PSIM simulations of a dc SQUID magnetometer

Abstract

Purpose – This paper aims to report the modelling and simulation work that predicts the behaviours of both a Josephson junction (JJ) and a dc superconducting quantum interference device (SQUID). It is pertinent to predict the SQUID magnetometers’ behaviours via simulations, before subjecting them to real experiments because they are quite expensive to acquire, and can be easily damaged during test analysis. Design/methodology/approach – To achieve this, power simulation (PSIM) was used to model and simulate a JJ, using the basic equation that describes the effective current through it. A dc SQUID magnetometer, which is composed of two JJs, was then modelled and simulated using the modelled JJ. Thermal noise simulation is also included, to observe its effects on the magnetometer’s output. A directly coupled flux-locked loop circuit was later included in the simulation to amplify and linearise the SQUID’s output, which is usually sinusoidal. Findings – When steady bias currents were applied to the JJ, the resulting voltage across it was seen to oscillate. The JJ’s and SQUID’s voltage–current characteristics, and voltage–flux characteristics were also observed in the simulations, and the results respectively agree with the behaviours of a typical JJ and dc SQUID magnetometer. Originality/value – A way of simulating SQUIDs, without a superconducting simulation tool, is presented. The work provides a much simpler way of studying the behaviour of dc SQUID magnetometers, due to the easy accessibility and fast simulation capability of the software used, with an added advantage of being able to simulate the thermal noise effects, without having to import this facility from secondary software.

Some implications of superconducting quantum interference to the application of master equations in engineering quantum technologies

“…With its ability to provide substantial cost savings and speed up the exploration of parameter space, modelling and simulation plays a central role in the engineering process. As Quantum Technologies (QTs) move away from laboratory demonstrations and become integrated into consumer systems, accurate modelling will become increasingly important [1][2][3][4][5] . Here robust, and generally hierarchical, quantitative simulations will be required which are capable of accurately and reliably predicting the behaviour of the system-under-development at different levels of abstraction.…”