Pith. sign in

REVIEW 7 cited by

Finite-Depth Preparation of Tensor Network States from Measurement

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2404.17087 v1 pith:6CJIODWQ submitted 2024-04-26 quant-ph cond-mat.str-el

classification quant-phcond-mat.str-el
keywords statesmeasurementsnetworkpreparabletensorcriteriapreparationquantum
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Although tensor network states constitute a broad range of exotic quantum states, their realization is challenging and often requires resources whose depth scales with system size. In this work, we explore criteria on the local tensors for enabling deterministic state preparation via a single round of measurements and on-site unitary feedback. We use these criteria to construct families of measurement-preparable states in one and two dimensions, tuning between distinct symmetry-breaking, symmetry-protected, and intrinsic topological phases of matter. For instance, in one dimension we chart out a three-parameter family of preparable states which interpolate between the AKLT, cluster, GHZ and other states of interest. Our protocol even allows one to engineer preparable quantum states with a range of desired correlation lengths and entanglement properties. In addition to such constructive approaches, we present diagnostics for verifying whether a given tensor network state is preparable using measurements. We conclude by charting out generalizations, such as considering multiple rounds of measurements, implementing matrix product operators, and using incomplete basis measurements.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 7 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. State preparation via measurement and feedback: pushing relations, state structures, and non-invertible symmetries

    quant-ph 2026-08 conditional novelty 8.0 of 10

    Finite-depth measurement-feedback preparation of 1D matrix product states is classified by pushable virtual-bond defects and their pushing relations, yielding explicit circuits and links to non-invertible symmetries.

  2. Quantum State Design and Emergent Confinement Mechanism in Measured Tensor Network States

    quant-ph 2025-04 conditional novelty 7.0 of 10

    Random matrix product states, when partially measured, produce projected ensembles whose randomness is governed by confined domain walls, with exact frame-potential formulas for two circuit architectures.

  3. Tower of Structured Excited States from Measurements

    quant-ph 2024-11 conditional novelty 7.0 of 10

    A phase-estimation measurement of a global charge or momentum projects an easy-to-prepare matrix product state onto towers of quantum many-body scar states and Dicke states in logarithmic circuit depth.

  4. Spacetime duality between sequential and measurement-feedback circuits

    quant-ph 2025-07 conditional novelty 6.0 of 10

    Sequential unitary and measurement-feedback circuits for preparing GHZ, topological, and fractal states are spacetime-dual, linking Kramers-Wannier duality to Z2 gauging and enabling constant-qubit order measurements.

  5. A tensor network formulation of Lattice Gauge Theories based only on symmetric tensors

    hep-lat 2024-12 conditional novelty 6.0 of 10

    A gauge-invariant PEPS ansatz is rebuilt with only globally symmetric tensors by doubling the link symmetry from ZN to ZN×ZN, making standard tensor network libraries applicable.

  6. Towards scalable active steering protocols for genuinely entangled state manifolds

    quant-ph 2024-12 conditional novelty 6.0 of 10

    A feedback protocol that uses the quantum Fisher information as a cost function prepares GHZ-type entangled state manifolds, with numerical evidence of scalability to at least 22 qubits.

  7. Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models

    quant-ph 2025-02 conditional novelty 5.0 of 10

    Quantum neural networks predict cloud cover as accurately as similarly sized classical neural networks on coarse-grained storm-resolving climate data, while both outperform a fitted Xu-Randall baseline.

Pith tools