QuantumSkynet: A High Dimensional Quantum Computing Simulator

Abstract

The use of classical computers to simulate quantum computing has been successful in aiding the study of quantum algorithms and circuits that are too complex to examine analytically. Current implementations of quantum computing simulators are limited to two-level quantum systems. Recent advances in high-dimensional quantum computing systems have demonstrated the viability of working with multilevel superposition and entanglement. These advances allow an agile increase in the number of dimensions of the system while maintaining quantum entanglement, achieving higher encoding of information and making quantum algorithms less vulnerable to decoherence and computational errors. In this paper, we introduce QuantumSkynet, a novel high-dimensional cloud-based quantum computing simulator. This platform allows simulations of qudit-based quantum algorithms. We also propose a unified generalization of high-dimensional quantum gates, which are available for simulations in QuantumSkynet. Finally, we report simulations and their results for qudit-based versions of the Deutsch-Jozsa and quantum phase estimation algorithms using QuantumSkynet.

Quantum Measurement Classification with Qudits

“…[20]. The DMKDE and DMKDC quantum circuits were simulated in the qudit-based quantum computer simulator QuantumSkynet [21]. The DMKDE quantum protocol can be extended to compute the expected value of a density matrix with qudits.…”

“…QuantumSkynet [21] is a high dimensional quantum computing simulator, that allows to implement high-dimensional quantum algorithms in a cloud-based environment. To simulate the quantum circuits related to this project, the following gates were simulated using QuantumSkynet:…”

“…The implementation of the algorithms DMKDE and DMKDC requires three phases: (i) Quantum State Preparation, (ii) Training Phase, and (iii) Prediction Phase. The first two steps were computed in a classical computer, with the Tensorflow implementations of the algorithms [20], while the prediction phase was simulated in the high dimensional quantum computer simulator QuantumSkynet [21].…”

“…[20], proposed two quantum-inspired machine learning methods, the Density Matrix Kernel Density Estimation (DMKDE), which is a non-parametric density estimation method, and the Density Matrix Kernel Density Classification (DMKDC), a supervised machine learning algorithm based on density matrices and kernel density estimation. In this article, we propose two quantum protocols to implement the prediction phase of the DMKDE and the DMKDC in a highdimensional quantum computer, the simulations were performed using the high-dimensional quantum simulator QuantumSkynet [21]. This article is organized as follows: In Section 2, we present the background with the descriptions of the DMKDE, the DMKDC, and the quantum simulator QuantumSkynet with some of its quantum gates, in Section 3, we describe the proposed high-dimensional quantum circuits, in Section 4, we show some results of the method on some toy data sets, and finally, we present the conclusions of the work in Section 5.…”

QuDiet: A classical simulation platform for qubit‐qudit hybrid quantum systems

“…The inception of this simulator was in the wake (or lack thereof) of accessible simulators that were capable of simulating multi‐valued logic in a user‐friendly manner. This meant that a lot of research time and effort was previously spent in the construction of matrices and checking their compatibility, dimensions and kronecker products manually before their output could be deciphered from a huge 1D‐array [25–27]. As an example, let us say a generalised gate is imposed on five qudits in a 4‐dimensional quantum system.…”