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#physics

61 posts33 participants0 posts today
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j_bertolotti

#PhysicsJournalClub
"Model-free estimation of the Cramér–Rao bound for deep learning microscopy in complex media"
by I. Starshynov et al.

Nat. Photon. (2025)
doi.org/10.1038/s41566-025-016

As everybody who ever tried to orient themselves while immersed in thick fog knows, scattering scrambles information. The question "how much information is still there?" is not particularly interesting as the answer is "essentially all of it", as elastic scattering can't destroy information. A much more interesting question is "how much information can we retrieve?" In order to even try to give an answer we need to be a bit more specific, so the authors placed a small reflective surface behind a scattering layer and asked how much information about its transverse position could be retrieved. This is a well-posed question, and the answer takes the form of a "Cramér–Rao bound" (en.wikipedia.org/wiki/Cram%C3%).
After estimating this upper bound, the authors investigate how well a trained neural network can do at this task, and show that a specifically built convolutional neural network can almost reach the theoretical bound.

[Conflict of interest: Ilya Starshynov (the first author) did his PhD in my group.]

#Physics#InformationTheory#Optics
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Nicole Sharp

How Insects Fly in the Rain

Getting caught in the rain is annoying for us but has the potential to be deadly for smaller creatures like insects. So how do they survive a deluge? First, they don’t resist a raindrop, and second, they have the kinds of surfaces water likes to roll or bounce off. The key to this second ability is micro- and nanoscale roughness. Surfaces like butterfly wings, water strider feet, and leaf surfaces contain lots of tiny gaps where air gets caught. Water’s cohesion — its attraction to itself — is large enough that water drops won’t squeeze into these tiny spaces. Instead, like the ball it resembles, a water drop slides or bounces away. (Video and image credit: Be Smart)

#biology#butterfly#cohesion
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