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The density-matrix renormalization group in the age of matrix product states

Canonical reference. 86% of citing Pith papers cite this work as background.

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abstract

The density-matrix renormalization group method (DMRG) has established itself over the last decade as the leading method for the simulation of the statics and dynamics of one-dimensional strongly correlated quantum lattice systems. In the further development of the method, the realization that DMRG operates on a highly interesting class of quantum states, so-called matrix product states (MPS), has allowed a much deeper understanding of the inner structure of the DMRG method, its further potential and its limitations. In this paper, I want to give a detailed exposition of current DMRG thinking in the MPS language in order to make the advisable implementation of the family of DMRG algorithms in exclusively MPS terms transparent. I then move on to discuss some directions of potentially fruitful further algorithmic development: while DMRG is a very mature method by now, I still see potential for further improvements, as exemplified by a number of recently introduced algorithms.

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Multimode-cavity picture of non-Markovian waveguide QED

quant-ph · 2024-03-11 · unverdicted · novelty 7.0

A multimode-cavity picture is introduced for non-Markovian waveguide QED via spatial decomposition, approximating dynamics with a finite and growing number of cavity modes.

Symmetry breaking phases and transitions in an Ising fusion category lattice model

cond-mat.str-el · 2026-04-22 · unverdicted · novelty 7.0

The Ising fusion category lattice model features a symmetric critical phase equivalent to the Ising model, a categorical ferromagnetic phase with threefold degeneracy, and a critical categorical antiferromagnetic phase with fourfold degeneracy described by an Ising CFT.

Dense $\mathrm{QC_2D_2}$ with uniform matrix product states

hep-lat · 2026-05-16 · unverdicted · novelty 6.0

Uniform MPS simulations of dense 1+1D SU(2) gauge theory find Tomonaga-Luttinger liquid infrared behavior with central charge 1, density modulations at the predicted wavenumber, and a smooth crossover in the Luttinger parameter from K~1 to K~1/2 that realizes the quarkyonic picture with coexisting q

Quantum Machine Learning for State Tomography Using Classical Data

quant-ph · 2025-07-01 · unverdicted · novelty 6.0

A variational quantum circuit trained solely on classical measurement outcomes reconstructs diverse quantum states including GHZ, spin-chain ground states, and random circuits with fidelities above 90% on simulators and real NISQ hardware.

Estimating the best separable approximation of non-pure spin-squeezed states

quant-ph · 2025-04-10 · unverdicted · novelty 6.0

Lower bounds on the best separable approximation distance for non-pure spin-squeezed states are obtained from the complete set of spin-squeezing inequalities, with symmetry-exploiting optimization for upper bounds, revealing finite-temperature entanglement in ordered phases of the XXZ model.

Preparing High-Fidelity Thermofield Double States

quant-ph · 2026-05-04 · unverdicted · novelty 6.0

A gapped parent Hamiltonian built from two copies of a target Hamiltonian plus ultra-local inter-copy couplings allows adiabatic preparation of high-fidelity thermofield double states for ETH-obeying systems.

Entanglement is Half the Story: Post-Selection vs. Partial Traces

quant-ph · 2026-05-04 · unverdicted · novelty 4.0

A hybrid tensor network framework interpolates between classical and quantum models via controllable post-selection, with a trainable hyperparameter that complements bond dimension to enhance quantum machine learning.

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Showing 16 of 16 citing papers.