This paper proposes solutions that increase the efficiency of parallel program execution on high-performance computing systems when simulating heteroepitaxial growth on multiprocessor systems with shared memory. The developed algorithms aim to implement in software the simulation of heteroepitaxial growth on multiprocessor NUMA nodes with shared memory. The primary prerequisite for the effective execution of parallel programs on the resources of a multiprocessor node is the incorporation of an architectural approach to the implementation of algorithms for data transfer through the shared memory of NUMA nodes. The proposed algorithms for optimizing synchronization in shared memory systems enhance the efficiency of accessing the shared memory of a multiprocessor node and reduce the time required for barrier synchronization. The developed methods and algorithms are implemented in the form of software for multiprocessor NUMA nodes with shared memory.

Arrays of vertically oriented carbon nanotubes (VOCNTs) with a height from 25 to 100 $$\mu$$ m and a specific resistance from 1.5 to 4 $$\Omega$$ cm have been grown by catalytic chemical vapor deposition on the Si/HfO $${}_{2}$$ /Fe surface for the first time. The growth of VOCNTs on hafnium oxide is observed within a temperature range of $$625{-}725$$ °C and does not occur at $$T\geq 750$$ °C. At the same time, the temperature dependence of the VOCNT growth rate is characterized by a value of $$\sim$$ 1.5 eV. Using high-resolution scanning electron microscopy and Raman spectroscopy, the predominance of nanotubes with diameters from 1 to 10 nm in the array is shown. It has been revealed that HfO $${}_{2}$$ nanocrystallization during the annealing of substrates complicates the SEM analysis of catalytic Fe particles, whose size on the surface of initial amorphous HfO $${}_{2}$$ is $$2{-}5$$ nm.

The paper provides a brief review of modern achievements in quantum information science with problems and prospects in the development of quantum computing. The elementary mathematical model of quantum computing and the concept of quantum supremacy are discussed. The application of ultracold atoms for the implementation of quantum processors is considered.

Separation of diseased brain tissues from normal brain tissues is one of the most important tasks in any system for detecting brain tumors. It is important to note that the field of brain tumor analysis has effectively applied medical image processing techniques, particularly on MR images, to automate crucial procedures including extraction, segmentation, and classification for tumor detection. Computer-aided diagnostic techniques are getting harder to employ and yet have many unresolved issues since tumors can vary in their sizes, locations, and shapes. More research has been centered on the noninvasive imaging capabilities of MRI. As a result, electronic methods are used to diagnose brain malignancies. One of the most popular and commonly used electronic methods for detecting brain cancers is magnetic resonance imaging (MRI). Hence, the MRI brain image based brain tumor model has been designed using the modified Mask R-CNN. In this designed model, Van Cittert algorithm is used for pre-processing the brain tumor MRI images to deblur and improve the quality of the gathered input images. The preprocessed data are segmented using Mask-KRCNN, which divides recognized objects into their pixel-level segments. The KNN classification technique may be used to train the Mask R-CNN algorithm to handle overlapping objects with multiple classes. Accuracy, error, sensitivity, specificity, precision, FPR, FNR, F1-Score, MCC, Kappa, MK, FM, NPV, FOR and FDR are some of the performance metrics for this designed model. The attained performance metrics values for the proposed model are 96, 4, 93, 98, 93, 1, 6, 93, 95, 94, 86, 93, 98, 2, and 2 $$\%$$ . Thus, the modified mask R-CNN with KNN algorithm primarily based on segmentation and type for prediction of brain tumor types plays better than the existing version.

Based on an analysis of the main modern trends in the design of hyperspectral equipment, it is shown that when creating new small-sized devices for using in ground-based observation systems, the use of integrated optoelectronic circuits and optical components in planar design is promising. In particular, the expediency of using micromirror arrays in scanning systems and Mach–Zehnder planar interferometers in spectrum separation systems was noted. This makes it possible to abandon bulky, slow, and not always reliable mechanical components and create devices with on-line hyperspectral image recording.

Experimental data on studying the phonon and optical properties of GaAs nanowires with orientation (111) located on a gold substrate with the help of Raman scattering spectroscopy (RSS) and photoluminescence (PL) are presented. Structural parameters of nanowires are determined by the atomic-force microscopy (AFM) and scanning electron microscopy (SEM) methods. In the micro-RSS and micro-PL spectra of a single GaAs nanowire, the modes of optical phonons of GaAs and their overtones up to the third order and an exciton luminescence band are observed. In the micro-PL spectra, anisotropy of the PL intensity is observed; the maximum/minimum signal is observed at the polarization-vector direction along/across the wire. Mapping of nano-PL of a single GaAs nanowire is performed with a spatial resolution of 20 nm, which is significantly smaller than the diffraction limit. When passing to the nanometer scale, a plasmon amplification of the signal of the near-field exciton nano-PL conditioned by the metallized AFM-needle is revealed.

The results are presented on changes in the parameters of pseudo-MOS transistors based on silicon-on-sapphire (SOS) mesastructures upon irradiation with swift heavy ions (SHIs) of Xe $${}^{+26}$$ (150 MeV) and Bi $${}^{+51}$$ (670 MeV) to a fluence of $$2\,\times\,10^{11}$$ cm $${}^{-2}$$ , indicating the accumulation of mechanical stresses and charges in the intermediate ferroelectric (Fe) layers of HfO $${}_{2}$$ films (HO) with a thickness of 20 nm and Hf $${}_{0.5}$$ Zr $${}_{0.5}$$ O $${}_{2}$$ (HZO) laminated with inserts of Al $${}_{2}$$ O $${}_{3}$$ monolayers (HA, HZA) or without them. SOS heterostructures are formed by direct bonding and hydrogen transfer of a silicon film (500 nm) with HA and HZA nanolayers pre-applied by plasma-stimulated atomic layer deposition onto sapphire. Electrophysical parameters are determined from the drain current—gate voltage characteristics ( $$I_{\textrm{ds}}$$ – $$V_{\textrm{g}})$$ of pseudo-MOS transistors with tungsten drain/source electrodes (100 nm) deposited by magnetron sputtering on SOS mesastructures through a lithographic mask. Comparison of the characteristics with Raman scattering analysis showed the correspondence of the mechanical compressive stresses introduced by SHI irradiation in silicon with the ratios of the Xe and Bi track volumes in the HA ferroelectric and sapphire.

A technique for testing the hypothesis about the independence of random variables, based on a nonparametric pattern recognition algorithm, is used in the analysis of ambiguous dependencies. The pattern recognition algorithm meets the maximum likelihood criterion. The assessment of distribution laws in classes is carried out using initial statistical data under the assumption of independence and dependence of the random variables being compared. To estimate probability densities in classes, nonparametric Rosenblatt–Parzen statistics are used. The blurring coefficients of kernel functions in nonparametric estimates of probability densities in classes are determined from the condition of the minimum of their standard deviations. Under these conditions, estimates of the probabilities of pattern recognition errors in classes are calculated. Based on their minimum value, a decision is made on the independence or dependence of random variables. The hypothesis about a significant difference in the probabilities of pattern recognition errors in classes is tested. The use of the proposed technique allows us to bypass the problem of decomposing the range of values of random variables into intervals, which is characteristic of the Pearson criterion. The effectiveness of the proposed method is compared with the Pearson criterion. The results of computational experiments using the studied criteria in the analysis of ambiguous dependencies between random variables are presented.

The problem of angular orientation of a moving object is solved using measurements of the strapdown inertial navigation system (SINS) and the satellite navigation system (SNS) under the most general assumptions about the character of the angular motion of the object and probabilistic characteristics of noises in inertial measurements. The soltion is obtained in the form of an extended Kalman filter in which the direction cosines of rotation in an inertial coordinate system are used as estimated orientation parameters and the vector of measurements by the SNS and SINS accelerometers is used as the observation vector. An example illustrating the high stability and convergence rate of the process of estimating the chosen parameters of angular orientation of the moving object is presented.

The possibility of processing small-view hilbertograms by the Gerchberg–Papoulis method to restore the spatial distribution of the refractive index was studied. The method consists in iterative transitions from the function estimates in the frequency and coordinate spaces with correction based on a priori information. Numerical modeling of the refractive index reconstruction for various test functions by the Gerchberg–Papoulis method using the Radon data, known for four angles, has been carried out. Using a four-angle tomographic complex implemented on the basis of a modified IAB-463M shadow device, experimental studies were carried out by the example of optical Hilbert diagnostics of reacting media in a high-speed shooting mode (up to 2000 frames per second).