Sharif Digital Repository

There are several methods for measuring thin film thickness, however, for the analysis of liquid film motors [1] we need a method which is capable of measuring the thickness using a single image of the film. In this work, we use the colors that appear on thin films, such as soup bubbles, which is a result of light interference to calculate the thickness of the layer  

One of the most elusive problems in quantum mechanics is the transition between classical and quantum physics. This problem can be traced back to the Schrodinger's cat. A key element that lies at the center of this problem is the lack of a clear understanding and characterization of macroscopic quantum states. Our understanding of Macroscopic Quantumness relies on states such as the Greenberger-Horne-Zeilinger(GHZ) or the NOON state. Here we take a first principle approach to this problem. We start from coherence as the key quantity that captures the notion of quantumness and demand the quantumness to be collective and macroscopic. To this end, we introduce macroscopic coherence which is the... 

With confidence in the recorded observations, the RLS method no longer estimates the recorded measurements by sensors, i.e. the displacement and speed of the floors, and only estimates the parameters. In contrast, in the EKF method, in addition to estimating the structure's parameters, a more precise estimation of the observations recorded by the sensors has been done by accepting the noise in the recorded observations. These methods, which are based on the Bayesian updating, investigate the two primary sources of uncertainty in a problem: a) measurement noise or observation noise, and b) process noise, which includes modeling errors. In these methodologies, the unknown system parameters,... 

In this research, the numerical simulation of the natural convection is performed by using the smoothed particle hydrodynamics based on the artificial compressibility method. For this aim, the formulation of the artificial compressibility method in the Eulerian reference frame for the mass and momentum equations is written in the Lagragian reference frame and the Lagrangin form of the energy equation is also considered to compute the thermal effects. The benefit of the artificial compressibility-based incompressible SPH (ACISPH) method over the weakly compressible SPH (WCSPH) method for computing the natural convection is that there is no need in the formulation considered here to use any... 

Entanglement is one of the key resources of quantum information science which makes identification of entangled states essential to a wide range of quantum technologies and phenomena.This problem is however both computationally and experimentally challenging.Here we use autoencoder neural networks to find semi-optimal measurements for detection of entangled states. We show that it is possible to find high-performance entanglement detectors with as few as three measurements. Also, with the complete information of the state, we develop a neural network that can identify all two-qubits entangled states almost perfectly.This result paves the way for automatic development of efficient... 

The vortex tube is a simple device that injects compressed gas (air) tangentially into the vortex chamber through one or more injection nozzles. After entering, the flow becomes rotational and an axial cold flow goes towards the cold outlet and a peripheral hot flow goes towards the hot outlet. Besides all the different applications of the vortex tube, the main application of this device is cooling. Here, the goal is to optimize the geometry and physical conditions to improve the performance, which is done by using a commercial software and numerical analysis of a vortex tube to understand the flow physics and optimization. In this research, we use experimental and numerical data for... 

Increasing in social communication via electronic ways has been made social network analysis of these communications more important each day. One of the most important aspects in social network analysis is community detection in such networks. There are many different ways to extract communities from social graph structure which in some of them the content of communication between actors has been noticed in community extraction algorithm. In this thesis after a short survey over advantages and disadvantages of existing methods for community detection, a new method for extracting communities from social networks has been suggested which in addition to streaming property of data it spot the... 

Quantum Information Processing (QIP) is one of the active areas of research in both theoretical and experimental physics. Any experimental technique that is used for a scalable implementation of QIP must satisfy DiVincenzo’s criteria [17]. Nuclear Magnetic Resonance (NMR) satisfies many of these conditions, but it is not scalable and cannot initialize the qubits to pure state [28]. NMR can be a great platform for studying the fundamentals of QIP. In this project, for a two­qubit system, we prepare pseudo pure states from the initial mixed states by using unitary operations and implement CNOT gates. According to the results of our experiments, we can apply all the gates with high fidelity.... 

Today organometallic perovskites are very important in fabrication of solar cells. This materials have advantages like high mobility of charge carriers, changing in range of light aborption with changing in structures atoms, having longer charge carrier diffusion lengths than other materials, high stability and efficiency, Low-cost fabrication process, having capability of studying and processing in low temperatures and having flexibility because of Weak chemical bond in perovskite structure. Due to the low stability and rapid decomposition of this material with the presence of light and moisture, in this study has tried to use PbS quantum dots which is used in sensitive dye solar cells as... 

The importance of using a fast and automatic method to classify variable stars for large amounts of data is undeniable. There have been many attempts for classifying variable stars by traditional algorithms, which require long pre-processing time. In recent years, neural networks as classifiers have come to notice. This thesis proposes the Hierarchical Classification technique, which contains several models with the same network structure. Our pre-processing method produces input data by using light curves and the period. We use OGLE-IV variable stars database to train and test the performance of Convolutional Neural Networks based on the Hierarchical Classification technique. We see that...