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Dielectric metasurfaces, composed of planar arrays of subwavelength dielectric structures that collectively mimic the operation of conventional bulk optical elements, have revolutionized the field of optics by their potential in constructing high-efficiency and multi-functional optoelectronic systems on chip. The performance of a dielectric metasurface is largely determined by its constituent material, which is highly desired to have a high refractive index, low optical loss and wide bandgap, and at the same time, be fabrication friendly. Here, we present a new material platform based on tantalum pentoxide (Ta₂O₅) for implementing high-performance dielectric metasurface optics over the ultraviolet and visible spectral region. This wide-bandgap dielectric, exhibiting a high refractive index exceeding 2.1 and negligible extinction coefficient across a broad spectrum, can be easily deposited over large areas with good quality using straightforward physical vapor deposition, and patterned into high-aspect-ratio subwavelength nanostructures through commonly-available fluorine-gas-based reactive ion etching. We implement a series of high-efficiency ultraviolet and visible metasurfaces with representative light-field modulation functionalities including polarization-independent high-numerical-aperture lensing, spin-selective hologram projection, and vivid structural color generation, and the devices exhibit operational efficiencies up to 80%. Our work overcomes limitations faced by scalability of commonly-employed metasurface dielectrics and their operation into the visible and ultraviolet spectral range, and provides a novel route towards realization of high-performance, robust and foundry-manufacturable metasurface optics.

 

Ear wearables (earables) are emerging platforms that are broadly adopted in various applications. There is an increasing demand for robust earables authentication because of the growing amount of sensitive information and the IoT devices that the earable could access. Traditional authentication methods become less feasible due to the limited input interface of earables. Nevertheless, the rich head-related sensing capabilities of earables can be exploited to capture human biometrics. In this paper, we propose EarSlide, an earable biometric authentication system utilizing the advanced sensing capacities of earables and the distinctive features of acoustic fingerprints when users slide their fingers on the face. It utilizes the inward-facing microphone of the earables and the face-ear channel of the ear canal to reliably capture the acoustic fingerprint. In particular, we study the theory of friction sound and categorize the characteristics of the acoustic fingerprints into three representative classes, pattern-class, ridge-groove-class, and coupling-class. Different from traditional fingerprint authentication only utilizes 2D patterns, we incorporate the 3D information in acoustic fingerprint and indirectly sense the fingerprint for authentication. We then design representative sliding gestures that carry rich information about the acoustic fingerprint while being easy to perform. It then extracts multi-class acoustic fingerprint features to reflect the inherent acoustic fingerprint characteristic for authentication. We also adopt an adaptable authentication model and a user behavior mitigation strategy to effectively authenticate legit users from adversaries. The key advantages of EarSlide are that it is resistant to spoofing attacks and its wide acceptability. Our evaluation of EarSlide in diverse real-world environments with intervals over one year shows that EarSlide achieves an average balanced accuracy rate of 98.37% with only one sliding gesture.

 

Using covariant expansions, recent work showed that pole skipping happens in general holographic theories with bosonic fields at frequencies i(l_b−s)2πT, wherel_bis the highest integer spin in the theory andstakes all positive integer values. We revisit this formalism in theories with gauge symmetry and upgrade the pole-skipping condition so that it works without having to remove the gauge redundancy. We also extend the formalism by incorporating fermions with general spins and interactions and show that their presence generally leads to a separate tower of pole-skipping points at frequencies i(l_f−s)2πT,l_fbeing the highest half-integer spin in the theory andsagain taking all positive integer values. We also demonstrate the practical value of this formalism using a selection of examples with spins 0,$$ \frac{1}{2} $$$\frac{1}{2}$,1,$$ \frac{3}{2} $$$\frac{3}{2}$,2.

 

Earables (ear wearables) are rapidly emerging as a new platform encompassing a diverse range of personal applications. The traditional authentication methods hence become less applicable and inconvenient for earables due to their limited input interface. Nevertheless, earables often feature rich around-the-head sensing capability that can be leveraged to capture new types of biometrics. In this work, we propose ToothSonic that leverages the toothprint-induced sonic effect produced by a user performing teeth gestures for earable authentication. In particular, we design representative teeth gestures that can produce effective sonic waves carrying the information of the toothprint. To reliably capture the acoustic toothprint, it leverages the occlusion effect of the ear canal and the inward-facing microphone of the earables. It then extracts multi-level acoustic features to reflect the intrinsic toothprint information for authentication. The key advantages of ToothSonic are that it is suitable for earables and is resistant to various spoofing attacks as the acoustic toothprint is captured via the user's private teeth-ear channel that modulates and encrypts the sonic waves. Our experiment studies with 25 participants show that ToothSonic achieves up to 95% accuracy with only one of the users' tooth gestures.