Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses

TL;DR

This paper introduces compact vacuum gap transmon qubits with high vacuum participation and surface loss sensitivity, enabling precise surface loss measurements and promising scalability for quantum processors.

Contribution

The work demonstrates small, vacuum-gap transmon qubits with high vacuum participation and exceptional surface loss sensitivity, advancing qubit design for scalable quantum computing.

Findings

Achieved vacuum participation ratio up to 99.6% in small transmon qubits.

Observed double exponential decay indicating strong TLS coupling.

Measured a qubit quality factor of 20 μs^{-2} per footprint area.

Abstract

State-of-the-art transmon qubits rely on large capacitors which systematically improves their coherence due to reduced surface loss participation. However, this approach increases both the footprint and the parasitic cross-coupling and is ultimately limited by radiation losses - a potential roadblock for scaling up quantum processors to millions of qubits. In this work we present transmon qubits with sizes as low as 36$ \times $39$ \mu$m$^2$ with $\gtrsim$100 nm wide vacuum gap capacitors that are micro-machined from commercial silicon-on-insulator wafers and shadow evaporated with aluminum. After the release in HF vapor we achieve a vacuum participation ratio up to 99.6\% in an in-plane design that is compatible with standard coplanar circuits. Qubit relaxation time measurements for small gaps with high vacuum electric fields of up to 22 V/m reveal a double exponential decay indicating comparably strong coupling to long-lived two-level-systems (TLS). The exceptionally high selectivity of $>$20 dB to the superconductor-vacuum surface allows to precisely back out the sub-single-photon dielectric loss tangent of aluminum oxide exposed to ambient conditions. In terms of future scaling potential we achieve a qubit quality factor by footprint area of $20 \mu \mathrm{s}^{-2}$, which is on par with the highest $T_1$ devices relying on larger geometries and expected to improve substantially for lower loss superconductors like NbTiN, TiN or Ta.