Narrowband photodetectors with tunable spectral responses are highly desirable for applications in image sensing, machine vision, and optical communication. Herein, a filterless and self‐driven perovskite narrowband photodetector (PNPD) based on the defect‐assisted charge collection narrowing (CCN) mechanism is reported, which is enabled by a high‐quality thick perovskite film. By adjusting the halide component of the perovskite layer, the bandgap is successfully modulated and the corresponding narrowband photodetectors show a wide spectral response range from the red to the near‐infrared (NIR), all with full‐widths at half maximum (FWHMs) below 30 nm. Specifically, the methylammonium lead iodide (MAPbI3) narrowband photodetector exhibits a characteristic detection peak at 800 nm with a very low noise current of ≈0.02 pA Hz–1/2, a high specific detectivity up to 1.27 × 1012 Jones, and a fast response speed with rise/fall time of 12.7/6.9 µs. Impressively, these values are among the highest of their kind reported previously, and allow demonstration of narrowband imaging. The excellent performance of self‐driven PNPDs lights up their prospect in high‐efficiency optoelectronic devices without external power sources.

To fast approximate the maximum likelihood estimator with massive data, Wang et al. (JASA, 2017) proposed an optimal subsampling method under the A-optimality criterion (OSMAC) for in logistic regression. This paper extends the scope of the OS-MAC framework to include generalized linear models with canonical link functions. The consistency and asymptotic normality of the estimator from a general subsampling algorithm are established, and optimal subsampling probabilities under the Aand L-optimality criteria are derived. Furthermore, using Frobenius norm matrix concentration inequality, finite sample properties of the subsample estimator based on optimal subsampling probabilities are derived. Since the optimal subsampling probabilities depend on the full data estimate, an adaptive two-step algorithm is developed. Asymptotic normality and optimality of the estimator from this adaptive algorithm are established. The proposed methods are illustrated and evaluated through numerical experiments on simulated and real datasets.

New mechanisms and modalities for multiband light detection are highly desirable for the ever‐growing developments in machine vision technologies. Demonstrated here is a unique talent of halide perovskites for making self‐driven dual‐band photodetectors with a negative broadband response in the above‐bandgap absorption region and a positive narrowband response in the sub‐bandgap absorption region. The device operates through a charge separation reversion mechanism by controlling the built‐in electric field and the thickness‐dependent light absorption profile in the active material. Impressively, the demarcation wavelengths between the negative broadband and the positive narrowband responses can be continuously adjusted, with the positive narrowband response easily tuned from 410 to 675 nm. The dual‐band photodetector exhibits an extremely low noise of 10−15 A Hz−1/2 and a high specific detectivity of >1012 Jones in both above‐bandgap and sub‐bandgap absorption regions, opening up application opportunities in intelligent recognition and biomedical diagnosis.

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