One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States | Paper Citation Record

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This paper cites Especially, a matrix product state (MPS) in the tool box is defined by [32] |ψM P S⟩ = 1X j1,j2,...,jN Θj1,j2,...,jN |j1,.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Especially, a matrix product state (MPS) in the tool box is defined by [32] |ψM P S⟩ = 1X j1,j2,...,jN Θj1,j2,...,jN |j1,

Reference 1

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One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States shortcut

Reference 2

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Reference 3

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This paper cites A prime example is Simon’s algorithm [4], which demonstrates an exponen- tial speedup compared to its classical counterparts and serves as the inspiration of Shor’s algorithm [46].

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States A prime example is Simon’s algorithm [4], which demonstrates an exponen- tial speedup compared to its classical counterparts and serves as the inspiration of Shor’s algorithm [46]

Reference 4

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This paper cites As indicated in Ref.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States As indicated in Ref

Reference 5

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This paper cites In fact, the idea of MBQC is related to the investigations on 2-D Ising mod- els.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States In fact, the idea of MBQC is related to the investigations on 2-D Ising mod- els

Reference 6

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One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States directions

Reference 7

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One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States freshman

Reference 8

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This paper cites good choice of space.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States good choice of space

Reference 9

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Reference 10

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This paper cites Bernstein & U.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Bernstein & U

Reference 12

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This paper cites Quantum computing 40 years later.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Quantum computing 40 years later

Reference 17

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This paper cites Aaronson & D.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Aaronson & D

Reference 19

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Reference 23

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This paper cites Quantum Probability Theory.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Quantum Probability Theory

Reference 24

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This paper cites Neville, C.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Neville, C

Reference 25

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This paper cites Jiang, & B.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Jiang, & B

Reference 26

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Observation 21e57fb6-3c5b-44c0-96e3-344e5781cd14 · outbound

This paper cites ZX-calculus for the working quantum computer scientist.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States ZX-calculus for the working quantum computer scientist

Reference 27

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One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Unresolved cited work

Reference 29

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Observation afdb9d9a-1740-49a9-a6ff-a29a0eaeaee3 · outbound

This paper cites Quantum-inspired sublinear classical algorithms for solving low-rank linear systems.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Quantum-inspired sublinear classical algorithms for solving low-rank linear systems

Reference 30

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One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension

Reference 31

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One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States A quantum-inspired classical algorithm for recommendation systems

Reference 32

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This paper cites Classical Sampling of Random Quantum Circuits with Bounded Fidelity.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Classical Sampling of Random Quantum Circuits with Bounded Fidelity

Reference 34

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This paper cites Quantum Path Computing: Computing Architecture with Propagation Paths in Multiple Plane Diffraction of Classical Sources of Fermion and Boson Particles.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Quantum Path Computing: Computing Architecture with Propagation Paths in Multiple Plane Diffraction of Classical Sources of Fermion and Boson Particles

Reference 37

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Observation 5088cec4-97f8-4d25-9827-6558d04bc66e · outbound

This paper cites Yang & X.-B.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Yang & X.-B

Reference 38

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This paper cites Atallah, M.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Atallah, M

Reference 39

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Observation 3aa0ee7d-9b1e-45bc-adbe-4d08366107ee · outbound

This paper cites Efficient simulation of parametrized quantum circuits under non-unital noise through Pauli backpropagation.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Efficient simulation of parametrized quantum circuits under non-unital noise through Pauli backpropagation

Reference 40

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Reference 41

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Observation 6c03d0ac-a96c-48b8-94fd-50b1080b7799 · outbound

This paper cites Berezutskii, A.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Berezutskii, A

Reference 42

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Observation 71ecb11d-d705-4dde-a69b-e4d262eb8f42 · outbound

This paper cites Masot-Llima & A.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Masot-Llima & A

Reference 44

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Observation ce0bd739-5e86-42ee-944d-411308b867c5 · outbound

This paper cites However, a curve should have tangent lines with slopes bigger than 1 if it could be fitted by N γ.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States However, a curve should have tangent lines with slopes bigger than 1 if it could be fitted by N γ

Reference 45

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Observation e729ffa4-2c35-4709-9735-89f7ced9ca94 · outbound

This paper cites Gabrielli, D.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Gabrielli, D

Reference 46

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Observation dd64e14f-b37b-4290-9608-3e7d04f4dd2d · outbound

This paper cites Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions

Reference 47

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Observation 1a3bc2c7-e125-480b-a7ee-ae0effdca6c7 · outbound

This paper cites Raussendorf & H.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Raussendorf & H

Reference 48

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Observation 752a7b17-ccb5-433d-af33-a7a9fd7b8388 · outbound

This paper cites Raussendorf, D.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Raussendorf, D

Reference 49

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Observation d5820973-5de6-4bf4-ad8a-ae68eb684605 · outbound

This paper cites The limits of my language mean the limits of my world.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States The limits of my language mean the limits of my world

Reference 50

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Observation 244bd3dd-0c6f-478a-af1e-b9dbf9b8f15c · outbound

This paper cites The author does not check the case strictly.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States The author does not check the case strictly

Reference 51

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Observation 35b0f354-04de-4a5b-a765-4bb7eacebe42 · outbound

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Reference 53

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Observation e06a66e7-ed74-4459-ab11-19ae6f7e5334 · outbound

This paper cites A typical example is the interpolation and approximation (of a polynomial) based on Cheby- shev polynomials.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States A typical example is the interpolation and approximation (of a polynomial) based on Cheby- shev polynomials

Reference 54

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Observation 2cf1acd4-35a0-40e0-9efd-27f36d9c39cf · outbound

This paper cites ht tps://en.m.wikipedia.org/wiki/Simon%27s_problem.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States ht tps://en.m.wikipedia.org/wiki/Simon%27s_problem

Reference 55

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Observation a40d7803-efaf-4f52-9e37-2552974d1bc3 · outbound

This paper cites Measurement-based quantum convolutional neural network for deep learning.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Measurement-based quantum convolutional neural network for deep learning

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:23:18.736312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 12a3cbae-675d-4da8-aec1-c7994b0226db · outbound

This paper cites What does it take to solve the 3D Ising model? Minimal necessary conditions for a valid solution.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States What does it take to solve the 3D Ising model? Minimal necessary conditions for a valid solution

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:23:18.529023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6fd00b5f-1055-4d58-8677-6eda6adcc24c · outbound

This paper cites This inter- esting formula can be found on http://kawaihome.link /jbooks/qcomp-short/q2gates/cz.html.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States This inter- esting formula can be found on http://kawaihome.link /jbooks/qcomp-short/q2gates/cz.html

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:18.935685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6b8420ed-8935-4f24-9320-4c7d7f376f6b · outbound

This paper cites pockets of reducibility.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States pockets of reducibility

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:18.928118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 625b9aec-a6f1-40f2-bc8b-eafca1d7bfdf · outbound

This paper cites An introduction to one-way quantum computing in distributed architectures.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States An introduction to one-way quantum computing in distributed architectures

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:23:18.275957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1ef28f7f-d821-4bc7-b6b3-fb0be9ff3a1c · outbound

This paper cites Gates, States, and Circuits: Quantum Gates.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States Gates, States, and Circuits: Quantum Gates

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:18.921004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 17274179-c3b4-48a0-9492-a77a0d3b121f · outbound

This paper cites They are differently defined in their sections, respectively.

One Polynomial Strategy for Computing Local Projections on Square-Lattice Cluster States They are differently defined in their sections, respectively

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:23:18.913862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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