect and analyse data streaming in from QED measurement setups in real-time. This is an understated evolution in Archer’s ability to adapt to its operating environments. Without it, the Archer team would most likely need to intervene and collect the data manually. Often, manual intervention is unviable, due to the time scales of the measurement event either being too short or too long during data capture, the sheer number of devices being measured, or simply that the data acquisition requires constant human attention.

High-level programming languages like Python are intuitive to use and allow Archer to implement more complex approaches to how it operates its measurement systems, which contain both data and code. At Archer, Python is one of the go-to languages for data analysis for its relative ease of use and the wealth of data analysis and visualisation packages available like NumPy, Pandas, and Matplotlib. Code to communicate with quantum measurement instruments is also usually written by the Archer team in Python.

The Archer team fabricates hundreds of QEDs on a wafer for measurements, testing and analysis. The data from the QEDs is typically collected from multiple instruments that have different hardware interfaces and software commands. The PyVISA software package can be used to ensure that a single set of instructions works with various hardware interfaces. An example measurement environment includes using Python to communicate with source meter units that measure current. These typically have a General-Purpose Interface Bus (GPIB) cable and Standard Commands for Programmable Instruments (SCPI) commands; although the user may only need to know Python.

However, despite the purpose built code, Archer still needs to use manufacturer-provided commands in a concerted approach, which can vary, and in these circumstances instrument drivers are used. Instrument drivers contain standardised commands that can work for one or a group of instruments. Drivers turn instrument commands into a high-level language and as a result make it much easier to control instruments.

As measurement and instrument control becomes increasingly complex at Archer, the team have routinely deployed QCoDeS. This has allowed the Archer team to collaborate internally across the different laboratories the company has access to in Australia.

QCoDeS is an open-source data acquisition framework that allows programmers to communicate with multiple instruments and includes automated file saving and real-time plotting. QCoDeS can be accessed in the code repository GitHub. The QCoDeS software is customisable and since its release in 2014, QCoDeS has garnered hundreds of contributors amounting to support for more than 170 instruments. With over 150,000 downloads through Anaconda, this open-source software has no doubt had a significant impact on the field of experimental physics.

The large community of developers and users contribute to, and improve, the QCoDeS software. This type of quality assurance has allowed Archer to easily deploy its data acquisition systems at relatively small scale with great benefits, including rapid testing with high reliably and accuracy. Indirectly, the harmonisation of data, code, and software, has also had the advantage of facilitating the seamless handling of information for partnerships and the innovation that stems from them.

To learn more about Python, visit the official site here: https://www.python.org/

QCoDeS on GitHub: https://qcodes.github.io/Qcodes/index.html