primary paper · identifier verified 2026-07-29
Dynamic Portfolio Optimization with Real Datasets Using Quantum Processors and Quantum-Inspired Tensor Networks
Samuel Mugel, Carlos Kuchkovsky, Escolástico Sánchez, Samuel Fernández-Lorenzo, Jorge Luis-Hita, Enrique Lizaso, Román Orús · 2020
- Identifier
- arXiv:2007.00017
- Canonical URL
- https://arxiv.org/abs/2007.00017
Why it is in this atlas
A reported application of tensor-network optimization to portfolio construction alongside quantum processors — the closest thing in this source set to the commercial framing, and narrower than that framing suggests.
Claims citing this source
- tn-012 · Active researchTensor-network methods have been applied to dynamic portfolio optimization on real datasets alongside quantum processors, but the reported work does not establish a general advantage.
- tn-014 · Active researchNo source in this atlas establishes that classical tensor-network contraction generally outperforms quantum hardware on industrial optimization workloads.