# Current-phase relations of InAs nanowire Josephson junctions: from interacting to multi-mode regimes

## TL;DR

This study investigates the current-phase relations of InAs nanowire Josephson junctions, revealing how gate voltage, device geometry, and phase bias influence mode behavior, electron interactions, and the electronic spectrum, aiding qubit development.

## Contribution

It provides a comprehensive analysis combining experimental measurements with analytical and numerical models to understand mode control and electron interactions in InAs nanowire Josephson junctions.

## Key findings

- Tunable number of modes and their transparency in the junction.
- Identification of regimes with electron-electron interactions indicating quantum dot formation.
- Microscopic simulations reveal the energy spectrum and spatial distribution of Andreev states.

## Abstract

Gate-tunable semiconductor-superconductor nanowires with superconducting leads form exotic Josephson junctions that are a highly desirable platform for two types of qubits: those with topological superconductivity (Majorana qubits) and those based on tunable anharmonicity (gatemon qubits). Controlling their behavior, however, requires understanding their electrostatic environment and electronic structure. Here we study gated InAs nanowires with epitaxial aluminum shells. By measuring current-phase relations (CPR) and comparing them with analytical and numerical calculations, we show that we can tune the number of modes, determine the transparency of each mode, and tune into regimes in which electron-electron interactions are apparent, indicating the presence of a quantum dot. To take into account electrostatic and geometrical effects, we perform microscopic self-consistent Schrodinger-Poisson numerical simulations, revealing the energy spectrum of Andreev states in the junction as well as their spatial distribution. Our work systematically demonstrates the effect of device geometry, gate voltage and phase bias on mode behavior, providing new insights into ongoing experimental efforts and predictive device design.