Analytical derivation of DC SQUID response

TL;DR

This paper derives explicit analytical expressions for the voltage and current responses of overdamped DC SQUIDs in resistive and superconducting states, facilitating practical design and simulation of SQUID-based circuits.

Contribution

It presents new analytical formulas for DC SQUID responses considering various inductance ranges and parameter spreads, improving upon previous numerical methods.

Findings

Analytical expressions match numerical results well.

Formulas applicable for inductance up to approximately 7.

Reduced simulation time for SQUID circuit design.

Abstract

We consider voltage and current responses formation in DC SQUID with overdamped Josephson junctions in resistive and superconducting state in the frame of resistively shunted junction (RSJ) model. For simplicity we neglect the junction capacitance and the noise effect. Explicit expressions for the responses in resistive state were obtained for a SQUID which is symmetrical with respect to bias current injection point. Normalized SQUID inductance $l = 2 e I_c L/\hbar$ (where $I_c$ is the critical current of Josephson junction, $L$ is the SQUID inductance, $e$ is the electron charge and $\hbar$ is the Planck constant) was assumed to be within the range $l \leq 1$, subsequently expanded up to $l \approx 7$ using two fitting parameters. SQUID current response in superconducting state was considered for arbitrary value of the inductance. Impact of small technological spread of parameters relevant for low-temperature superconductor (LTS) technology was studied with generalization of the developed analytical approach for a case of small difference of critical currents and shunt resistances of the Josephson junctions, and inequality of SQUID inductive shoulders for both resistive and superconducting states. Comparison with numerical calculation results shows that developed analytical expressions can be used in practical LTS SQUIDs and SQUID-based circuits design, e.g. large serial SQIF, drastically decreasing the time of simulation.