Extracting average properties of disordered spin chains with translationally invariant tensor networks

2025/04/29 by Vervoort, Kevin, Tang, Wei, Bultinck, Nick · 1 citation
#Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Quantum Physics (quant-ph) #Strongly Correlated Electrons (cond-mat.str-el)

paper · doi:10.48550/arxiv.2504.21089

Abstract

We develop a tensor network-based method for calculating disorder-averaged expectation values in random spin chains without having to explicitly sample over disorder configurations. The algorithm exploits statistical translation invariance and works directly in the thermodynamic limit. We benchmark our method on the infinite-randomness critical point of the random transverse field Ising model.

Citations

• Random transverse and longitudinal field Ising chains
• Simulating thermal density operators with cluster expansions and tensor networks
• Tangent-space methods for truncating uniform MPS
• Approximating Gibbs states of local Hamiltonians efficiently with projected entangled pair states
• Post-matrix product state methods: To tangent space and beyond
• Matrix product states, projected entangled pair states, and variational renormalization group methods for quantum spin systems
• Solving gapped Hamiltonians locally
• Exploiting Quantum Parallelism to Simulate Quantum Random Many-Body Systems
• Strong disorder RG approach of random systems
• Crossover effects in the random-exchange spin-12antiferromagnetic chain
• Finite Temperature and Dynamical Properties of the Random Transverse-Field Ising Spin Chain
• A Numerical Study of the Random Transverse-Field Ising Spin Chain

Cited by

• Statistics-encoded tensor network approach in disordered quantum many-body spin chains

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