Negative inertia is an unusual and counter-intuitive property of matter, extensively investigated in some of the most exotic branches of physics and engineering at both macroscopic and microscopic levels. Such an exotic property promises a wide range of applications, from Alcubierre drive to acoustic wave manipulation. Here, a novel approach to the realization of negative inertia and the concept of negative-inertia converters are introduced for both translational and rotational motion. The proposed devices, capable of exhibiting negative mass and negative moment of inertia, base their operational principle on actuating the loading inertia, concealed within the housing of the device, synchronously with the displacement of the housing itself. Negative-inertia converters share many similarities with negative-impedance converters, including their proneness to instability. Thus, an equivalent circuit model of the proposed devices is developed and simulated in lossless and lossy environments. Friction, unavoidable in every practical system, is found to be the main cause of instability. The derived closed-form stability condition suggests that the effective inertia of a system containing a negative-inertia converter must remain positive to ensure the stability. Despite this limitation, negative-inertia converters may become the key elements in applications requiring reduction of an object’s inertia.

Optical sources with highly temperature-stable output intensity and low power consumption are desired in portable devices for metrology, and in medical applications, communications, and illumination. This paper introduces and demonstrates an optical stabilization scheme that uses the drift in peak-emission wavelength of light emitted from an LED as a temperature feedback signal to realize output intensity temperature coefficients below 100 ppm/K. The control principle relies on a conventional feedback loop but with a specially designed weakly polarizing optical interference coating that exhibits different transmittivity/reflectivity ratio dependence on wavelength for two different polarizations and by using a weighted sum of two polarizations as the output power correcting signal in a feedback loop. The method does not need a thermometer or temperature control stage, and its calibration can be performed electronically, adding to the simplicity of the design and making it also suitable for portable and battery-operated instruments.

This paper describes theoretical reliability analysis of a system containing n optical ports in which each optical port contains m redundant vertical-cavity surface-emitting lasers. We study the wearout failure statistics, modelled with lognormal distribution, for three different chip-level integration approaches: (A) each laser on its own chip, resulting in m·n chips, (B) m redundant lasers associated with one channel are on a single chip, resulting in n chips, and (C) all m·n lasers integrated on a single chip. We present a model that includes the run-to-run reliability parameter fluctuation and find that the three integration schemes consistently exhibit MTTF(C) ≥ MTTF(A) ≥ MTTF(B) for lognormal distribution shape parameters observed in commercial vertical-cavity surface-emitting lasers. We also provide analytic approximations for the failure statistics for all three integration approaches enabling straightforward calculation of the failure statistics for any redundancy and channel number.

Spectral unmixing of outdoor nighttime lighting mixtures is a linear but challenging problem due to spectral variability and contributions from unknown light sources. This paper presents a quadratic programming algorithm for constrained linear unmixing abundance estimation that extends the conventional fully constrained least squares approach through a physically motivated set of three linear constraints: estimated abundances must be non-negative, their sum must not be greater than unity, and the spectral signature reconstructed from estimated abundances must not exceed the measured signal in any spectral band. Unlike alternative optimization or neural network approaches, the proposed formulation requires no hyperparameter tuning or stochastic training, and yields a unique globally optimal solution whenever the endmember spectra are linearly independent, as verified for the case study considered here. The accuracy of the algorithm is evaluated using a physically motivated dataset generation framework grounded in the Generalized Linear Mixing Model, which is capable of modeling wavelength-dependent surface reflections and variable fractions of unknown light sources. Experiments conducted on a database of measured illumination sources demonstrate that the proposed formulation outperforms the classical fully constrained least squares baseline. Specifically, it reduces the abundance RMSE from 0.1539 to 0.1484 and improves the endmember detection F1 score from 0.795 to 0.803, with differences confirmed to be statistically significant. Furthermore, the model remains robust to surface reflections present in up to 80% of the evaluated mixtures. It maintains reliable abundance estimates for unknown spectral contributions up to approximately 15%, with accuracy gradually decreasing beyond this level. Finally, both the optimization method and the dataset generation framework are completely independent of the underlying channel configuration, making them readily adaptable to arbitrary choices of spectral channels and application domains beyond public lighting analysis.