arXiv · 2309.15761
Density matrix representation of hybrid tensor networks for noisy quantum devices
Abstract
The hybrid tensor network (HTN) method is a general framework allowing for the construction of an effective wavefunction with the combination of classical tensors and quantum tensors, i.e., amplitudes of quantum states. In particular, hybrid tree tensor networks (HTTNs) are very useful for simulating larger systems beyond the available size of the quantum hardware. However, while the realistic quantum states in NISQ hardware are highly likely to be noisy, this framework is formulated for pure states. In this work, as well as discussing the relevant methods, i.e., Deep VQE and entanglement forging under the framework of HTTNs, we investigate the noisy HTN states by introducing the expansion operator for providing the description of the expansion of the size of simulated quantum systems and the noise propagation. This framework enables the general tree HTN states to be explicitly represented and their physicality to be discussed. We also show that the expectation value of a measured observable exponentially vanishes with the number of contracted quantum tensors. Our work will lead to providing the noise-resilient construction of HTN states.
Explore related subjects
Keep this discovery
Hiroyuki Harada, Yasunari Suzuki, Bo Yang, Yuuki Tokunaga, Suguru Endo. 2023-09-27. Density matrix representation of hybrid tensor networks for noisy quantum devices. https://doi.org/10.22331/q-2025-08-07-1823
Cite the original work for its findings. Save a collection to share your selection of sources.