How Correlated Adsorbate Dynamics on Realistic Substrates Can Give Rise to 1/{\omega} Electric-Field Noise in Surface Ion Traps
Benjamin Foulon, Keith G. Ray, Chang-Eun Kim, Yuan Liu, Brenda M., Rubenstein, and Vincenzo Lordi

TL;DR
This study computationally demonstrates that correlated motions of adsorbates on trap electrodes can produce the characteristic 1/omega electric field noise, shedding light on the origin of anomalous heating in ion traps.
Contribution
First computational analysis showing that collective adsorbate motions cause 1/omega noise in ion traps, linking atomistic dynamics to experimental observations.
Findings
Correlated adsorbate motions produce 1/omega noise.
Multilayer and collective motions are key sources.
Results suggest adsorbate dynamics are central to anomalous heating.
Abstract
Ion traps are promising architectures for implementing scalable quantum computing, but they suffer from excessive "anomalous" heating that prevents their full potential from being realized. This heating, which is orders of magnitude larger than that expected from Johnson-Nyquist noise, results in ion motion that leads to decoherence and reduced fidelity in quantum logic gates. The exact origin of anomalous heating is an open question, but experiments point to adsorbates on trap electrodes as a likely source. Many different models of anomalous heating have been proposed, but these models have yet to pinpoint the atomistic origin of the experimentally-observed electric field noise scaling observed in ion traps at frequencies between 0.1-10 MHz. In this work, we perform the first computational study of the ion trap electric field noise produced by the motions of multiple…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsElectrochemical Analysis and Applications · EEG and Brain-Computer Interfaces
