Quantum Algorithm Implementations for Beginners (original) (raw)
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Breaking Barriers: Unleashing the Power of Quantum Algorithms
Quantum computing is a rapidly developing field with the potential to revolutionize our ability to solve certain computational problems . While classical computers operate using classical bits, quantum computers use quantum bits (qubits), which can exist in a superposition of states, allowing for parallel computations. The existence of quantum algorithms, which can solve certain problems exponentially faster than classical algorithms, is one of the most exciting aspects of quantum computing. These exotic algorithms are designed to take advantage of quantum mechanical properties such as entanglement and interference, and have the potential to transform a range of fields, including cryptography, optimization, and machine learning.
A practicable guide to the quantum computation architectures
2019
The primordial model of quantum computation was introduced over thirty years ago and the first quantum algorithms have appeared for over twenty years. Yet the exact architectures for quantum computer seem foreign to an undergraduate student major in computer science or engineering, even though the mass media has helped popularize the terminologies in the past decade. Despite being a cutting-edge technology from both the theoretical and the experimental perspectives, quantum computation is indeed imminent and it would be helpful to give the undergraduate students at least a skeleton understanding of what a quantum computer stands for. Since instruction-set architectures originated from classical computing models are familiar, we propose analogously a set of quantum instructions, which can be composed to implement renowned quantum algorithms. Albeit the similarity one can draw between classical and quantum computer architectures, current quantum instructions are fundamentally incommensurable from their classical counterparts because they lack the innate capability to implement logical deductions and recursions. We discuss this trait in length and illustrate why it is held responsible that current quantum computers not be considered general computers.
An introduction to quantum computing for non-physicists
ACM Computing Surveys, 2000
Richard Feynman's observation that certain quantum mechanical effects cannot be simulated efficiently on a computer led to speculation that computation in general could be done more efficiently if it used these quantum effects. This speculation proved justified when Peter Shor described a polynomial time quantum algorithm for factoring integers.
Quantum computation is an emerging field of research at the intersection of computer science, information theory and quantum physics. With applications in cryptography, simulation of complex quantum mechanical systems, artificial intelligence, weather forecast and market prediction, quantum computers will be indispensable in the future. Recent years have seen immense progress on the experimental front, with the IBM Quantum Experience (IBM QE), real quantum computers are within reach for anyone. We introduce here the basic concepts of quantum computation for using IBM QE, needing only the knowledge of matrix multiplication.
An Introduction to Quantum Computing for non phsicists
Richard Feynman's observation that certain quantum mechanical effects cannot be simulated efficiently on a computer led to speculation that computation in general could be done more efficiently if it used these quantum effects. This speculation proved justified when Peter Shor described a polynomial time quantum algorithm for factoring integers.
ACM Transactions on Quantum Computing, 2021
In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some ...
Algorithms and Architectures for Quantum Computers
This research group seeks to understand and develop the experimental and theoretical potential for information processing and communications using the laws of quantum physics. Two fundamental questions motivate our work: (1) How can a large-scale, reliable quantum computer be realized? (2) What new algorithms, cryptographic primitives, and metrology techniques are enabled by quantum information? The first question is primarily experimental. We intend to build a large-scale, reliable quantum computer over the next few decades. Based on our successes with realizing small quantum computers, and after three years of testing, modeling, and planning, we have come to understand how this can be achieved by combining fault tolerance techniques developed by von Neumann, with methods from atomic physics.
Progress in Quantum Electronics, 1998
Quantum computers require quantum logic, something fundamentally different to classical Boolean logic. This difference leads to a greater efficiency of quantum computation over its classical counter-part. In this review we explain the basic principles of quantum computation, including the construction of basic gates, and networks. We illustrate the power of quantum algorithms using the simple problem of Deutsch, and explain, again in very simple terms, the well known algorithm of Shor for factorisation of large numbers into primes. We then describe physical implementations of quantum computers, focusing on one in particular, the linear ion-trap realization. We explain that the main obstacle to building an actual quantum computer is the problem of decoherence, which we show may be circumvented using the methods of quantum error correction.
Quantum programming: From theories to implementations
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This paper surveys the new field of programming methodology and techniques for future quantum computers, including design of sequential and concurrent quantum programming languages, their semantics and implementations. Several verification methods for quantum programs and communication protocols are also reviewed. The potential applications of programming techniques and related formal methods in quantum engineering are pointed out.