arXiv subjects

Muhammad Usman

Publications and source records attributed to Muhammad Usman.

At least 199 records · Page 11Linked to original sources

arXiv2019

Atomic-level Characterisation of Quantum Computer Arrays by Machine Learning

Atomic level qubits in silicon are attractive candidates for large-scale quantum computing, however, their quantum properties and controllability are sensitive to details such as the number of donor atoms comprising a qubit and their precise location. This work combines machine learning techniques with million-atom simulations of scanning-tunnelling-microscope (STM) images of dopants to formulate a theoretical framework capable of determining the number of dopants at a particular qubit location and their positions with exact lattice-site precision. A convolutional neural network was trained on 100,000 simulated STM images, acquiring a characterisation fidelity (number and absolute donor positions) of above 98\% over a set of 17,600 test images including planar and blurring noise. The method established here will enable a high-precision post-fabrication characterisation of dopant qubits in silicon, with high-throughput potentially alleviating the requirements on the level of resource required for quantum-based characterisation, which may be otherwise a challenge in the context of large qubit arrays for universal quantum computing.

cond-mat.mes-hall↗

arXiv2019

Analysis of Coauthorship Network in Political Science using Centrality Measures

In recent era, networks of data are growing massively and forming a shape of complex structure. Data scientists try to analyze different complex networks and utilize these networks to understand the complex structure of a network in a meaningful way. There is a need to detect and identify such a complex network in order to know how these networks provide communication means while using the complex structure. Social network analysis provides methods to explore and analyze such complex networks using graph theories, network properties and community detection algorithms. In this paper, an analysis of coauthorship network of Public Relation and Public Administration subjects of Microsoft Academic Graph (MAG) is presented, using common centrality measures. The authors belong to different research and academic institutes present all over the world. Cohesive groups of authors have been identified and ranked on the basis of centrality measures, such as betweenness, degree, page rank and closeness. Experimental results show the discovery of authors who are good in specific domain, have a strong field knowledge and maintain collaboration among their peers in the field of Public Relations and Public Administration.

cs.SI↗

arXiv2018

q-LMF: Quantum Calculus-based Least Mean Fourth Algorithm

Channel estimation is an essential part of modern communication systems as it enhances the overall performance of the system. In recent past a variety of adaptive learning methods have been designed to enhance the robustness and convergence speed of the learning process. However, the need for an optimal technique is still there. Herein, for non-Gaussian noisy environment we propose a new class of stochastic gradient algorithm for channel identification. The proposed $q$-least mean fourth ($q$-LMF) is an extension of least mean fourth (LMF) algorithm and it is based on the $q$-calculus which is also known as Jackson derivative. The proposed algorithm utilizes a novel concept of error-correlation energy and normalization of signal to ensure high convergence rate, better stability and low steady-state error. Contrary to the conventional LMF, the proposed method has more freedom for large step-sizes. Extensive experiments show significant gain in the performance of the proposed $q$-LMF algorithm in comparison to the contemporary techniques.

eess.SP↗

arXiv2018

Automating Motion Correction in Multishot MRI Using Generative Adversarial Networks

Multishot Magnetic Resonance Imaging (MRI) has recently gained popularity as it accelerates the MRI data acquisition process without compromising the quality of final MR image. However, it suffers from motion artifacts caused by patient movements which may lead to misdiagnosis. Modern state-of-the-art motion correction techniques are able to counter small degree motion, however, their adoption is hindered by their time complexity. This paper proposes a Generative Adversarial Network (GAN) for reconstructing motion free high-fidelity images while reducing the image reconstruction time by an impressive two orders of magnitude.

cs.CV↗

arXiv2018

Impact of disorder on the optoelectronic properties of GaN$_y$As$_{1-x-y}$Bi$_x$ alloys and heterostructures

We perform a systematic theoretical analysis of the nature and importance of alloy disorder effects on the electronic and optical properties of GaN$_{y}$As$_{1-x-y}$Bi$_{x}$ alloys and quantum wells (QWs), using large-scale atomistic supercell electronic structure calculations based on the tight-binding method. Using ordered alloy supercell calculations we also derive and parametrise an extended basis 14-band \textbf{k}$\cdot$\textbf{p} Hamiltonian for GaN$_{y}$As$_{1-x-y}$Bi$_{x}$. Comparison of the results of these models highlights the role played by short-range alloy disorder -- associated with substitutional nitrogen (N) and bismuth (Bi) incorporation -- in determining the details of the electronic and optical properties. Systematic analysis of large alloy supercells reveals that the respective impact of N and Bi on the band structure remain largely independent, a robust conclusion we find to be valid even in the presence of significant alloy disorder where N and Bi atoms share common Ga nearest neighbours. Our calculations reveal that N- (Bi-) related alloy disorder strongly influences the conduction (valence) band edge states, leading in QWs to strong carrier localisation, as well as inhomogeneous broadening and modification of the conventional selection rules for optical transitions. Our analysis provides detailed insight into key properties and trends in this unusual material system, and enables quantitative evaluation of the potential of GaN$_{y}$As$_{1-x-y}$Bi$_{x}$ alloys for applications in photonic and photovoltaic devices.

cond-mat.mtrl-sci↗

arXiv2018

Higgs dark energy in inert doublet model

Scalar fields are among the possible candidates for dark energy. This paper is devoted to the scalar fields from the inert doublet model, where instead of one as in the standard model, two SU(2) Higgs doublets are used. The component fields of one SU(2) doublet ($ϕ_1$) act in an identical way to the standard model Higgs while the component fields of the second SU(2) doublet ($ϕ_2$) are taken to be the dark energy candidate (which is done by assuming that the phase transition in the field has not yet occurred). It is found that one can arrange for late time acceleration (dark energy) by using an SU(2) Higgs doublet in the inert Higgs doublet model, whose vacuum expectation value is zero, in the quintessential regime.

physics.gen-ph↗

arXiv2018

Large-scale atomistic simulations demonstrate dominant alloy disorder effects in GaBi$_x$As$_{1-x}$/GaAs multiple quantum wells

Bismide semiconductor materials and heterostructures are considered a promising candidate for the design and implementation of photonic, thermoelectric, photovoltaic, and spintronic devices. This work presents a detailed theoretical study of the electronic and optical properties of strongly-coupled GaBi$_x$As$_{1-x}$/GaAs multiple quantum well (MQW) structures. Based on a systematic set of large-scale atomistic tight-binding calculations, our results reveal that the impact of atomic-scale fluctuations in alloy composition is stronger than the inter-well coupling effect, and plays an important role in the electronic and optical properties of MQW structures. Independent of QW geometry parameters, alloy disorder leads to a strong confinement of charge carriers, a large broadening of the hole energies, and a red shift in the ground-state transition wavelength. Polarisation-resolved optical transition strengths exhibit a striking effect of disorder, where the inhomogeneous broadening could exceed an order of magnitude for MQWs, in comparison to a factor of about three for single quantum wells. The strong influence of alloy disorder effects persists when small variations in the size and composition of MQWs typically expected in a realistic experimental environment are considered. The presented results highlight the limited scope of continuum methods and emphasise on the need for large-scale atomistic approaches to design devices with tailored functionalities based on the novel properties of bismide materials.

cond-mat.mtrl-sci↗

arXiv2018

SIT: A Lightweight Encryption Algorithm for Secure Internet of Things

The Internet of Things (IoT) being a promising technology of the future is expected to connect billions of devices. The increased number of communication is expected to generate mountains of data and the security of data can be a threat. The devices in the architecture are essentially smaller in size and low powered. Conventional encryption algorithms are generally computationally expensive due to their complexity and requires many rounds to encrypt, essentially wasting the constrained energy of the gadgets. Less complex algorithm, however, may compromise the desired integrity. In this paper we propose a lightweight encryption algorithm named as Secure IoT (SIT). It is a 64-bit block cipher and requires 64-bit key to encrypt the data. The architecture of the algorithm is a mixture of feistel and a uniform substitution-permutation network. Simulations result shows the algorithm provides substantial security in just five encryption rounds. The hardware implementation of the algorithm is done on a low cost 8-bit micro-controller and the results of code size, memory utilization and encryption/decryption execution cycles are compared with benchmark encryption algorithms. The MATLAB code for relevant simulations is available online at https://goo.gl/Uw7E0W.

cs.CR↗

arXiv2018

Using Deep Autoencoders for Facial Expression Recognition

Feature descriptors involved in image processing are generally manually chosen and high dimensional in nature. Selecting the most important features is a very crucial task for systems like facial expression recognition. This paper investigates the performance of deep autoencoders for feature selection and dimension reduction for facial expression recognition on multiple levels of hidden layers. The features extracted from the stacked autoencoder outperformed when compared to other state-of-the-art feature selection and dimension reduction techniques.

cs.CV↗

arXiv2018

Interactive Diversity Optimization of Environments

The design of a building requires an architect to balance a wide range of constraints: aesthetic, geometric, usability, lighting, safety, etc. At the same time, there are often a multiplicity of diverse designs that can meet these constraints equally well. Architects must use their skills and artistic vision to explore these rich but highly constrained design spaces. A number of computer-aided design tools use automation to provide useful analytical data and optimal designs with respect to certain fitness criteria. However, this automation can come at the expense of a designer's creative control. We propose uDOME, a user-in-the-loop system for computer-aided design exploration that balances automation and control by efficiently exploring, analyzing, and filtering the space of environment layouts to better inform an architect's decision-making. At each design iteration, uDOME provides a set of diverse designs which satisfy user-defined constraints and optimality criteria within a user defined parameterization of the design space. The user then selects a design and performs a similar optimization with the same or different parameters and objectives. This exploration process can be repeated as many times as the designer wishes. Our user studies indicates that \DOME, with its diversity-based approach, improves the efficiency and effectiveness of even novice users with minimal training, without compromising the quality of their designs.

cs.HC↗

arXiv2017

A Robust Variable Step Size Fractional Least Mean Square (RVSS-FLMS) Algorithm

In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).

math.OC↗

arXiv2017

The extra scalar degrees of freedom from the two Higgs doublet model for dark energy

In principle a minimal extension of the standard model of Particle Physics, the two Higgs doublet model, can be invoked to explain the scalar field responsible of dark energy. The two doublets are in general mixed. After diagonalization, the lightest CP-even Higgs and CP-odd Higgs are jointly taken to be the dark energy candidate. The dark energy obtained from Higgs fields in this case is indistinguishable from the cosmological constant.

physics.gen-ph↗

arXiv2017

Constraints on Two Higgs Doublet Model Parameters in the light of rare $B$-Decays

We established the allowed parameters of two-Higgs doublet model(2HDM) from flavor physics observables, precisely from rare $B$ meson decays. In our analysis most formidable constraints on the 2HDM parameters arise from the branching ratio of rare radiative $B$ meson decay i.e., $B\to X_{s}γ$. However, the constraints arising from the branching ratio of $B_{s}\toμ^{+}μ^{-}$ decay in $m_{H^{\pm}}-\tanβ$ plane give $m_{H^{\pm}} >$ 80 GeV for the value of $\tanβ\sim 2$, that is in agreement with large electron-positron collider (LEP) data. Furthermore, we also investigate the bounds on the $CP$-even $m_{H}$ and $CP$-odd $m_{A^{0}}$ Higgs boson not only from above mentioned physical observables, but also from the zero crossing of the forward-backward asymmetry of $B\to K^{\ast}μ^{+}μ^{-}$ decay. Therefore, these bounds on parameters of the 2HDM will provides a fertile ground to test the 2HDM at current and future $B$-physics experiments.

hep-ph↗

arXiv2017

A Meshless method of lines for the numerical solution of Coupled Drinfeld's-Sokolov-Wilson System

This paper applies meshless method of lines, which uses radial basis functions (RBFs) as a spatial collocation scheme to solve the Coupled Drinfeld's-Sokolov-Wilson System. Runge-Kutta method is used for time integration of the system of ODEs obtained as a result of spatial discretization in contrast to usual RBFs or finite difference methods. Accuracy (L2 and L1) is compared with the existing results from other methods available in the literature.

math.NA↗

arXiv2017

Two-electron states of a group V donor in silicon from atomistic full configuration interaction

Two-electron states bound to donors in silicon are important for both two qubit gates and spin readout. We present a full configuration interaction technique in the atomistic tight-binding basis to capture multi-electron exchange and correlation effects taking into account the full bandstructure of silicon and the atomic scale granularity of a nanoscale device. Excited $s$-like states of $A_1$-symmetry are found to strongly influence the charging energy of a negative donor centre. We apply the technique on sub-surface dopants subjected to gate electric fields, and show that bound triplet states appear in the spectrum as a result of decreased charging energy. The exchange energy, obtained for the two-electron states in various confinement regimes, may enable engineering electrical control of spins in donor-dot hybrid qubits.

cond-mat.mes-hall↗

arXiv2017

RVP-FLMS : A Robust Variable Power Fractional LMS Algorithm

In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm. The proposed algorithm named as robust variable power FLMS (RVP-FLMS) dynamically adapts the fractional power of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problems of system identification and channel equalization are considered. The experiments clearly show that the proposed approach achieves better convergence rate and lower steady-state error compared to the FLMS. The MATLAB code for the related simulation is available online at https://goo.gl/dGTGmP.

math.OC↗

arXiv2016

On the dark matter as a geometric effect in $f(\mathcal{R})$ gravity

A mysterious type of matter is supposed to exist, because the observed rotational velocity curves of particle moving around the galactic center and the expected rotational velocity curves do not match. There are also a number of proposals in the modified gravity for this discrepancy. In this contrast, in $2008$, B$\ddot{\text{o}}$hmer et al. presented an interesting idea in (Astropart Phys 29(6):386-392, 2008) where they showed that a $f(\mathcal{R})$ gravity model could actually explain dark matter to be a geometric effect only. They solved the gravitational field equations in vacuum using generic $f(\mathcal{R})$ gravity model for constant velocity regions and found that the resulting modifications in the Einstein-Hilbert Lagrangian is of the form $\mathcal{R}^{1+m}$, where $m=V_{tg}^2/c^2$; $V_{tg}$ being the tangential velocity of the test particle moving around galactic dark matter region and, $c$, the speed of light. From observations it is known that $m\approx\mathcal{O}(10^{-6})$. In this article, we perform two things (1) We show that the form of $f(\mathcal{R})$ they claimed is not correct. In doing the calculations, we found that when the radial component of the metric for constant velocity regions is a constant then the exact solutions for $f(\mathcal{R})$ obtained is of the form of $\mathcal{R}^{1-α}$ which corresponds to a negative correction rather than positive, $α$ is a function of $m$. (2) We also show that we can not have an analytic solution of $f(\mathcal{R})$ for all values of tangential velocity including the observed value of tangential velocity $200-300$Km/s if the radial coefficient of the metric which describes the dark matter regions is \emph{not a constant}. Thus, we have to rely on the numerical solutions to get an approximate model for dark matter in $f(\mathcal{R})$ gravity.

gr-qc↗

arXiv2016

Dark energy via multi-Higgs doublet models: accelerated expansion of the Universe in inert doublet model scenario

hep-ph↗