Quick Navigation
Topics
Superconducting Qubits
Granular aluminum: A superconducting material for high impedance quantum circuits
arXiv
Authors: Lukas Grünhaupt, Martin Spiecker, Daria Gusenkova, Nataliya Maleeva, Sebastian T. Skacel, Ivan Takmakov, Francesco Valenti, Patrick Winkel, Hannes Rotzinger, Alexey V. Ustinov, Ioan M. Pop
Year
2018
Paper ID
7340
Status
Preprint
Abstract Read
~2 min
Abstract Words
151
Citations
N/A
Abstract
Superconducting quantum information processing machines are predominantly based on microwave circuits with relatively low characteristic impedance, of about 100 Ohm, and small anharmonicity, which can limit their coherence and logic gate fidelity. A promising alternative are circuits based on so-called superinductors, with characteristic impedances exceeding the resistance quantum RQ = 6.4 kΩ. However, previous implementations of superinductors, consisting of mesoscopic Josephson junction arrays, can introduce unintended nonlinearity or parasitic resonant modes in the qubit vicinity, degrading its coherence. Here we present a fluxonium qubit design using a granular aluminum (grAl) superinductor strip. Granular aluminum is a particularly attractive material, as it self-assembles into an effective junction array with a remarkably high kinetic inductance, and its fabrication can be in-situ integrated with standard aluminum circuit processing. The measured qubit coherence time T2R up to 30 μs illustrates the potential of grAl for applications ranging from protected qubit designs to quantum limited amplifiers and detectors.
Why This Paper Matters
- This paper contributes to the Superconducting Qubits research area in the Quantum Articles archive.
- It adds a 2018 reference point for readers tracking recent quantum research.
- Superconducting quantum information processing machines are predominantly based on microwave circuits with relatively low characteristic impedance, of about 100 Ohm, and small...
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.