Qiskit is an open source framework of Quantum Computing. It provides tools for creating and manipulating quantum programs and running them on prototype quantum devices on IBM Q Experience or on simulators on a local computer.
Quantum computing is a new paradigm that utilizes quantum mechanics phenomena like superposition and entanglement. It has the potential to solve certain problems exponentially faster than classical computers by using qubits that can be in superposition of states. Some key applications are factoring, simulation, and optimization problems. However, building large-scale quantum computers faces challenges like preventing decoherence of qubits and developing error correction techniques. While still in development, quantum computing could revolutionize fields like encryption, communication, and material science in the future through a hybrid model combining classical and quantum processing.
Quantum Computers New Generation of Computers PART1 by Prof Lili SaghafiProfessor Lili Saghafi
This lecture is intended to introduce the concepts and terminology used in Quantum Computing, to provide an overview of what a Quantum Computer is, and why you would want to program one.
The material here is using very high level concepts and is designed to be accessible to both technical and non-technical audiences.
Some background in physics, mathematics and programming is useful to help understand the concepts presented.
Exploits Quantum Mechanical effects
Built around “Qubits” rather than “bits”
Operates in an extreme environment
Enables quantum algorithms to solve very hard problems
Quantum computing and quantum communications utilize principles of quantum mechanics such as superposition and entanglement to process and transmit information in novel ways. Current research is exploring how to build reliable quantum computers and networks using technologies like ion traps, quantum dots, and optical methods. While still in early stages, quantum information science shows promise for solving computationally difficult problems in fields such as artificial intelligence, cybersecurity, and drug discovery. Pioneering work by groups like D-Wave, IBM, and China are helping advance our understanding of how to harness quantum effects for powerful new computing and communication applications.
Shor's algorithm is for quantum computer. Using this algorithm any arbitrarily large number can be factored in polynomial time. which is not possible in classical computer
Quantum computing is a new paradigm that utilizes quantum mechanics phenomena like superposition and entanglement. It has the potential to solve certain problems exponentially faster than classical computers by using qubits that can be in superposition of states. Some key applications are factoring, simulation, and optimization problems. However, building large-scale quantum computers faces challenges like preventing decoherence of qubits and developing error correction techniques. While still in development, quantum computing could revolutionize fields like encryption, communication, and material science in the future through a hybrid model combining classical and quantum processing.
Quantum Computers New Generation of Computers PART1 by Prof Lili SaghafiProfessor Lili Saghafi
This lecture is intended to introduce the concepts and terminology used in Quantum Computing, to provide an overview of what a Quantum Computer is, and why you would want to program one.
The material here is using very high level concepts and is designed to be accessible to both technical and non-technical audiences.
Some background in physics, mathematics and programming is useful to help understand the concepts presented.
Exploits Quantum Mechanical effects
Built around “Qubits” rather than “bits”
Operates in an extreme environment
Enables quantum algorithms to solve very hard problems
Quantum computing and quantum communications utilize principles of quantum mechanics such as superposition and entanglement to process and transmit information in novel ways. Current research is exploring how to build reliable quantum computers and networks using technologies like ion traps, quantum dots, and optical methods. While still in early stages, quantum information science shows promise for solving computationally difficult problems in fields such as artificial intelligence, cybersecurity, and drug discovery. Pioneering work by groups like D-Wave, IBM, and China are helping advance our understanding of how to harness quantum effects for powerful new computing and communication applications.
Shor's algorithm is for quantum computer. Using this algorithm any arbitrarily large number can be factored in polynomial time. which is not possible in classical computer
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 is a new method of computing based on quantum mechanics that offers greater computational power than classical computers. Quantum computers use quantum bits or qubits that can exist in superpositions of states allowing massive parallelism. Several approaches like ion traps, quantum dots and NMR have demonstrated quantum computing. However, challenges remain around errors from decoherence and a lack of reliable reading mechanisms. If these obstacles can be overcome, quantum computers may solve problems in artificial intelligence, cybersecurity, drug design and more exponentially faster than classical computers.
Quantum computing has become a noteworthy topic in academia and industry. The multinational companies in the world have been obtaining impressive advances in all areas of quantum technology during the last two decades. These companies try to construct real quantum computers in order to exploit their theoretical preferences over today’s classical computers in practical applications. However, they are challenging to build a full-scale quantum computer because of their increased susceptibility to errors due to decoherence and other quantum noise. Therefore, quantum error correction (QEC) and fault-tolerance protocol will be essential for running quantum algorithms on large-scale quantum computers.
The overall effect of noise is modeled in terms of a set of Pauli operators and the identity acting on the physical qubits (bit flip, phase flip and a combination of bit and phase flips). In addition to Pauli errors, there is another error named leakage errors that occur when a qubit leaves the defined computational subspace. As the location of leakage errors is unknown, these can damage even more the quantum computations. Thus, this talk will briefly provide quantum error models.
Quantum computing is the computing which uses the laws of quantum mechanics to process information. Quantum computer works on qubits, which stands for "Quantum Bits".
With quantum computers, factoring of prime numbers are possible.
An overview of quantum computing, with its features, capabilities and types of problems it can solve. Also covers some current and future implementations of quantum computing, and a view of the patent landscape.
This document discusses the history and future of quantum computing. It explains how quantum computers work using principles of quantum mechanics like superposition and entanglement. Quantum computers can perform multiple computations simultaneously by exploiting the ability of qubits to exist in superposition. Current research involves building larger quantum registers with more qubits and performing calculations with 2 qubits. The future of quantum computing may enable solving certain problems much faster than classical computers, with desktop quantum computers potentially arriving within 10 years.
What is Quantum Computing
What is Quantum bits (Qubit)
What is Reversible Logic gates and Logic Circuits
What is Quantum Neuron (Quron)
What are the methods of implementing ANN using Quantum computing
This document discusses quantum computing applications in the financial sector. It describes how quantum computers work using qubits that can be in multiple states at once, allowing for greater processing power. Examples of applications include improving traffic management through quantum machine learning, predicting crimes using social media analysis, and addressing the COVID pandemic through computational chemistry. Major companies developing quantum computing include Microsoft, Google, which has achieved quantum supremacy. The document also discusses how quantum cryptography can enhance banking security through quantum key distribution and the ability to detect any third party interference.
This slide starts from a basic explanation between Bit and Qubit. It then follows with a brief history behind Quantum Computer, current trends, and update with concerns to make the quantum computer practically useful.
This document provides an introduction to quantum cryptography. It explains that quantum cryptography uses principles of quantum mechanics like quantum entanglement and the Heisenberg uncertainty principle to securely distribute encryption keys. It notes that quantum cryptography combines the concepts of one-time pads and quantum key distribution, using quantum mechanics to detect any attempts at eavesdropping. The document also briefly discusses the history of cryptography, how quantum key distribution works, advantages and disadvantages of quantum cryptography, and its future applications.
An introduction to quantum machine learning.pptxColleen Farrelly
Very basic introduction to quantum computing given at Indaba Malawi 2022. Overviews some basic hardware in classical and quantum computing, as well as a few quantum machine learning algorithms in use today. Resources for self-study provided.
The document provides an overview of fundamental concepts in quantum computing, including quantum properties like superposition, entanglement, and uncertainty principle. It discusses how quantum bits can represent more than classical bits by being in superpositions of states. Basic quantum gates like Hadamard, Pauli X, and phase shift gates are also introduced, along with pioneers in the field like Feynman, Deutsch, Shor, and Grover. Potential applications of quantum computing are listed.
Quantum computing is an emerging new theory of computation based on the principles of quantum mechanics. It is the basis for a fundamentally new information processing model that is garnering increasing attention in the media and from commercial information technology companies. In certain computing tasks, it can theoretically arrive at a solution more efficiently than classical computers. In this session, we explore the basic principles behind quantum computing, including qubit superposition and entanglement -- the basis for quantum parallelism. We explore quantum logic gates as an abstracted representation of underlying hardware and discuss a simple quantum gate circuit that demonstrates parallelism. We also review the current state of the technology and what has been demonstrated compared to what is theoretically predicted. Current trends in the quantum computing industry will be presented along with proposed possible uses in biomedical informatics.
This document provides an introduction to quantum programming languages. It begins with basic concepts in quantum mechanics like state superposition and entanglement. It then discusses popular quantum algorithms like Deutsch, Shor, and Grover algorithms. The document reviews several quantum programming languages including quantum pseudocode, Quipper which is embedded in Haskell, and the Python toolbox QuTiP. It also mentions Mathematica packages for quantum computation. Finally, it introduces the IBM Quantum Experience platform for designing and running quantum circuits in a quantum processor or simulator.
Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations.
This presentation is designed to elucidate about the Quantum Computing - History - Principles - QUBITS - Quantum Computing Models - Applications - Advantages and Disadvantages.
This document discusses quantum cryptography and its advantages over traditional cryptography. It provides background on traditional public and private key cryptography and explains that quantum cryptography uses the principles of quantum mechanics to securely transmit encryption keys. The document outlines the basics of how quantum cryptography works, including using photon polarization to represent bits, and describes an example of how it could be implemented using MATLAB. It also lists some of the key companies working in the field of quantum cryptography.
The Extraordinary World of Quantum ComputingTim Ellison
Originally presented at QCon London - 6 March-2018.
The classical computer on your lap or housed in your data centre manipulates data represented with a binary encoding -- quantum computers are different. They use atomic level mechanics to represent multiple data states simultaneously, leading to a phenomenal exponential increase in the representable state of data, and new solutions to problems that are infeasible using today's classical computers. This session assumes no prior knowledge of quantum technology and presents a introduction to the field of quantum computing, including an introduction to the quantum bit, the types of problem suited to quantum computing, a demo of running algorithms on IBM's quantum machines, and a peek into the future of quantum computers.
This document provides an overview of quantum computers, including a brief history of computing technology, limitations of current computing approaches, and the theory behind quantum computing. Quantum computers use quantum particles and properties like superposition and entanglement to perform exponentially more computations than digital computers. While quantum computers currently exist only as theoretical constructs or limited prototypes, algorithms like Shor's algorithm show their potential to solve problems much faster than classical computers for applications like factoring large numbers. Several research groups worldwide are working to advance the technology with the goal of developing fully functional quantum computers within the next 10-20 years.
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.
- The document discusses quantum computing and its potential applications. It notes that while quantum computers may be able to efficiently simulate physical processes, quantum error correction is needed for scalability.
- Current quantum hardware has around 50-100 qubits but higher qubit numbers and lower error rates are needed. Quantum computers in the "Noisy Intermediate-Scale Quantum" era may be able to explore physics and have some commercial uses, but more powerful quantum technologies will likely require decades more of work.
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 is a new method of computing based on quantum mechanics that offers greater computational power than classical computers. Quantum computers use quantum bits or qubits that can exist in superpositions of states allowing massive parallelism. Several approaches like ion traps, quantum dots and NMR have demonstrated quantum computing. However, challenges remain around errors from decoherence and a lack of reliable reading mechanisms. If these obstacles can be overcome, quantum computers may solve problems in artificial intelligence, cybersecurity, drug design and more exponentially faster than classical computers.
Quantum computing has become a noteworthy topic in academia and industry. The multinational companies in the world have been obtaining impressive advances in all areas of quantum technology during the last two decades. These companies try to construct real quantum computers in order to exploit their theoretical preferences over today’s classical computers in practical applications. However, they are challenging to build a full-scale quantum computer because of their increased susceptibility to errors due to decoherence and other quantum noise. Therefore, quantum error correction (QEC) and fault-tolerance protocol will be essential for running quantum algorithms on large-scale quantum computers.
The overall effect of noise is modeled in terms of a set of Pauli operators and the identity acting on the physical qubits (bit flip, phase flip and a combination of bit and phase flips). In addition to Pauli errors, there is another error named leakage errors that occur when a qubit leaves the defined computational subspace. As the location of leakage errors is unknown, these can damage even more the quantum computations. Thus, this talk will briefly provide quantum error models.
Quantum computing is the computing which uses the laws of quantum mechanics to process information. Quantum computer works on qubits, which stands for "Quantum Bits".
With quantum computers, factoring of prime numbers are possible.
An overview of quantum computing, with its features, capabilities and types of problems it can solve. Also covers some current and future implementations of quantum computing, and a view of the patent landscape.
This document discusses the history and future of quantum computing. It explains how quantum computers work using principles of quantum mechanics like superposition and entanglement. Quantum computers can perform multiple computations simultaneously by exploiting the ability of qubits to exist in superposition. Current research involves building larger quantum registers with more qubits and performing calculations with 2 qubits. The future of quantum computing may enable solving certain problems much faster than classical computers, with desktop quantum computers potentially arriving within 10 years.
What is Quantum Computing
What is Quantum bits (Qubit)
What is Reversible Logic gates and Logic Circuits
What is Quantum Neuron (Quron)
What are the methods of implementing ANN using Quantum computing
This document discusses quantum computing applications in the financial sector. It describes how quantum computers work using qubits that can be in multiple states at once, allowing for greater processing power. Examples of applications include improving traffic management through quantum machine learning, predicting crimes using social media analysis, and addressing the COVID pandemic through computational chemistry. Major companies developing quantum computing include Microsoft, Google, which has achieved quantum supremacy. The document also discusses how quantum cryptography can enhance banking security through quantum key distribution and the ability to detect any third party interference.
This slide starts from a basic explanation between Bit and Qubit. It then follows with a brief history behind Quantum Computer, current trends, and update with concerns to make the quantum computer practically useful.
This document provides an introduction to quantum cryptography. It explains that quantum cryptography uses principles of quantum mechanics like quantum entanglement and the Heisenberg uncertainty principle to securely distribute encryption keys. It notes that quantum cryptography combines the concepts of one-time pads and quantum key distribution, using quantum mechanics to detect any attempts at eavesdropping. The document also briefly discusses the history of cryptography, how quantum key distribution works, advantages and disadvantages of quantum cryptography, and its future applications.
An introduction to quantum machine learning.pptxColleen Farrelly
Very basic introduction to quantum computing given at Indaba Malawi 2022. Overviews some basic hardware in classical and quantum computing, as well as a few quantum machine learning algorithms in use today. Resources for self-study provided.
The document provides an overview of fundamental concepts in quantum computing, including quantum properties like superposition, entanglement, and uncertainty principle. It discusses how quantum bits can represent more than classical bits by being in superpositions of states. Basic quantum gates like Hadamard, Pauli X, and phase shift gates are also introduced, along with pioneers in the field like Feynman, Deutsch, Shor, and Grover. Potential applications of quantum computing are listed.
Quantum computing is an emerging new theory of computation based on the principles of quantum mechanics. It is the basis for a fundamentally new information processing model that is garnering increasing attention in the media and from commercial information technology companies. In certain computing tasks, it can theoretically arrive at a solution more efficiently than classical computers. In this session, we explore the basic principles behind quantum computing, including qubit superposition and entanglement -- the basis for quantum parallelism. We explore quantum logic gates as an abstracted representation of underlying hardware and discuss a simple quantum gate circuit that demonstrates parallelism. We also review the current state of the technology and what has been demonstrated compared to what is theoretically predicted. Current trends in the quantum computing industry will be presented along with proposed possible uses in biomedical informatics.
This document provides an introduction to quantum programming languages. It begins with basic concepts in quantum mechanics like state superposition and entanglement. It then discusses popular quantum algorithms like Deutsch, Shor, and Grover algorithms. The document reviews several quantum programming languages including quantum pseudocode, Quipper which is embedded in Haskell, and the Python toolbox QuTiP. It also mentions Mathematica packages for quantum computation. Finally, it introduces the IBM Quantum Experience platform for designing and running quantum circuits in a quantum processor or simulator.
Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations.
This presentation is designed to elucidate about the Quantum Computing - History - Principles - QUBITS - Quantum Computing Models - Applications - Advantages and Disadvantages.
This document discusses quantum cryptography and its advantages over traditional cryptography. It provides background on traditional public and private key cryptography and explains that quantum cryptography uses the principles of quantum mechanics to securely transmit encryption keys. The document outlines the basics of how quantum cryptography works, including using photon polarization to represent bits, and describes an example of how it could be implemented using MATLAB. It also lists some of the key companies working in the field of quantum cryptography.
The Extraordinary World of Quantum ComputingTim Ellison
Originally presented at QCon London - 6 March-2018.
The classical computer on your lap or housed in your data centre manipulates data represented with a binary encoding -- quantum computers are different. They use atomic level mechanics to represent multiple data states simultaneously, leading to a phenomenal exponential increase in the representable state of data, and new solutions to problems that are infeasible using today's classical computers. This session assumes no prior knowledge of quantum technology and presents a introduction to the field of quantum computing, including an introduction to the quantum bit, the types of problem suited to quantum computing, a demo of running algorithms on IBM's quantum machines, and a peek into the future of quantum computers.
This document provides an overview of quantum computers, including a brief history of computing technology, limitations of current computing approaches, and the theory behind quantum computing. Quantum computers use quantum particles and properties like superposition and entanglement to perform exponentially more computations than digital computers. While quantum computers currently exist only as theoretical constructs or limited prototypes, algorithms like Shor's algorithm show their potential to solve problems much faster than classical computers for applications like factoring large numbers. Several research groups worldwide are working to advance the technology with the goal of developing fully functional quantum computers within the next 10-20 years.
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.
- The document discusses quantum computing and its potential applications. It notes that while quantum computers may be able to efficiently simulate physical processes, quantum error correction is needed for scalability.
- Current quantum hardware has around 50-100 qubits but higher qubit numbers and lower error rates are needed. Quantum computers in the "Noisy Intermediate-Scale Quantum" era may be able to explore physics and have some commercial uses, but more powerful quantum technologies will likely require decades more of work.
Strengths and limitations of quantum computingVinayak Sharma
Quantum computing as a research field has been around for about 30 years. It seems like a way to overcome the challenges that classical (boolean based) computers are facing due to “quantum tunneling” effect. Although, there are various theoretical and practical challenges that are needed to be dealt with if we want quantum computes to perform better that classical computers (i.e achieving “quantum supremacy”). This seminar will aim to shed light on basics of quantum computing and its strengths and weaknesses.
Video Links
Part 1: https://www.youtube.com/watch?v=-WLD_HnUvy0
Part 2: https://www.youtube.com/watch?v=xXzUmpk8ztU
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.
This document discusses quantum computation and the future of computing. It covers:
1) The basics of quantum mechanics and how quantum computation works by initializing a system in a superposition and evolving it using quantum gates before measurement.
2) The different models of quantum computation including circuit-based, adiabatic, and one-way quantum computing. It notes that these models are equivalent in computational power.
3) The potential for quantum computers to solve certain problems like integer factorization exponentially faster than classical computers, though challenges remain in the near term due to noise and errors. Larger quantum computers may be able to achieve "quantum supremacy" over classical systems.
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.
Genomics algorithms on digital NISQ accelerators - 2019-01-25Aritra Sarkar
This document discusses using quantum computing to accelerate genomics algorithms. It outlines a roadmap for theoretical and hardware-based quantum genomics solutions (QGS), from perfect qubits to noisy intermediate-scale quantum (NISQ) devices. Near-term algorithms like VQE, QAOA, and variational quantum search are proposed to solve problems like sequence alignment and de novo sequencing. Implementation details are discussed, such as mapping problems to graph algorithms, hybrid classical-quantum programming, and efficiently loading DNA data. The goal is to develop variational algorithms for genomics and implement them on the OpenQL platform to explore their potential on NISQ devices.
This document describes a student's graduation project on using superconducting circuits for quantum computation. It provides an introduction to the topic and outlines the structure of the project. The project will first introduce the concept of a qubit and basics of quantum computation. It will then describe different types of qubit technologies before focusing on superconducting circuits. The document will explain the necessary quantum phenomena like coherence and noise. It will explore superconducting qubits in detail and how to couple them. Finally, it will demonstrate how to perform logical operations using superconducting qubits.
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 trends and directions. It introduces Francisco Gálvez as the presenter and covers the following topics: IBM's quantum computers including the IBM Quantum Experience platform, basic concepts in quantum computing, quantum architecture focusing on superconducting qubits, quantum algorithms like Shor's and Grover's algorithms, applications of quantum computing, and the IBM Quantum Experience platform which allows users to design and run quantum circuits on real quantum processors.
The basics of quantum computing, associated mathematics, DJ algorithms and coding details are covered.
These slides are used in my videos https://youtu.be/6o2jh25lrmI, https://youtu.be/Wj73E4pObRk, https://youtu.be/OkFkSXfGawQ and https://youtu.be/OkFkSXfGawQ
Quantum computing is a rapidly developing field of computer science that explores the application of quantum mechanics to information processing. It promises to revolutionize the way we solve complex problems that are currently beyond the capabilities of classical computers.
This PowerPoint presentation provides an introduction to the basics of quantum computing, including the principles of quantum mechanics, the properties of quantum bits or qubits, quantum entanglement, quantum superposition, and types of quantum computing .
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.
Quantum computing uses quantum properties like superposition and entanglement to represent and process data. A qubit can represent 1s and 0s simultaneously using superposition, allowing quantum computers to perform exponentially more calculations at once than classical computers. However, decoherence causes qubits to lose quantum properties when interacting with the environment, introducing errors. Current research focuses on cloud access to quantum processors and hybrid classical-quantum systems to simplify programming and address decoherence. The goal is for quantum computers to achieve "quantum supremacy" by solving problems intractable for classical computers.
Quantum computers are incredibly powerful machines that take a new approach to processing information. Built on the principles of quantum mechanics, they exploit complex and fascinating laws of nature that are always there, but usually remain hidden from view. By harnessing such natural behavior, quantum computing can run new types of algorithms to process information more holistically. They may one day lead to revolutionary breakthroughs in materials and drug discovery, the optimization of complex manmade systems, and artificial intelligence. We expect them to open doors that we once thought would remain locked indefinitely. Acquaint yourself with the strange and exciting world of quantum computing.
This document discusses quantum computation and its advantages over classical computation. Quantum computation uses quantum bits (qubits) that can exist in superpositions of states rather than just 1s and 0s. This allows quantum processors to perform multiple computations simultaneously. While challenging to implement physically, quantum algorithms like Shor's algorithm could solve certain problems like integer factorization vastly faster than any classical computer. Nanotechnology is needed to build qubits that can maintain coherent superpositions, potentially enabling the construction of a functional quantum computer.
We provide project guidance for final year MTech, BTech, MSc, MCA, ME, BE, BSc, BCA & Diploma students in Electronics, Computer Science, Information Technology, Instrumentation, Electrical & Electronics, Power electronics, Mechanical, Automobile etc. We provide live project assistance and will make the students involve throughout the project. We specialize in Matlab, VLSI, CST, JAVA, .NET, ANDROID, PHP, NS2, EMBEDDED, ARDUINO, ARM, DSP, etc based areas. We research in Image processing, Signal Processing, Wireless communication, Cloud computing, Data mining, Networking, Artificial Intelligence and several other areas. We provide complete support in project completion, documentation and other works related to project.Success is a lousy teacher. It seduces smart people into thinking they can't lose.we have better knowledge in this field and updated with new innovative technologies.
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Quantum computing uses quantum mechanical phenomena like superposition and entanglement to perform computations. It has the potential to solve certain problems like factoring large numbers and simulating quantum systems much faster than classical computers. The basic unit of quantum information is the qubit, which can exist in superpositions of states. Quantum algorithms like Deutsch's algorithm and Shor's algorithm demonstrate quantum speedups using techniques like interference and parallelism. Physical implementations of quantum computers face challenges like controlling and measuring qubits while preventing decoherence. Significant progress has been made in developing algorithms and implementing small qubit systems, but scaling to larger, fully functional quantum computers remains an ongoing challenge.
Call for Chapters- Edited Book: Real World Challenges in Quantum Electronics ...Christo Ananth
Most experts would consider this the biggest challenge. Quantum computers are extremely sensitive to noise and errors caused by interactions with their environment. This can cause errors to accumulate and degrade the quality of computation. Developing reliable error correction techniques is therefore essential for building practical quantum computers. While quantum computers have shown impressive performance for some tasks, they are still relatively small compared to classical computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge. Developing high-quality quantum hardware, such as qubits and control electronics, is a major challenge. There are many different qubit technologies, each with its own strengths and weaknesses, and developing a scalable, fault-tolerant qubit technology is a major focus of research. Funding agencies, such as government agencies, are rising to the occasion to invest in tackling these quantum computing challenges. Researchers — almost daily — are making advances in the engineering and scientific challenges to create practical quantum computers
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
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zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Programming Foundation Models with DSPy - Meetup SlidesZilliz
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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Quantum Properties
Three quantum mechanical properties —
Superposition
Superposition refers to a
combination of states we would
ordinarily describe independently. To
make a classical analogy, if you play
two musical notes at once, what you
will hear is a superposition of the
two notes.
Entanglement
Entanglement is a famously counter-
intuitive quantum phenomenon
describing behavior we never see in
the classical world. Entangled
particles behave together as a
system in ways that cannot be
explained using classical logic.
Interference
Finally, quantum states can undergo
interference due to a phenomenon
known as phase. Quantum
interference can be understood
similarly to wave interference; when
two waves are in phase, their
amplitudes add, and when they are
out of phase, their amplitudes cancel.
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Properties that make QC Different
• Superposition
Exponential speedups as number of qubits grow
• Entanglement
Spooky action at a distance.
• Reversible computing
10-15W vs 20kW
• Privacy (No-cloning theorem)
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Quantum Algorithms
● Shor’s factorization algorithm
● Grover’s search algorithm
● Deutsch - Jozsa algorithm
● HHL algorithm - Useful in the NISQ era (these are mostly hybrid algorithms)
● QAOA - Quantum Approximate Optimization Algorithm
● VQE - Variational Quantum Eigen-solver
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Problems
● Hard to build and retain qubits due to decoherence
● High amount of noise
● Need for better quantum algorithms (Optimization)
● Algorithms like Shor’s can’t be implemented today
● All hardwares have their own pros and cons
● Data storage?
● Debugging?
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Categories
Quantum Mechanics
Quantum Information
Quantum
Computation
Gate based Annealing , ...
Quantum
Cryptography
Information Theory
Quantum Key
Distribution
Quantum Error
Correction
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Qiskit
• SDK for working with Noisy Intermediate-Scale Quantum (NISQ) Computers
• Apache 2.o License
• Designed to be backend agnostic
• Includes out-of-the-box local simulators and support for running on IBMQ
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About Terra
Qiskit Terra provides the
foundational roots for our software
stack. Within Terra is a set of tools
for composing quantum programs at
the level of circuits and pulses,
optimizing them for the constraints of
a particular physical quantum
processor, and managing the batched
execution of experiments on remote-
access backends. Terra is modularly
constructed, simplifying the addition
of extensions for circuit optimizations
and backends.
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About Aqua
Qiskit Aqua contains a library of
cross-domain quantum algorithms
upon which applications for near-
term quantum computing can be
built. Aqua is designed to be
extensible, and employs a pluggable
framework where quantum
algorithms can easily be added. It
currently allows the user to
experiment on chemistry, AI,
optimization and finance applications
for near-term quantum computers.
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About Ignis
Qiskit Ignis is a framework for
understanding and mitigating noise in
quantum circuits and systems. The
experiments provided in Ignis are
grouped into the topics of
characterization, verification and
mitigation. Characterization
experiments are designed to measure
noise parameters in the system.
Verification experiments are designed
to verify gate and small circuit
performance. Mitigation experiments
run calibration circuits that are
analyzed to generate mitigation
routines that can be applied to
arbitrary sets of results run on the
same backend.
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About Aer
Qiskit Aer provides a high
performance simulator framework for
the Qiskit software stack. It contains
optimized C++ simulator backends
for executing circuits compiled in
Qiskit Terra, and tools for
constructing highly configurable
noise models for performing realistic
noisy simulations of the errors that
occur during execution on real
devices.