Quantum mechanics explains the behavior of matter and its movement with energy in the scale of atoms and subatomic particles. In quantum circuits there are many gates such as Hadamard Gate, Pauli Gates, many more gates for half turns, quarter turns, eighth turns, sixteenth turns and so on, rest for spinning, parametrized etc. Linear operators in general and quantum mechanics can be represented in the form of vectors and in turn can be viewed as matrices format because linear operators are totally equivalent with the matrices view point. This paper discloses creation of various quantum matrices using Quantum bits. Square, Identity and Transposition of matrices are performed considering whole process in entanglement. Angle, phase, coordinates, magnitude, complex numbers and amplitude has been noted and documented in this paper for further research.
For more information please visit http://crimsonpublishers.com/cojec/pdf/COJEC.000506.pdf
https://arxiv.org/abs/2011.04370
A concept of quantum computing is proposed which naturally incorporates an additional kind of uncertainty, i.e. vagueness (fuzziness), by introducing obscure qudits (qubits), which are simultaneously characterized by a quantum probability and a membership function. Along with the quantum amplitude, a membership amplitude for states is introduced. The Born rule is used for the quantum probability only, while the membership function can be computed through the membership amplitudes according to a chosen model. Two different versions are given here: the "product" obscure qubit in which the resulting amplitude is a product of the quantum amplitude and the membership amplitude, and the "Kronecker" obscure qubit, where quantum and vagueness computations can be performed independently (i.e. quantum computation alongside truth). The measurement and entanglement of obscure qubits are briefly described.
This document discusses image compression using the discrete cosine transform (DCT). It develops simple Mathematica functions to compute the 1D and 2D DCT. The 1D DCT transforms a list of real numbers into elementary frequency components. It is computed via matrix multiplication or using the discrete Fourier transform with twiddle factors. The 2D DCT applies the 1D DCT to rows and then columns, making it separable. These functions illustrate how Mathematica can be used to prototype image processing algorithms.
The document discusses the dynamic response of structures with uncertain properties. It begins with an introduction discussing how stochasticity impacts dynamic response and efficient quantification of uncertainty. It then covers stochastic single degree of freedom and multiple degree of freedom damped systems. Equivalent damping factors are derived for single degree systems with random natural frequencies. The spectral function approach is also introduced for representing multiple degree of freedom stochastic systems in the frequency domain.
This document discusses fast algorithms for computing the discrete cosine transform (DCT) and inverse discrete cosine transform (IDCT) using Winograd's method.
The conventional DCT and IDCT algorithms have high computational complexity due to cosine functions. Winograd's algorithm reduces the number of multiplications required for matrix multiplication by rearranging terms.
The document proposes applying Winograd's algorithm to DCT and IDCT computation by representing the transforms as matrix multiplications. This approach reduces the number of multiplications required for an 8x8 block from over 16,000 to just 736 multiplications, with fewer additions and subtractions as well. This leads to faster DCT and IDCT computation compared
Special Plenary Lecture at the International Conference on VIBRATION ENGINEERING AND TECHNOLOGY OF MACHINERY (VETOMAC), Lisbon, Portugal, September 10 - 13, 2018
http://www.conf.pt/index.php/v-speakers
Propagation of uncertainties in complex engineering dynamical systems is receiving increasing attention. When uncertainties are taken into account, the equations of motion of discretised dynamical systems can be expressed by coupled ordinary differential equations with stochastic coefficients. The computational cost for the solution of such a system mainly depends on the number of degrees of freedom and number of random variables. Among various numerical methods developed for such systems, the polynomial chaos based Galerkin projection approach shows significant promise because it is more accurate compared to the classical perturbation based methods and computationally more efficient compared to the Monte Carlo simulation based methods. However, the computational cost increases significantly with the number of random variables and the results tend to become less accurate for a longer length of time. In this talk novel approaches will be discussed to address these issues. Reduced-order Galerkin projection schemes in the frequency domain will be discussed to address the problem of a large number of random variables. Practical examples will be given to illustrate the application of the proposed Galerkin projection techniques.
This document discusses dynamics of structures with uncertainties. It begins with an introduction to stochastic single degree of freedom systems and how natural frequency variability can be modeled using probability distributions. It then discusses how to extend this approach to stochastic multi degree of freedom systems using stochastic finite element formulations and modal projections. Key challenges with statistical overlap of eigenvalues are noted. The document provides mathematical models of equivalent damping in stochastic systems and examples of stochastic frequency response functions.
In the last decades, a new model of computation based on quantum mechanics has gained attention in the computer science community. We give an introduction to this model starting from the basics, with no prerequisites. Then, with the help of some simple examples, we see why quantum computers outperform standard ones in certain tasks. We then move to the topic of quantum entanglement and show how sharing quantum information can create a strong provable correlation among distant parties. With this basic understanding of quantum computation and quantum entanglement, we can already illustrate two interesting cryptographic protocols: quantum key distribution and position verification. Both perform classically impossible tasks: the first allows to detect an intruder intercepting a secret communication, while the second allows certifying somebody's GPS location.
This document provides an introduction to blind source separation and non-negative matrix factorization. It describes blind source separation as a method to estimate original signals from observed mixed signals. Non-negative matrix factorization is introduced as a constraint-based approach to solving blind source separation using non-negativity. The alternating least squares algorithm is described for solving the non-negative matrix factorization problem. Experiments applying these methods to artificial and real image data are presented and discussed.
https://arxiv.org/abs/2011.04370
A concept of quantum computing is proposed which naturally incorporates an additional kind of uncertainty, i.e. vagueness (fuzziness), by introducing obscure qudits (qubits), which are simultaneously characterized by a quantum probability and a membership function. Along with the quantum amplitude, a membership amplitude for states is introduced. The Born rule is used for the quantum probability only, while the membership function can be computed through the membership amplitudes according to a chosen model. Two different versions are given here: the "product" obscure qubit in which the resulting amplitude is a product of the quantum amplitude and the membership amplitude, and the "Kronecker" obscure qubit, where quantum and vagueness computations can be performed independently (i.e. quantum computation alongside truth). The measurement and entanglement of obscure qubits are briefly described.
This document discusses image compression using the discrete cosine transform (DCT). It develops simple Mathematica functions to compute the 1D and 2D DCT. The 1D DCT transforms a list of real numbers into elementary frequency components. It is computed via matrix multiplication or using the discrete Fourier transform with twiddle factors. The 2D DCT applies the 1D DCT to rows and then columns, making it separable. These functions illustrate how Mathematica can be used to prototype image processing algorithms.
The document discusses the dynamic response of structures with uncertain properties. It begins with an introduction discussing how stochasticity impacts dynamic response and efficient quantification of uncertainty. It then covers stochastic single degree of freedom and multiple degree of freedom damped systems. Equivalent damping factors are derived for single degree systems with random natural frequencies. The spectral function approach is also introduced for representing multiple degree of freedom stochastic systems in the frequency domain.
This document discusses fast algorithms for computing the discrete cosine transform (DCT) and inverse discrete cosine transform (IDCT) using Winograd's method.
The conventional DCT and IDCT algorithms have high computational complexity due to cosine functions. Winograd's algorithm reduces the number of multiplications required for matrix multiplication by rearranging terms.
The document proposes applying Winograd's algorithm to DCT and IDCT computation by representing the transforms as matrix multiplications. This approach reduces the number of multiplications required for an 8x8 block from over 16,000 to just 736 multiplications, with fewer additions and subtractions as well. This leads to faster DCT and IDCT computation compared
Special Plenary Lecture at the International Conference on VIBRATION ENGINEERING AND TECHNOLOGY OF MACHINERY (VETOMAC), Lisbon, Portugal, September 10 - 13, 2018
http://www.conf.pt/index.php/v-speakers
Propagation of uncertainties in complex engineering dynamical systems is receiving increasing attention. When uncertainties are taken into account, the equations of motion of discretised dynamical systems can be expressed by coupled ordinary differential equations with stochastic coefficients. The computational cost for the solution of such a system mainly depends on the number of degrees of freedom and number of random variables. Among various numerical methods developed for such systems, the polynomial chaos based Galerkin projection approach shows significant promise because it is more accurate compared to the classical perturbation based methods and computationally more efficient compared to the Monte Carlo simulation based methods. However, the computational cost increases significantly with the number of random variables and the results tend to become less accurate for a longer length of time. In this talk novel approaches will be discussed to address these issues. Reduced-order Galerkin projection schemes in the frequency domain will be discussed to address the problem of a large number of random variables. Practical examples will be given to illustrate the application of the proposed Galerkin projection techniques.
This document discusses dynamics of structures with uncertainties. It begins with an introduction to stochastic single degree of freedom systems and how natural frequency variability can be modeled using probability distributions. It then discusses how to extend this approach to stochastic multi degree of freedom systems using stochastic finite element formulations and modal projections. Key challenges with statistical overlap of eigenvalues are noted. The document provides mathematical models of equivalent damping in stochastic systems and examples of stochastic frequency response functions.
In the last decades, a new model of computation based on quantum mechanics has gained attention in the computer science community. We give an introduction to this model starting from the basics, with no prerequisites. Then, with the help of some simple examples, we see why quantum computers outperform standard ones in certain tasks. We then move to the topic of quantum entanglement and show how sharing quantum information can create a strong provable correlation among distant parties. With this basic understanding of quantum computation and quantum entanglement, we can already illustrate two interesting cryptographic protocols: quantum key distribution and position verification. Both perform classically impossible tasks: the first allows to detect an intruder intercepting a secret communication, while the second allows certifying somebody's GPS location.
This document provides an introduction to blind source separation and non-negative matrix factorization. It describes blind source separation as a method to estimate original signals from observed mixed signals. Non-negative matrix factorization is introduced as a constraint-based approach to solving blind source separation using non-negativity. The alternating least squares algorithm is described for solving the non-negative matrix factorization problem. Experiments applying these methods to artificial and real image data are presented and discussed.
This 3 sentence summary provides the key details from the document:
The document describes using a 1-D engine simulation model in GT-POWER to develop and test a model predictive control strategy for an internal combustion engine, where predictive models of the engine were identified using the LOLIMOT algorithm and incorporated into a model-based predictive controller, and this control strategy was first tested in a model-in-the-loop simulation and then later validated through hardware-in-the-loop experiments on a real engine testbed.
This document discusses developing near-optimal state feedback controllers for nonlinear discrete-time systems using iterative approximate dynamic programming (ADP) algorithms. Specifically:
1) An infinite-horizon optimal state feedback controller is developed for discrete-time systems based on the dual heuristic programming (DHP) algorithm.
2) A new optimal control scheme is developed using the generalized DHP (GDHP) algorithm and a discounted cost functional.
3) An infinite-horizon optimal stabilizing state feedback controller is designed based on the globalized dual heuristic programming (GHJB) algorithm.
4) Finite-horizon optimal controllers with an ε-error bound are proposed, where the number of optimal control steps can be determined
Tensor representations in signal processing and machine learning (tutorial ta...Tatsuya Yokota
Tutorial talk in APSIPA-ASC 2020.
Title: Tensor representations in signal processing and machine learning.
Introduction to tensor decomposition (テンソル分解入門)
Basics of tensor decomposition (テンソル分解の基礎)
The document summarizes quantum Fourier transforms (QFTs) for 1, 2, and 3 qubit systems. It shows that a 1 qubit QFT is equivalent to a Hadamard gate. For 2 and 3 qubits, it represents the QFT formulas as quantum circuits, and verifies that they perform the Fourier transform by examining the state at each gate. The QFT generalizes the discrete Fourier transform to operate on quantum states, allowing it to be used in algorithms like Shor's algorithm.
Illustration Clamor Echelon Evaluation via Prime Piece PsychotherapyIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
The document describes a discrete-time Kalman filter implemented in MATLAB to estimate the position of an underwater vehicle using sensor measurements. It presents the state space modeling equations used in the filter, including modifying the state vector to address non-linearities in the direction measurement. Simulation results using a carefully designed trajectory show the filter provides estimates with errors generally within a few meters for position, a few centimeters for velocity bias, and a few meters for range over 1000 iterations.
Simulations of a typical CMOS amplifier circuit using the Monte Carlo methodIJERA Editor
In the present paper of Microelectronics, some simulations of a typical circuit of amplification, using a CMOS transistor, through the computational tools were performed. At that time, PSPICE® was used, where it was possible to observe the results, which are detailed in this work. The imperfections of the component due to manufacturing processes were obtained from simulations using the Monte Carlo method. The circuit operating point, mean and standard deviation were obtained and the influence of the threshold voltage Vth was analyzed.
This document discusses image compression using the discrete cosine transform (DCT). It develops simple Mathematica functions to compute the 1D and 2D DCT. The 1D DCT transforms a list of real numbers into elementary frequency components. It is computed via matrix multiplication or using the discrete Fourier transform with twiddle factors. The 2D DCT applies the 1D DCT to rows and then columns of an image, making it separable. These functions illustrate how Mathematica can be used to prototype image processing algorithms.
This document discusses image compression using the discrete cosine transform (DCT). It begins by explaining the 1D DCT and how it converts a signal into elementary frequency components. It then shows how to compute the 1D and 2D DCT using Mathematica functions. The 2D DCT is computed by applying the 1D DCT to rows and then columns of an image. Examples compress a test image and recover it to demonstrate the process works as expected.
This document contains an exam for an Instrumentation course with 8 questions. Question 1 defines key terms related to instrumentation accuracy and errors. Question 2 describes the principle and applications of the Bourdon tube and ionization gauge. Question 3 derives an expression for potentiometric transducers and calculates the maximum nonlinearity error and optimal potentiometer value. Question 4 discusses materials used in strain gauges and the relationship between gauge factor and Poisson's ratio. Question 5 explains the magnetostrictive effect and operation of a magnetostrictive transducer and photo pulse pickup transducer. Question 6 describes the principles of dual slope integrating analog to digital conversion. Question 7 explains dual slope ramp digital voltmeters and laser Doppler anemometry. Question 8
A Redundant Adder Architecture in Ternary Quantum-Dot Cellular AutomataVIT-AP University
Now researchers are moving toward emerging technologies to replace the
conventional CMOS technology. Quantum-dot cellular automata (QCA) are one of
them for high-performance computing circuits. Ternary QCA is one of the finest
research areas in this domain for replacement of binary logic. In this paper, we
proposed a new redundant adder architecture using Ternary QCA technology. Our proposed architecture has 233 numbers of cells with an area of 0.35 μm2. All the proposed ternary logic layouts are implemented in TQCA designer tool.
This is my second version of the quantum notes collected as part of my study.
This organizes content from various open source for study and reference only.
Quantum Computing 101, Part 1 - Hello Quantum WorldAaronTurner9
This is the first part of a blog series on quantum computing, broadly derived from CERN’s Practical introduction to quantum computing video series, Michael Nielson’s Quantum computing for the determined video series, and the following (widely regarded as definitive) references:
• [Hidary] Quantum Computing: An Applied Approach
• [Nielsen & Chuang] Quantum Computing and Quantum Information [a.k.a. “Mike & Ike”]
• [Yanofsky & Mannucci] Quantum Computing for Computer Scientists
My objective is to keep the mathematics to an absolute minimum (albeit not quite zero), in order to engender an intuitive understanding. You can think it as a quantum computing cheat sheet.
This document contains the instructions and content for a physics exam consisting of 9 questions testing knowledge of topics including: circuits, electrostatics, logic gates, alternating currents, radioactivity, and the Rutherford scattering experiment. The exam provides relevant physical constants, diagrams, and equations to aid in solving problems testing conceptual understanding and calculations. It directs students to show all work and uses the exam code, test format, and copyright statement to identify the assessment and protect content.
This document contains the instructions and content for a physics exam. It includes:
1) Instructions for candidates on the structure of the exam and requirements for completing it.
2) A list of common physical constants for reference.
3) Nine exam questions covering topics in physics like electricity, electronics, optics, and nuclear physics. Each question contains multiple parts requiring calculations and explanations.
4) Diagrams, figures, and equations to support the questions.
In summary, the document provides a physics exam paper testing knowledge across several core topics in the subject through multiple choice and free response questions.
This document outlines the syllabus for the subject Digital Principles and System Design. It contains 5 units that cover topics such as Boolean algebra, logic gates, combinational logic, sequential logic, asynchronous sequential logic, memory and programmable logic. The objectives of the course are to understand logic simplification methods, design combinational and sequential logic circuits using HDL, understand various types of memory and programmable devices. The syllabus allocates 45 periods to cover all the units in depth. Relevant textbooks and references are also provided.
This document summarizes an electrical engineering student's final project report on using an Unscented Kalman Filter (UKF) to estimate the state of a balancing robot. The UKF was able to accurately track states and uncertainties in simulation, but had difficulty estimating the true robot length from experimental datasets, likely due to insufficient oscillation of the robot. While the UKF and Extended KF agreed on the estimated length, more accurate methods may be needed such as Monte Carlo simulation with more samples.
Precise position control of a magnetic levitation system System using Differe...CHANDRASHEKHAR GUTTE
A cascaded sliding mode control for magnetic levitation systems. A disturbance observer-based sliding mode controller is designed for the electrical loop while a state and disturbance observer-based sliding mode controller is designed for the electromechanical loop. The overall stability of the system is rigorously established. The performance of the proposed scheme is compared with a conventional linear quadratic regulator combined with a proportional-integral controller by simulation as well as experimentation on a magnetic levitation setup in a laboratory
An enhanced control strategy based imaginary swapping instant for induction m...IJECEIAES
This document presents a novel control approach for an induction motor using an improved direct torque control with space vector modulation (DTC-SVM) based on an imaginary swapping instant technique. The control strategy aims to reduce the torque and flux ripples of the induction motor by using imaginary vectors to determine the effective period for power transfer, without requiring sector determination or angle identification. Simulation results show that the proposed adaptive DTC technique significantly reduces torque and flux ripples compared to the conventional direct torque control, and provides better performance and robustness against parameter variations.
Design of Binary to BCD Code Converter using Area Optimized Quantum Dot Cellu...CSCJournals
The Integrated Circuit Technology (IC) is growing day to day to improve circuit performance and density for compact systems. A novel technology, Quantum dot Cellular Automata (QCA) was introduced to overcome the scaling limitations of CMOS technology. In order to bring a new paradigm of IC design in an efficient and optimized manner, a binary to BCD code converter is designed using QCA technology based area optimized adder. It is observed that the proposed binary to BCD code converter design gives better results in terms of the area and number of QCA cells. The results obtained by the proposed design shows that 61% of area reduced compared to boolean expression based design, this design is further optimized to reduce the QCA cell count by 45% with respect to the design in [1].
This document summarizes a presentation on multiscale modeling of organic photovoltaic devices. It discusses the operating principles of organic solar cells and their internal morphologies. It then presents the mathematical model developed, which uses a multiscale approach to model exciton transport and dissociation, charge transport, and the electric field. Numerical results are shown applying the model to different device structures, demonstrating the effects of morphology on performance. Applications to light harvesting capacitors and artificial retinas are also discussed.
This 3 sentence summary provides the key details from the document:
The document describes using a 1-D engine simulation model in GT-POWER to develop and test a model predictive control strategy for an internal combustion engine, where predictive models of the engine were identified using the LOLIMOT algorithm and incorporated into a model-based predictive controller, and this control strategy was first tested in a model-in-the-loop simulation and then later validated through hardware-in-the-loop experiments on a real engine testbed.
This document discusses developing near-optimal state feedback controllers for nonlinear discrete-time systems using iterative approximate dynamic programming (ADP) algorithms. Specifically:
1) An infinite-horizon optimal state feedback controller is developed for discrete-time systems based on the dual heuristic programming (DHP) algorithm.
2) A new optimal control scheme is developed using the generalized DHP (GDHP) algorithm and a discounted cost functional.
3) An infinite-horizon optimal stabilizing state feedback controller is designed based on the globalized dual heuristic programming (GHJB) algorithm.
4) Finite-horizon optimal controllers with an ε-error bound are proposed, where the number of optimal control steps can be determined
Tensor representations in signal processing and machine learning (tutorial ta...Tatsuya Yokota
Tutorial talk in APSIPA-ASC 2020.
Title: Tensor representations in signal processing and machine learning.
Introduction to tensor decomposition (テンソル分解入門)
Basics of tensor decomposition (テンソル分解の基礎)
The document summarizes quantum Fourier transforms (QFTs) for 1, 2, and 3 qubit systems. It shows that a 1 qubit QFT is equivalent to a Hadamard gate. For 2 and 3 qubits, it represents the QFT formulas as quantum circuits, and verifies that they perform the Fourier transform by examining the state at each gate. The QFT generalizes the discrete Fourier transform to operate on quantum states, allowing it to be used in algorithms like Shor's algorithm.
Illustration Clamor Echelon Evaluation via Prime Piece PsychotherapyIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
The document describes a discrete-time Kalman filter implemented in MATLAB to estimate the position of an underwater vehicle using sensor measurements. It presents the state space modeling equations used in the filter, including modifying the state vector to address non-linearities in the direction measurement. Simulation results using a carefully designed trajectory show the filter provides estimates with errors generally within a few meters for position, a few centimeters for velocity bias, and a few meters for range over 1000 iterations.
Simulations of a typical CMOS amplifier circuit using the Monte Carlo methodIJERA Editor
In the present paper of Microelectronics, some simulations of a typical circuit of amplification, using a CMOS transistor, through the computational tools were performed. At that time, PSPICE® was used, where it was possible to observe the results, which are detailed in this work. The imperfections of the component due to manufacturing processes were obtained from simulations using the Monte Carlo method. The circuit operating point, mean and standard deviation were obtained and the influence of the threshold voltage Vth was analyzed.
This document discusses image compression using the discrete cosine transform (DCT). It develops simple Mathematica functions to compute the 1D and 2D DCT. The 1D DCT transforms a list of real numbers into elementary frequency components. It is computed via matrix multiplication or using the discrete Fourier transform with twiddle factors. The 2D DCT applies the 1D DCT to rows and then columns of an image, making it separable. These functions illustrate how Mathematica can be used to prototype image processing algorithms.
This document discusses image compression using the discrete cosine transform (DCT). It begins by explaining the 1D DCT and how it converts a signal into elementary frequency components. It then shows how to compute the 1D and 2D DCT using Mathematica functions. The 2D DCT is computed by applying the 1D DCT to rows and then columns of an image. Examples compress a test image and recover it to demonstrate the process works as expected.
This document contains an exam for an Instrumentation course with 8 questions. Question 1 defines key terms related to instrumentation accuracy and errors. Question 2 describes the principle and applications of the Bourdon tube and ionization gauge. Question 3 derives an expression for potentiometric transducers and calculates the maximum nonlinearity error and optimal potentiometer value. Question 4 discusses materials used in strain gauges and the relationship between gauge factor and Poisson's ratio. Question 5 explains the magnetostrictive effect and operation of a magnetostrictive transducer and photo pulse pickup transducer. Question 6 describes the principles of dual slope integrating analog to digital conversion. Question 7 explains dual slope ramp digital voltmeters and laser Doppler anemometry. Question 8
A Redundant Adder Architecture in Ternary Quantum-Dot Cellular AutomataVIT-AP University
Now researchers are moving toward emerging technologies to replace the
conventional CMOS technology. Quantum-dot cellular automata (QCA) are one of
them for high-performance computing circuits. Ternary QCA is one of the finest
research areas in this domain for replacement of binary logic. In this paper, we
proposed a new redundant adder architecture using Ternary QCA technology. Our proposed architecture has 233 numbers of cells with an area of 0.35 μm2. All the proposed ternary logic layouts are implemented in TQCA designer tool.
This is my second version of the quantum notes collected as part of my study.
This organizes content from various open source for study and reference only.
Quantum Computing 101, Part 1 - Hello Quantum WorldAaronTurner9
This is the first part of a blog series on quantum computing, broadly derived from CERN’s Practical introduction to quantum computing video series, Michael Nielson’s Quantum computing for the determined video series, and the following (widely regarded as definitive) references:
• [Hidary] Quantum Computing: An Applied Approach
• [Nielsen & Chuang] Quantum Computing and Quantum Information [a.k.a. “Mike & Ike”]
• [Yanofsky & Mannucci] Quantum Computing for Computer Scientists
My objective is to keep the mathematics to an absolute minimum (albeit not quite zero), in order to engender an intuitive understanding. You can think it as a quantum computing cheat sheet.
This document contains the instructions and content for a physics exam consisting of 9 questions testing knowledge of topics including: circuits, electrostatics, logic gates, alternating currents, radioactivity, and the Rutherford scattering experiment. The exam provides relevant physical constants, diagrams, and equations to aid in solving problems testing conceptual understanding and calculations. It directs students to show all work and uses the exam code, test format, and copyright statement to identify the assessment and protect content.
This document contains the instructions and content for a physics exam. It includes:
1) Instructions for candidates on the structure of the exam and requirements for completing it.
2) A list of common physical constants for reference.
3) Nine exam questions covering topics in physics like electricity, electronics, optics, and nuclear physics. Each question contains multiple parts requiring calculations and explanations.
4) Diagrams, figures, and equations to support the questions.
In summary, the document provides a physics exam paper testing knowledge across several core topics in the subject through multiple choice and free response questions.
This document outlines the syllabus for the subject Digital Principles and System Design. It contains 5 units that cover topics such as Boolean algebra, logic gates, combinational logic, sequential logic, asynchronous sequential logic, memory and programmable logic. The objectives of the course are to understand logic simplification methods, design combinational and sequential logic circuits using HDL, understand various types of memory and programmable devices. The syllabus allocates 45 periods to cover all the units in depth. Relevant textbooks and references are also provided.
This document summarizes an electrical engineering student's final project report on using an Unscented Kalman Filter (UKF) to estimate the state of a balancing robot. The UKF was able to accurately track states and uncertainties in simulation, but had difficulty estimating the true robot length from experimental datasets, likely due to insufficient oscillation of the robot. While the UKF and Extended KF agreed on the estimated length, more accurate methods may be needed such as Monte Carlo simulation with more samples.
Precise position control of a magnetic levitation system System using Differe...CHANDRASHEKHAR GUTTE
A cascaded sliding mode control for magnetic levitation systems. A disturbance observer-based sliding mode controller is designed for the electrical loop while a state and disturbance observer-based sliding mode controller is designed for the electromechanical loop. The overall stability of the system is rigorously established. The performance of the proposed scheme is compared with a conventional linear quadratic regulator combined with a proportional-integral controller by simulation as well as experimentation on a magnetic levitation setup in a laboratory
An enhanced control strategy based imaginary swapping instant for induction m...IJECEIAES
This document presents a novel control approach for an induction motor using an improved direct torque control with space vector modulation (DTC-SVM) based on an imaginary swapping instant technique. The control strategy aims to reduce the torque and flux ripples of the induction motor by using imaginary vectors to determine the effective period for power transfer, without requiring sector determination or angle identification. Simulation results show that the proposed adaptive DTC technique significantly reduces torque and flux ripples compared to the conventional direct torque control, and provides better performance and robustness against parameter variations.
Design of Binary to BCD Code Converter using Area Optimized Quantum Dot Cellu...CSCJournals
The Integrated Circuit Technology (IC) is growing day to day to improve circuit performance and density for compact systems. A novel technology, Quantum dot Cellular Automata (QCA) was introduced to overcome the scaling limitations of CMOS technology. In order to bring a new paradigm of IC design in an efficient and optimized manner, a binary to BCD code converter is designed using QCA technology based area optimized adder. It is observed that the proposed binary to BCD code converter design gives better results in terms of the area and number of QCA cells. The results obtained by the proposed design shows that 61% of area reduced compared to boolean expression based design, this design is further optimized to reduce the QCA cell count by 45% with respect to the design in [1].
This document summarizes a presentation on multiscale modeling of organic photovoltaic devices. It discusses the operating principles of organic solar cells and their internal morphologies. It then presents the mathematical model developed, which uses a multiscale approach to model exciton transport and dissociation, charge transport, and the electric field. Numerical results are shown applying the model to different device structures, demonstrating the effects of morphology on performance. Applications to light harvesting capacitors and artificial retinas are also discussed.
This document discusses the design of minimum cost, fault tolerant adder circuits in reversible logic for quantum computing. It aims to minimize quantum cost, reduce critical path delay and number of gates, and optimize garbage outputs. The document provides an overview of reversible and quantum computing principles. It then proposes designs for reversible fault tolerant full adders and carry skip/lookahead adders. Performance is analyzed in terms of gates, garbage outputs, delay and quantum cost, showing improvements over existing designs. The document concludes the reversible circuit designs are preferable for quantum computing due to their lower quantum costs.
Quantum computing uses quantum mechanics phenomena like superposition and entanglement to perform operations on quantum bits (qubits) and solve certain problems much faster than classical computers. One such problem is integer factorization, for which Peter Shor devised an algorithm in 1994 that a quantum computer could solve much more efficiently than classical computers. While quantum computing is still in development, it has the potential to break popular encryption systems like RSA and simulate quantum systems. Practical implementations of quantum computing include ion traps, NMR, optical photons, and solid-state approaches. Quantum computing could enable applications in encryption-breaking, simulation, and cryptography, among other areas.
A Survey Paper on Different Encoding Techniques Based on Quantum ComputingIRJET Journal
This document provides an overview of different encoding techniques for quantum computing. It discusses key concepts in quantum computing including quantum bits (qubits), quantum gates, the no-cloning theorem, and the Bloch sphere. It also summarizes several commonly used quantum gates like CNOT, Toffoli, Fredkin, and Hadamard gates. Finally, it discusses some important data encoding protocols in quantum computing like BB84 and six-state protocols.
MP3 Audio Decoding involves perceptual audio encoding using psychoacoustic analysis and quantization. It uses a filter bank to split audio into 32 subbands and a hybrid filter bank combining MDCT and traditional filter banks. Quantization and encoding involves bit allocation across scalefactor bands based on masking thresholds from the psychoacoustic model. The decoder reconstructs audio using inverse quantization and filtering.
Similar to Quantum Matrices Using Quantum Gates (20)
127. Reviewer Certificate in BP InternationalManu Mitra
Manu Mitra received Certificate No. BPI/PR/Cert/2811G.33/MAN from the University of Bridgeport in the USA, dated March 12, 2024. The certificate was issued to Manu Mitra by the University of Bridgeport located in the United States of America.
126. Reviewer Certificate in BP InternationalManu Mitra
Manu Mitra received Certificate No. BPI/PR/Cert/_3628G/MAN from the University of Bridgeport, USA, dated March 11, 2024. The certificate was issued to Manu Mitra and is associated with the University of Bridgeport.
125. Reviewer Certificate in BP International [2024]Manu Mitra
Manu Mitra received Certificate No. BPI/PR/Cert/3067G.3/MAN from the University of Bridgeport in the USA, dated March 11, 2024. The certificate was issued to Manu Mitra by the University of Bridgeport located in the United States of America.
123. Reviewer Certificate in BP InternationalManu Mitra
Manu Mitra received Certificate No. BPI/PR/Cert/_7278A/MAN from the University of Bridgeport, USA, dated February 19, 2024. The certificate was issued to Manu Mitra by the University of Bridgeport located in the United States of America.
122. Reviewer Certificate in BP InternationalManu Mitra
Manu Mitra received Certificate No. BPI/PR/Cert/8900A/MAN from the University of Bridgeport, USA, dated February 3, 2024. The certificate was issued to Manu Mitra and lists his name, the certifying institution, the certificate number, and date of issuance.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.