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Paper Citation Record · LEDGER

Quantum-informed surrogate sampling for combinatorial optimization

As of 8 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2607.22372.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.22372 v1

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measured 84 of 84 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T05:02:02.295263Z

measured 84 of 84 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

84 of 84 outbound references displayed

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  • verified fuzzy0
  • unresolved76
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  • malformed identifier2
  • metadata mismatch0

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Outbound references

Observation bea7bbbf-a5b5-4fbf-ad5c-ed91293e347b · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 1

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Observation b1ee64a1-b4dd-4535-af75-1e9c11fad3fc · outbound

This paper cites [33], we can useregularized warm-start QAOA(R WS-QAOA) to generate correlations that can be supplied to QISS.

Quantum-informed surrogate sampling for combinatorial optimization [33], we can useregularized warm-start QAOA(R WS-QAOA) to generate correlations that can be supplied to QISS

Reference 2

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Observation f3f0d57f-68ae-4b0c-81b1-cd5f53b49a32 · outbound

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Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 3

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Observation 4e506a7a-e4bb-4451-b484-0079e956aa91 · outbound

This paper cites 8: (i) Simulated Annealing (SA) and (ii) a low-rank Burer–Monteiro (BM) implementation of the Goemans–Williamson SDP relaxation for MaxCut.

Quantum-informed surrogate sampling for combinatorial optimization 8: (i) Simulated Annealing (SA) and (ii) a low-rank Burer–Monteiro (BM) implementation of the Goemans–Williamson SDP relaxation for MaxCut

Reference 4

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Observation 5957a23e-17da-4c3e-86d0-a6ae8d0ce283 · outbound

This paper cites We therefore supply QISS with the one-body expectations⟨Z i⟩for all i∈Vtogether with the two-body correlators⟨Z iZj⟩that do not factorize, i.e.

Quantum-informed surrogate sampling for combinatorial optimization We therefore supply QISS with the one-body expectations⟨Z i⟩for all i∈Vtogether with the two-body correlators⟨Z iZj⟩that do not factorize, i.e

Reference 5

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Observation 16b6a1c5-f615-4afa-92f4-cbad5d01b298 · outbound

This paper cites 10, we compare the independence ratios averaged over 40 instances at each system sizeN.

Quantum-informed surrogate sampling for combinatorial optimization 10, we compare the independence ratios averaged over 40 instances at each system sizeN

Reference 6

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Observation 051a04e6-06e8-4dde-bedf-9b21709c30b3 · outbound

This paper cites Hogg and D.

Quantum-informed surrogate sampling for combinatorial optimization Hogg and D

Reference 7

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Observation 290be637-08e0-44ef-98fd-821a0a528901 · outbound

This paper cites Hogg, Phys.

Quantum-informed surrogate sampling for combinatorial optimization Hogg, Phys

Reference 8

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Observation 1dfd450c-ce43-4129-8d41-5b98d97217aa · outbound

This paper cites A Quantum Approximate Optimization Algorithm.

Quantum-informed surrogate sampling for combinatorial optimization A Quantum Approximate Optimization Algorithm

Reference 9

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Observation 64619ab4-a4e4-4161-911d-3fec0c14e7a1 · outbound

This paper cites Montanaro, Physical Review Research2(2020), 10.1103/physrevresearch.2.013056.

Quantum-informed surrogate sampling for combinatorial optimization Montanaro, Physical Review Research2(2020), 10.1103/physrevresearch.2.013056

Reference 10

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Observation d3d21eb0-61a6-4c5b-a513-893fbbc8df95 · outbound

This paper cites Challenges and Opportunities in Quantum Optimization.

Quantum-informed surrogate sampling for combinatorial optimization Challenges and Opportunities in Quantum Optimization

Reference 11

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Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

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Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

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Observation a41084ec-c162-446e-a984-db755472169a · outbound

This paper cites Mechanisms for quantum advantage in global optimization of nonconvex functions,.

Quantum-informed surrogate sampling for combinatorial optimization Mechanisms for quantum advantage in global optimization of nonconvex functions,

Reference 14

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Observation 44585dc2-e8be-478b-a34b-ae130b1dca8c · outbound

This paper cites Pagano andet al., Proc.

Quantum-informed surrogate sampling for combinatorial optimization Pagano andet al., Proc

Reference 15

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Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

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Observation 7c0bddcd-14e2-437e-bb91-c96d811c92f9 · outbound

This paper cites Ebadi, A.

Quantum-informed surrogate sampling for combinatorial optimization Ebadi, A

Reference 17

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Observation 7dca08ff-d014-4801-b066-097ac3af1471 · outbound

This paper cites Pelofske, A.

Quantum-informed surrogate sampling for combinatorial optimization Pelofske, A

Reference 18

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Observation 65c398a0-fba3-4a47-87fa-09eb056b66d4 · outbound

This paper cites Shaydulin, C.

Quantum-informed surrogate sampling for combinatorial optimization Shaydulin, C

Reference 19

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Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

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Observation 5621a642-4b37-4a3d-8eb6-2518bc3f6677 · outbound

This paper cites Boulebnane and A.

Quantum-informed surrogate sampling for combinatorial optimization Boulebnane and A

Reference 21

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Observation b6f16748-68bc-4d9f-8d47-145822e4e301 · outbound

This paper cites Applying the quantum approximate optimization algorithm to general constraint satisfaction problems.

Quantum-informed surrogate sampling for combinatorial optimization Applying the quantum approximate optimization algorithm to general constraint satisfaction problems

Reference 22

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Observation 491c4daf-c759-4a8c-9e2a-967ae166d115 · outbound

This paper cites Quantum speedups in solving near-symmetric optimization problems by low-depth QAOA.

Quantum-informed surrogate sampling for combinatorial optimization Quantum speedups in solving near-symmetric optimization problems by low-depth QAOA

Reference 23

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Observation 2eb4eac1-af4e-4853-ae1d-cc05197c4417 · outbound

This paper cites Akshay, D.

Quantum-informed surrogate sampling for combinatorial optimization Akshay, D

Reference 24

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Observation e92f342a-c2a8-4dd6-bf76-564ec4e683f8 · outbound

This paper cites The Quantum Approximate Optimization Algorithm Needs to See the Whole Graph: A Typical Case.

Quantum-informed surrogate sampling for combinatorial optimization The Quantum Approximate Optimization Algorithm Needs to See the Whole Graph: A Typical Case

Reference 25

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Observation c7e721f5-5b45-4eb9-a045-f08bd61c2918 · outbound

This paper cites Limitations of Local Quantum Algorithms on Random Max-k-XOR and Beyond.

Quantum-informed surrogate sampling for combinatorial optimization Limitations of Local Quantum Algorithms on Random Max-k-XOR and Beyond

Reference 26

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Observation 7b00b3f6-5317-4d67-b80e-dbbdd67a029b · outbound

This paper cites Basso, D.

Quantum-informed surrogate sampling for combinatorial optimization Basso, D

Reference 27

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Observation 517d4228-b1b2-4542-baf8-0b7c9f48f332 · outbound

This paper cites Concentration bounds for quantum states and limitations on the QAOA from polynomial approximations.

Quantum-informed surrogate sampling for combinatorial optimization Concentration bounds for quantum states and limitations on the QAOA from polynomial approximations

Reference 28

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Observation d546cfc3-9d92-4f3b-a5f7-407992a06c1d · outbound

This paper cites The Quantum Approximate Optimization Algorithm Needs to See the Whole Graph: Worst Case Examples.

Quantum-informed surrogate sampling for combinatorial optimization The Quantum Approximate Optimization Algorithm Needs to See the Whole Graph: Worst Case Examples

Reference 29

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Observation 4b14bf33-b8f6-4a1d-a738-1687f8f395a1 · outbound

This paper cites Local algorithms and the failure of log-depth quantum advantage on sparse random CSPs.

Quantum-informed surrogate sampling for combinatorial optimization Local algorithms and the failure of log-depth quantum advantage on sparse random CSPs

Reference 30

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Observation 4e90d629-ab45-4edc-a95c-1bf412ecd9d2 · outbound

This paper cites Limits of local algorithms over sparse random graphs.

Quantum-informed surrogate sampling for combinatorial optimization Limits of local algorithms over sparse random graphs

Reference 31

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Observation 9f9053a3-ebf8-43f8-998d-d48e949be11c · outbound

This paper cites The Overlap Gap Property and Approximate Message Passing Algorithms for $p$-spin models.

Quantum-informed surrogate sampling for combinatorial optimization The Overlap Gap Property and Approximate Message Passing Algorithms for $p$-spin models

Reference 32

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source=pdf_text observed=2026-08-01T05:02:01.248270Z digest=sha256:267b7b8c9da5f473238a006779cfc2fe135d7a6cdc36b0bacbc15e61f651953f

Observation 1e00da0a-e63b-4793-a49a-60d7a2a9c82b · outbound

This paper cites The Overlap Gap Property: a Geometric Barrier to Optimizing over Random Structures.

Quantum-informed surrogate sampling for combinatorial optimization The Overlap Gap Property: a Geometric Barrier to Optimizing over Random Structures

Reference 33

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Observation eb24c00d-778b-41eb-bc1e-a32e39298775 · outbound

This paper cites Limitations of optimization algorithms on noisy quantum devices.

Quantum-informed surrogate sampling for combinatorial optimization Limitations of optimization algorithms on noisy quantum devices

Reference 34

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Observation eda8dfe5-a4da-447c-9d6a-ad8d11b1ffba · outbound

This paper cites Limitations of variational quantum algorithms: a quantum optimal transport approach.

Quantum-informed surrogate sampling for combinatorial optimization Limitations of variational quantum algorithms: a quantum optimal transport approach

Reference 35

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Observation b97534b6-8ce1-4f63-9617-9d4a59c38fdb · outbound

This paper cites Dupont, B.

Quantum-informed surrogate sampling for combinatorial optimization Dupont, B

Reference 36

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Observation a30c9556-b56e-42cd-8c14-38fc50e0a393 · outbound

This paper cites A scalable quantum-enhanced greedy algorithm for maximum independent set problems,.

Quantum-informed surrogate sampling for combinatorial optimization A scalable quantum-enhanced greedy algorithm for maximum independent set problems,

Reference 37

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Observation 66ab8ec9-285f-4093-a37c-d19f9d80cf2b · outbound

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Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 38

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Observation 413f8760-3be8-4a5a-9a47-ae306d537995 · outbound

This paper cites Regularized warm-started quantum approximate optimization and conditions for surpassing classical solvers on the max-cut problem,.

Quantum-informed surrogate sampling for combinatorial optimization Regularized warm-started quantum approximate optimization and conditions for surpassing classical solvers on the max-cut problem,

Reference 39

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Observation d599d0a2-b28e-456f-a858-2ed67c938909 · outbound

This paper cites Quantum Supremacy through the Quantum Approximate Optimization Algorithm.

Quantum-informed surrogate sampling for combinatorial optimization Quantum Supremacy through the Quantum Approximate Optimization Algorithm

Reference 40

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Observation 0573fbb4-012b-47ff-a42a-e5b0f15d4ce7 · outbound

This paper cites Lower bounding the maxcut of high girth 3-regular graphs using the qaoa,.

Quantum-informed surrogate sampling for combinatorial optimization Lower bounding the maxcut of high girth 3-regular graphs using the qaoa,

Reference 41

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source=pdf_text observed=2026-08-01T05:02:01.282083Z digest=sha256:dc59761a4392a89ea9e4d204ae03ac302261c1c1bc4e4ec52e95465f1807f2de

Observation 923d428f-d874-4bce-9652-1ac07a70a15c · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 42

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source=pdf_text observed=2026-08-01T05:02:01.285843Z digest=sha256:db4e39cb3378cab1e0b95042c2a0581fbd3d128159e463acbe22649e99cf78ad

Observation a5129714-7e20-4881-86eb-9ef3c139681f · outbound

This paper cites Layden, G.

Quantum-informed surrogate sampling for combinatorial optimization Layden, G

Reference 43

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source=pdf_text observed=2026-08-01T05:02:01.289235Z digest=sha256:5036725f14c0e19ecee66e427abcb816e56edf6d512b6ec76555a5b94d0ab172

Observation 38a5b2d0-4115-41b9-8438-6d093b73aeae · outbound

This paper cites QAOA-MC: Markov chain Monte Carlo enhanced by Quantum Alternating Operator Ansatz.

Quantum-informed surrogate sampling for combinatorial optimization QAOA-MC: Markov chain Monte Carlo enhanced by Quantum Alternating Operator Ansatz

Reference 44

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source=pdf_text observed=2026-08-01T05:02:01.292441Z digest=sha256:47a0492a4d4c3cb669db6e5e5dbdef1cebeb43f78e7895aeff6fe998d1b52b3a

Observation 0cd17284-db17-4f0c-890b-d4fb991eecb0 · outbound

This paper cites Quantum-enhanced markov chain monte carlo for combinatorial optimization,.

Quantum-informed surrogate sampling for combinatorial optimization Quantum-enhanced markov chain monte carlo for combinatorial optimization,

Reference 45

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source=pdf_text observed=2026-08-01T05:02:01.295853Z digest=sha256:8d058d35972c7243c06401072d9a452dc5e791d889130d782e35a9cb490e4b56

Observation b11af5c4-f219-41f3-9eb0-ecf7e6dced07 · outbound

This paper cites Divide-and-Conquer Neural Network Surrogates for Quantum Sampling: Accelerating Markov Chain Monte Carlo in Large-Scale Constrained Optimization Problems.

Quantum-informed surrogate sampling for combinatorial optimization Divide-and-Conquer Neural Network Surrogates for Quantum Sampling: Accelerating Markov Chain Monte Carlo in Large-Scale Constrained Optimization Problems

Reference 46

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source=pdf_text observed=2026-08-01T05:02:01.298950Z digest=sha256:125bd870b1c94e4bae81b2f060e579fda1a161df6a0d931d70c0761ff6bacb47

Observation 4105295d-328b-4df9-968b-ab875fe6c9a5 · outbound

This paper cites Quantum-Enhanced Optimization by Warm Starts.

Quantum-informed surrogate sampling for combinatorial optimization Quantum-Enhanced Optimization by Warm Starts

Reference 47

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source=pdf_text observed=2026-08-01T05:02:01.302336Z digest=sha256:69a0fc03296faa02f9c22af19fe0087a7d9862aa71002899f4a6acfd06b21204

Observation 10e15e11-7e17-4001-ac66-a9fa45e324e0 · outbound

This paper cites Obstacles to State Preparation and Variational Optimization from Symmetry Protection.

Quantum-informed surrogate sampling for combinatorial optimization Obstacles to State Preparation and Variational Optimization from Symmetry Protection

Reference 48

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source=pdf_text observed=2026-08-01T05:02:01.305616Z digest=sha256:fa6e77af0957d5acb12f76e47ab30a3bb77bad09e2f5423f5b5f4575af12f0b1

Observation 3fb944e5-cc33-4606-84c7-cc6cab6d06af · outbound

This paper cites Extending relax-and-round combinatorial optimization solvers with quantum correlations.

Quantum-informed surrogate sampling for combinatorial optimization Extending relax-and-round combinatorial optimization solvers with quantum correlations

Reference 49

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source=pdf_text observed=2026-08-01T05:02:01.308806Z digest=sha256:521b667097496c4ab0bc55dbf15c5b2d1da7114ca4861553992d5623ccb81466

Observation 122a8624-ff99-4f2b-aa12-20388112a3a4 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 50

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source=pdf_text observed=2026-08-01T05:02:01.312096Z digest=sha256:fb3269d0fbad0526b05a47f8a31f0d30388145ba22676ff2bc198ed205e03ad4

Observation d656f980-153f-44f5-9d2a-58bbba6af461 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 51

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source=pdf_text observed=2026-08-01T05:02:01.315399Z digest=sha256:8ad0ef1fe6c05bc9c4ff73d64170cfa79c5d2c083b39fd2c4ac198fff1aa0649

Observation 87227738-97d4-4f23-b32e-adf9857823f9 · outbound

This paper cites Martinez, O.

Quantum-informed surrogate sampling for combinatorial optimization Martinez, O

Reference 52

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source=pdf_text observed=2026-08-01T05:02:01.318418Z digest=sha256:114d89881c54cea429470fa6bc2e1e1b6fb158b398f50c47270b6fbb9b784423

Observation 8688f874-dfc6-4895-8509-bd412552b16a · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 53

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source=pdf_text observed=2026-08-01T05:02:01.321579Z digest=sha256:d54ba404daf09d75364a9875e520a0272dd19ab33ce372fefe3f651db684d999

Observation 78a946e6-0060-4b2d-af43-18ac04214594 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 54

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source=pdf_text observed=2026-08-01T05:02:01.324559Z digest=sha256:d2cd0a45ee04960f51387fadd171b889665ad79e9c7eb03bc769ca728c47effd

Observation 6ebb22cb-dad3-482b-b7fb-27411369edad · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-01T05:02:01.327677Z digest=sha256:8ac535c7e6e3c6f7f11541622a1fd5a770913f0c5a221a47b382a29b82bd5068

Observation 9457662e-dede-4bf3-8304-d482ef5f0394 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 56

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source=pdf_text observed=2026-08-01T05:02:01.330962Z digest=sha256:ba5d3a1848d43793948641ee5399c5ae26e62ab9ac90654f74ddd4f3775f5f9a

Observation 12378d8f-d349-4ca4-8d2b-0c4ef2671e03 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 57

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source=pdf_text observed=2026-08-01T05:02:01.334165Z digest=sha256:cefe74ce0653f9f1d33e3b8885957c62742732e1a8e28aff81cd35d0ea9dc949

Observation 0366f6ce-e9f1-472d-a204-5015c03299dd · outbound

This paper cites Chancellor, Quantum Science and Technology4, 045004 (2019).

Quantum-informed surrogate sampling for combinatorial optimization Chancellor, Quantum Science and Technology4, 045004 (2019)

Reference 58

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source=pdf_text observed=2026-08-01T05:02:01.337420Z digest=sha256:d607b4526818535beba6dfff1650c9e0d784ce60b73afac22f4186afe69544b8

Observation 8124bcbd-9dc2-42bc-92a4-6475a5a9aef1 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 59

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source=pdf_text observed=2026-08-01T05:02:01.341060Z digest=sha256:7ccd3c7f31b5c8b6072e2b781e69d8e5056cb71bcaea430bebbfa7308db212af

Observation 8d3fb898-54a1-4483-b573-d1840a03458e · outbound

This paper cites Bak´ o, A.

Quantum-informed surrogate sampling for combinatorial optimization Bak´ o, A

Reference 60

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source=pdf_text observed=2026-08-01T05:02:01.344265Z digest=sha256:13092b5bbbb58c65aa5e425dc6d4ecc6fee907f1682c8655119a516c6241f14f

Observation 634e47ca-9fe3-44d0-9620-ebc49189b81e · outbound

This paper cites Sciorilli, L.

Quantum-informed surrogate sampling for combinatorial optimization Sciorilli, L

Reference 61

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source=pdf_text observed=2026-08-01T05:02:01.348003Z digest=sha256:daca6fc3b24a1b555e987712948dcfde8bbacb4c415a2a000b02a7930068745f

Observation afde56e9-58a3-4abe-aa61-ef5cfe74f8f8 · outbound

This paper cites An information-minimal geometry for qubit-efficient optimization,.

Quantum-informed surrogate sampling for combinatorial optimization An information-minimal geometry for qubit-efficient optimization,

Reference 62

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source=pdf_text observed=2026-08-01T05:02:01.351443Z digest=sha256:91c6be7b59732e569c99ca966f574fc28ebeb26ec9e68c6ff6ea38ddd2f44e9f

Observation 2e3104af-75a0-42d8-9279-1f464fddb792 · outbound

This paper cites Quantum Computing in the NISQ era and beyond.

Quantum-informed surrogate sampling for combinatorial optimization Quantum Computing in the NISQ era and beyond

Reference 63

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source=pdf_text observed=2026-08-01T05:02:01.354476Z digest=sha256:5827f098237c27eb127b998278e4544ebf2a6ab8b3aed1fa7adc4df568e572bd

Observation 538d7428-4612-4c8c-9748-802d07bdc3e3 · outbound

This paper cites Lucas, Frontiers in PhysicsV olume 2 - 2014(2014), 10.3389/fphy.2014.00005.

Quantum-informed surrogate sampling for combinatorial optimization Lucas, Frontiers in PhysicsV olume 2 - 2014(2014), 10.3389/fphy.2014.00005

Reference 64

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source=pdf_text observed=2026-08-01T05:02:01.359528Z digest=sha256:4c7143f25609ba12bcc97f84901b602d93d3a900e779d3258cdfb85491732bb9

Observation a1bc5593-5804-4d28-a7d4-da52611e154d · outbound

This paper cites The Quantum Approximate Optimization Algorithm at High Depth for MaxCut on Large-Girth Regular Graphs and the Sherrington-Kirkpatrick Model.

Quantum-informed surrogate sampling for combinatorial optimization The Quantum Approximate Optimization Algorithm at High Depth for MaxCut on Large-Girth Regular Graphs and the Sherrington-Kirkpatrick Model

Reference 65

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source=pdf_text observed=2026-08-01T05:02:01.377768Z digest=sha256:88070d9d90c84c2f130b4aa69c819b63c1024d712bcff48a82fa8ae98606a974

Observation 06cf0065-6cc7-451f-84c2-539acf14e374 · outbound

This paper cites Regular trees in random regular graphs,.

Quantum-informed surrogate sampling for combinatorial optimization Regular trees in random regular graphs,

Reference 66

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source=pdf_text observed=2026-08-01T05:02:01.415993Z digest=sha256:7dab8bf5108b7dafc9b7e912f1a78e25321793b8d071ac758822e4e25d76492a

Observation 9dc7a1f3-fbab-438e-a624-36fbb8dd82b9 · outbound

This paper cites Wybo and M.

Quantum-informed surrogate sampling for combinatorial optimization Wybo and M

Reference 67

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source=pdf_text observed=2026-08-01T05:02:01.452914Z digest=sha256:ee3b0135a1d2faf1f0ded5ab9face2f66909222f8128a11dc404a9d5d6bf2741

Observation 4407238c-56e1-4065-9366-2fe2ccd49ae8 · outbound

This paper cites Gray, Journal of Open Source Software3, 819 (2018).

Quantum-informed surrogate sampling for combinatorial optimization Gray, Journal of Open Source Software3, 819 (2018)

Reference 68

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source=pdf_text observed=2026-08-01T05:02:01.500630Z digest=sha256:c86ca2a1a331f30cda942212655b933a0be5135b77f6fb940929f715f0706824

Observation 64e6fdc1-26f8-498a-bd42-ff5c9cc83b45 · outbound

This paper cites Pearl,Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference(Morgan Kaufmann, 1988).

Quantum-informed surrogate sampling for combinatorial optimization Pearl,Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference(Morgan Kaufmann, 1988)

Reference 69

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source=pdf_text observed=2026-08-01T05:02:01.541525Z digest=sha256:4de351412a0d0cd3c7005696399402e6d6e59f24eca4511d25951b7d96475ae4

Observation 1ac376b5-22f8-48e1-bda7-a0e2e9739865 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 70

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Observation 43bf5cb3-98f0-465c-b693-a18f5d95082e · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 71

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source=pdf_text observed=2026-08-01T05:02:01.649312Z digest=sha256:7a23b8b71c1ddbfe9b847f3d202b4ffa6d8814ecd514f1309894ade31ed98a61

Observation f15c02ed-c129-4527-a933-696c8147dfb0 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 72

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source=pdf_text observed=2026-08-01T05:02:01.698245Z digest=sha256:0f9b3e8c73ca30b52f8d68eb9bdce28d3941b42a91182ebb0a95058ec6464898

Observation e54e3f62-420e-4ff8-9393-6b9180b3035f · outbound

This paper cites Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor.

Quantum-informed surrogate sampling for combinatorial optimization Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor

Reference 73

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source=pdf_text observed=2026-08-01T05:02:01.742412Z digest=sha256:235da67f457e6fb111252dfd5f825f50f4d2978500aba0865a8e5e696b98b6a1

Observation 541a8d4b-12b4-40df-9f38-64947d0dc754 · outbound

This paper cites Temme, S.

Quantum-informed surrogate sampling for combinatorial optimization Temme, S

Reference 74

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source=pdf_text observed=2026-08-01T05:02:01.820369Z digest=sha256:1ed99a8db4fe7e4d532bf81786cda73ba97554ef4803037b10d4612dda6a8087

Observation 050584a1-a4e6-4897-b239-e9b4114a7bc1 · outbound

This paper cites Li and S.

Quantum-informed surrogate sampling for combinatorial optimization Li and S

Reference 75

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source=pdf_text observed=2026-08-01T05:02:01.867875Z digest=sha256:c741eeedd19b754b8a816aaad56a17a25facabdceef79d237508e98832cd32be

Observation ba6268c4-9e62-4360-ba29-47ac0b8113e2 · outbound

This paper cites Halperin, D.

Quantum-informed surrogate sampling for combinatorial optimization Halperin, D

Reference 76

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source=pdf_text observed=2026-08-01T05:02:01.979810Z digest=sha256:8a28bdd05a2ad75f2ab2c32011721119017b72ee0f6851747ef79c2e1e35a65d

Observation 75a7975e-bc75-4161-aafa-3027e251c1f5 · outbound

This paper cites Kirkpatrick, C.

Quantum-informed surrogate sampling for combinatorial optimization Kirkpatrick, C

Reference 77

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source=pdf_text observed=2026-08-01T05:02:02.015130Z digest=sha256:51b59e5fe07a07956721ba40cb0ec3e8252ace238ea65dfa972d185d95a3c74a

Observation 42dc0b06-cf09-4942-8f59-92ab02cef6b7 · outbound

This paper cites dwave-samplers: Ocean-compatible classical samplers,.

Quantum-informed surrogate sampling for combinatorial optimization dwave-samplers: Ocean-compatible classical samplers,

Reference 78

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source=pdf_text observed=2026-08-01T05:02:02.060272Z digest=sha256:e4497533ee83038f8d7e542f3d5a1fc62811310f767a570abc8bc94821eac75e

Observation 65a0c60e-21d3-472c-872e-322810c1dd05 · outbound

This paper cites Burer, R.

Quantum-informed surrogate sampling for combinatorial optimization Burer, R

Reference 79

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source=pdf_text observed=2026-08-01T05:02:02.100782Z digest=sha256:8dc37b970021110eb238e548ed11c365b49ea54140c5cd97108c416c28cdcd09

Observation 6982974e-c4cd-45e7-a271-3c59bc53b292 · outbound

This paper cites Dunning, S.

Quantum-informed surrogate sampling for combinatorial optimization Dunning, S

Reference 80

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source=pdf_text observed=2026-08-01T05:02:02.135516Z digest=sha256:c32aeec6a3e805ce44ea7b794a310a59306454a9d1be8a61a7fd86b1c0bc6814

Observation 71225f54-6b2e-42e0-b576-9139cdcc0276 · outbound

This paper cites Large independent sets on random $d$-regular graphs with fixed degree $d$.

Quantum-informed surrogate sampling for combinatorial optimization Large independent sets on random $d$-regular graphs with fixed degree $d$

Reference 81

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-01T05:02:02.166293Z digest=sha256:63d9fd4a305ddfa4fa11223bca3ccfc479ed88b72f6ac6c2fcf3c4fa40f91db7

Observation a906cf99-6398-4d40-abe7-c9ab3f7eb5a7 · outbound

This paper cites an unresolved cited work.

Quantum-informed surrogate sampling for combinatorial optimization Unresolved cited work

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-01T05:02:02.196117Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:02:02.196117Z digest=sha256:9c26dc50ffbbb7c7856981e349ec7328d2d9fb4b6a0578ee6e45b93f88beba7f

Observation b8016006-75bf-4501-b1b5-71570f8d0da8 · outbound

This paper cites Hukushima and K.

Quantum-informed surrogate sampling for combinatorial optimization Hukushima and K

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-01T05:02:02.256036Z

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source=pdf_text observed=2026-08-01T05:02:02.256036Z digest=sha256:854bc22f811386c2de98a3df300c64e3686d7ebdaf46f0bade26673e07e76536

Observation 586ee4d9-d0b7-4c55-ac29-6589709edc69 · outbound

This paper cites Parisi, Phys.

Quantum-informed surrogate sampling for combinatorial optimization Parisi, Phys

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-01T05:02:02.295263Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:02:02.295263Z digest=sha256:dace1ac5d811de612de0a23deeb06a24627c87169cfc9f7f78952d84a1a703a9

Pith citing papers

No inbound Pith citation observations are available.