research
Exceptional Points Count Hidden Noise Sources
Noise-averaged dephasing signatures can distinguish non-Gaussian environments that share the same lower-order statistics.
Summary
Noise-averaged dephasing signatures can distinguish non-Gaussian environments that share the same lower-order statistics.
A theoretical model links the largest exceptional-point order in a dephasing response to the number of independent noise sources and their higher-order statistics. An atomtronic readout is proposed; the result is not yet a device demonstration.
Why it matters
Noise-averaged dephasing signatures can distinguish non-Gaussian environments that share the same lower-order statistics.
Limits and context
- An atomtronic readout is proposed; the result is not yet a device demonstration.
Key claims
Noise-averaged dephasing signatures can distinguish non-Gaussian environments that share the same lower-order statistics.
Qualification: An atomtronic readout is proposed; the result is not yet a device demonstration.
Evidence: source-2026-10-31-017
Sources
- arXiv preprint 2610.40612, original v1arXiv · primary research
Corrections
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