AI Fairness-From Machine Learning to Federated Learning

This article reviews the theory of fairness in AI-frommachine learning to federated learning,where the constraints on precision AI fairness and perspective solutions are also discussed.For a reliable and quantitative evaluation of AI fairness,many associated concepts have been proposed,formulated and classified.However,the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure fairness.The privacy worries induce the data unfairness and hence,the biases in the datasets for evaluating AI fairness are unavoidable.The imbalance between algorithms’utility and humanization has further reinforced suchworries.Even for federated learning systems,these constraints on precision AI fairness still exist.Aperspective solution is to reconcile the federated learning processes and reduce biases and imbalances accordingly.

Characterization of amphiboles from the Kola super-deep borehole, Russia by Raman and infrared spectroscopy

We present here for the first time,the Raman and infrared spectroscopic investigation of amphiboles from the World's deepest borehole,the Kola super-deep borehole,at the depth of 11.66 km.The Kola Super-deep borehole(SG-3)(henceforth referred as KSDB)is located in the northwest of the Kola Peninsula in the northern frame of the Pechenga structure,Russia.It was drilled in the north-eastern part of the Baltic Shield(69о5’N,30о44’E)and reached a depth of 12.262 km.It has been drilled in the northern limb of the Pechenga geosyncline composed of rhythmically inter-bedded volcanogenic and tuffaceous-sedimentary strata extending to the NW at 300°–310°and dipping to SW at angles of 30°–50°.The SG-3 geological section is represented by two complexes–Proterozoic and Archaean.Amphibolite facies is dominant in the depth region from 6000 m to 12,000m to the deepest.The Raman spectra of the sample reveal abundant presence of plagioclase and amphiboles.The most distinct Raman peak in this study indicates the tremolite-ferro-actinolite rich enrichment of the borehole samples at this depth corroborating earlier conventional petrographic studies.

Temperature Dependent Zeno Time for a Two Level Atom Traversing through a Thermal Magnetic Barrier in the Framework of Weak Measurement

The Zeno time has been calculated for a metastable two-level atom tunneling through a interacting thermal magnetic field. The process of weak measurement has been utilized for the estimation of the timescale. Zeno time has been shown to be temperature dependent. From the calculation it is evident that the Zeno time decreases with the increase of temperature. Moreover, the result restricts the Zeno time to a maximum limiting value, irrespective of how frequent the measurement process is.

Quantum Path Predictability for an Electronic Mach-Zehnder Interferometer in Presence of Environment Induced Decoherence and Quantum Erasing Process

In this paper, we have estimated the temperature dependent path predictability for an electronic Mach-Zehnder interferometer. The increment of path predictability can directly be associated with stronger decoherence process. We have also theoretically predicted that placing two detectors in both the paths, which are at the same equilibrium temperature with the system, erases all the memory of path information and hence acts like a quantum eraser.