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The Influence of the Anharmonism of Matter on Thermal Radiation
Published in David N. Klyshko, Yuri Sviridov, Photons and Nonlinear Optics, 2018
David N. Klyshko, Yuri Sviridov
An excited molecule may cross into the ground state through a two-photon transition—the emission of two photons of frequencies ω1 and ω2 (see Figure 1.9g). In the absence of a real intermediate level, these photons appear practically simultaneously. In the case of a cascade (i.e., resonance) two-photon transition, the second photon is radiated with a delay that is equal, on the average, to the radiation lifetime of the intermediate state. It is important that the photons appear in pairs in both cases: as a result, components of the field with frequencies ω1 and ω2 turn out to be statistically dependent. Likewise, n-photon transitions bind n spectral components of the thermal radiation field. At the same time, linear systems, like the harmonic oscillator, have an equidistant set of levels such that ω1 = ω2 = · · ·; therefore, cascade multiphoton transitions in such systems do not result in correlations between different frequency components of the field. The correlation of different-frequency modes is clearly not peculiar to quantum models.
Optimised Floating Point FFT Core for Improved OMP CS System
Published in International Journal of Electronics, 2022
Alahari Radhika, K. Satya Prasad, K. Kishan Rao
An emerging and progressing domain of compressive sensing (CS) has gained considerable attention in signal processing, statistics, computational sciences and other methodological approaches. The classic Nyquist-Shannon theorem of continuous spectrum sampling affirms that transmissions can be retrieved from an equidistant set of samples at a rate twice the largest in the signal of interest. By utilising this resource much of the signal processing has shifted from analogue to digital, making increasingly durable, highly versatile and cost productive sensing systems than their analogue equivalents. The extracted Nyquist rate is therefore so intense in several core real-life applications that the design of such a system that can take on that rate cannot be made feasible or even extremely difficult. For certain ways, detection and interpretation of signals still face an immense challenge amid the exponential growth in computing capacity. Therefore, realistic approaches to the problems of computing and storage when using higher dimensional data usually thrive on compression, that intends to provide a suitable distortion-specific representation. A similar approach to the compression of the signal focuses on a framework for a sparse and thus compressible image representation. Sparse interpretation implies that the signal lengthcan be seen only with coefficientsnonzero. It provides a compressed signal representation by retrieving only the values and locations of the non-zero coefficients. Sparse approaches have paved the way to several standard transformation encoding schemes, such as JPEG, JPEG2000, MPEG and MP3 that use compressive sparing. The principle is taken a step further by streamlined sensing, which decreases complexity and procurement computing costs. It will indeed utilise to instantly sense the data in a compressed form instead of the first sampling at a greater incidence and then the compression of the sampled data. If a signal has a recognised sparse representation the number of samples requisite can be reduced considerably under the Nyquist rate and still be able to retrieve the signal adequately under appropriate conditions. This system allows for data to be compressed when sensing, thus the term compressive sensing.