Abstract: The subject of quantum computing brings together ideas from classical information theory, computer
science, and quantum physics. This review aims to summarize not just quantum computing, but the whole
subject of quantum information theory. Information can be identified as the most general thing which must
propagate from a cause to an effect. It therefore has a fundamentally important role in the science of physics.
However, the mathematical treatment of information, especially information processing, is quite recent, dating
from the mid-20th century. This has meant that the full significance of information as a basic concept in physics
is only now being discovered. This is especially true in quantum mechanics. The theory of quantum information
and computing puts this significance on a firm footing, and has led to some profound and exciting new insights
into the natural world. Among these are the use of quantum states to permit the secure transmission of classical
information (quantum cryptography), the use of quantum entanglement to permit reliable transmission of
quantum states (teleportation), the possibility of preserving quantum coherence in the presence of irreversible
noise processes (quantum error correction), and the use of controlled quantum evolution for efficient
computation (quantum computation). The common theme of all these insights is the use of quantum
entanglement as a computational resource.
Keywords: quantum bits, quantum registers, quantum gates and quantum networks
The document discusses methods for studying quantum dynamics, localization, and quantum machine learning. It is divided into four parts. Part I develops numerical and analytical methods for studying complex quantum systems and their dynamics. Part II explores scenarios where dynamics is slow and information is localized, focusing on disorder-induced and kinetically constrained localization. Part III designs thermodynamic protocols to speed up thermalization while keeping dissipated work constant. Part IV examines intersections between tensor network methods and machine learning, applying techniques like neural network quantum states and tensor networks to problems in machine learning and approximating probability distributions.
Quantum information theory deals with integrating information theory with quantum mechanics by studying how information can be stored and retrieved from quantum systems. Quantum computing uses quantum physics and quantum bits (qubits) that can exist in superpositions of states to perform computations in parallel and solve problems like factoring prime numbers faster than classical computers. Key challenges for quantum computing include preventing decoherence and protecting fragile quantum states.
A quantum computer performs calculations using quantum mechanics and quantum properties like superposition and entanglement. It uses quantum bits (qubits) that can exist in superpositions of states unlike classical computer bits. A quantum computer could solve some problems, like factoring large numbers, much faster than classical computers. The document discusses the history of computing generations and quantum computing, how quantum computers work using qubits, superpositions and entanglement, and potential applications like encryption cracking and simulation.
Quantum computing provides an alternative computational model based on quantum mechanics. It utilizes quantum phenomena such as superposition and entanglement to perform computations using quantum logic gates on qubits. This allows quantum computers to potentially solve certain problems exponentially faster than classical computers. However, building large-scale quantum computers remains a challenge. In the meantime, smaller quantum systems are being developed and quantum algorithms are being experimentally tested on these devices. Researchers are also working on methods to efficiently simulate quantum computations on classical computers.
This document provides an overview of quantum computing, including its history, basic concepts, applications, advantages, difficulties, and future directions. It discusses how quantum computing originated in the 1980s with the goal of building a computer that is millions of times faster than classical computers and theoretically uses no energy. The basic concepts covered include quantum mechanics, superpositioning, qubits, quantum gates, and how quantum computers could perform calculations that are intractable on classical computers, such as factoring large numbers. The document also outlines some of the challenges facing quantum computing as well as potential future advances in the field.
This document provides an introduction to quantum computing, including its history, key concepts, applications, and current challenges. Some of the main points covered include:
- Quantum computing uses quantum phenomena like superposition and entanglement to perform operations on quantum bits (qubits).
- Important quantum computing concepts include qubits, quantum information, superposition, entanglement, teleportation, and parallelism.
- Potential applications include quantum networking, secure communications, artificial intelligence, and molecular simulations.
- Current challenges to developing quantum computers include limited qubit numbers and physical machine size. Further development could revolutionize computation for certain problems.
The Quantum computing has become a buzzword now a days, however it has not been the favorite of the researchers until recent times.
Let's follow about
What's Quantum Computing?
It's Evolution
Primary Focus
Future
This document provides an overview of a lecture on classical and quantum information theory. It discusses topics such as Maxwell's demon, the laws of thermodynamics, Shannon information theory, quantum measurement, the qubit model, and differences between classical and quantum information theory. The lecture aims to compare classical and quantum information concepts and highlight new properties that emerge from quantum mechanics.
The document discusses methods for studying quantum dynamics, localization, and quantum machine learning. It is divided into four parts. Part I develops numerical and analytical methods for studying complex quantum systems and their dynamics. Part II explores scenarios where dynamics is slow and information is localized, focusing on disorder-induced and kinetically constrained localization. Part III designs thermodynamic protocols to speed up thermalization while keeping dissipated work constant. Part IV examines intersections between tensor network methods and machine learning, applying techniques like neural network quantum states and tensor networks to problems in machine learning and approximating probability distributions.
Quantum information theory deals with integrating information theory with quantum mechanics by studying how information can be stored and retrieved from quantum systems. Quantum computing uses quantum physics and quantum bits (qubits) that can exist in superpositions of states to perform computations in parallel and solve problems like factoring prime numbers faster than classical computers. Key challenges for quantum computing include preventing decoherence and protecting fragile quantum states.
A quantum computer performs calculations using quantum mechanics and quantum properties like superposition and entanglement. It uses quantum bits (qubits) that can exist in superpositions of states unlike classical computer bits. A quantum computer could solve some problems, like factoring large numbers, much faster than classical computers. The document discusses the history of computing generations and quantum computing, how quantum computers work using qubits, superpositions and entanglement, and potential applications like encryption cracking and simulation.
Quantum computing provides an alternative computational model based on quantum mechanics. It utilizes quantum phenomena such as superposition and entanglement to perform computations using quantum logic gates on qubits. This allows quantum computers to potentially solve certain problems exponentially faster than classical computers. However, building large-scale quantum computers remains a challenge. In the meantime, smaller quantum systems are being developed and quantum algorithms are being experimentally tested on these devices. Researchers are also working on methods to efficiently simulate quantum computations on classical computers.
This document provides an overview of quantum computing, including its history, basic concepts, applications, advantages, difficulties, and future directions. It discusses how quantum computing originated in the 1980s with the goal of building a computer that is millions of times faster than classical computers and theoretically uses no energy. The basic concepts covered include quantum mechanics, superpositioning, qubits, quantum gates, and how quantum computers could perform calculations that are intractable on classical computers, such as factoring large numbers. The document also outlines some of the challenges facing quantum computing as well as potential future advances in the field.
This document provides an introduction to quantum computing, including its history, key concepts, applications, and current challenges. Some of the main points covered include:
- Quantum computing uses quantum phenomena like superposition and entanglement to perform operations on quantum bits (qubits).
- Important quantum computing concepts include qubits, quantum information, superposition, entanglement, teleportation, and parallelism.
- Potential applications include quantum networking, secure communications, artificial intelligence, and molecular simulations.
- Current challenges to developing quantum computers include limited qubit numbers and physical machine size. Further development could revolutionize computation for certain problems.
The Quantum computing has become a buzzword now a days, however it has not been the favorite of the researchers until recent times.
Let's follow about
What's Quantum Computing?
It's Evolution
Primary Focus
Future
This document provides an overview of a lecture on classical and quantum information theory. It discusses topics such as Maxwell's demon, the laws of thermodynamics, Shannon information theory, quantum measurement, the qubit model, and differences between classical and quantum information theory. The lecture aims to compare classical and quantum information concepts and highlight new properties that emerge from quantum mechanics.
Speaker: Mehran Shaghaghi
Ph.D. Candidate
Department of Physics and Astronomy, University of British Columbia, Canada
Title: Quantum Mechanics Dilemmas
Organized by the Knowledge Diffusion Network
Time: Tuesday, December 11th , 2007.
Location: Department of Physics, Sharif University of Technology, Tehran
1. Quantum computing is the research area centered on creating computer technology that uses quantum theory concepts that explain the nature and conduct of energy and matter at the level of the quantum (atomic and subatomic).
2. A quantum computer could achieve enormous processing power through multi-state capacity and execute functions simultaneously using all possible permutations.
3. This paper explores how quantum computing could improve analytical and computing capabilities for solving power system problems by enabling parallel processing across many potential solutions simultaneously.
Quantum Computer is a machine that is used for Quantum Computation with the help of using Quantum Physics properties. Where classical computers encode information in binary “bits” that can either 0s or 1s but quantum computer use Qubits. Like the classical computer, the Quantum computer also uses 0 and 1, but qubits have a third state that allows them to represent one or zero at the same time and it’s called “Superposition”. This research paper has presented the Basics of Quantum Computer and The Future of Quantum Computer. So why Quantum Computer can be Future Computer, Because Quantum Computer is faster than any other computer, as an example, IBM’s Computer Deep Blue examined 200 million possible chess moves each second. Quantum Computer would be able to examine 1 trillion possible chess moves per second. It can be 100 million times faster than a classical computer. The computer makes human life easier and also focuses on increasing performance to make technology better. One such way is to reduce the size of the transistor and another way is to use Quantum Computer. The main aim of this paper is to know that how Quantum Computers can become the future computer.
This document provides an overview of quantum computing, including:
- The current state of quantum computing technology, which involves noisy intermediate-scale quantum computers with 10s to 100s of qubits and moderate error rates.
- The difference between quantum and classical information, noting that quantum information uses superposition and entanglement, exponentially increasing computational power.
- An example quantum algorithm, Bernstein-Vazirani, which can solve a problem in one query that classical computers require n queries to solve, demonstrating quantum computing's potential computational advantages.
Building a quantum internet is a key ambition for many countries around the world, such a breakthrough will give them competitive advantage in a promising disruptive technology, and opens a new world of innovations and unlimited possibilities.
Quantum computers harness quantum mechanics to perform computations by taking advantage of properties like superposition and entanglement. As transistors continue shrinking to the quantum scale, quantum effects like tunneling pose problems for classical computing. Quantum computers represent qubits as quantum states and use gates to manipulate them, allowing multiple computations to occur simultaneously. While challenges remain, quantum computing could solve problems like the travelling salesman problem much faster by exploring many possibilities at once.
A file on Quantum Computing for people with least knowledge about physics, electronics, computers and programming. Perfect for people with management backgrounds. Covers understandable details about the topic.
Quantum Computers are the future and this manual explains the topic in the best possible way.
Few Applications of quantum physics or mechanics around the worldHome
This document provides a lab practical presentation on the topic of quantum physics. It includes the presenter's name, registration number, department, and institution. The introduction provides an overview of quantum mechanics, noting that it differs from classical physics in its treatment of energy, momentum, and other physical quantities at the atomic and subatomic scale. The document then discusses the historical development of quantum mechanics in the early 20th century by scientists like Planck, Einstein, Bohr, Schrodinger, Heisenberg, and others. It provides examples of quantum mechanics applications in areas like electronics, cryptography, quantum computing, nanotechnology, and medicine. The document concludes by emphasizing that quantum mechanics has enabled many modern technologies and influenced fields like
Quantum artificial intelligence.
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
Quantum Computers PART 3 Computer That Program itself by Prof. Lili SaghafiProfessor Lili Saghafi
The light switch game
The energy program
Calculate The Distance Between Two Large Vectors
Quantum Computers can LEARN
A computer that programs itself
Uncertainty is a feature
D-WaveQuantum ComputingAccess & applications via cloud deploymentRakuten Group, Inc.
D-Wave Systems provides quantum computing via cloud deployment. Their mission is to solve hard problems in AI/ML using their annealing-based quantum computers. They have developed hybrid quantum-classical algorithms and architectures. Their current product is the D-Wave 2000Q quantum processor with 2000 qubits. It uses superconducting qubits in a CMOS fabrication process. D-Wave has established the quantum effects of superposition, entanglement and tunneling on their processors. They are working to develop applications in finance, healthcare and machine learning using their quantum-classical hybrid approach.
The document discusses various research projects involving the automated design and optimization of complex physical, chemical, and biological systems using evolutionary algorithms and machine learning techniques. It describes current and planned usage of computer clusters to run simulations and experiments for protein structure prediction, software self-assembly, and modeling physico-chemical systems through evolutionary optimization of parameters. The research requires significant computational resources to process large datasets and evaluate models in parallel.
This document discusses several topics related to quantum information technology and quantum computing:
- It describes how a double quantum dot qubit works using electron states and how current tunneling can show interference.
- It explains that lower temperatures result in higher coherence times for qubits like double electron gallium arsenide qubits due to less electron-phonon coupling and dephasing.
- It discusses how error correction works in quantum computing by encoding logical qubits across multiple physical qubits to reduce error probabilities. Hardware-based error correction like Toffoli gates may be needed for larger quantum computers.
- Long-term quantum information storage over 180 seconds is demonstrated using donor spin qubits in silicon, where electron and nuclear spins are
Big Fast Data in High-Energy Particle PhysicsAndrew Lowe
Experiments at CERN (the European Organization for Nuclear Research) generate colossal amounts of data. Physicists must sift through about 30 petabytes of data produced annually in their search for new particles and interesting physics. The tidal wave of data produced by the Large Hadron Collider (LHC) at CERN places an unprecedented challenge for experiments' data acquisition systems, and it is the need to select rare physics processes with high efficiency while rejecting high-rate background processes that drives the architectural decisions and technology choices. Although filtering and managing large data sets is of course not exclusive to particle physics, the approach that has been taken is somewhat unique. In this talk, I describe the typical journey taken by data from the readout electronics of one experiment to the results of a physics analysis.
Introduction to Quantum Computation. Part - 1Arunabha Saha
Introduction to quantum computation. Here the very basic maths described needed for quantum information theory as well as computation. Postulates of quantum mechanics and the Hisenberg`s Uncertainty principle. Basic operator theories are described here.
Em computação quântica, um algoritmo quântico é um algoritmo que funciona em um modelo realístico de computação quântica. O modelo mais utilizado é o modelo do circuito de computação quântica.
String theory predicts 11 dimensions, with 10 defining space and 1 defining time. Small extra dimensions are predicted to be curled up in Calabi-Yau shapes within spacetime. This leaves 7 new dimensions that have not been directly observed. The document discusses theories that these new dimensions may exist as a non-local grid pattern between fundamental units of spacetime, known as quantum cells. This proposed grid could explain phenomena like entanglement and tunneling that are currently not accounted for within the standard model of physics.
This document presents a second order integral sliding mode control approach for speed control of a DC motor system. The DC motor system is modeled as a second order system with uncertainty and disturbances. Three controllers are designed and compared - a second order integral sliding mode controller, a conventional sliding mode controller, and a PID controller. Simulation results show that the proposed second order integral sliding mode controller has the fastest response time, no overshoot, smooth control input, and drives the sliding surface to zero, performing better than the other controllers in terms of robustness and disturbance rejection.
“Relationship of Kinematic Variables with the Performance of Standing Broad J...IOSR Journals
Abstract: The purpose of investigation was to study the relationship of kinematics variables with the
performance of standing broad jump. Subjects were randomly selected from J.N.V. University, Jodhpur and
M.D.S. University, Ajmer. The criterion measure used for this study was the performance in standing broad
jump and selected kinematics variables. To analyze the raw data coefficient of correlation (r) were calculated
and results were compared with the help of Analysis of variance (ANOVA) technique where level of significance
was set at .05.
Speaker: Mehran Shaghaghi
Ph.D. Candidate
Department of Physics and Astronomy, University of British Columbia, Canada
Title: Quantum Mechanics Dilemmas
Organized by the Knowledge Diffusion Network
Time: Tuesday, December 11th , 2007.
Location: Department of Physics, Sharif University of Technology, Tehran
1. Quantum computing is the research area centered on creating computer technology that uses quantum theory concepts that explain the nature and conduct of energy and matter at the level of the quantum (atomic and subatomic).
2. A quantum computer could achieve enormous processing power through multi-state capacity and execute functions simultaneously using all possible permutations.
3. This paper explores how quantum computing could improve analytical and computing capabilities for solving power system problems by enabling parallel processing across many potential solutions simultaneously.
Quantum Computer is a machine that is used for Quantum Computation with the help of using Quantum Physics properties. Where classical computers encode information in binary “bits” that can either 0s or 1s but quantum computer use Qubits. Like the classical computer, the Quantum computer also uses 0 and 1, but qubits have a third state that allows them to represent one or zero at the same time and it’s called “Superposition”. This research paper has presented the Basics of Quantum Computer and The Future of Quantum Computer. So why Quantum Computer can be Future Computer, Because Quantum Computer is faster than any other computer, as an example, IBM’s Computer Deep Blue examined 200 million possible chess moves each second. Quantum Computer would be able to examine 1 trillion possible chess moves per second. It can be 100 million times faster than a classical computer. The computer makes human life easier and also focuses on increasing performance to make technology better. One such way is to reduce the size of the transistor and another way is to use Quantum Computer. The main aim of this paper is to know that how Quantum Computers can become the future computer.
This document provides an overview of quantum computing, including:
- The current state of quantum computing technology, which involves noisy intermediate-scale quantum computers with 10s to 100s of qubits and moderate error rates.
- The difference between quantum and classical information, noting that quantum information uses superposition and entanglement, exponentially increasing computational power.
- An example quantum algorithm, Bernstein-Vazirani, which can solve a problem in one query that classical computers require n queries to solve, demonstrating quantum computing's potential computational advantages.
Building a quantum internet is a key ambition for many countries around the world, such a breakthrough will give them competitive advantage in a promising disruptive technology, and opens a new world of innovations and unlimited possibilities.
Quantum computers harness quantum mechanics to perform computations by taking advantage of properties like superposition and entanglement. As transistors continue shrinking to the quantum scale, quantum effects like tunneling pose problems for classical computing. Quantum computers represent qubits as quantum states and use gates to manipulate them, allowing multiple computations to occur simultaneously. While challenges remain, quantum computing could solve problems like the travelling salesman problem much faster by exploring many possibilities at once.
A file on Quantum Computing for people with least knowledge about physics, electronics, computers and programming. Perfect for people with management backgrounds. Covers understandable details about the topic.
Quantum Computers are the future and this manual explains the topic in the best possible way.
Few Applications of quantum physics or mechanics around the worldHome
This document provides a lab practical presentation on the topic of quantum physics. It includes the presenter's name, registration number, department, and institution. The introduction provides an overview of quantum mechanics, noting that it differs from classical physics in its treatment of energy, momentum, and other physical quantities at the atomic and subatomic scale. The document then discusses the historical development of quantum mechanics in the early 20th century by scientists like Planck, Einstein, Bohr, Schrodinger, Heisenberg, and others. It provides examples of quantum mechanics applications in areas like electronics, cryptography, quantum computing, nanotechnology, and medicine. The document concludes by emphasizing that quantum mechanics has enabled many modern technologies and influenced fields like
Quantum artificial intelligence.
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
Quantum Computers PART 3 Computer That Program itself by Prof. Lili SaghafiProfessor Lili Saghafi
The light switch game
The energy program
Calculate The Distance Between Two Large Vectors
Quantum Computers can LEARN
A computer that programs itself
Uncertainty is a feature
D-WaveQuantum ComputingAccess & applications via cloud deploymentRakuten Group, Inc.
D-Wave Systems provides quantum computing via cloud deployment. Their mission is to solve hard problems in AI/ML using their annealing-based quantum computers. They have developed hybrid quantum-classical algorithms and architectures. Their current product is the D-Wave 2000Q quantum processor with 2000 qubits. It uses superconducting qubits in a CMOS fabrication process. D-Wave has established the quantum effects of superposition, entanglement and tunneling on their processors. They are working to develop applications in finance, healthcare and machine learning using their quantum-classical hybrid approach.
The document discusses various research projects involving the automated design and optimization of complex physical, chemical, and biological systems using evolutionary algorithms and machine learning techniques. It describes current and planned usage of computer clusters to run simulations and experiments for protein structure prediction, software self-assembly, and modeling physico-chemical systems through evolutionary optimization of parameters. The research requires significant computational resources to process large datasets and evaluate models in parallel.
This document discusses several topics related to quantum information technology and quantum computing:
- It describes how a double quantum dot qubit works using electron states and how current tunneling can show interference.
- It explains that lower temperatures result in higher coherence times for qubits like double electron gallium arsenide qubits due to less electron-phonon coupling and dephasing.
- It discusses how error correction works in quantum computing by encoding logical qubits across multiple physical qubits to reduce error probabilities. Hardware-based error correction like Toffoli gates may be needed for larger quantum computers.
- Long-term quantum information storage over 180 seconds is demonstrated using donor spin qubits in silicon, where electron and nuclear spins are
Big Fast Data in High-Energy Particle PhysicsAndrew Lowe
Experiments at CERN (the European Organization for Nuclear Research) generate colossal amounts of data. Physicists must sift through about 30 petabytes of data produced annually in their search for new particles and interesting physics. The tidal wave of data produced by the Large Hadron Collider (LHC) at CERN places an unprecedented challenge for experiments' data acquisition systems, and it is the need to select rare physics processes with high efficiency while rejecting high-rate background processes that drives the architectural decisions and technology choices. Although filtering and managing large data sets is of course not exclusive to particle physics, the approach that has been taken is somewhat unique. In this talk, I describe the typical journey taken by data from the readout electronics of one experiment to the results of a physics analysis.
Introduction to Quantum Computation. Part - 1Arunabha Saha
Introduction to quantum computation. Here the very basic maths described needed for quantum information theory as well as computation. Postulates of quantum mechanics and the Hisenberg`s Uncertainty principle. Basic operator theories are described here.
Em computação quântica, um algoritmo quântico é um algoritmo que funciona em um modelo realístico de computação quântica. O modelo mais utilizado é o modelo do circuito de computação quântica.
String theory predicts 11 dimensions, with 10 defining space and 1 defining time. Small extra dimensions are predicted to be curled up in Calabi-Yau shapes within spacetime. This leaves 7 new dimensions that have not been directly observed. The document discusses theories that these new dimensions may exist as a non-local grid pattern between fundamental units of spacetime, known as quantum cells. This proposed grid could explain phenomena like entanglement and tunneling that are currently not accounted for within the standard model of physics.
This document presents a second order integral sliding mode control approach for speed control of a DC motor system. The DC motor system is modeled as a second order system with uncertainty and disturbances. Three controllers are designed and compared - a second order integral sliding mode controller, a conventional sliding mode controller, and a PID controller. Simulation results show that the proposed second order integral sliding mode controller has the fastest response time, no overshoot, smooth control input, and drives the sliding surface to zero, performing better than the other controllers in terms of robustness and disturbance rejection.
“Relationship of Kinematic Variables with the Performance of Standing Broad J...IOSR Journals
Abstract: The purpose of investigation was to study the relationship of kinematics variables with the
performance of standing broad jump. Subjects were randomly selected from J.N.V. University, Jodhpur and
M.D.S. University, Ajmer. The criterion measure used for this study was the performance in standing broad
jump and selected kinematics variables. To analyze the raw data coefficient of correlation (r) were calculated
and results were compared with the help of Analysis of variance (ANOVA) technique where level of significance
was set at .05.
This document provides a review of existing methods for handwritten character recognition based on geometrical properties. It begins by classifying character recognition as either printed or handwritten, and describes the different phases a character recognition system typically includes: image acquisition, preprocessing, segmentation, feature extraction, and classification. Preprocessing steps like binarization, noise removal, normalization and morphological operations are discussed. Feature extraction methods focused on include statistical, global and structural features. Geometrical features involving lines, loops, strokes and their directions are highlighted. Classification algorithms mentioned are neural networks, SVM, k-nearest neighbor, and genetic algorithms. The literature review provides examples of character recognition research using geometrical features like horizontal/vertical line analysis and directional feature
This document discusses weight optimization of the vertical tail in-board box structure of an aircraft through stress analysis. The vertical tail structure is modeled in CATIA and imported into MSC Patran for finite element analysis. The structure is meshed and material properties are applied. Boundary conditions representing the fixed root and free top surface are applied. Stress analysis is performed and high stress regions are identified. An iterative approach is used to introduce lightening cutouts in the spar and rib webs to reduce weight. Two iterations are performed, reducing the total weight by 1.66kg while maintaining similar deformation levels and stresses below material yield strength, demonstrating an effective weight optimization approach.
This document analyzes the capacity-based performance of optimal antenna selection for an 8x8 MIMO system. It simulates optimal antenna selection and finds that selecting 4 antennas provides channel capacity close to using all 8 antennas. The highest capacity of 44bps is achieved with 8 antennas selected. The capacity remains constant up to 18dB, 16dB and 12dB for antenna selection factors of 7, 6 and 5, respectively. For factors 1-4, capacity increases with SNR. For fading channels, 4 antenna selection authorizes channel capacity similar to using all 8 antennas in 8x8 MIMO.
This document summarizes interference avoidance techniques for OFDM-based cellular networks. It discusses how OFDM is used to reduce interference and improve capacity. It then categorizes interference coordination techniques into interference mitigation and interference avoidance. Various static interference avoidance techniques are described, including conventional frequency planning, fractional frequency reuse, partial frequency reuse, and soft frequency reuse. These techniques aim to reduce inter-cell interference by controlling frequency usage and power levels in different network channels and regions.
The document summarizes how RSA encryption can be used as a data security mechanism for RFID tags. It begins with background on RFID and existing security issues like eavesdropping, replay attacks, and cloning attacks. It then provides an overview of the RSA encryption algorithm and gives an example of how it can encrypt a message using a public key and decrypt it with a private key. The proposed solution is to have RFID readers first authenticate tags by encrypting and verifying a password before transmitting any other data. This prevents unauthorized access to tag information. In conclusion, the document recommends RSA encryption as a robust approach to addressing security issues in RFID systems.
Design and Analysis of Microstrip Antenna for CDMA Systems CommunicationIOSR Journals
This paper proposes a newly designed microstrip patch antennas (MSA) for wireless application
(CDMA Systems). The designed single antenna E-shaped patch antenna. Two parallel slots are in corporated
into the patch of a microstrip antenna to expand it bandwidth, and designed antenna operates in the frequency
range of 1.85 to 1.99 GHz. The antenna is designed using air as a dielectric substrate between the ground plane
and substrate patch antenna. IE3D is a full-wave electromagnetic simulator based on the method of moments
(MoM) technique. It has been widely used in the design of MICs, RFICs, patch antennas, wire antennas, and
other RF/wireless antennas. It can be used to calculate and plot the S parameters, VSWR, current distributions
as well as the radiation patterns. The results obtained for each patch were 2D and 3D view of patch, Directivity,
Gain, beam width and other such parameters, true and mapped 3D radiation pattern, and 2D polar radiation
pattern. The antenna successfully achieves the exhibit a broad impedance bandwidth of 27 % (at VSWR < 2)
with respect to the center frequency of 1.9 GHz is designed, fabricated, and finally measured on Spectrum
analyzer. The radiation pattern and directivity are also presented.. Gain maximum achievable is 3 dBi and good
return loss (S11 parameters) of -30 dB is achieved along with broadside radiation pattern.
This document describes an intelligent meta search engine that was developed to efficiently retrieve relevant web documents. The meta search engine submits user queries to multiple traditional search engines including Google, Yahoo, Bing and Ask. It then uses a crawler and modified page ranking algorithm to analyze and rank the results from the different search engines. The top results are then generated and displayed to the user, aimed to be more relevant than results from individual search engines. The meta search engine was implemented using technologies like PHP, MySQL and utilizes components like a graphical user interface, query formulator, metacrawler and redundant URL eliminator.
This document proposes a reactive power control scheme based on correlation coefficients between voltage and current signals. The scheme calculates cross-correlation coefficients using sampled voltage and current data from a power supply. It determines the current power factor and reactive power compensation needed to achieve a desired power factor. The number of required capacitor banks is calculated and signals are sent to close circuit breakers and insert the appropriate capacitors into the system. The technique aims to accurately correct power factor during one cycle of the fundamental frequency for improved power system efficiency.
This document proposes an IoT-based monitoring system for smart home services using a tri-level context making model. The system includes sensor nodes with various sensors that collect environmental data and send it wirelessly to an ARM microcontroller connected to the internet. The microcontroller analyzes the data using the tri-level context model to generate high-level contexts and determine appropriate actions. This allows users to monitor parameters and control devices via the internet. The system was prototyped and tested through scenarios like disaster management and health care services.
The document discusses a method for 3D object recognition from 2D images using centroidal representation. It involves several steps: filtering and binarizing the image, detecting edges, calculating the object center point, extracting features around the centroid, and creating mathematical models using wavelet transforms and autoregression. Centroidal samples represent distances from the center to the boundary every 45 degrees. Wavelet transforms and autoregression are used to create scale and position invariant representations of the object for recognition.
This document reviews techniques for automated extraction of regions of interest (ROIs) from histopathology images. It begins with an overview of the clinical workflow for histopathological image analysis, including tissue sample collection, preprocessing, embedding, sectioning, staining, and visualization. It then discusses challenges in automated analysis, particularly ROI extraction, and reviews several existing techniques including thresholding, hidden Markov models, watershed algorithms, and cellular automata active contours. Specifically, it examines works that use downsampling, multiscale processing, and object detection to extract ROIs. Overall, the document provides a summary of current approaches for automated ROI extraction from whole slide histopathology images.
This document summarizes a research paper that proposes a new algorithm for maintaining the shape and integrity of bio-signals over a body sensor network. The algorithm uses set theory operations instead of interpolation to synchronize signals. It also proposes a secure key management scheme to enhance security in wireless body area networks and analyzes energy consumption. The paper reviews related work in body sensor networks, describes the methodology used in the research, and presents results on evaluating the proposed algorithm's energy efficiency and effectiveness compared to previous methods.
This document discusses load rebalancing algorithms for distributed hash tables in cloud computing. It proposes a fully distributed algorithm to cope with load balancing issues. The algorithm is compared to a centralized approach and another distributed solution.
The proposed system uses multiple balancers to partition a main cloud into smaller balanced clouds or partitions. When clients upload or download files, the balancers monitor load across partitions and direct requests to less busy partitions to improve performance and quality of service. Experimental results show the distributed approach with balancers improves response time, download speed, capacity, and client satisfaction compared to no balancing.
Snake robots have a unique ability to move through challenging environments that are difficult or dangerous for humans, such as rubble after disasters. The document reviews research on snake robot applications and discusses their potential future uses in India. Snake robots could be used for agriculture, sanitation, firefighting, surveillance, nuclear plant maintenance, exploration, rescue operations, and more. While snake robots have limitations currently, further innovation may help exploit their potential and enable infinite applications. The document concludes snake robots have great scope and applicability in India.
The document presents a dynamic model for lifting railway tracks as a one-mass system. It derives the equation of motion for the model numerically using a Runge-Kutta integration scheme. The model accounts for parameters like mass, stiffness, damping, and lifting force. Numerical solutions show that damping coefficients affect the duration and quality of lifting, while lifting forces impact the lift value and duration. The dynamic model allows studying how system parameters influence behavior and stability during railway track lifting.
This document describes the design of a low noise amplifier (LNA) for wideband wireless receivers operating in the S-band frequency range of 2-4 GHz. It first discusses designing an LNA using lumped elements, achieving a maximum gain of 10 dB at 2.5 GHz and minimum noise figure of 2.4 dB at 4 GHz. It then presents an improved design using microstrip matching networks, obtaining a lower minimum noise figure of 0.424 dB at 2.6 GHz and higher maximum gain of 10.84 dB at 2.4 GHz. The microstrip design demonstrates better performance for noise figure and gain across the 2-4 GHz band compared to the lumped element approach.
This document proposes a method to improve data storage security in cloud computing using Identity-Based Cryptography (IBC) and Elliptic Curve Cryptography (ECC). IBC reduces key management complexity and eliminates the need for certificates by using a user's identity as their public key. ECC provides data confidentiality through encryption and data integrity is provided by Elliptic Curve Digital Signature Algorithm (ECDS). The proposed method involves a Private Key Generator (PKG) that generates user keys, a Trusted Cloud (TC) that stores encrypted user data, and users who encrypt data using IBC and ECC before storing it on the TC. This is intended to provide secure and flexible data storage in cloud computing.
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Quantum computers have the potential to vastly outperform classical computers for certain problems. They make use of quantum bits (qubits) that can exist in superpositions of states and become entangled with each other. This allows quantum computers to perform calculations on all possible combinations of inputs simultaneously. However, building large-scale quantum computers faces challenges such as maintaining quantum coherence long enough to perform useful computations. Researchers are working to develop quantum algorithms and overcome issues like decoherence. If successful, quantum computers could solve problems in domains like cryptography, simulation, and machine learning that are intractable for classical computers.
Quantum computing is a rapidly emerging technology that uses principles of quantum mechanics like superposition and entanglement to perform operations on quantum bits (qubits) and solve complex problems. It has the potential to vastly outperform classical computers for certain problems. The document discusses key aspects of quantum computing including how it differs from classical computing, what qubits are, how quantum computers work using elements like superconductors and Josephson junctions, and potential applications in areas like artificial intelligence, drug development, weather forecasting, and cybersecurity. It also covers advantages like speed and ability to solve complex problems, as well as current disadvantages like difficulty to build and susceptibility to errors.
This document discusses quantum computers, which harness quantum phenomena like superposition and entanglement to perform operations. A qubit, the basic unit of information in a quantum computer, can exist in multiple states simultaneously. While this allows massive parallelism and an exponential increase in computational power over classical computers, building large-scale quantum computers faces challenges in maintaining coherence. Potential applications include cryptography, optimization problems, and software testing due to quantum computers' probabilistic solving approach.
The document discusses the history and progression of computer generations from vacuum tubes to microprocessors. It then covers the concepts of quantum computing, including quantum bits that can represent both 0 and 1 simultaneously, quantum entanglement, and how quantum computers could solve problems like integer factorization exponentially faster than classical computers. Some applications proposed include networking, simulation, and cryptography, but challenges remain in scaling up quantum systems and preventing decoherence.
Quantum computers is a machine that performs calculations based on the laws of quantum mechanics which is the behaviour of particles at the subatomic level.
On the atomic scale matter obeys the rules of quantum mechanics, which are quite different from the classical rules that determine the properties of conventional logic gates. So if computers are to become smaller in the future, new, quantum technology must replace or supplement for this.
This document provides an overview of quantum computing. It discusses how quantum computing works using quantum bits that can exist in superposition allowing both 1s and 0s to be represented simultaneously. Several methods for demonstrating quantum computing are described, including nuclear magnetic resonance, ion traps, quantum dots, and optical techniques. Quantum computing provides advantages like faster processing speeds and an exponential increase in storage capacity. Challenges that must be overcome include error correction and fighting decoherence. The document outlines desirable features for an ideal quantum computing system.
Quantum computers use principles of quantum mechanics rather than classical binary logic. They have qubits that can represent superpositions of 0 and 1, allowing massive parallelism. Key effects like superposition, entanglement, and tunneling give them advantages over classical computers for problems like factoring and searching. Early quantum computers have been built with up to a few hundred qubits, and algorithms like Shor's show promise for cryptography applications. However, challenges remain around error correction and controlling quantum states as quantum computers scale up. D-Wave has produced commercial quantum annealing systems with over 1000 qubits, but debate continues on whether these demonstrate quantum advantage. Overall, quantum computing could transform fields like AI, simulation, and optimization if challenges around building reliable large-scale quantum
Quantum computers have the potential to solve certain problems much faster than classical computers by exploiting principles of quantum mechanics, such as superposition and entanglement. However, building large-scale, reliable quantum computers faces challenges related to decoherence and controlling quantum systems. Current research aims to develop quantum algorithms and overcome issues in scaling up quantum hardware to perform more complex computations than today's most powerful supercomputers.
The document discusses applications of superconductor materials and devices in quantum information science. It covers 5 topics: 1) an overview of the quantum information landscape, 2) macroscopic quantum phenomena in superconductor devices and superconductor qubits, 3) the transmon qubit which is a leading qubit platform, 4) topological superconducting qubits based on Majorana fermion states, and 5) S-TI-S Josephson junctions which are a compelling qubit platform. Superconductivity is expected to play a major role in developing qubit devices and quantum circuits.
This document discusses nanocomputing and quantum computing. It covers architectures like quantum dot cellular automata and crossbar switching. It discusses how nanocomputers would work using quantum states and spins. Applications of quantum computing include breaking codes and optimization problems. Challenges include maintaining the fragile quantum states long enough to perform computations. Overall, nanoscale quantum computing could revolutionize computing by massively increasing computing power.
This presentation is about quantum computing.which going to be new technological concept for computer operating system.In this subject the research is going on.
Pulse Compression Sequence (PCS) are widely used in radar to increase the range resolution. Binary sequence has the limitation that the compression ratio is small. Ternary code is suggested as an alternative. The design of ternary sequence with good Discriminating Factor (DF) and merit factor can be considered as a nonlinear multivariable optimization problem which is difficult to solve. In this paper, we proposed a new method for designing ternary sequence by using Modified Simulated Annealing Algorithm (MSAA). The general features such as global convergence and robustness of the statistical algorithm are revealed.
1. The document provides an overview of quantum computation, discussing its history and advantages over classical computing.
2. Quantum computers can perform certain tasks like factoring large numbers and simulating quantum systems much faster than classical computers by taking advantage of quantum mechanics principles like superposition and parallelism.
3. One of the major advantages is that a quantum computer with just a few hundred qubits could theoretically operate on more states simultaneously than there are atoms in the observable universe, massively increasing its computational power over classical computers.
This document provides an overview of using quantum computers for quantum simulation. It discusses how quantum computers can efficiently store quantum states using superpositions, while classical computers require exponential resources. The document reviews Lloyd's method for implementing time evolution under a Hamiltonian via Trotterization. It also discusses other techniques like pseudo-spectral methods and quantum lattice gases. The goal of quantum simulation is to study properties of quantum systems that cannot be efficiently simulated classically.
A Technical Seminar on Quantum Computers By SAIKIRAN PANJALASaikiran Panjala
A quantum computer harnesses the power of atoms and molecules to perform calculations exponentially faster than classical computers by exploiting quantum mechanical phenomena like superposition and entanglement. While theoretical quantum algorithms could solve problems like integer factorization that are intractable on classical computers, building a large-scale, practical quantum computer remains a significant technological challenge due to issues like qubit coherence. Researchers are working towards developing quantum computers using technologies like superconductors, trapped ions, and optical lattices.
This document discusses the history and development of computers from the first to fifth generations. It then covers key concepts related to quantum computing such as qubits, superposition, entanglement, and algorithms like Shor's and Grover's. Challenges with building large-scale quantum computers are also summarized such as issues with decoherence and scaling the number of qubits. Potential applications of quantum computing in areas like encryption, simulation, and random number generation are outlined.
Quantum Computing and its security implicationsInnoTech
Quantum computers work with qubits that can exist in superposition and be entangled. They have enormous computational power compared to digital computers and could solve problems like prime factorization rapidly. This poses risks to current encryption methods and allows for perfectly secure quantum communication. Several types of quantum computers are being developed, from quantum annealers to analog and universal models, with the latter offering exponential speedups but being the hardest to build. Significant progress is being made, with quantum computers in the tens of qubits now and the need to transition encryption to post-quantum algorithms within the next decade.
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This document provides a review of mobility management techniques in vehicular ad hoc networks (VANETs). It discusses three modes of communication in VANETs: vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and hybrid vehicle (HV) communication. For each communication mode, different mobility management schemes are required due to their unique characteristics. The document also discusses mobility management challenges in VANETs and outlines some open research issues in improving mobility management for seamless communication in these dynamic networks.
This document provides a review of different techniques for segmenting brain MRI images to detect tumors. It compares the K-means and Fuzzy C-means clustering algorithms. K-means is an exclusive clustering algorithm that groups data points into distinct clusters, while Fuzzy C-means is an overlapping clustering algorithm that allows data points to belong to multiple clusters. The document finds that Fuzzy C-means requires more time for brain tumor detection compared to other methods like hierarchical clustering or K-means. It also reviews related work applying these clustering algorithms to segment brain MRI images.
1) The document simulates and compares the performance of AODV and DSDV routing protocols in a mobile ad hoc network under three conditions: when users are fixed, when users move towards the base station, and when users move away from the base station.
2) The results show that both protocols have higher packet delivery and lower packet loss when users are either fixed or moving towards the base station, since signal strength is better in those scenarios. Performance degrades when users move away from the base station due to weaker signals.
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This document describes the design and implementation of 4-bit QPSK and 256-bit QAM modulation techniques using MATLAB. It compares the two techniques based on SNR, BER, and efficiency. The key steps of implementing each technique in MATLAB are outlined, including generating random bits, modulation, adding noise, and measuring BER. Simulation results show scatter plots and eye diagrams of the modulated signals. A table compares the results, showing that 256-bit QAM provides better performance than 4-bit QPSK. The document concludes that QAM modulation is more effective for digital transmission systems.
The document proposes a hybrid technique using Anisotropic Scale Invariant Feature Transform (A-SIFT) and Robust Ensemble Support Vector Machine (RESVM) to accurately identify faces in images. A-SIFT improves upon traditional SIFT by applying anisotropic scaling to extract richer directional keypoints. Keypoints are processed with RESVM and hypothesis testing to increase accuracy above 95% by repeatedly reprocessing images until the threshold is met. The technique was tested on similar and different facial images and achieved better results than SIFT in retrieval time and reduced keypoints.
This document studies the effects of dielectric superstrate thickness on microstrip patch antenna parameters. Three types of probes-fed patch antennas (rectangular, circular, and square) were designed to operate at 2.4 GHz using Arlondiclad 880 substrate. The antennas were tested with and without an Arlondiclad 880 superstrate of varying thicknesses. It was found that adding a superstrate slightly degraded performance by lowering the resonant frequency and increasing return loss and VSWR, while decreasing bandwidth and gain. Specifically, increasing the superstrate thickness or dielectric constant resulted in greater changes to the antenna parameters.
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1) The document proposes a model for a frequency tunable inverted-F antenna that uses ferrite material.
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This document summarizes a research paper that presents a speech enhancement method using stationary wavelet transform. The method first classifies speech into voiced, unvoiced, and silence regions based on short-time energy. It then applies different thresholding techniques to the wavelet coefficients of each region - modified hard thresholding for voiced speech, semi-soft thresholding for unvoiced speech, and setting coefficients to zero for silence. Experimental results using speech from the TIMIT database corrupted with white Gaussian noise at various SNR levels show improved performance over other popular denoising methods.
This document reviews the design of an energy-optimized wireless sensor node that encrypts data for transmission. It discusses how sensing schemes that group nodes into clusters and transmit aggregated data can reduce energy consumption compared to individual node transmissions. The proposed node design calculates the minimum transmission power needed based on received signal strength and uses a periodic sleep/wake cycle to optimize energy when not sensing or transmitting. It aims to encrypt data at both the node and network level to further optimize energy usage for wireless communication.
This document discusses group consumption modes. It analyzes factors that impact group consumption, including external environmental factors like technological developments enabling new forms of online and offline interactions, as well as internal motivational factors at both the group and individual level. The document then proposes that group consumption modes can be divided into four types based on two dimensions: vertical (group relationship intensity) and horizontal (consumption action period). These four types are instrument-oriented, information-oriented, enjoyment-oriented, and relationship-oriented consumption modes. Finally, the document notes that consumption modes are dynamic and can evolve over time.
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This document reviews cryptography techniques to secure the Ad-hoc On-Demand Distance Vector (AODV) routing protocol in mobile ad-hoc networks. It discusses various types of attacks on AODV like impersonation, denial of service, eavesdropping, black hole attacks, wormhole attacks, and Sybil attacks. It then proposes using the RC6 cryptography algorithm to secure AODV by encrypting data packets and detecting and removing malicious nodes launching black hole attacks. Simulation results show that after applying RC6, the packet delivery ratio and throughput of AODV increase while delay decreases, improving the security and performance of the network under attack.
The document describes a proposed modification to the conventional Booth multiplier that aims to increase its speed by applying concepts from Vedic mathematics. Specifically, it utilizes the Urdhva Tiryakbhyam formula to generate all partial products concurrently rather than sequentially. The proposed 8x8 bit multiplier was coded in VHDL, simulated, and found to have a path delay 44.35% lower than a conventional Booth multiplier, demonstrating its potential for higher speed.
This document discusses image deblurring techniques. It begins by introducing image restoration and focusing on image deblurring. It then discusses challenges with image deblurring being an ill-posed problem. It reviews existing approaches to screen image deconvolution including estimating point spread functions and iteratively estimating blur kernels and sharp images. The document also discusses handling spatially variant blur and summarizes the relationship between the proposed method and previous work for different blur types. It proposes using color filters in the aperture to exploit parallax cues for segmentation and blur estimation. Finally, it proposes moving the image sensor circularly during exposure to prevent high frequency attenuation from motion blur.
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A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
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Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
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.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 15, Issue 1 (Sep. - Oct. 2013), PP 30-34
www.iosrjournals.org
www.iosrjournals.org 30 | Page
Quantum communication and quantum computing
*Sweety Mittal, **Nilesh Kumar Dokania
Lecturar,Yaduvanshi college of engg and technology
Assistant Professor, Guru Nanak Institute Of Management
Abstract: The subject of quantum computing brings together ideas from classical information theory, computer
science, and quantum physics. This review aims to summarize not just quantum computing, but the whole
subject of quantum information theory. Information can be identified as the most general thing which must
propagate from a cause to an effect. It therefore has a fundamentally important role in the science of physics.
However, the mathematical treatment of information, especially information processing, is quite recent, dating
from the mid-20th century. This has meant that the full significance of information as a basic concept in physics
is only now being discovered. This is especially true in quantum mechanics. The theory of quantum information
and computing puts this significance on a firm footing, and has led to some profound and exciting new insights
into the natural world. Among these are the use of quantum states to permit the secure transmission of classical
information (quantum cryptography), the use of quantum entanglement to permit reliable transmission of
quantum states (teleportation), the possibility of preserving quantum coherence in the presence of irreversible
noise processes (quantum error correction), and the use of controlled quantum evolution for efficient
computation (quantum computation). The common theme of all these insights is the use of quantum
entanglement as a computational resource.
Keywords: quantum bits, quantum registers, quantum gates and quantum networks
I. Introduction
First proposed in the 1970s, quantum computing relies on quantum physics by taking advantage of
certain quantum physics properties of atoms or nuclei that allow them to work together as quantum bits, or
qubits, to be the computer's processor and memory. By interacting with each other while being isolated from the
external environment, qubits can perform certain calculations exponentially faster than conventional computers.
. A quantum computer can do an arbitrary reversible classical computation on all the numbers simultaneously,
which a binary system cannot do, and also has some ability to produce interference between various different
numbers. By doing a computation on many different numbers at once, then interfering the results to get a single
answer, a quantum computer has the potential to be much more powerful than a classical computer of the same
size. In using only a single processing unit, a quantum computer can naturally perform myriad operations in
parallel. Quantum computing is not well suited for tasks such as word processing and email, but it is ideal for
tasks such as cryptography and modeling and indexing very large databases.
The review concludes with an outline of the main features of quantum information physics and avenues
for future research.
Fig 1. Basics of quantum computer
II. Requirements of hardware:
Storage: We'll need to store Qbits long enough to perform an interesting computation
Isolation: The Obits must be well isolated from the environment to minimize the decoherece effect.
Readout: We'll need to measure the Qbits efficiently and reliably.
Gates: We'll need to manipulate the quantum states of individual Qbit, so that we can perform quantum gates.
2. Quantum communication and quantum computing
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Precision: The quantum gates should be implemented with highly precision if we want the device to work
properly.
Ion Trap: This idea has been suggested by Ignacio Cirac and Peter Zoller. In this scheme the Qbit is
represented by a single ion held in linear Paul trap.
Cavity QED: Pellizzari, Cardiner, Cirac and Zoller have suggested that several neutral atoms to be stored in a
small high finesse optical cavity. The quantum information can be stored in the internal states of the atoms
NMR: This scheme uses nuclear magnetic resonance technology and the Qbits are carried by a a certain nuclear
spin in a particular molecule.
2.2 Algorithm
We describe a quantum algorithm that generalizes the quantum linear system algorithm to arbitrary
problem specifications. We develop a state preparation routine that can initialize generic states, show how
simple ancilla measurements can be used to calculate many quantities of interest, and integrate a quantum-
compatible preconditioner that greatly expands the number of problems that can achieve exponential speedup
over classical linear systems solvers. To demonstrate the algorithm’s applicability, we show how it can be used
to compute the electromagnetic scattering cross section of an arbitrary target exponentially faster than the best
classical algorithm.
2.3 Complexity
Quantum Hamiltonian complexity is an exciting area combining deep questions and techniques from
both quantum complexity theory and condensed matter physics. The connection between these fields arises from
the close relationship between their defining questions: the complexity of constraint satisfaction problems in
complexity theory and the properties of ground states of local Hamiltonians in condensed matter theory.
quantum Hamiltonian complexity provides new approaches and techniques for tackling fundamental questions
in condensed matter physics, in particular the classical simulation of quantum many body systems. The area law
plays a central role in recent progress on using tensor network based techniques for simulating such systems.
The goal of this semester long program is to bring together leading computer scientists, condensed matter
physicists and mathematicians working on these questions, and to build upon the existing bridges and
collaborations between them. One of the important priorities will be to help establish a common language
between the three groups, so that key insights from all three areas can be pooled in tackling the outstanding
issues at the heart of quantum Hamiltonian complexity
2.4 Quantum Cryptography
According to Quantum Mechanics, given the most precise description possible of how things are now,
the most you can do is predict the probability that things will turn out one way or another. Many people
(including, famously, Albert Einstein) found this a disturbing feature of the theory, which suggested to them that
Quantum Mechanics was not the real theory of nature, and that we were missing something. However, in a
pivotal paper in 1964, John Bell showed a way of processing measurement results from certain experiments so
that there is a threshold value, a maximum value which can be obtained by models (known as Local Hidden
Variable models) which describe all possible models of physics which obey two fundamental properties: the
theories should not be capable of transmitting information faster than the speed of light, and measurement
results should be predetermined. However, the way that Bell combined these measurement results also predicted
that a Quantum Mechanical system would exceed this threshold value, i.e., one of those assumptions on the
nature of the physical world must be false. This prediction has been confirmed by numerous experiments in the
intervening years.
To most, this unpredicatability of measurement results would present a problem. However,
cryptographers look to benefit from such features. Information is always represented by measurable physical
properties, and if such properties exist then, their value can be predicted with certainty without in any way
disturbing a system. This is just a description of a perfect eavesdropping. Conversely, if such properties do not
exist prior to measurements, then there is nothing to eavesdrop on. Hence, measuring the so-called Bell
Inequalities in an experiment provides a test of just how much a quantum transmission has been eavesdropped.
Remarkably, this requires very little by way of assumptions about the protocols that are being followed - it
doesn't matter what devices we are using, or if we even trust the person who manufactured the devices or not -
provided a Bell inequality is violated, we can use the measurement results to communicate securely. This is
known as Device Independent cryptography. These ideas were first applied to the classic task in cryptography;
key distribution, although has since been applied in various other instances such as the expansion of a sequence
of random numbers.
3. Quantum communication and quantum computing
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III. Working In Quantum Computing
3.1.1 How Computers Work
Computers function by storing data in a binary number format, which result in a series of 1s & 0s
retained in electronic components such astransistors. each component of computer memory is called a bit and
can be manipulated through the steps of Boolean logic so that the bits change, based upon the algorithms applied
by the computer program, between the 1 and 0 modes (sometimes referred to as "on" and "off").
3.1.2 How a Quantum Computer Would Work
A quantum computer, on the other hand, would store information as either a 1, 0, or a quantum
superposition of the two states. Such a "quantum bit," called a qubit, allows for far greater flexibility than the
binary system.
Specifically, a quantum computer would be able to perform calculations on a far greater order of
magnitude than traditional computers ... a concept which has serious concerns and applications in the realm of
cryptography & encryption. Some fear that a successful & practical quantum computer would devastate the
world's financial system by ripping through their computer security encryptions, which are based on factoring
large numbers that literally cannot be cracked by traditional computers within the life span of the universe. A
quantum computer, on the other hand, could factor the numbers in a reasonable period of time.
3.2 Architecture
Fig2:Quantum Computing Sample Architecture
A sufficiently transparent architecture facilitates tool interoperability, focused point-tool development, and
incremental improvements. Quantum algorithm designers and those developing quantum circuit optimizations
can explore new algorithms and error-correction procedures in more realistic settings
involving actual noise and physical resource constraints. Researchers can also simulate important quantum
algorithms on proposed new technologies before doing expensive lab experiments. Our four-phase design flow,
shown in Figure , maps a high-level program representing a quantum algorithm
into a low-level set of machine instructions to be implemented on a physical device. The high-level quantum
programming language encapsulates the mathematical abstractions of quantum mechanics and linear algebra.1
The design flow’s first three phases are part of the quantum computer compiler (QCC). The last phase
implements the algorithm on a quantum device or simulator.
Fig3: Quantum Computing Layered Architeutre
4.1 Ongoing Research in Quantum Computing
Researchers in industry and government labs are exploring various aspects of quantum design and
automation with a wide range of applications. In addition to the examples described below, universities in the
US, Canada, Europe, Japan, and China are carrying out much broader efforts.
4. Quantum communication and quantum computing
www.iosrjournals.org 33 | Page
4.1.1 BBN Technologies
Based in Cambridge, Massachusetts, BBN Technologies (www.bbn.com) developed the world’s first
quantum key distribution (QKD) network with funding from the US Defense Advanced Research Projects
Agency.The fiber-optical DARPA Quantum Network offers 24x7 quantum cryptography to
secure standard Internet traffic such as Web browsing, e-commerce, and streaming video.
4.1.2 D-Wave Systems
Located in Vancouver, British Columbia, Canada, D-Wave Systems (www.dwavesys.com) builds
superconductor-based software-programmable custom integrated circuits for quantum optimization algorithms
and quantum-physical simulations. These ICs form the heart of a quantum computing
system designed to deliver massively more powerful and faster performance for
cryptanalysis,logistics,bioinformatics,and other applications.
4.1.3 Hewlett-Packard
The Quantum Science Research Group at HP Labs in Palo Alto,California,is exploring nanoscale quantum
optics for information- processing applications (www.hpl.hp.com/research/qsr). In addition, the Quantum
Information Processing Group at the company’s research facility in Bristol, UK, is studying quantum
computation, cryptography, and teleportation and communication
(www.hpl.hp. com/research/qip).
4.1.4 Hypres
Located in Elmsford, New York, Hypres Inc. (www.hypres.com) is the leading developer of
superconducting digital for wireless and optical communication. Based on rapid singleflux
quantum logic, these circuits have achieved gate speeds up to 770 GHz in the laboratory.
4.1.5 IBM Research
Scientists at IBM’s Almaden Research Center in California and the T.J.Watson Research Center’s
Yorktown office in New York developed a nuclear magnetic resonance (NMR) quantum computer
that factored 15 into 3 5 (http://archives.cnn.com/ 2000/TECH/computing/08/15/quantum.reut). Researchers
at the Watson facility and the Zurich Research Lab are also developing Josephson junction quantum devices
(www. research.ibm. com/ss_computing) as well as studying quantum information theory
(www.research.ibm.com/quantuminfo).
4.1.6 Id Quantique
Based in Geneva, Switzerland, id Quantique (www.idquantique. com) is a leading provider of quantum
cryptography solutions, including wire-speed link encryptors, QKD appliances, a turnkey service for securing
communication transfers, and quantum random number generators.The company’s optical
instrumentation product portfolio includes single-photon counters and short-pulse laser sources.
4.1.7 Los Alamos National Lab
The Los Alamos National Lab (http://qso.lanl.gov/qc) in New Mexico is studying quantum-optical
long-distance secure communications and QKD for satellite communications. It has also conducted
groundbreaking work on quantum error correction, decoherence, quantum teleportation, and the adaptation of
NMR technology to quantum information processing.
4.1.8 Magiq Technologies
MagiQ Technologies (www.magiqtech.com), headquartered in New York City, launched the world’s
first commercial quantum cryptography device in 2003. MagiQ Quantum Private Network systems incorporate
QKD over metro-area fiberoptic links to protect against both cryptographic deciphering
and industrial espionage.
4.1.9 NEC Labs
Scientists at NEC’s Fundamental and Environmental Research Laboratories in Japan, in collaboration
with the Riken Institute of Physical and Chemical Research, have demonstrated a basic quantum circuit in a
solid-state quantum device (www.labs.nec.co.jp/Eng/innovative/E3/top.html). Recently, NEC researchers have
also been involved in realizing the fastest fortnight-long, continuous quantum cryptography final-key
generation.
5. Quantum communication and quantum computing
www.iosrjournals.org 34 | Page
4.1.10 NIST
Established in 2000, the Quantum Information Program at the US National Institute of Standards and
Technology (http:// qubit.nist.gov) is building a prototype 10-qubit quantum processor— made of trapped ions,
neutral atoms, or “artificial atoms” made of superconducting electrical circuits—to provide a proofin- principle
of quantum information processing. Researchers at the program’s facilities in Boulder,Colorado, and
Gaithersburg, Maryland, are also developing a high-speed QKD system with
efficient and precise single-photon sources and detectors.
4.1.11 NTT Basic Research Labs
NTT’s Superconducting Quantum Physics Research Group in Japan focuses on the development of
quantum cryptography protocols (www.brl.ntt.co.jp/group/shitsuryo-g/qc). In particular, they have exhibited
quantum cryptography using a single photon realized in a photonic network of optical fibers.
5.1 Future Outlook
At present, quantum computers and quantum information technology remains in its pioneering stage.
At this very moment obstacles are being surmounted that will provide the knowledge needed to thrust quantum
computers up to their rightful position as the fastest computational machines in existence. Error correction has
made promising progress to date, nearing a point now where we may have the tools required to build a computer
robust enough to adequately withstand the effects of decoherence. Quantum hardware, on the other hand,
remains an emerging field, but the work done thus far suggests that it will only be a matter time before we have
devices large enough to test Shor's and other quantum algorithms. Thereby, quantum computers will emerge as
the superior computational devices at the very least, and perhaps one day make today's modern computer
obsolete. Quantum computation has its origins in highly specialized fields of theoretical physics, but its future
undoubtedly lies in the profound effect it will have on the lives of all mankind.
Fig 4
IV. Conclusion
The field of quantum computing is growing rapidly as many of today's leading computing groups,
universities, colleges, and all the leading IT vendors are researching the topic. This pace is expected to increase
as more research is turned into practical applications. Although practical machines lie years in the future, this
formerly fanciful idea is gaining plausibility.
The current challenge is not to build a full quantum computer right away; instead to move away from
the experiments in which we merely observe quantum phenomena to experiments in which we can control these
phenomena. Systems in which information obeys the laws of quantum mechanics could far exceed the
performance of any conventional computer. Therein lies the opportunity and the reward. No one can predict
when we will build the first quantum computer; it could be this year, perhaps in the next 10 years, or centuries
from now. Obviously, this mind-boggling level of computing power has enormous commercial, industrial, and
scientific applications, but there are some significant technological and conceptual issue to resolve first.
But quantum computers will come.
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