Tensor Network States for Vibrational Spectroscopy

Abstract

This review elaborates on the foundation, the advantages, and the prospects of tensor network representations for quantum states in vibrational spectroscopy. The focus is on the recently introduced matrix product state decomposition of nuclear quantum states and its optimization by the density matrix renormalization group algorithm.

65 pages, 20 figures

References in corpus (3)

• Renormalization algorithms for Quantum-Many Body Systems in two and higher dimensions
• Towards overcoming the entanglement barrier when simulating long-time evolution
• Comparison of MPS based real time evolution algorithms for Anderson Impurity Models

Cited by in corpus (8)

• Excited-state DMRG made simple with FEAST
• Flexible DMRG-based framework for anharmonic vibrational calculations
• Multicomponent Heat-Bath Configuration Interaction with the Perturbative Correction for the Calculation of Protonic Excited States
• Vibrational Entanglement through the Lens of Quantum Information Measures
• Modal Backflow Neural Quantum States for Anharmonic Vibrational Calculations
• A Synthesis of Hidden Subgroup Quantum Algorithms and Quantum Chemical Dynamics
• Solving intractable chemical problems by tensor decomposition
• Accurate, full-dimensional computations of thousands of complex vibrational eigenstates with tree tensor network states