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The classical moving target segmentation (MTS) algorithm in a video can segment the moving targets out by calculating frame by frame, but the algorithm encounters a real-time problem as the data increases. Recently, the benefits of quantum computing in video processing have been demonstrated, but it is still scarce for MTS. In this paper, a quantum moving target segmentation algorithm for grayscale video based on background difference method is proposed, which can simultaneously model the background of all frames and perform background difference to segment the moving targets. In addition, a feasible quantum subtractor is designed to perform the background difference operation. Then, several quantum units, including quantum cyclic shift transformation, quantum background modeling, quantum background difference, and quantum binarization, are designed in detail to establish the complete quantum circuit. For a video containing 2 m frames (every frame is a 2 n × 2 n image with q grayscale levels), the complexity of our algorithm is O (n + q) . This is an exponential speedup over the classical algorithm and also outperforms the existing quantum algorithms. Finally, the experiment on IBM Q demonstrates the feasibility of our algorithm in this noisy intermediate-scale quantum (NISQ) era. [ABSTRACT FROM AUTHOR]

We propose a circuit optimization algorithm that facilitates the implementation of various applications on noise intermediate-scale quantum (NISQ) devices. The algorithm is hardware-independent and reduces the overall circuit cost of Hamiltonian simulation, particularly by minimizing the number of CNOT gates. Our approach employs a sub-circuit synthesis scheme for intermediate representation and proposes the practical template matching algorithm (TM) for gate elimination to minimize CNOT counts. This algorithm demonstrates low complexity and enhances the circuit performance of Hamiltonian simulations. In our simulations, we benchmarked different algorithms across various Hamiltonian models to quantify and compare the benefits of our approach. Compared with advanced generic compilers and specific quantum compilers, the results obtained from simulating our algorithm show an average reduction of 1.5 × (up to 2.56 × ) in CNOT counts, and 1.4 × (up to 3.1 × ) in circuit depth. This improvement further advances the practical application of Hamiltonian simulation in the NISQ era. [ABSTRACT FROM AUTHOR]

In this work, we present a protocol for comparing the performance of arbitrary quantum processes executed on spatially or temporally disparate quantum platforms using Local Operations and Classical Communication (LOCC). The protocol involves sampling local unitary operators, which are then communicated to each platform via classical communication to construct quantum state preparation and measurement circuits. Subsequently, the local unitary operators are implemented on each platform, resulting in the generation of probability distributions of measurement outcomes. The max process fidelity is estimated from the probability distributions, which ultimately quantifies the relative performance of the quantum processes. Furthermore, we demonstrate that this protocol can be adapted for quantum process tomography. We apply the protocol to compare the performance of five quantum devices from IBM and the "Qianshi" quantum computer from Baidu via the cloud. The experimental results unveil two notable aspects: Firstly, the protocol adeptly compares the performance of the quantum processes implemented on different quantum computers. Secondly, the protocol scales, although still exponentially, much more favorably with the number of qubits, when compared to the full quantum process tomography. We view our work as a catalyst for collaborative efforts in cross-platform comparison of quantum computers. [ABSTRACT FROM AUTHOR]

Regarding the massive multiple-input multiple-output (MIMO) uplink, the quantum version detection based on the minimum mean square error criterion is developed for complexity consideration. Specifically, a comprehensive quantum algorithm for encoding the estimated signal into a quantum state is presented, synthesizing the subroutines of state preparation, Hamiltonian simulation, phase estimation and so on. Indispensable assumptions along with the quantum algorithm are summarized and assumption testing in a MIMO scenario is conducted. Both theoretical analyses from the mathematical point of view and simulated realizations in massive MIMO systems basically confirm the applicability of the quantum algorithm. With desired precision, the quantum algorithm achieves almost quadratic speedup over all classical counterparts. Whereas, with weaker precision accompanied by undetermined performance loss, the quantum algorithm eventually breaks through polynomial-time detection complexity and achieves exponential speedup. Future work will be directed toward the error dependence improvement, classical form outputs and experimental applications in quantum communication systems. [ABSTRACT FROM AUTHOR]

In this letter, we propose a hybrid analog/digital detection algorithm, the Correlated Interference Cancellation (CIC) algorithm, for Impulse Radio Ultra-WideBand (IR-UWB) system. The CIC algorithm correlates received signal with its delayed versions in the analog domain and samples the correlation output at the symbol rate. The symbol rate samples are processed in the digital domain to perform interference cancellation. Therefore, CIC works for high data rate systems with heavy InterSymbol Interference (ISI). Simulation results show that CIC achieves good performance in typical UWB channels. [ABSTRACT FROM AUTHOR]