Atomic-state diagnostics and optimization in cold-atom experiments

We report on the creation, observation and optimization of superposition states of cold atoms. In our experiments, rubidium atoms are prepared in a magneto-optical trap and later, after switching off the trapping fields, Faraday rotation of a weak probe beam is used to characterize atomic states prepared by application of appropriate light pulses and external magnetic fields. We discuss the signatures of polarization and alignment of atomic spin states and identify main factors responsible for deterioration of the atomic number and their coherence and present means for their optimization, like relaxation in the dark with the strobe probing. These results may be used for controlled preparation of cold atom samples and in situ magnetometry of static and transient fieldsComment: 15 pages and 9 figures (including supplementary information

Role of the molybdenum addition on the mechanical properties and structure of the NiCoMnIn alloys

In this paper, the influence of Mo addition on the structure and mechanical properties of the NiCoMnIn alloys have been studied. Series of polycrystalline NiCoMnIn alloys containing from 0 to 5 mas.% of Mo were produced by the arc melting technique. For the alloys containing Mo, two-phase microstructure was observed. Mo-rich precipitates were distributed randomly in the matrix. The relative volume fraction of the precipitates depends on the Mo content. The numbers of the Mo rich precipitates increases with the Mo contents. The structures of the phases were determined by the TEM. The mechanical properties of the alloys are strongly affected by Mo addition contents. Brittleness of the alloys increases with the Mo contents

Neural Network Contour Error Predictor in CNC Control Systems

Paper presented as poster presentation at MMAR 2016 conference (Międzyzdroje,Poland, 29 Aug.-1 Sept. 2016)This article presents a method for predicting contour error using artificial neural networks. Contour error is defined as the minimum distance between actual position and reference toolpath and is commonly used to measure machining precision of Computerized Numerically Controlled (CNC) machine tools. Offline trained Nonlinear Autoregressive networks with exogenous inputs (NARX) are used to predict following error in each axis. These values and information about toolpath geometry obtained from the interpolator are then used to compute the contour error. The method used for effective off-line training of the dynamic recurrent NARX neural networks is presented. Tests are performed that verify the contour error prediction accuracy using a biaxial CNC machine in a real-time CNC control system. The presented neural network based contour error predictor was used in a predictive feedrate optimization algorithm with constrained contour error

Topological Mott insulator in odd-integer filled Anderson lattice model with Hatsugai-Kohmoto interactions

Recently, quantum anomalous Hall state at odd integer filling in moir\'e stacked MoTe$_2$/WSe$_2$ has been convincingly interpreted as a topological Mott insulator state appearing due to strong interactions in {\it band} basis [arXiv:2210.11486]. In this work, we aim to analyze the formation of a topological Mott insulator due to interactions in {\it orbital} basis instead, being more natural for systems where interactions originate from the character of $f$ or $d$ orbitals rather than band flatness. For that reason, we study an odd-integer filled Anderson lattice model incorporating odd-parity hybridization between orbitals with different degrees of correlations introduced in the Hatsugai-Kohmoto spirit. We demonstrate that a topological Mott insulating state can be realized in a considered model only when weak intra- and inter-orbital correlations involving dispersive states are taken into account. Interestingly, we find that all topological transitions between trivial and $\mathbb{Z}_2$ topological Mott insulating phases are not accompanied by a spectral gap closing, consistently with a phenomenon called {\it first-order topological transition}. Instead, they are signaled by a kink developed in spectral function at one of the time reversal invariant momenta. We believe that our approach can provide insightful phenomenology of topological Mott insulators in spin-orbit coupled $f$ or $d$ electron systems.Comment: 7 pages, 4 fig

PSO based feedrate optimization with contour error constraints for NURBS toolpaths

Paper presented at MMAR 2016 conference (Międzyzdroje, Poland, 29 Aug.-1 Sept. 2016)Generation of a time-optimal feedrate profile for CNC machines has received significant attention in recent years. Most methods focus on achieving maximum allowable feedrate with constrained axial acceleration and jerk without considering manufacturing precision. Manufacturing precision is often defined as contour error which is the distance between desired and actual toolpaths. This paper presents a method of determining the maximum feedrate for NURBS toolpaths while constraining velocity, acceleration, jerk and contour error. Contour error is predicted during optimization by using an artificial neural-network. Optimization is performed by Particle Swarm Optimization with Augmented Lagrangian constraint handling technique. Results of a time-optimal feedrate profile generated for an example toolpath are presented to illustrate the capabilities of the proposed method

Correlation of eigenstates in the critical regime of quantum Hall systems

We extend the multifractal analysis of the statistics of critical wave functions in quantum Hall systems by calculating numerically the correlations of local amplitudes corresponding to eigenstates at two different energies. Our results confirm multifractal scaling relations which are different from those occurring in conventional critical phenomena. The critical exponent corresponding to the typical amplitude, $\alpha_0\approx 2.28$, gives an almost complete characterization of the critical behavior of eigenstates, including correlations. Our results support the interpretation of the local density of states being an order parameter of the Anderson transition.Comment: 17 pages, 9 Postscript figure