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Programmable and reconfigurable optics hold significant potential for transforming a broad spectrum of applications, spanning space explorations to biomedical imaging, gas sensing, and optical cloaking. The ability to adjust the optical properties of components like filters, lenses, and beam steering devices could result in dramatic reductions in size, weight, and power consumption in future optoelectronic devices. Among the potential candidates for reconfigurable optics, chalcogenide‐based phase change materials (PCMs) offer great promise due to their non‐volatile and analogue switching characteristics. Although PCM have found widespread use in electronic data storage, these memory devices are deeply sub‐micron‐sized. To incorporate phase change materials into free‐space optical components, it is essential to scale them up to beyond several hundreds of microns while maintaining reliable switching characteristics. This study demonstrated a non‐mechanical, non‐volatile transmissive filter based on low‐loss PCMs with a 200 × 200 µm²switching area. The device/metafilter can be consistently switched between low‐ and high‐transmission states using electrical pulses with a switching contrast ratio of 5.5 dB. The device was reversibly switched for 1250 cycles before accelerated degradation took place. The work represents an important step toward realizing free‐space reconfigurable optics based on PCMs.

 

This paper addresses the end-to-end sample complexity bound for learning in closed loop the state estimator-based robust H2 controller for an unknown (possibly unstable) Linear Time Invariant (LTI) system, when given a fixed state-feedback gain. We build on the results from Ding et al. (1994) to bridge the gap between the parameterization of all state-estimators and the celebrated Youla parameterization. Refitting the expression of the relevant closed loop allows for the optimal linear observer problem given a fixed state feedback gain to be recast as a convex problem in the Youla parameter. The robust synthesis procedure is performed by considering bounded additive model uncertainty on the coprime factors of the plant, such that a min-max optimization problem is formulated for the robust H2 controller via an observer approach. The closed-loop identification scheme follows Zhang et al. (2021), where the nominal model of the true plant is identified by constructing a Hankel-like matrix from a single time-series of noisy, finite length input-output data by using the ordinary least squares algorithm from Sarkar et al. (2020). Finally, a H∞ bound on the estimated model error is provided, as the robust synthesis procedure requires bounded additive uncertainty on the coprime factors of the model. Reference Zhang et al. (2022b) is the extended version of this paper. 

Recent studies have reported worldwide vegetation suppression in response to increasing atmospheric vapor pressure deficit (VPD). Here, we integrate multisource datasets to show that increasing VPD caused by warming alone does not suppress vegetation growth in northern peatlands. A site-level manipulation experiment and a multiple-site synthesis find a neutral impact of rising VPD on vegetation growth; regional analysis manifests a strong declining gradient of VPD suppression impacts from sparsely distributed peatland to densely distributed peatland. The major mechanism adopted by plants in response to rising VPD is the “open” water-use strategy, where stomatal regulation is relaxed to maximize carbon uptake. These unique surface characteristics evolve in the wet soil‒air environment in the northern peatlands. The neutral VPD impacts observed in northern peatlands contrast with the vegetation suppression reported in global nonpeatland areas under rising VPD caused by concurrent warming and decreasing relative humidity, suggesting model improvement for representing VPD impacts in northern peatlands remains necessary.

 

Optical phase-change materials have enabled nonvolatile programmability in integrated photonic circuits by leveraging a reversible phase transition between amorphous and crystalline states. To control these materials in a scalable manner on-chip, heating the waveguide itself via electrical currents is an attractive option which has been recently explored using various approaches. Here, we compare the heating efficiency, fabrication variability, and endurance of two promising heater designs which can be easily integrated into silicon waveguides—a resistive microheater using n-doped silicon and one using a silicon p-type/intrinsic/n-type (PIN) junction. Raman thermometry is used to characterize the heating efficiencies of these microheaters, showing that both devices can achieve similar peak temperatures but revealing damage in the PIN devices. Subsequent endurance testing and characterization of both device types provide further insights into the reliability and potential damage mechanisms that can arise in electrically programmable phase-change photonic devices.