TensorCircuit-NG: A Universal, Composable, and Scalable Platform for Quantum Computing and Quantum Simulation

• URL: http://arxiv.org/abs/2602.14167v1
• Date: Sun, 15 Feb 2026 14:37:37 GMT
• Title: TensorCircuit-NG: A Universal, Composable, and Scalable Platform for Quantum Computing and Quantum Simulation
• Authors: Shi-Xin Zhang, Yu-Qin Chen, Weitang Li, Jiace Sun, Wei-Guo Ma, Pei-Lin Zheng, Yu-Xiang Huang, Qi-Xiang Wang, Hui Yu, Zhuo Li, Xuyang Huang, Zong-Liang Li, Zhou-Quan Wan, Shuo Liu, Jiezhong Qiu, Jiaqi Miao, Zixuan Song, Yuxuan Yan, Kazuki Tsuoka, Pan Zhang, Lei Wang, Heng Fan, Chang-Yu Hsieh, Hong Yao, Tao Xiang,
• Abstract summary: We presentCircuit-NG, a next-generation quantum software platform designed to bridge the gap between quantum physics, artificial intelligence, and high-performance computing.<n>Circuit-NG establishes a unified, tensor-native programming paradigm where quantum circuits, tensor networks, and neural networks fuse into a single, end-to-end differentiable computational graph.
• Score: 33.05172028111655
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present TensorCircuit-NG, a next-generation quantum software platform designed to bridge the gap between quantum physics, artificial intelligence, and high-performance computing. Moving beyond the scope of traditional circuit simulators, TensorCircuit-NG establishes a unified, tensor-native programming paradigm where quantum circuits, tensor networks, and neural networks fuse into a single, end-to-end differentiable computational graph. Built upon industry-standard machine learning backends (JAX, TensorFlow, PyTorch), the framework introduces comprehensive capabilities for approximate circuit simulation, analog dynamics, fermion Gaussian states, qudit systems, and scalable noise modeling. To tackle the exponential complexity of deep quantum circuits, TensorCircuit-NG implements advanced distributed computing strategies, including automated data parallelism and model-parallel tensor network slicing. We validate these capabilities on GPU clusters, demonstrating a near-linear speedup in distributed variational quantum algorithms. TensorCircuit-NG enables flagship applications, including end-to-end QML for CIFAR-100 computer vision, efficient pipelines from quantum states to neural networks via classical shadows, and differentiable optimization of tensor network states for many-body physics.

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