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Computing technologies and methodologies always take a turn and right now, quantum computing and its mechanics are the most engaged field. This lets us propose models using quantum physics concepts and quantum mechanics. This not only opens us the scope for gaining better efficiency but also gains a new way of proposing algorithms. The current problem with the financial models is that they do not consider the negative possibilities that might lead to wrong and also inconsistent results. Additionally, this also makes usquestion the algorithm in the work itself. Even if the systems do solve all these inconsistencies, the hardware requirements of those systemsare very high. This algorithm uses quantum-based theories to make daily computations faster without extra or high-end hardware. This algorithm is more oriented toward the financial model where it takes into consideration of negative cases. Experimental results show thatthe algorithm proposed obtains the desired and optimum values based on models like Ising, Markowitz, and QUBO. [ABSTRACT FROM AUTHOR]

Information is divided into two types: classical and quantum. Quantum computing, quantum cryptography, and quantum teleportation are just a few of the miracles they can do when working together. Some of the uses range from assisting in the prevention of spies reading private messages to assisting in the prevention of spies reading private communications. Quantum purification and quantum error correction are examples of techniques that will make their implementation easier. Although some of these concepts are still beyond present technological capabilities, quantum cryptography has been established. The possibilities for small-scale quantum computer device prototypes by the end of the millennium are promising. This paper is focusing on addressing the depended approaches which deal with implementation cryptography based on quantumcomputing. Remembering that cryptography is a method of encryption that uses the naturally occurring propertiesof quantum mechanics to secure and transmit data in a way that cannot be hacked. Cryptography is the process ofencrypting and protecting data so that only the person who has the right secret key can decrypt it. For decades now, quantum computing has been hailed as one of the next big revolutions. Quantum computing is not just fasterthan traditional computing methods, but a fundamentally different approach to solve seemingly intractable problems. The mathematical operations that most traditional cryptographic algorithms rely on could be cracked with a sufficiently strong quantum computer. This paper aims to explain how quantum computing affects currentcryptography and expose readers to fundamental post-quantum methods. Quantum computing's influence on IT professionals is becoming increasingly important. As a result, we provide a straightforward introduction to post-quantum cryptography, including quantum-resistant algorithms and quantum key distribution. [ABSTRACT FROM AUTHOR]

Quantum computing technology is in an evolutionary stage with the active involvement of more than 600 renowned companies and almost 30 national laboratories and government agencies worldwide as per the report published by The Quantum Insider. The efficacy of any emerging technology is assessed through three factors: time, cost, and quality. Parallel computing is possible in quantum computers due to superposition and entanglement of qubits which offers exceptional speed advantage in cracking complex problems. Thus the two requirements of time and cost are fulfilled. However, the quality aspect is lagging on account of a few constraints. This technology is poised to become a disruptive technology as a lot of research and development activities are being carried out globally to improve the quality and accuracy of the results to acceptable standards. In the next decade, this exotic technology will transform the entire industry and turbocharge innovation globally. [ABSTRACT FROM AUTHOR]

Machine learning is the process of discovering patterns in data and using those patterns to forecast or predict future occurrences of those patterns. The machine learning process consists of three steps: input data management, model construction, and model evaluation. Combining machine learning and quantum computing allows for the design and operation of quantum circuits with behavior resembling that of classical machine learning. Variable quantum circuits are frequently used in quantum machine learning. Parameterized variables, a crucial part of variable quantum circuits, must be adjusted in order to achieve good performance of these circuits. It is possible to modify parameterized variables in a variety of ways, such as by using gradient methods or linear programming to determine the circuit's optimal point. This study proposes a method for automatically designing a variational quantum circuit to classify the different datasets, including the well-known 1-dimensional and 2-dimensional datasets, iris and MNIST, using a genetic algorithm to find the best values for the parameterized variables. The Qiskit quantum simulation tools are employed in these experiments. The results show that genetic algorithms can find solutions with greater accuracy than linear-based optimizers by 94 percent and 37.5 percent, respectively, for the iris dataset and the MNIST dataset. [ABSTRACT FROM AUTHOR]

Quantum machine learning is a new field of study that aims to apply the advantages of quantum computing, such as superposition, which is one of the intriguing properties that could speed up computation, to machine learning. Like classical machine learning models, quantum machine learning models can learn from specific input data and perform specific prediction tasks. However, quantum machine learning models are currently in the form of quantum circuits with parameterizable gates. In this paper, the implementation of a quantum classification model is investigated using the two most well-known quantum machine learning development tools: Cirq with TensorFlow Quantum (TFQ) and Qiskit with PyTorch. The quantum classification circuit is trained to recognize images of handwritten digits using the MNIST dataset. However, because the quantum computer is still in development and is difficult to access and use, quantum simulators are the best alternative for the time being. The performance of the quantum classification model implemented by the two development tools is then compared in this paper experimentally using quantum simulators on two different hardware configurations. In addition, the experimental setups differ in the number of input qubits used to store the image's classical pixel values. Finally, the wall time and CPU time used to run the training process, as well as classification accuracy, are examined. In terms of accuracy, Qiskit with PyTorch outperforms Cirq with TFQ only in the lower number of qubits but the results are similar in the higher number of qubits. The experiment results in terms of run-time are highly different. From the result, we find that Cirq is noticeably faster than Qiskit in every experiment by at least 90 times. [ABSTRACT FROM AUTHOR]

Based on an idea by Richard Feynman, quantum computing is a relatively new technological innovation that promises to very quickly solve problems that one usually encounters in Science and Engineering (i.e., optimization and numerical problems). Currently, there are no full-blown quantum computers; nevertheless, researchers are working on quantum technology, if one is allowed. to say so, propose new ideas, solve old technological problems, implement new hardware design principles, etc., and all these Developments are quite encouraging for the future of quantum computing. Given these facts, it makes sense to propose the use of quantum technology for the solution of common and not-so-common problems encountered in Science and Technology today. [ABSTRACT FROM AUTHOR]

Quantum computers are here, and the search for applications and use of these allow us to overcome the limits that today's hardware information processing gives us is constantly going on. Quantum machine learning is one of the many emerging fields that use quantum computers to process information. In this paper, we present a method and a set of experiments where we see the potential and capacity of the Noisy intermediate-scale quantum hardware for the execution of different models having as the basis in some of them the quantum algorithm corresponding to the Quantum Fourier Transform. With this, we demonstrate the effectiveness of how this algorithm can enhance the performance of quantum computations in quantum machine learning models in near-term applications. We used the systems offered by IBM Quantum and the cross-platform Python library for quantum differentiable programming Pennylane by Xanadu Quantum Technologies Inc. [ABSTRACT FROM AUTHOR]

The rapid development of quantum computing and cryptography unleash the thinking of an internet network that is based on quantum mechanics. The quantum-based internet is predicted to be more secure than the classical one due to its entanglement distribution strategy. The main challenge that can face the quantum internet is the nature of quantum bits which require special circumstances to stay stable. Quantum bit entanglement is fragile and decoherence which leads to missing the entangled photons and disconnection of communication. Recently, different solutions have been suggested to overcome this challenge which are mainly counting on the technologies and materials that can increase the photon lifetime and enhance the ability to transfer it over long distances without losses. In this paper a general overview of this new and interesting research topic is presented which can be considered as an onset for the researchers who are interested in this promising field. [ABSTRACT FROM AUTHOR]

In this busy world, there is an estimation of 3.5 exabytes of information data been generated in a single day and the data is shared on more than 10 million computing devices. As We, human beings are wholeheartedly dependent on the digital based computing devices for knowledge sharing by means of text and image information for each and every commotion of the day. Now, the sustenance of life without computing is considered as perplexed. As per a report submitted by association of semiconductor industries which states that by 2040, it is not possible to provide power to computer machine which is available in good running conditions present throughout the globe. It's a known fact that the fundamental functionality of a computer system to modify and save the information data. Presently all the computer systems are using the classical technique to manipulate the data using single bits that stores the information data in form of 0's and 1's. [1To overcome the inability stated by semiconductor industry, the quantum physics has come up with a new concept which specifies that the quantum elements have the tendency to move in both directions i.e. fore and rear directions and its presence can be felt in both places at same time and travel itself instantly]1. This peculiar tendency of quantum particles had lead to quantum computing. The most critical property of quantum computing is its enhanced asset for characterization and construction of information data. A mechanism is developed to work on various operations for computation of information data. Qubits i.e quantum bits are used in Quantum computing, it consist of a third state excluding the traditional data states 0 and 1.Hence the time duration taken by quantum computing to modify the information data is much lesser than that of traditional computing. In this paper, we try to explore the concepts of quantum computing, how it is related to physics, how it can be used and implemented. [ABSTRACT FROM AUTHOR]

Ettore Majorana, in his short life, unintendedly has uncovered the most profound problem in quantum computation by his discovery of Majorana fermion, a particle which is its own anti-particle. Owing to its non-Abelian exchange statistics, Majorana fermions may act as a qubit for a universal quantum computer which is fault-tolerant. The existence of such particle is predicted in mid-gap states (zero modes) of a topological superconductor as bound states that have a highly entangled degenerate ground state. This introductory overview will focus on the simplest theoretical proposals of Majorana fermions for topological quantum computing in superconducting systems, emphasizing the quest from the scalability problem of quantum computer to its possible solution with topological quantum computer employing non-Abelian anyons on various platforms of certain Majorana fermion 'signature' encountered. [ABSTRACT FROM AUTHOR]

The fundamental link between physics and computation leads to an exciting field of quantum computation. Since the birth of the programmable digital computer, random number generators in computers have been developed. In principle, the pseudo random number generators currently implemented in digital computers are predictable. However, a quantum random number generator is employed to ideally generate unpredictable random numbers. In this essay, we explain why a one-qubit quantum computer can be a quantum random number generator and how this leads to justifying the foundations of quantum mechanics. [ABSTRACT FROM AUTHOR]

Linear optics is a promising physical architecture for the implementation of the quantum computing devices. The key element of the linear optical quantum computer is an optical circuit realizing the sequence of transformations defined by the required quantum algorithm. The most prominent approach is the reconfigurable integrated photonics which allows to miniaturize standard optical setups on the chosen integrated photonic platform. In this paper, we propose a universal linear-optical circuit design comprised of the series of multiport beamsplitters followed by the phaseshifting elements. The proposed unitary composer device can be straightforwardly implemented using standard integrated photonic technologies. We provide guidelines for appropriate multiport beamsplitter fabrication using integrated waveguide lattices. To exemplify the performance of the composer we provide the six-mode CNOT linear optical gate circuit design fitted to described interferometric circuit. [ABSTRACT FROM AUTHOR]

Methods of processing quantum data become more important as quantum computing devices improve their quality towards fault tolerant universal quantum computers. These methods include discrimination and filtering of quantum states given as an input to the device that may find numerous applications in quantum information technologies. In the present paper, we address a scheme of a classification of input states, which is nondestructive and deterministic for certain inputs, while probabilistic, in general case. This can be achieved by incorporating phase estimation algorithm into the hybrid quantum-classical computation scheme, where quantum block is trained classically. We perform proof-of-principle implementation of this idea using superconducting quantum processor of IBM Quantum Experience. Another aspect we are interested in is a mitigation of errors occurring due to the quantum device imperfections. We apply a series of heuristic tricks at the stage of classical postprocessing in order to improve raw experimental data and to recognize patterns in them. These ideas may find applications in other realization of hybrid quantum-classical computations with noisy quantum machines. [ABSTRACT FROM AUTHOR]

This paper shows a novel way of simulating a Markov process by a quantum computer. The main purpose of the paper is to show a particular application of quantum computing in the field of stochastic processes analysis. Using a Quantum computer, the process could be superposed, where the random variables of the Markov chain are represented by entangled qubit states, which gives the great opportunity of having all the possible scenarios simultaneously. [ABSTRACT FROM AUTHOR]

The qubit state is represented by a coherent superposition of its orthonormal basis states (|0❭ and |1❭). The probability distribution of a qubit is a discrete probability distribution of the qubits probability amplitudes. Setting a custom probability amplitudes allows a qubit to evolve to any desired state. In this paper a controlled n-root of X gate is simulated on a real quantum processor using IBMs Quantum Experience platform. A custom quantum gate could be constructed where the only inputs are the control and target qubits and the desired probability distribution for the target qubit. [ABSTRACT FROM AUTHOR]

The application of quantum mechanics contributes to the field of cryptography with very important advantage as it offers a mechanism for detecting the eavesdropper. The pioneering work of quantum key distribution uses mutually unbiased bases (MUBs) to prepare and measure qubits (or qudits). Weak mutually unbiased bases (WMUBs) have weaker properties than MUBs properties, however, unlike MUBs, a complete set of WMUBs can be constructed for systems with composite dimensions. In this paper, we study the use of weak mutually unbiased bases (WMUBs) in quantum key distribution for composite dimensional finite systems. We prove that the security analysis of using a complete set of WMUBs to prepare and measure the quantum states in the generalized BB84 protocol, gives better results than using the maximum number of MUBs that can be constructed, when they are analyzed against the intercept and resend attack. [ABSTRACT FROM AUTHOR]

Deterministic doping by single ion implantation, the precise placement of individual dopant atoms into devices, is a path for the realization of quantum computer test structures where quantum bits (qubits) are based on electron and nuclear spins of donors or color centers. We present a donor - quantum dot type qubit architecture and discuss the use of medium and highly charged ions extracted from an Electron Beam Ion Trap/Source (EBIT/S) for deterministic doping. EBIT/S are attractive for the formation of qubit test structures due to the relatively low emittance of ion beams from an EBIT/S and due to the potential energy associated with the ions' charge state, which can aid single ion impact detection. Following ion implantation, dopant specific diffusion mechanisms during device processing affect the placement accuracy and coherence properties of donor spin qubits. For bismuth, range straggling is minimal but its relatively low solubility in silicon limits thermal budgets for the formation of qubit test structures. [ABSTRACT FROM AUTHOR]

Here, I summarize the results presented in B.Kraus, Phys. Rev. Lett. 107, 250503 (2011). Recently, it has been shown that certain circuits, the so-called match gate circuits, can be compressed to an exponentially smaller universal quantum computation. We use this result to demonstrate that the simulation of a 1-D Ising chain consisting of n qubits can be performed on a universal quantum computer running on only log(n) qubits. We show how the adiabatic evolution can be simulated on this exponentially smaller system and how the magnetization can be measured. Since the Ising model displays a quantum phase transition, this result implies that a quantum phase transition of a very large system can be observed with current technology. [ABSTRACT FROM AUTHOR]

This paper reviews the history and current (2008) state-of-the-art methods for programming quantum computers. We analyze the needs for programming quantum computers in the near future (when actual quantum computing hardware is available), and use this analysis to predict the direction in which the field is moving, and make recommendations for further development of quantum programming language tools. [ABSTRACT FROM AUTHOR]

Quantum computers will perform computations at the atomic scale and operate according to the rules of quantum mechanics wherein quantum bits can exist in two or more states at once. Quantum entanglement is a remarkable property which plays a crucial role in quantum computation and can be utilized for applications like quantum teleportation. Another field, embryonics is inspired by the basic processes of molecular biology and by the embryonic development of living beings. Embryonic systems have properties unique to the living world like self-repair and self-reconstruction. Self-repair allows partial reconstruction in case of a minor fault, while self-replication allows complete reconstruction of the original device in case of a major fault. This paper presents a novel algorithm based on quantum teleportation for development of embryonic systems, called as Quantum Teleportation Embryonic Algorithm (QTEA). An example application of a robust quantum BCD to seven segment decoder is also presented. The results obtained are quite interesting and hold great promise for design of dependable systems through synthesis of quantum computing and embryonic systems. © 2006 American Institute of Physics [ABSTRACT FROM AUTHOR]

Quantum computing is a novel paradigm that promises to be the future of computing. The performance of quantum algorithms has proved to be stunning. ANN within the context of classical computation has been used for approximation and classification tasks with some success. This paper presents an idea of quantum neural networks along with the training algorithm and its convergence property. It synergizes the unique properties of quantum bits or qubits with the various techniques in vogue in neural networks. An example application of Fisher’s Iris data set, a benchmark classification problem has also been presented. The results obtained amply demonstrate the classification capabilities of the quantum neuron and give an idea of their promising capabilities. © 2006 American Institute of Physics [ABSTRACT FROM AUTHOR]

Quantum versions of random walks have diverse applications that are motivating experimental implementations as well as theoretical studies. Recent results showing quantum walks are "universal for quantum computation" relate to algorithms, to be run on quantum computers. We consider whether an experimental implementation of a quantum walk could provide useful computation before we have a universal quantum computer. [ABSTRACT FROM AUTHOR]