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We propose a high-performance state-vector emulator of a gate-based quantum processors developed in the Rust programming language. It supports OpenQASM 2.0 programming language [1] for quantum circuits specification and has a user-friendly Python based API. We present a wide range of numerical benchmarks of the emulator. We expect that our emulator will be used for design and validation of new quantum algorithms. [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]