Introduces the Born-Reciprocal Tensor Network to realize UV/IR mixing as an entanglement bridge in renormalization geometry, with a large-volume limit restoring standard Wilsonian decoupling.
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2010.Log-Gases and Random Matrices (LMS-34)
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representative citing papers
Quantum coherences bind to hydrodynamic voids forming polaron-like objects, parametrically enhancing lifetimes and producing subdiffusive Green's functions in charge-conserving dynamics.
First tensor-network simulation of real-time hadronic scattering in (1+1)D SU(2) lattice gauge theory reveals entanglement and spatial delocalization in the baryon-number-one sector at strong coupling.
An adaptive patching method exploits block-sparse QTT structures to reduce computational costs for tensor contractions and enables efficient evaluation of bubble diagrams and Bethe-Salpeter equations.
Self-interactions in scalar and gauge theories suppress gravitational particle production in a quench modeling cosmic expansion, as computed with tensor networks.
Compressible tight-binding Hamiltonians on N=2^L sites map to L-pseudospin MPOs and can be solved at billion-site scale with TensorBinding.jl without explicit matrix storage.
Linear stabilizer entropy (purity minus stabilizer purity) is an exponentially reliable non-stabilizerness monotone, a 'resource proxy', over Haar-random, Clifford-orbit and random-MPS ensembles, with a positive averaged gap across the XY-model phase diagram.
A new open-source C++ package computes nested commutators [H,[H,...A]] exactly and symbolically in the thermodynamic limit for spin-1/2 hypercubic lattices.
SeQuant introduces a graph-theoretic tensor network canonicalizer for efficient symbolic manipulation and numerical evaluation of tensors over commutative and non-commutative rings, with support for noncovariant and nested tensors.
Presents a tensor-parallel distributed MPS method with block-cyclic partitioning and pivoted QR that emulates Google's RCS benchmark at bond dimension 16384 on 32 nodes, claiming three orders of magnitude better accuracy than prior methods.
Tensor network calculation of magic and entanglement in SU(2) lattice gauge theory ground state shows a crossover from magic-rich to less-magic regime at g_star.
A modified boost-operator method yields new integrable anyonic chains (including su(2)_k spin-3/2, TY(Z_n), Fib×Fib, Fib×Ising) and a criterion for when Temperley-Lieb algebras appear.
Backreaction in semiclassical scalar QED in 1+1D avoids instabilities and produces over-screening at high external charges.
The study uncovers symmetry-protected topological phases with coexisting spontaneous symmetry breaking in the triangular Majorana-Hubbard ladder model of interacting Majorana fermions.
In the Bose-Hubbard model, density correlation fronts propagate ballistically for all interaction strengths, while the correlation transport distance shows sub-ballistic growth in the chaotic phase due to distance-dependent long-time tails and enhanced front decay.
A quantics tensor train solver resolves the Gross-Pitaevskii equation across seven orders of magnitude in length scale in one dimension and on grids larger than a trillion points in two dimensions.
DMRG shows the Lieb ferrimagnetic phase on the trimer-chain extended Hubbard model at half filling remains stable up to V ≳ U/4 before phase separation into a doublon-populated phase and either metallic unsaturated FM or singlet phase.
A Julia package implementing Weingarten calculus and Wick contractions for symbolic Haar integration over compact groups and random matrix ensembles.
PEPSKit.jl is a Julia package that supplies high-level algorithms for ground-state, time-evolution and finite-temperature iPEPS simulations with symmetry support on various lattices.
Lecture notes and accompanying library teach replica tensor network methods to compute circuit-averaged observables in random quantum circuits by mapping them to classical statistical mechanics models.
Tensor networks developed for quantum states are reviewed as tools for machine learning models, with assessment of their potential computational, explanatory, and privacy advantages alongside remaining challenges.
Introductory lecture notes on tensor networks with emphasis on matrix-product states, their algorithms, higher-dimensional generalizations, and applications to mixed states and open quantum systems, accompanied by Julia code.
citing papers explorer
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When Renormalisation Remembers: UV/IR Mixing as an Entanglement Bridge
Introduces the Born-Reciprocal Tensor Network to realize UV/IR mixing as an entanglement bridge in renormalization geometry, with a large-volume limit restoring standard Wilsonian decoupling.
-
Long-lived local quantum coherences from hydrodynamic large deviations
Quantum coherences bind to hydrodynamic voids forming polaron-like objects, parametrically enhancing lifetimes and producing subdiffusive Green's functions in charge-conserving dynamics.
-
Hadronic scattering in (1+1)D SU(2) lattice gauge theory from tensor networks
First tensor-network simulation of real-time hadronic scattering in (1+1)D SU(2) lattice gauge theory reveals entanglement and spatial delocalization in the baryon-number-one sector at strong coupling.
-
Adaptive Patching for Tensor Train Computations
An adaptive patching method exploits block-sparse QTT structures to reduce computational costs for tensor contractions and enables efficient evaluation of bubble diagrams and Bethe-Salpeter equations.
-
Quantum dynamics of cosmological particle production: interacting quantum field theories with matrix product states
Self-interactions in scalar and gauge theories suppress gravitational particle production in a quench modeling cosmic expansion, as computed with tensor networks.
-
Tensor network solvers for ultra-large tight-binding Hamiltonians: algorithms and applications
Compressible tight-binding Hamiltonians on N=2^L sites map to L-pseudospin MPOs and can be solved at billion-site scale with TensorBinding.jl without explicit matrix storage.
-
Stabilizer entropy is trustworthy for mixed states
Linear stabilizer entropy (purity minus stabilizer purity) is an exponentially reliable non-stabilizerness monotone, a 'resource proxy', over Haar-random, Clifford-orbit and random-MPS ensembles, with a positive averaged gap across the XY-model phase diagram.
-
QCommute: a tool for symbolic computation of nested commutators in quantum many-body spin-1/2 systems
A new open-source C++ package computes nested commutators [H,[H,...A]] exactly and symbolically in the thermodynamic limit for spin-1/2 hypercubic lattices.
-
SeQuant Framework for Symbolic and Numerical Tensor Algebra. I. Core Capabilities
SeQuant introduces a graph-theoretic tensor network canonicalizer for efficient symbolic manipulation and numerical evaluation of tensors over commutative and non-commutative rings, with support for noncovariant and nested tensors.
-
Tensor-Parallel Emulation of Quantum Circuits with Block-Cyclic Distributed Matrix Product States
Presents a tensor-parallel distributed MPS method with block-cyclic partitioning and pivoted QR that emulates Google's RCS benchmark at bond dimension 16384 on 32 nodes, claiming three orders of magnitude better accuracy than prior methods.
-
Magic and entanglement in 1+1-dimensional SU(2) lattice gauge theory
Tensor network calculation of magic and entanglement in SU(2) lattice gauge theory ground state shows a crossover from magic-rich to less-magic regime at g_star.
-
Constrained integrability and anyonic chains
A modified boost-operator method yields new integrable anyonic chains (including su(2)_k spin-3/2, TY(Z_n), Fib×Fib, Fib×Ising) and a criterion for when Temperley-Lieb algebras appear.
-
Revisiting semiclassical scalar QED in 1+1 dimensions
Backreaction in semiclassical scalar QED in 1+1D avoids instabilities and produces over-screening at high external charges.
-
Symmetry-Protected Topological Phases in the Triangular Majorana-Hubbard Ladder
The study uncovers symmetry-protected topological phases with coexisting spontaneous symmetry breaking in the triangular Majorana-Hubbard ladder model of interacting Majorana fermions.
-
Dynamical Behaviour of Density Correlations Across the Chaotic Phase for Interacting Bosons
In the Bose-Hubbard model, density correlation fronts propagate ballistically for all interaction strengths, while the correlation transport distance shows sub-ballistic growth in the chaotic phase due to distance-dependent long-time tails and enhanced front decay.
-
Solving the Gross-Pitaevskii equation on multiple different scales using the quantics tensor train representation
A quantics tensor train solver resolves the Gross-Pitaevskii equation across seven orders of magnitude in length scale in one dimension and on grids larger than a trillion points in two dimensions.
-
Trimers in the Extended Hubbard Model
DMRG shows the Lieb ferrimagnetic phase on the trimer-chain extended Hubbard model at half filling remains stable up to V ≳ U/4 before phase separation into a doublon-populated phase and either metallic unsaturated FM or singlet phase.
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IntegrateUnitary.jl: A Julia package for symbolic integration over Haar measures
A Julia package implementing Weingarten calculus and Wick contractions for symbolic Haar integration over compact groups and random matrix ensembles.
-
PEPSKit.jl: A Julia package for projected entangled-pair state simulations
PEPSKit.jl is a Julia package that supplies high-level algorithms for ground-state, time-evolution and finite-temperature iPEPS simulations with symmetry support on various lattices.
-
Lecture Notes on Replica Tensor Networks for Random Quantum Circuits
Lecture notes and accompanying library teach replica tensor network methods to compute circuit-averaged observables in random quantum circuits by mapping them to classical statistical mechanics models.
-
Quantum-inspired tensor networks in machine learning models
Tensor networks developed for quantum states are reviewed as tools for machine learning models, with assessment of their potential computational, explanatory, and privacy advantages alongside remaining challenges.
-
Introduction to matrix-product states and tensor networks
Introductory lecture notes on tensor networks with emphasis on matrix-product states, their algorithms, higher-dimensional generalizations, and applications to mixed states and open quantum systems, accompanied by Julia code.