Hybrid Tree Tensor Networks for Quantum Simulation
Abstrak
Hybrid tensor networks (hTNs) offer a promising solution for encoding variational quantum states beyond the capabilities of efficient classical methods or noisy quantum computers alone. However, their practical usefulness and many operational aspects of hTN-based algorithms, like the optimization of hTNs, the generalization of standard contraction rules to an hybrid setting, and the design of application-oriented architectures have not been thoroughly investigated yet. In this work, we introduce a novel algorithm to perform ground-state optimizations with hybrid tree tensor networks (hTTNs), discussing its advantages and roadblocks, and identifying a set of promising applications. We benchmark our approach on two paradigmatic models, namely the Ising model at the critical point and the Toric-code Hamiltonian. In both cases, we successfully demonstrate that hTTNs can improve upon classical equivalents with equal bond dimension in the classical part.
Topik & Kata Kunci
Penulis (7)
Julian Schuhmacher
Marco Ballarin
Alberto Baiardi
Giuseppe Magnifico
Francesco Tacchino
Simone Montangero
Ivano Tavernelli
Akses Cepat
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Cek di sumber asli →- Tahun Terbit
- 2025
- Sumber Database
- DOAJ
- DOI
- 10.1103/PRXQuantum.6.010320
- Akses
- Open Access ✓