Recent increasing interest in quantum computers has spurred research into practical engineering applications for quantumalgorithms. One potential application is process control. The unique quantum phenomena involved ...
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Recent increasing interest in quantum computers has spurred research into practical engineering applications for quantumalgorithms. One potential application is process control. The unique quantum phenomena involved with quantum computing brings up interesting considerations for control. This work focuses on non-determinism, first through a motivating simulation utilizing a continuous stirred-tank reactor. Following this, two methods of potentially ensuring system stability in the presence of non-determinism are discussed. The first involves including an additional gate to the modified Grover's algorithm presented in our previous work, which is designed to prevent a qubit state corresponding to an undesired control input from being measured. The second method involves defining an inner region where, if the state leaves the region, a classical stabilizing controller is activated to drive the state back inside the region.
The quantumalgorithms for Monte Carlo integration (QMCI), which are based on quantum amplitude estimation (QAE), speed up expected value calculation compared with classical counterparts and have been widely investiga...
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The quantumalgorithms for Monte Carlo integration (QMCI), which are based on quantum amplitude estimation (QAE), speed up expected value calculation compared with classical counterparts and have been widely investigated along with their applications to industrial problems such as financial derivative pricing. In this paper, we consider an expected value of a function of a stochastic variable and a real-valued parameter and how to calculate derivatives of the expectation with respect to the parameter. This problem is related to calculating sensitivities of financial derivatives and so of industrial importance. Based on QMCI and the general-order central difference formula for numerical differentiation, we propose two quantum methods for this problem and evaluate their complexities. The first one, which we call the naive iteration method, simply calculates the formula by iterative computations and additions of the terms in it and then estimates its expected value by QAE. The second one, which we name the sum-in-QAE method, performs the summation of the terms at the same time as the sum over the possible values of the stochastic variable in a single QAE. We see that, depending on the smoothness of the function and the number of qubits available, either of two methods is better than the other. In particular, when the function is nonsmooth or we want to save the qubit number, the sum-in-QAE method can be advantageous.
quantum machine learning (QML) and quantum communication (QC) are emerging areas of research for complexity-efficient data processing, information retrieval, system, and simulations. Towards next-generation vehicular ...
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ISBN:
(纸本)9798350311143
quantum machine learning (QML) and quantum communication (QC) are emerging areas of research for complexity-efficient data processing, information retrieval, system, and simulations. Towards next-generation vehicular technology, quantum circuits and algorithms are critical in providing faster and more reliable solutions. Here, we show a modified quantum K-nearest neighbour (QKNN) algorithm for symbol detection in the communication system. In the proposed algorithm, we embed a quantum swap-test circuit for the distance computation between unknown symbols with known training symbols with a memory-efficient strategy, which eliminated quantum search operations for the small-search space such as 16-QAM symbols. The proposed quantum circuit is simulated on an IBM quantum machine and the numerical results are shown to demonstrate the efficacy of the proposed framework. The classification accuracy as a performance metric is shown and the improvement of quantum resources in terms of gate complexity is discussed.
Malicious users using quantum computers can employ quantum attacks on modern cryptography algorithms. Grover's search algorithm, a well-known quantum algorithm, can reduce the search complexity of O(2(n)) to root ...
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Malicious users using quantum computers can employ quantum attacks on modern cryptography algorithms. Grover's search algorithm, a well-known quantum algorithm, can reduce the search complexity of O(2(n)) to root 2(n) for symmetric key cryptography with an n-bit key. To apply the Grover search algorithm, the target encryption process must be implemented in a quantum circuit. In this paper, we present optimized quantum circuits for Korean block ciphers based on ARX architectures. We adopt the optimal quantum adder and design it in parallel way. Compared to previous implementations, we provide performance improvements of 78%, 85%, and 70% in terms of circuit depth for LEA, HIGHT, and CHAM, respectively, while keeping the number of qubits and quantum gates minimum. The depth of a circuit is an important factor related to its execution time. Finally, we estimate the cost of the Grover key search for Korean block ciphers and evaluate the post-quantum security based on the criteria presented by NIST.
Due to efficient encoding and decoding algorithms, BCH codes have many applications in data storage systems and satellite communications. Meanwhile, one advantage of BCH codes is to construct quantum codes. In this pa...
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Due to efficient encoding and decoding algorithms, BCH codes have many applications in data storage systems and satellite communications. Meanwhile, one advantage of BCH codes is to construct quantum codes. In this paper, we assume that q 1mod m, where m is a positive integer. We first study a class of q-ary quantum codes of length r(q(m)-1)/q-1 by CSS construction, where r |q-1. Then, we construct two families of q-ary quantum codes of length r (q(2m)-1)/q(2)-1 by Hermitian construction. These constructions produce new quantum codes with larger dimensions.
The trace norm of matrices plays an important role in quantuminformation and quantum computing. How to quantify it in today’s noisy intermediate scale quantum(NISQ) devices is a crucial task for information processi...
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The trace norm of matrices plays an important role in quantuminformation and quantum computing. How to quantify it in today’s noisy intermediate scale quantum(NISQ) devices is a crucial task for informationprocessing. In this paper, we present three variational quantumalgorithms on NISQ devices to estimate the trace norms corresponding to different *** with the previous methods, our means greatly reduce the requirement for quantum resources. Numerical experiments are provided to illustrate the effectiveness of our algorithms.
Graph optimization problems are used in many different fields, including machine learning, network architecture, and logistics. They often require determining the best way to arrange variables in a way that minimizes ...
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Through the two specific problems, the 2D hidden linear function problem and the 1D magic square problem, Bravyi et al. have recently shown that there exists a separation between QNC(0) and NC0, where QNC(0) and NC0 a...
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Through the two specific problems, the 2D hidden linear function problem and the 1D magic square problem, Bravyi et al. have recently shown that there exists a separation between QNC(0) and NC0, where QNC(0) and NC0 are the classes of polynomial-size and constant-depth quantum and classical circuits with bounded fan-in gates, respectively. In this paper, we present another problem with the same property, the magic pentagram problem based on themagic pentagram game, which is a nonlocal game. In otherwords, we show that the problem can be solved with certainty by a QNC(0) circuit but not by any NC0 circuits.
The globe is observing the emergence of the Internet of Things more prominently recognized as IoT. In this day and age, there exist numerous technological apparatuses that possess the capability to be interconnected w...
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