Attention-based neural networks for quantum computing simulations
Quantum code-related entities are obtained and one or more of a set of one or more trained neural network models are selected for inferencing based on the quantum code-related …
Quantum code-related entities are obtained and one or more of a set of one or more trained neural network models are selected for inferencing based on the quantum code-related …
Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this …
This paper explores artificial intelligence (AI) methods for the approximate compiling of unitaries, focusing on the use of fixed two-qubit gates and arbitrary single-qubit …
Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and …
One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to a process to port code while adapting the code for a …
Quantum physics has changed the way we understand our environment, and one of its branches, quantum mechanics, has demonstrated accurate and consistent theoretical results. Quantum …
This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By …
Methods and systems use one or more machine learning models to automatically generate three-dimensional sound. A multimodal content item is accessed by a computing device. …
Quantum physics has changed the way we understand our environment, and one of its branches, quantum mechanics, has demonstrated accurate and consistent theoretical results. Quantum …
Quantum Computing is envisioned as one of the scientific areas with greater transformative potential. Already there exist applications running in quantum devices for different …