An algorithm for the estimation of the frequency of a complex sinusoid in noise is proposed. The estimator consists of multiple applications of lowpass filtering and decimation, frequency estimation by linear prediction, and digital heterodyning. The estimator has a significantly reduced threshold relative to existing phase-based algorithms and performance close to that of maximum likelihood estimation. In addition, the mean-squared error performance is within 0.7 dB of the Cramér-Rao bound (CRB) at signal-to-noise ratios (SNRs) above threshold. Unlike many autocorrelation and phase-based methods, the proposed algorithm's performance is uniform across a frequency range of to . The computational complexity of the algorithm is shown to be favorable compared with maximum likelihood estimation via the fast Fourier transform (FFT) algorithm when significant zero-padding is required.

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As-for-Sb and Sb-for-As anion exchange reactions have been investigated by the exposure of GaSb surfaces to As2 and As4 species and by the exposure of GaAs to Sb2, respectively. The effect of surface temperature, anion soak time, and anion species (either As2 or As4) on the chemistry governing the anion exchange reactions during GaAsySb1−y∕GaSb and GaSbyAs1−y∕GaAs heterostructure formation by molecular beam epitaxy is examined. It is found that when GaSb surfaces are exposed to arsenic, the anion exchange reaction competes with the formation of isoelectronic compounds, AsSby, which form clusters precipitating in the GaAsySb1−y∕GaSb heterostructures. The relative amount of GaAs and AsSby depends on the surface temperature, the As soak time, and on the As species, i.e., As2 or As4. We observe specific process conditions that minimize AsSby formation, yielding more abrupt heterojunction interfaces. In the case of the Sb2∕GaAs system, the Sb-for-As anion exchange does not occur to a significant degree, but surface segregation of antimony is found. A chemical model for the As-for-Sb anion exchange reaction is proposed.

Here, we present a new approach based on manifold learning for knowledge discovery and inverse design with minimal complexity in photonic nanostructures. Our approach builds on studying submanifolds of responses of a class of nanostructures with different design complexities in the latent space to obtain valuable insight about the physics of device operation to guide a more intelligent design. In contrast to the current methods for inverse design of photonic nanostructures, which are limited to preselected and usually overcomplex structures, we show that our method allows evolution from an initial design toward the simplest structure while solving the inverse problem.

A thermodynamic approach is presented to assess the extent of anion exchange reactions during the heteroepitaxy (molecular beam epitaxy) of dissimilar anion III-V compound semiconductor structures. It is shown that the extent of anion exchange can be predicted by the change in the Gibbs free energy. Bond strength changes can only be used as a guide in comparing the relative tendency for exchange, rather than as a criterion. The driving force for anion exchange strongly depends on the conditions during interface formation. A number of important factors, including bond strength, misfit strain energy, surface structure and energy, the equilibrium between dimers V 2 and tetramers V 4 , and segregation are discussed in terms of their contributions to the thermodynamics. r