Boosting quantum annealing performance through direct polynomial unconstrained binary optimization | Paper Citation Record

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This paper cites Thus, one needs to find an equiva- lent encoding as a QUBO problem to solve 3-SAT on such hardware.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Thus, one needs to find an equiva- lent encoding as a QUBO problem to solve 3-SAT on such hardware

Reference 2

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This paper cites In principle, it is desirable forJ to be as large as possible in order to speed up the absolute computing time.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization In principle, it is desirable forJ to be as large as possible in order to speed up the absolute computing time

Reference 3

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Reference 4

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This paper cites Typical gap profiles of PUBO and QUBO formulations of randomly generated 3-SAT instances.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Typical gap profiles of PUBO and QUBO formulations of randomly generated 3-SAT instances

Reference 5

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Observation 35dd532c-829f-4a2a-a393-fc7a18a5e541 · outbound

This paper cites Finding an optimal QUBO reduction for a given PUBO problem is in generalNP-hard.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Finding an optimal QUBO reduction for a given PUBO problem is in generalNP-hard

Reference 6

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Reference 7

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This paper cites Figure 2 investigates the correlations between these two quantities for10 000random instances generated via toughSAT with N = 6 and M = round(4.24N) = 25.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Figure 2 investigates the correlations between these two quantities for10 000random instances generated via toughSAT with N = 6 and M = round(4.24N) = 25

Reference 8

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Reference 9

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This paper cites In this section, we in- vestigate how varying this strength affects the minimum energy gap.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization In this section, we in- vestigate how varying this strength affects the minimum energy gap

Reference 10

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This paper cites However, hx is actually a free parameter that can be tuned to optimize the annealing schedule.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization However, hx is actually a free parameter that can be tuned to optimize the annealing schedule

Reference 11

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This paper cites (b) Each CNOT gate can be further decomposed into one RZZ gate of fixed angle and multiple single-qubit rotations.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization (b) Each CNOT gate can be further decomposed into one RZZ gate of fixed angle and multiple single-qubit rotations

Reference 12

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Reference 13

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Reference 14

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This paper cites Martoňák, G.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Martoňák, G

Reference 15

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This paper cites Hauke, H.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Hauke, H

Reference 16

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This paper cites Rajak, S.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Rajak, S

Reference 17

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This paper cites Yarkoni, E.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Yarkoni, E

Reference 18

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Reference 19

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Reference 20

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Observation eb6f93f1-8ab7-40cb-9cdf-8b0823e3f938 · outbound

This paper cites Micheletti, P.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Micheletti, P

Reference 21

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This paper cites Slongo, P.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Slongo, P

Reference 22

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This paper cites Outeiral, G.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Outeiral, G

Reference 23

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Observation 854a2e8c-64f3-40f8-b00d-cf23cc84fe56 · outbound

This paper cites Polynomial unconstrained binary optimisation inspired by optical simulation.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Polynomial unconstrained binary optimisation inspired by optical simulation

Reference 24

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This paper cites Polynomial Reduction Methods and their Impact on QAOA Circuits.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Polynomial Reduction Methods and their Impact on QAOA Circuits

Reference 25

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Reference 26

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This paper cites Babbush, B.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Babbush, B

Reference 27

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This paper cites Stein, F.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Stein, F

Reference 28

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This paper cites Hsieh, R.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Hsieh, R

Reference 29

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 30

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This paper cites Glover, G.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Glover, G

Reference 31

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Reference 32

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This paper cites Jansen, M.-B.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Jansen, M.-B

Reference 33

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Reference 34

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Reference 35

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This paper cites Cheung, P.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Cheung, P

Reference 36

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This paper cites Čepait˙ e, A.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Čepait˙ e, A

Reference 37

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This paper cites Tighter Lower Bounds on Quantum Annealing Times.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Tighter Lower Bounds on Quantum Annealing Times

Reference 38

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This paper cites Bottarelli, M.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Bottarelli, M

Reference 39

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This paper cites Altshuler, H.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Altshuler, H

Reference 40

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This paper cites A Quantum Approximate Optimization Algorithm.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization A Quantum Approximate Optimization Algorithm

Reference 41

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 42

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Observation c4e51f48-0fd4-43bc-aeb3-0703853bbe83 · outbound

This paper cites Blanes, F.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Blanes, F

Reference 43

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This paper cites Boros and P.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Boros and P

Reference 44

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This paper cites Alleviating the quantum Big-$M$ problem.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Alleviating the quantum Big-$M$ problem

Reference 45

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This paper cites Aspvall, M.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Aspvall, M

Reference 46

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 47

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 48

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 49

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Reference 50

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Observation e9b00876-1ee0-4734-9fbf-9c46a2aebdf7 · outbound

This paper cites Albash and D.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Albash and D

Reference 51

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This paper cites Willsch, M.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Willsch, M

Reference 52

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This paper cites Bernaschi, I.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Bernaschi, I

Reference 53

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This paper cites Mézard, G.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Mézard, G

Reference 54

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This paper cites Žnidarič, Scaling of the running time of the quantum adiabatic algorithm for propositional satisfiability, Phys.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Žnidarič, Scaling of the running time of the quantum adiabatic algorithm for propositional satisfiability, Phys

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 56

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This paper cites Efficient QUBO transformation for Higher Degree Pseudo Boolean Functions.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Efficient QUBO transformation for Higher Degree Pseudo Boolean Functions

Reference 57

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Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 58

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Observation 14d7a344-dde4-4066-86fa-3046fdc852e8 · outbound

This paper cites Bose, Exponential speed-up of quantum annealing via n-local catalysts (2024), arXiv:2409.13029 [quant-ph].

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Bose, Exponential speed-up of quantum annealing via n-local catalysts (2024), arXiv:2409.13029 [quant-ph]

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T21:30:05.945178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a3e1f0-71d0-4e3c-b5ad-593985c93c96 · outbound

This paper cites Bermudez, D.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Bermudez, D

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.716813Z

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 551ceccc-e06e-491f-9871-ea8042ce1b78 · outbound

This paper cites an unresolved cited work.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:30:06.706037Z

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 8db599f8-ab7d-40b0-98fc-5630fc21c1e1 · outbound

This paper cites Andrade, Z.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Andrade, Z

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.696233Z

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 d2a79f61-4453-44d1-a6a6-79eb93356b65 · outbound

This paper cites Nagies, K.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Nagies, K

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.686443Z

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 9a23f1f4-6baa-49c3-89c8-7a5652eeadf9 · outbound

This paper cites an unresolved cited work.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:30:06.676145Z

Source-reported events for the cited work

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Observation 0c3121ea-a81d-42af-9952-13bbfab64727 · outbound

This paper cites Decker, C.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Decker, C

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.666068Z

Source-reported events for the cited work

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Observation 8c72ffa0-2286-4db1-a0c8-aa108e2f3e6e · outbound

This paper cites Chancellor, S.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Chancellor, S

Reference 66

Resolution: verified exact; doi, observed 2026-08-11T21:30:06.097215Z

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 42b3545b-89e5-4a43-859d-e3db13cf3618 · outbound

This paper cites Rakyta and Z.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Rakyta and Z

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.655463Z

Source-reported events for the cited work

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Observation 5044fa99-8832-457b-a7b8-04ac79d53dcb · outbound

This paper cites Madden and A.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Madden and A

Reference 68

Resolution: verified exact; doi, observed 2026-08-11T21:30:06.084849Z

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 0204266b-1415-48fb-a7c4-68ca1e068265 · outbound

This paper cites Orús and J.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Orús and J

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.645165Z

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 8a9fdb74-673f-4187-a2f9-525ea5609141 · outbound

This paper cites Lanting, A.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Lanting, A

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.633713Z

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 18a462f3-76be-49cd-bee3-6b506e67e19f · outbound

This paper cites Hauke, L.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Hauke, L

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T21:30:05.988582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32366fe4-7714-47cc-893d-8f46708eca9a · outbound

This paper cites Genuine Multipartite Entanglement in Quantum Optimization.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Genuine Multipartite Entanglement in Quantum Optimization

Reference 72

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:30:06.126657Z

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 09c1bb7c-31b1-49d5-9e8e-5f289da287f2 · outbound

This paper cites Lipkin, N.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Lipkin, N

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.623067Z

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 22a874ff-599d-4a00-80e1-190c9ce936dd · outbound

This paper cites Meshkov, A.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Meshkov, A

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.613630Z

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 004c7b10-770e-4813-a59a-d548002220ad · outbound

This paper cites Glick, H.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Glick, H

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.604315Z

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 8cdb98c6-bfd9-4d85-9d7f-d66f287fb83d · outbound

This paper cites an unresolved cited work.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:30:06.594456Z

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 f418f75f-70cb-4d1d-b2ac-b8f6a6f12833 · outbound

This paper cites Ohzeki, Quantum Monte Carlo simulation of a par- ticular class of non-stoquastic Hamiltonians in quantum annealing, Sci.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Ohzeki, Quantum Monte Carlo simulation of a par- ticular class of non-stoquastic Hamiltonians in quantum annealing, Sci

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T21:30:06.011837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b5e4ebe-8c2c-4c13-9c6f-10328b69d8b5 · outbound

This paper cites Seki and H.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Seki and H

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.578414Z

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 3dab9d0e-dd5b-4bf4-bcbf-613a386d400b · outbound

This paper cites an unresolved cited work.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:30:06.567617Z

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 c0dc8823-5663-4ab7-b6de-5f77be5f477c · outbound

This paper cites an unresolved cited work.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:30:06.556612Z

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 8dbf14aa-0a12-4229-b4de-61d80463af69 · outbound

This paper cites Lucas, Ising formulations of many NP problems, Front.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Lucas, Ising formulations of many NP problems, Front

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.545671Z

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 897484ae-c84b-4a93-ac33-dce45bedb2c4 · outbound

This paper cites Dominguez, J.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Dominguez, J

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.534193Z

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 0911d5d3-4680-4985-abd4-f87b00746646 · outbound

This paper cites an unresolved cited work.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:30:06.523092Z

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 6cdd7b57-e2dc-481e-9eca-e3b57ddbbb05 · outbound

This paper cites Glos, and J.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Glos, and J

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.512391Z

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 560addbc-64dc-4b9f-81cb-ed4d1e60b377 · outbound

This paper cites Adiabatic Quantum Algorithms for the NP-Complete Maximum-Weight Independent Set, Exact Cover and 3SAT Problems.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Adiabatic Quantum Algorithms for the NP-Complete Maximum-Weight Independent Set, Exact Cover and 3SAT Problems

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T21:30:06.040006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d91d6c6-53b7-4e62-bba4-192510c01732 · outbound

This paper cites Herrman, L.

Boosting quantum annealing performance through direct polynomial unconstrained binary optimization Herrman, L

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:30:06.502321Z

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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