Tensor Network Techniques for Quantum Computation

Fuente: arXiv
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Auteurs principaux: Collura, Mario, Lami, Guglielmo, Ranabhat, Nishan, Santini, Alessandro
Format: Preprint
Publié: 2025
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author Collura, Mario
Lami, Guglielmo
Ranabhat, Nishan
Santini, Alessandro
author_facet Collura, Mario
Lami, Guglielmo
Ranabhat, Nishan
Santini, Alessandro
contents This book serves as an introductory yet thorough guide to tensor networks and their applications in quantum computation and quantum information, designed for advanced undergraduate and graduate-level readers. In Part I, foundational topics are covered, including tensor structures and network representations like Matrix Product States (MPS) and Tree Tensor Networks (TTN). These preliminaries provide readers with the core mathematical tools and concepts necessary for quantum physics and quantum computing applications, bridging the gap between multi-linear algebra and complex quantum systems. Part II explores practical applications of tensor networks in simulating quantum dynamics, with a particular focus on the efficiency they offer for systems of high computational complexity. Key topics include Hamiltonian dynamics, quantum annealing, open system dynamics, and optimization strategies using TN frameworks. A final chapter addresses the emerging role of "quantum magic" in tensor networks. It delves into non-stabilizer states and their contribution to quantum computational power beyond classical simulability, featuring methods such as stabilizer-enhanced MPS and the Clifford-dressed TDVP.
format Preprint
id arxiv_https___arxiv_org_abs_2503_04423
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Tensor Network Techniques for Quantum Computation
Collura, Mario
Lami, Guglielmo
Ranabhat, Nishan
Santini, Alessandro
Quantum Physics
This book serves as an introductory yet thorough guide to tensor networks and their applications in quantum computation and quantum information, designed for advanced undergraduate and graduate-level readers. In Part I, foundational topics are covered, including tensor structures and network representations like Matrix Product States (MPS) and Tree Tensor Networks (TTN). These preliminaries provide readers with the core mathematical tools and concepts necessary for quantum physics and quantum computing applications, bridging the gap between multi-linear algebra and complex quantum systems. Part II explores practical applications of tensor networks in simulating quantum dynamics, with a particular focus on the efficiency they offer for systems of high computational complexity. Key topics include Hamiltonian dynamics, quantum annealing, open system dynamics, and optimization strategies using TN frameworks. A final chapter addresses the emerging role of "quantum magic" in tensor networks. It delves into non-stabilizer states and their contribution to quantum computational power beyond classical simulability, featuring methods such as stabilizer-enhanced MPS and the Clifford-dressed TDVP.
title Tensor Network Techniques for Quantum Computation
topic Quantum Physics
url https://arxiv.org/abs/2503.04423