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.
This is my personal notes related to quantum computing, collected as part of my study. It offers quantum circuits, quantum algorithms, matrix operations, Kronecker, dot products, derivation of Pauli's X, Y , Z gates , preparation of Bell state using Hadamard and CNOT, and finally defines the six quantum states for a qubit
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.
This is my personal notes related to quantum computing, collected as part of my study. It offers quantum circuits, quantum algorithms, matrix operations, Kronecker, dot products, derivation of Pauli's X, Y , Z gates , preparation of Bell state using Hadamard and CNOT, and finally defines the six quantum states for a qubit
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Alice wants to teleport an unknown quantum state ฯ to Bob using prior entanglement and classical communication. They share one half of an entangled Bell state ฮฒ each. Alice combines her half of ฮฒ with ฯ and performs a teleportation circuit involving CNOT and Hadamard gates. She then measures her two qubits and sends the results to Bob. Based on the received classical bits, Bob applies a Pauli operator to reconstruct the state ฯ exactly at his location.
The document provides an overview of quantum computing, including its history, data representation using qubits, quantum gates and operations, and Shor's algorithm for integer factorization. Shor's algorithm uses quantum parallelism and the quantum Fourier transform to find the period of a function, from which the factors of a number can be determined. While quantum computing holds promise for certain applications, classical computers will still be needed and future computers may be a hybrid of classical and quantum components.
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states. A controlled-NOT (CN) gate inverts the target qubit if the control qubit is 1. A controlled-controlled-NOT (CCN) gate inverts the target qubit if both control qubits are 1. Shor's algorithm uses quantum Fourier transforms and modular exponentiation to factor integers into prime factors exponentially faster than classical computers. It finds the period of the function x raised to a power (mod N), from which the factors can be derived.
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Report-Implementation of Quantum Gates using VerilogShashank Kumar
ย
It was a project-based work in which I was guided to implement the quantum-based gates which would be equivalent to classical gates So, the project name was "FPGA Implementation of Digital Logic Design using Quantum Computing". Actually, it is to mitigate the problem, since in quantum any NAND based circuit is not shown universal as in the classical it was so tried by using the "IBM Quantum Composer" to make such circuit which would behave as the NAND gate and also reversible in nature as per the quantum physics says and simulated the circuitry using the "Verilog".
This document summarizes key concepts about combinational logic circuits. It defines combinational logic as circuits whose outputs depend only on the current inputs, in contrast to sequential logic which also depends on prior inputs. Common combinational circuits are described like half and full adders used for arithmetic, as well as decoders. The design process for combinational circuits is outlined involving specification, formulation, optimization and technology mapping. Implementation of functions using NAND and NOR gates is 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.
Ec2203 digital electronics questions anna university by www.annaunivedu.organnaunivedu
ย
EC2203 Digital Electronics Anna University Important Questions for 3rd Semester ECE , EC2203 Digital Electronics Important Questions, 3rd Sem Question papers,
http://www.annaunivedu.org/digital-electronics-ec-2203-previous-year-question-paper-for-3rd-sem-ece-anna-univ-question/
A review on reversible logic gates and their implementationDebraj Maji
ย
The document provides an overview of reversible logic gates and their implementation. It discusses how reversible logic gates can reduce power dissipation compared to irreversible logic gates. Some key reversible logic gates are described, including NOT, CNOT, Feynman, Toffoli, and Fredkin gates. Their truth tables and quantum costs are given. The document serves to introduce researchers to reversible logic gates that can be used to design more complex computing circuits with potential applications in quantum computing and low-power electronics.
Quantum computing - A Compilation of ConceptsGokul Alex
ย
Excerpts of the Talk Delivered at the 'Bio-Inspired Computing' Workshop conducted by Department of Computational Biology and Bioinformatics, University of Kerala.
The document discusses combinational logic circuits. It covers sum-of-products and product-of-sums forms for representing logic functions. Methods for analyzing and simplifying logic circuits are presented, including Boolean algebra, Karnaugh maps, and deriving truth tables from logic diagrams. Examples of common logic circuits like adders, decoders, and converters are provided along with steps for designing combinational logic circuits.
This document provides an overview of the MATLAB Robotics Toolbox. It describes that the toolbox contains functions for studying robot kinematics, dynamics, trajectory generation, visualization and simulation for arm-type robots. It also contains functions for mobile robots and computer vision. The document provides instructions on how to download, install and use the toolbox to define robots, perform forward and inverse kinematics, calculate Jacobians and trajectories, and simulate robot dynamics.
An Efficient Construction of Online Testable Circuits using Reversible Logic ...ijsrd.com
ย
The vital for many safety critical applications is the testable fault tolerant system. Due to its less heat dissipating characteristics, the reversible logic gaining interest in the recent times. Any Boolean logic function can be implemented using reversible gates. The credential part of the paper proposes a technique to convert any reversible logic gate to a testable gate that is also reversible. The resultant reversible testable gate can detect online any single bit errors that include Single Stuck Faults and Single Event Upsets S. Karp et.al. The proposed technique is illustrated using an example that converts a reversible decoder circuit to an online testable reversible decoder circuit.
The document discusses programmable logic arrays (PLAs) and programmable array logic (PALs). PLAs have programmable AND gates that feed into programmable OR gates, allowing implementation of combinational logic circuits. PALs similarly have a programmable AND array but fixed OR gates, so each output depends on a specific set of product terms. Both PLAs and PALs can implement state machines and digital circuits through programming. Examples show mapping logic functions to the architectures and programming the resulting AND-OR configurations.
A Survey Paper on Different Encoding Techniques Based on Quantum ComputingIRJET Journal
ย
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.
A Novel Parity Preserving Reversible Binary-to-BCD Code Converter with Testab...VIT-AP University
ย
The reversible logic circuit is popular due to its quantum gates involved
where quantum gates are reversible and noted down feature of no information loss.
In this paper, parity preserving reversible binary-to-BCD code converter is
designed, and effect of reversible metrics is analyzed such as gate count, ancilla
input, garbage output, and quantum cost. This design can build blocks of basic
existing parity preserving reversible gates. The building blocks of the code converter
reversible circuit constructed on Toffoli gate based as well as elemental gate
based such as CNOT, C-V, and C-V+ gates. In addition, qubit transition analysis of
the quantum circuit in the regime of quantum computing has been presented. The heuristic approach has been developed in quantum circuit construction and the
optimized quantum cost for the circuit of binary-to-BCD code converter. Logic functions validate the development of quantum circuit. Moving the testability aim
are figured in the quantum logic circuit testing such as single missing gate and single missing control point fault.
NexGen Solutions for cloud platforms, powered by GenQAIVijayananda Mohire
ย
This is our next generation solutions powered by emerging technologies like AI, quantum computing, Blockchain, quantum cryptography etc. We have various offers that can help improved productivity, help automate and improve ease of doing business. We offer cloud based solutions and have a Hub to interface major cloud platforms.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Alice wants to teleport an unknown quantum state ฯ to Bob using prior entanglement and classical communication. They share one half of an entangled Bell state ฮฒ each. Alice combines her half of ฮฒ with ฯ and performs a teleportation circuit involving CNOT and Hadamard gates. She then measures her two qubits and sends the results to Bob. Based on the received classical bits, Bob applies a Pauli operator to reconstruct the state ฯ exactly at his location.
The document provides an overview of quantum computing, including its history, data representation using qubits, quantum gates and operations, and Shor's algorithm for integer factorization. Shor's algorithm uses quantum parallelism and the quantum Fourier transform to find the period of a function, from which the factors of a number can be determined. While quantum computing holds promise for certain applications, classical computers will still be needed and future computers may be a hybrid of classical and quantum components.
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states. A controlled-NOT (CN) gate inverts the target qubit if the control qubit is 1. A controlled-controlled-NOT (CCN) gate inverts the target qubit if both control qubits are 1. Shor's algorithm uses quantum Fourier transforms and modular exponentiation to factor integers into prime factors exponentially faster than classical computers. It finds the period of the function x raised to a power (mod N), from which the factors can be derived.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
โ help.mbaassignments@gmail.com โ
or
Call us at : 08263069601
Report-Implementation of Quantum Gates using VerilogShashank Kumar
ย
It was a project-based work in which I was guided to implement the quantum-based gates which would be equivalent to classical gates So, the project name was "FPGA Implementation of Digital Logic Design using Quantum Computing". Actually, it is to mitigate the problem, since in quantum any NAND based circuit is not shown universal as in the classical it was so tried by using the "IBM Quantum Composer" to make such circuit which would behave as the NAND gate and also reversible in nature as per the quantum physics says and simulated the circuitry using the "Verilog".
This document summarizes key concepts about combinational logic circuits. It defines combinational logic as circuits whose outputs depend only on the current inputs, in contrast to sequential logic which also depends on prior inputs. Common combinational circuits are described like half and full adders used for arithmetic, as well as decoders. The design process for combinational circuits is outlined involving specification, formulation, optimization and technology mapping. Implementation of functions using NAND and NOR gates is 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.
Ec2203 digital electronics questions anna university by www.annaunivedu.organnaunivedu
ย
EC2203 Digital Electronics Anna University Important Questions for 3rd Semester ECE , EC2203 Digital Electronics Important Questions, 3rd Sem Question papers,
http://www.annaunivedu.org/digital-electronics-ec-2203-previous-year-question-paper-for-3rd-sem-ece-anna-univ-question/
A review on reversible logic gates and their implementationDebraj Maji
ย
The document provides an overview of reversible logic gates and their implementation. It discusses how reversible logic gates can reduce power dissipation compared to irreversible logic gates. Some key reversible logic gates are described, including NOT, CNOT, Feynman, Toffoli, and Fredkin gates. Their truth tables and quantum costs are given. The document serves to introduce researchers to reversible logic gates that can be used to design more complex computing circuits with potential applications in quantum computing and low-power electronics.
Quantum computing - A Compilation of ConceptsGokul Alex
ย
Excerpts of the Talk Delivered at the 'Bio-Inspired Computing' Workshop conducted by Department of Computational Biology and Bioinformatics, University of Kerala.
The document discusses combinational logic circuits. It covers sum-of-products and product-of-sums forms for representing logic functions. Methods for analyzing and simplifying logic circuits are presented, including Boolean algebra, Karnaugh maps, and deriving truth tables from logic diagrams. Examples of common logic circuits like adders, decoders, and converters are provided along with steps for designing combinational logic circuits.
This document provides an overview of the MATLAB Robotics Toolbox. It describes that the toolbox contains functions for studying robot kinematics, dynamics, trajectory generation, visualization and simulation for arm-type robots. It also contains functions for mobile robots and computer vision. The document provides instructions on how to download, install and use the toolbox to define robots, perform forward and inverse kinematics, calculate Jacobians and trajectories, and simulate robot dynamics.
An Efficient Construction of Online Testable Circuits using Reversible Logic ...ijsrd.com
ย
The vital for many safety critical applications is the testable fault tolerant system. Due to its less heat dissipating characteristics, the reversible logic gaining interest in the recent times. Any Boolean logic function can be implemented using reversible gates. The credential part of the paper proposes a technique to convert any reversible logic gate to a testable gate that is also reversible. The resultant reversible testable gate can detect online any single bit errors that include Single Stuck Faults and Single Event Upsets S. Karp et.al. The proposed technique is illustrated using an example that converts a reversible decoder circuit to an online testable reversible decoder circuit.
The document discusses programmable logic arrays (PLAs) and programmable array logic (PALs). PLAs have programmable AND gates that feed into programmable OR gates, allowing implementation of combinational logic circuits. PALs similarly have a programmable AND array but fixed OR gates, so each output depends on a specific set of product terms. Both PLAs and PALs can implement state machines and digital circuits through programming. Examples show mapping logic functions to the architectures and programming the resulting AND-OR configurations.
A Survey Paper on Different Encoding Techniques Based on Quantum ComputingIRJET Journal
ย
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.
A Novel Parity Preserving Reversible Binary-to-BCD Code Converter with Testab...VIT-AP University
ย
The reversible logic circuit is popular due to its quantum gates involved
where quantum gates are reversible and noted down feature of no information loss.
In this paper, parity preserving reversible binary-to-BCD code converter is
designed, and effect of reversible metrics is analyzed such as gate count, ancilla
input, garbage output, and quantum cost. This design can build blocks of basic
existing parity preserving reversible gates. The building blocks of the code converter
reversible circuit constructed on Toffoli gate based as well as elemental gate
based such as CNOT, C-V, and C-V+ gates. In addition, qubit transition analysis of
the quantum circuit in the regime of quantum computing has been presented. The heuristic approach has been developed in quantum circuit construction and the
optimized quantum cost for the circuit of binary-to-BCD code converter. Logic functions validate the development of quantum circuit. Moving the testability aim
are figured in the quantum logic circuit testing such as single missing gate and single missing control point fault.
NexGen Solutions for cloud platforms, powered by GenQAIVijayananda Mohire
ย
This is our next generation solutions powered by emerging technologies like AI, quantum computing, Blockchain, quantum cryptography etc. We have various offers that can help improved productivity, help automate and improve ease of doing business. We offer cloud based solutions and have a Hub to interface major cloud platforms.
This is our project work at our startup for Data Science. This is part of our internal training and focused on data management for AI, ML and Generative AI apps
This is our contributions to the Data Science projects, as developed in our startup. These are part of partner trainings and in-house design and development and testing of the course material and concepts in Data Science and Engineering. It covers Data ingestion, data wrangling, feature engineering, data analysis, data storage, data extraction, querying data, formatting and visualizing data for various dashboards.Data is prepared for accurate ML model predictions and Generative AI apps
Considering the need and demand for high quality digital platforms that can help clients to get the most of the newer technology, we have proposed an IT Hub that allows for rapid on boarding of clients to various modules on a need basis, allowing them to subscribe to modules they need only. We have various modules.
This document offers a high level overview of our IT Hub that offers various modules allowing for clients to onboard faster and get the benefits of a large set of vendor products, tools, IDE related to AI, Quantum and Generative AI technologies.
This is my hands-on projects in quantum technologies. These are few of the key projects that I worked with that demonstrates my skills in using various concepts, tools, IDE and deriving the solutions by using quantum principles like superposition, and entanglement along with quantum circuits in realizing the concepts
Azure Quantum Workspace for developing Q# based quantum circuitsVijayananda Mohire
ย
This document provides steps to develop quantum circuits using Q# on Azure Quantum. It instructs the user to create an Azure subscription, log into the Azure portal, create a Quantum Workspace, and provision storage. It then explains how to define Q# operations, simulate them locally using %simulate, connect to the Azure Quantum workspace with %azure.connect, specify an execution target with %azure.target, submit jobs with %azure.submit, check job status with %azure.status, retrieve outputs with %azure.output, and view all jobs with %azure.jobs. An example quantum random number generation program written in Q# is provided.
This is my journey taken from year 2012 on wards, after graduation in my MS with major in AI. I have taken various certification courses, trainings, hands-on labs; few key ones are from Google, and Microsoft.
Agricultural and allied industries play a vital role in the progress of a nation and sustainable economic growth. Farmers play a vital role in this progress. Their hard work and efforts need to be praised and possibly offer them various tools and digital assets that can automate some of their various repetitive tasks such as back office operations, crop monitoring, and post-harvesting routines that might divert the attention of farmers from their core job.
We, at Bhadale IT have developed various products and services that are revolutionary and can offer effective solutions with our industrial partnerships with digital technology leaders like Intel and Microsoft. We have drafted this solution brief to illustrate our products and service offerings for the agricultural industry. We can tailor make highly customized solutions to meet individual project and farmer needs that can include use of various technologies like artificial intelligence, machine learning, data science and related machinery like drones and geo-spatial datasets and various information that can offer precise farming techniques and use of technology in improving production, improvised use of fertilizers, organic farming and reduced crop loss due to rodents, insects and regional diseases.
The focus of this solution is for farmers to adopt and migrate to digital cloud platform to Microsoft Azure that can boost quality and quantity of crop production and improve their supply chain and offer faster and mature downstream business operations.
This is our cloud offerings based on our partnership and relationship with Intel and Microsoft. We offer highly optimized Intel motherboards, memory, and software stack that is best suited for Azure cloud platform and can handle various types of models (IaaS, PaaS, SaaS) and Azure workloads in the public or private cloud.
Explore the fundamentals of GitHub Copilot and its potential to enhance productivity and foster innovation for both individual developers and businesses. Discover how to implement it within your organization and unleash its power for your own projects.
In this learning path, you'll:
Gain a comprehensive understanding of the distinctions between GitHub Copilot for Individuals, GitHub Copilot for Business, and GitHub Copilot X.
Explore various use cases for GitHub Copilot for Business, including real-life examples showcasing how customers have leveraged it to boost their productivity.
Receive step-by-step instructions on enabling GitHub Copilot for Individuals and GitHub Copilot for Business, ensuring a seamless integration into your workflows.
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical ImplicationsVijayananda Mohire
ย
This journey provides learners with a thorough exploration of ChatGPT, starting with an introduction to large language models and their capabilities, the series progresses through practical applications, advanced techniques, industry impacts, and important ethical considerations. Each course aims to equip learners with an in-depth understanding of the model, its functionality, and its wide-ranging applications.
Red Hat Enterprise Linux (RHEL) and Hybrid Cloud Infrastructure. Products that are developed for multi-cloud hybrid platform enabling seamless integration and portability of workloads across Red Hat and partner Infrastructure, public and private clouds.
Learners will be exposed to the foundations of Red Hat, Red Hat Enterprise Linux (RHEL) portfolio including Hybrid Cloud Infrastructure, how to identify target customers, distinguish Red Hat solutions from the competition, review key use cases, align to the sales conversation framework for positioning the solutions, and much more!
Upon completing this learning path, learners will receive the Red Hat Sales Specialist - Red Hat Enterprise Linux accreditation and be prepared to advance to the Red Hat Sales Specialist - Red Hat Enterprise Linux II learning path
This is my annual learning at Red Hat related to accreditation and courses at Red Hat partner training portal.
Learners will be exposed to the foundations of Red Hat, Red Hat Enterprise Linux (RHEL) portfolio including Hybrid Cloud Infrastructure, how to identify target customers, distinguish Red Hat solutions from the competition, review key use cases, align to the sales conversation framework for positioning the solutions, and much more!
Generative AI is a cutting-edge technology that will transform nearly every business function, ranging from content creation and product design, to improving customer experience and marketing new ideas. While the benefits of Generative AI are immense, the technology has its limitations and poses some ethical considerations. In this Journey, learners of all levels will develop a shared understanding of what Generative AI is, the guardrails for use and identify of how to use, build and experiment with the technology in a responsible manner. Learners will also develop skills for leading through this disruption with empathy, while cultivating the human skills to sustain the transformation
The document provides a transcript for Vijayananda Mohire that includes their legal name, username, contact email, a list of 130+ modules completed on the Microsoft learning platform totaling over 130 hours, and descriptions of each module completed including titles, descriptions, and durations.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
ย
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power gridโs behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
ย
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
ย
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
ย
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
ย
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
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1. Quantum Computing โ Notes Ver 1.2
Prepared By: Vijayananda Mohire
Sources: Various open courses, MOOC trainings and self study; no intention for any copyright infringements
Question 1
Design a reversible circuit, using NOT, CNOT, Toffoli, and Fredkin gates,which acts on the four inputs a,b,c,d, to
perform the operation swap243(a,b,c,d) which swaps b and d if a=0, and swaps c and d if a=1. Bit a should be
left unchanged
Answer 1
High level functionwith the circuit
fredkin(a,c,d)
not(a)
fredkin(a,b,d)
not(a)
Question 2
Design a reversible circuit, using NOT, CNOT, Toffoli, and Fredkin gates, which acts on the four inputs
a,b,c,d, to swap c and d only when both a=1 and b=1. You may use a fifth bit e, given as initialized to
e=0, in your circuit; this bit must also end as e=0. C
Answer 2
High level functionwith the circuit
toffoli(a,b,e)
fredkin(e,c,d)
toffoli(a,b,e)
2. Question 3
Sample RandomNumber using Q#
Answer 3
open Microsoft.Quantum.Arrays;
open Microsoft.Quantum.Measurement;
operation SampleRandomNumber(nQubits : Int) : Result[] {
// We prepare a register of qubits in a uniform
// superposition state, such that when we measure,
// all bitstrings occur with equal probability.
use register = Qubit[nQubits] {
// Set qubits in superposition.
ApplyToEachA(H, register);
// Measure all qubits and return.
return ForEach(MResetZ, register);
}
}
Question 4
Run a basic quantum circuit expressed using the Qiskit library to an IonQ target via the Azure Quantum
service.
Answer 4
First, import the required packages for this sample:
from qiskit import QuantumCircuit
from qiskit.visualization import plot_histogram
from qiskit.tools.monitor import job_monitor
from azure.quantum.qiskit import AzureQuantumProvider
#Connect to backend Azure quantum service, using below function
from azure.quantum.qiskit import AzureQuantumProvider
provider = AzureQuantumProvider ( resource_id = " ", location = " " )
# Create a Quantum Circuit acting on the q register
circuit = QuantumCircuit(3, 3)
circuit.name = "Qiskit Sample - 3-qubit GHZ circuit"
circuit.h(0)
circuit.cx(0, 1)
circuit.cx(1, 2)
circuit.measure([0,1,2], [0, 1, 2])
# Print out the circuit
circuit.draw()
โโโโโ โโโ
q_0: โค H โโโโ โโโโโโโโคMโโโโโโโ
โโโโโโโโดโโ โโฅโโโโ
q_1: โโโโโโค X โโโโ โโโโซโโคMโโโโ
โโโโโโโโดโโ โ โโฅโโโโ
q_2: โโโโโโโโโโโค X โโโซโโโซโโคMโ
โโโโโ โ โ โโฅโ
c: 3/โโโโโโโโโโโโโโโโโฉโโโฉโโโฉโ
0 1 2
3. #Create a Backend object to connect to the IonQ Simulator back-end:
simulator_backend = provider.get_backend("ionq.simulator")
job = simulator_backend.run(circuit, shots=100)
job_id = job.id()
print("Job id", job_id)
#Create a job monitor object
job_monitor(job)
#To wait until the job is completed and return the results, run:
result = job.result()
qiskit.result.result.Result
print(result)
connect to real hardware (Quantum Processing Unit or QPU)
qpu_backend = provider.get_backend("ionq.qpu")
# Submit the circuit to run on Azure Quantum
qpu_job = qpu_backend.run(circuit, shots=1024)
job_id = qpu_job.id()
print("Job id", job_id)
# Monitor job progress and wait until complete:
job_monitor(qpu_job)
# Get the job results (this method also waits for the Job to complete):
result = qpu_job.result()
print(result)
counts = {format(n, "03b"): 0 for n in range(8)}
counts.update(result.get_counts(circuit))
print(counts)
plot_histogram(counts)
Question 5
Develop Google AI sample Cirq circuit
Answer 5
import cirq
qubits = [cirq.GridQubit(x, y) for x in range(3) for y in range(3)]
print(qubits[0])
# This is an Pauli X gate. It is an object instance.
x_gate = cirq.X
# Applying it to the qubit at location (0, 0) (defined above)
# turns it into an operation.
x_op = x_gate(qubits[0])
print(x_op)
cz = cirq.CZ(qubits[0], qubits[1])
x = cirq.X(qubits[2])
moment = cirq.Moment([x, cz])
x2 = cirq.X(qubits[2])
cz12 = cirq.CZ(qubits[1], qubits[2])
moment0 = cirq.Moment([cz01, x2])
4. moment1 = cirq.Moment([cz12])
circuit = cirq.Circuit((moment0, moment1))
print(circuit)
Question 6
Design a simple Tensorflow based quantum Colab sample
Answer 6
!pip install tensorflow==2.4.1
!pip install tensorflow-quantum
import tensorflow as tf
import tensorflow_quantum as tfq
import cirq
import sympy
import numpy as np
# visualization tools
%matplotlib inline
import matplotlib.pyplot as plt
from cirq.contrib.svg import SVGCircuit
a, b = sympy.symbols('a b')
# Create two qubits
q0, q1 = cirq.GridQubit.rect(1, 2)
# Create a circuit on these qubits using the parameters you created above.
circuit = cirq.Circuit(
cirq.rx(a).on(q0),
cirq.ry(b).on(q1), cirq.CNOT(control=q0, target=q1))
SVGCircuit(circuit)
# Calculate a state vector with a=0.5 and b=-0.5.
resolver = cirq.ParamResolver({a: 0.5, b: -0.5})
output_state_vector = cirq.Simulator().simulate(circuit, resolver).final_state_vector
output_state_vector
5. Question 7
Design a simple qubit based quantum circuit using IBMQiskit
Answer 7
import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, Aer, IBMQ, assemble
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
from math import pi, sqrt
# Loading your IBM Quantum account(s)
provider = IBMQ.load_account()
sim = Aer.get_backend('aer_simulator')
# Let's do an X-gate on a |0> qubit
qc = QuantumCircuit(1)
qc.x(0)
qc.draw()
qc.y(0) # Do Y-gate on qubit 0
qc.z(0) # Do Z-gate on qubit 0
qc.draw()
# Create the X-measurement function:
def x_measurement(qc, qubit, cbit):
"""Measure 'qubit' in the X-basis, and store the result in 'cbit'"""
qc.h(qubit)
qc.measure(qubit, cbit)
return qc
initial_state = [1/sqrt(2), -1/sqrt(2)]
# Initialize our qubit and measure it
qc = QuantumCircuit(1,1)
qc.initialize(initial_state, 0)
x_measurement(qc, 0, 0) # measure qubit 0 to classical bit 0
qc.draw()
6. Question 8
How to find if matrix is Unitary
Answer 8
Consider a 2*2 Matrix A with different values. We take 2 examples as shown below to prove how these are valid or
not for quantum representation
A =
0 1
๐ 0
and AT
=
0 ๐
1 0
Next, A*AT
=
๐ 0
0 ๐
= i *
1 0
0 1
which is an Identity matrix I
So this matrix is Unitary and valid for quantum representations
Next example,
A =
1 โ1
0 1
and AT
=
1 0
โ1 1
Next, A*AT
=
2 0
โ1 0
= which isNOT an Identity matrix, as 2 is not correct
So this matrix is NOT unitary and NOT valid for quantum representations
Question 9
Generate the Unitary matrix for the given quantum circuit
Answer 9
First let me get the matricesfor NOT and CNOT gates
NOT =
0 1
1 0
and for CNOT
1 0 0 0
0 1 0 0
0 0 0 1
0 0 1 0
Gate Matrices have to be multiplied. However, when matrix is generated for single qubit ,tensor product with
identity is required.
So getting the I for the NOT gates
7. 0 1
1 0
tensor product
0 1
1 0
=
0 0 1 0
0 0 0 1
1 0 0 0
0 1 0 0
this is the Identity I
Now multiply these as per circuit order
I * CNOT Matrix *I
0 0 1 0
0 0 0 1
1 0 0 0
0 1 0 0
*
0 0 1 0
0 0 0 1
1 0 0 0
0 1 0 0
*
0 0 1 0
0 0 0 1
1 0 0 0
0 1 0 0
=
๐ ๐ ๐ ๐
๐ ๐ ๐ ๐
๐ ๐ ๐ ๐
๐ ๐ ๐ ๐
The multiplication can be made easier using online tool like
https://www.dcode.fr/matrix-multiplication
This is based on theory, however this needs to be done using simulator like Qiskit based Composer and get the
Unitary matrix
Question 10: Derive Pauliโs X gate
Answer 10: There are 3 Pauliโs gates namely X, Y and Z that represent the various gate operations on the Bloch
sphere.
Pauliโs X gate offer a NOT type of operation and is represented by bra-ket and matrix notations. Below is anexample
of deriving the X gate
Please note bra is represented by < 0 | and ket by |0 >. Arranging the matricesin proper shape is the key in getting
the proper results. There is also a conjugate transpose required, meaning the cols matrix is transformed to row
matrix and these are then multiplied
I have used a different method to represent the state vector rows and columns; however this is not the best one.
You can use KET based COLS first and BRA based ROWS, and then do the operation. Pauli X is a NOT gate, so the 0->1
and 1>0 are reflectedin the matrices. Please get these things clear first
8. Question 11: Derive Pauliโs Y gate
Answer 11: In a similar way the Pauliโs X is derived, Pauliโs Y is derived
10. Question 13: Show an example of inner product
Answer 13: Inner product of 2 matricesis the dot product and results in a scalar.
Question 14: Show an example of outer product
Answer 14: Outer product of 2 matrices is the tensor product and resultsin a vector matrix.
11. Question 15: Show an example of outer product using Pauli X & Y with anexample of Trace
Answer 15: Using Pauliโs X & Y matrices
Question 16: Show how Bell State is derived
Answer 16: Bell state preparation uses 3 steps:
1. State initialization
2. Use Hadamard and Identity gate for superposition and getting the Kronecker matrix
3. Use a CNOT to multiply with the Kronecker matrix
Detailsin the following notes below
12.
13. Question 17: State the types of quantum states
Answer 17: Quantum qubit can have 6 possible states, 2 each for the X, Y and Z directions of the Bloch sphere
Another way to represent these are shown below, |0>, |1>,| +>, |->,| I > and | โI >
Image source: https://andisama.medium.com/qubit-an-intuition-1-first-baby-steps-in-exploring-the-quantum-world-
16f693e456d8
14. Question 18: Define the notations for the different types of quantum states like plus, minus etc
Answer 18: Quantum qubit state notations are mainly represented in matrix and bra-ket forms with transformation
from one notation to another as required to solve a problem .Below are matrix notations for 0,1, + and โ states.
These can be re-written from matrix to state, like col matrix [1 0] can be written as ket notation | 0> as per the need
of the problem to be solved
Question 19: Apply an H gate on the |+> and show the results
Answer 19: First we get the matrix notation for H and |+> states, then we multiply them, details shown below
15. Question 20: Apply an X gate on the |0> and show the results
Answer 20: First we get the matrix notation for X and |0> states, then we multiply them, as shown below
Question 21: Apply an X gate on the |-> and show the results
Answer 21: First we get the matrix notation for X and |-> states, then we multiply them, details shown below
,results show on Bloch sphere for Question 19 and 20
Question 22: Test the below matrices for the validity of being the bitflip X gate
Answer 22: First we get the matrix notation of the X gate and test it againsteach given matrix that should result in
the NOT operation
16. Question 23: Given H acting on |0> produces |+> & H|1> = |->, which is the correct H operator
Answer 23: First we get the matrix for H and testeach given matrix that produces the required results
Question 24: Express |+> state in the Z โ basis(Hadamard)
Answer 24:
17. Question 25: Using Matrix and related gates derive Bell states
Answer 25: Please refer images below
18.
19. Question 26: Show the Eigen vectors and Eigen values for PaulisXYZ
Answer 26: Eigen values in each case are + and โ. Eigen vectors are shown below
Question 27: Please test if these states are separable?
Answer 27: Please refer image below
20. Question 28: Show the probability of finding a qubitin a given state
Answer 28: Please refer image below
Question 29: Show unitary rotation matrices around Pauli XYZ
Answer 29: Please refer image
c
21. Question 30
Describe how you would represent a large set of particlesin a Fock space rather than the Hilbert space
Answer 30
Fock space is a newerway (Second Quantization) to represent multi-particles in aneasier way unlike in the Hilbert
space. Below is the broad wayin simple terms
ERRATA: Please note that instead of 6 basis states as mentioned, ONLY 5 have been represented in the KET form,
you can add another term here, say a โzero to make the complete set of 6 base states
Question 31
Describe in simple words how Fock space uses Hilbert space
Answer 31
Fock space offers newer way of abstracting the state-space representations as previously done in the First
Quantization. This helps iseasier and shorter way in showing the quantum states.
22. References:
1. MIT OpenCourseWare , https://ocw.mit.edu/
2. IBMQuantum Lab, https://quantum-computing.ibm.com/lab
3. Azure Quantum, https://azure.microsoft.com/en-in/services/quantum/
4. QuTech Academy, https://www.qutube.nl/
5. Andi Sama Blog, https://andisama.medium.com/qubit-an-intuition-1-first-baby-steps-in-exploring-the-
quantum-world-16f693e456d8
6. Einstein Relatively Easy, https://einsteinrelativelyeasy.com/
7. The Web and Google Search
Disclaimer: I have no intention for any copyright infringement, nor I promise that the results are true and right.
Please use your caution to self-check the results against the quantum postulates. I am reachable at
vijaymohire@gmail.com for any clarifications