Low-energy states of local Hamiltonians have half-system entanglement entropies upper-bounded by the thermal entropies of two fictitious systems whose combined energies match the state's energy.
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Quantum annealing processors implement analog-digital quantum computing via effective XY-model evolution combined with auxiliary-qubit arbitrary-basis initialization and measurement, demonstrated through oscillations, fermionic quantum walks, and Anderson localization.
An iPEPS-based tensor-network approach computes dispersion relations in 2D and 3D quantum systems, with the first such calculations demonstrated for three-dimensional lattices on the transverse-field Ising model.
SCALE and ACE are new convolutional backflow architectures for Neural Quantum States that deliver O(N^3) scaling with high accuracy and over 40x speedup on Hubbard and t-J models up to 32x32 lattices.
A discretization-plus-coarse-graining scheme turns continuous-space interacting particles into a tensor-network-representable lattice model, enabling partition-function calculations for the 2D hard-disk problem.
A gauge-covariant PEPS ansatz with virtual flux tensors ensures translation-invariant physical expectation values for 2D interacting systems in a magnetic field, allowing gauge-independent simulations without enlarged magnetic unit cells.
An optimized matrix product state representation with DMRG-inspired solver solves the Peierls-Boltzmann transport equation for crystalline silicon phonons with high fidelity at 10^{-3} compression and sublinear scaling in grid size.
Dismagicker is a non-Clifford unitary that suppresses non-stabilizerness in quantum states, improving simulation accuracy when combined with Clifford disentanglers.
A new duality operator using generalized matrix product operators maps out-of-equilibrium boundaries in the symmetric simple exclusion process to equilibrium boundaries satisfying Liggett's condition.
A tensor network algorithm computes momentum-resolved spectral functions for large non-periodic super-moiré systems by mapping tight-binding problems to solvable quantum many-body simulations using kernel polynomial methods and quantum Fourier transforms.
Conditioning on rare boundary measurement outcomes in a quantum East circuit generates states with finite two-point correlations at arbitrary distances and an underlying Sierpiński-triangle fractal structure.
Analytical Pauli-string coefficients plus multistage state refinement let tensor networks find low eigenstates of million-dimensional Laplacians with high fidelity on 20 qubits.
Nonadiabatic renormalization group produces nested fiber bundle structures and shared-leg tensor networks for strongly coupled multiscale quantum systems, shown on interacting boson models and ab initio quantum chemistry.
A learnable Gaussian-basis locality parameter α lowers NNVMC variational energies on the 3D electron gas and sharpens the Fermi-liquid–Wigner-crystal transition for message-passing ansatze.
A stochastic MCMC sampling method with umbrella sampling provides unbiased loop corrections to belief propagation for exact factorization-based tensor network contraction on loopy graphs with symmetric potentials.
MPO encodings of the Magnus expansion and Dyson series for accurate time evolution of time-dependent 1D quantum Hamiltonians on finite or infinite lattices with long-range interactions.
Numerical tensor-network study identifies Néel, Ising, collinear, and incommensurate spiral phases plus their transitions in the J1-J2 XY antiferromagnet on the honeycomb lattice.
Ground states of a tuned spin-1 XXZ chain in the Haldane phase enable high-fidelity single-qubit gates via measurement-based quantum computation.
A comprehensive review organizing progress at the AI-quantum information intersection from both directions.
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Quantum matter is weakly entangled at low energies
Low-energy states of local Hamiltonians have half-system entanglement entropies upper-bounded by the thermal entropies of two fictitious systems whose combined energies match the state's energy.
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Analog-Digital Quantum Computing with Quantum Annealing Processors
Quantum annealing processors implement analog-digital quantum computing via effective XY-model evolution combined with auxiliary-qubit arbitrary-basis initialization and measurement, demonstrated through oscillations, fermionic quantum walks, and Anderson localization.
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Dispersion Relations in Two- and Three-Dimensional Quantum Systems
An iPEPS-based tensor-network approach computes dispersion relations in 2D and 3D quantum systems, with the first such calculations demonstrated for three-dimensional lattices on the transverse-field Ising model.
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Pareto Frontier of Neural Quantum States: Scalable, Affordable, and Accurate Convolutional Backflow for Strongly Correlated Lattice Fermions
SCALE and ACE are new convolutional backflow architectures for Neural Quantum States that deliver O(N^3) scaling with high accuracy and over 40x speedup on Hubbard and t-J models up to 32x32 lattices.
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Statistical mechanics in continuous space with tensor network methods
A discretization-plus-coarse-graining scheme turns continuous-space interacting particles into a tensor-network-representable lattice model, enabling partition-function calculations for the 2D hard-disk problem.
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Gauge-covariant projected entangled paired states for interacting systems in a magnetic field
A gauge-covariant PEPS ansatz with virtual flux tensors ensures translation-invariant physical expectation values for 2D interacting systems in a magnetic field, allowing gauge-independent simulations without enlarged magnetic unit cells.
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Solving the Peierls-Boltzmann transport equation with matrix product states
An optimized matrix product state representation with DMRG-inspired solver solves the Peierls-Boltzmann transport equation for crystalline silicon phonons with high fidelity at 10^{-3} compression and sublinear scaling in grid size.
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Dismagicker: Unitary Gate for Non-Stabilizerness Reduction
Dismagicker is a non-Clifford unitary that suppresses non-stabilizerness in quantum states, improving simulation accuracy when combined with Clifford disentanglers.
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Intertwining Markov Processes via Matrix Product Operators
A new duality operator using generalized matrix product operators maps out-of-equilibrium boundaries in the symmetric simple exclusion process to equilibrium boundaries satisfying Liggett's condition.
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Tensor network approach to momentum-resolved spectroscopy in non-periodic super-moir\'e systems
A tensor network algorithm computes momentum-resolved spectral functions for large non-periodic super-moiré systems by mapping tight-binding problems to solvable quantum many-body simulations using kernel polynomial methods and quantum Fourier transforms.
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Exact large deviations and emergent long-range correlations in sequential quantum East circuits
Conditioning on rare boundary measurement outcomes in a quantum East circuit generates states with finite two-point correlations at arbitrary distances and an underlying Sierpiński-triangle fractal structure.
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Efficient Pauli-decomposition and multistage state-refinement for tensor network based differential equation solver
Analytical Pauli-string coefficients plus multistage state refinement let tensor networks find low eigenstates of million-dimensional Laplacians with high fidelity on 20 qubits.
-
Nonadiabatic Renormalization Group for Strongly Coupled Multiscale Quantum Systems
Nonadiabatic renormalization group produces nested fiber bundle structures and shared-leg tensor networks for strongly coupled multiscale quantum systems, shown on interacting boson models and ab initio quantum chemistry.
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Enhancing Neural-Network Variational Monte Carlo through Basis Transformation
A learnable Gaussian-basis locality parameter α lowers NNVMC variational energies on the 3D electron gas and sharpens the Fermi-liquid–Wigner-crystal transition for message-passing ansatze.
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Stochastic Loop Corrections to Belief Propagation for Tensor Network Contraction
A stochastic MCMC sampling method with umbrella sampling provides unbiased loop corrections to belief propagation for exact factorization-based tensor network contraction on loopy graphs with symmetric potentials.
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Matrix Product Operator Encodings of the Magnus Expansion and Dyson Series
MPO encodings of the Magnus expansion and Dyson series for accurate time evolution of time-dependent 1D quantum Hamiltonians on finite or infinite lattices with long-range interactions.
-
Magnetic phases in the $J_{1}$-$J_{2}$ antiferromagnetic XY model on the honeycomb lattice
Numerical tensor-network study identifies Néel, Ising, collinear, and incommensurate spiral phases plus their transitions in the J1-J2 XY antiferromagnet on the honeycomb lattice.
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Measurement-Based Quantum Computation Using the Spin-1 XXZ Model with Uniaxial Anisotropy
Ground states of a tuned spin-1 XXZ chain in the Haldane phase enable high-fidelity single-qubit gates via measurement-based quantum computation.
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When AI meets quantum information: A comprehensive review
A comprehensive review organizing progress at the AI-quantum information intersection from both directions.