Optimized Noise Filtration through Dynamical Decoupling
Hermann Uys, Michael J. Biercuk, John J. Bollinger

TL;DR
This paper introduces optimized dynamical decoupling sequences for qubits that significantly improve phase error suppression in high-frequency noise environments, validated through theoretical analysis and experiments with $^{9}$Be$^{+}$ ions.
Contribution
It presents a new analytical method for designing noise-filtering sequences that are spectrum-independent, enhancing qubit coherence in high-frequency noise conditions.
Findings
Sequences outperform traditional methods in high-frequency noise suppression
Experimental validation with $^{9}$Be$^{+}$ ions demonstrates effectiveness
Sequences are spectrum-independent up to a single scaling factor
Abstract
One approach to maintaining phase coherence of qubits through dynamical decoupling consists of applying a sequence of Hahn spin-echo pulses. Recent studies have shown that, in certain noise environments, judicious choice of the delay times between these pulses can greatly improve the suppression of phase errors compared to traditional approaches. By enforcing a simple analytical condition, we obtain sets of dynamical decoupling sequences that are designed for optimized noise filtration and are spectrum-independent up to a single scaling factor set by the coherence time of the system. We demonstrate the efficacy of these sequences in suppressing phase errors through measurements on a model qubit system, Be ions in a Penning trap. Our combined theoretical and experimental studies show that in high-frequency-dominated noise environments this approach may suppress phase errors…
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.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAtomic and Subatomic Physics Research · Quantum Information and Cryptography · Blind Source Separation Techniques
