Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:1812.04170.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T09:39:16.946463Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
50
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 7e7c8584-9ac4-4d57-af32-6a602a5823f5 · inbound
Learning to learn with quantum neural networks via classical neural networks cites this paper.
Learning to learn with quantum neural networks via classical neural networks For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 70
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T23:00:03.118504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ba1e9fe5-251a-4e28-b863-3b111b958c81 · inbound
Analysis of Quantum Approximate Optimization Algorithm under Realistic Noise in Superconducting Qubits cites this paper.
Analysis of Quantum Approximate Optimization Algorithm under Realistic Noise in Superconducting Qubits For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T21:44:58.900790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 465e9257-4937-451d-b77a-baa9df0debf6 · inbound
Light Cone Cancellation for Variational Quantum Eigensolver in Solving Noisy Max-Cut cites this paper.
Light Cone Cancellation for Variational Quantum Eigensolver in Solving Noisy Max-Cut For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T01:55:55.121418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 16f858d1-9fae-44fc-b7fe-dbd5d9211132 · inbound
Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm cites this paper.
Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T21:57:10.445727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dcc5ed57-756f-4e8d-9967-335240b02661 · inbound
Optimisation-Free Recursive QAOA for the Binary Paint Shop Problem cites this paper.
Optimisation-Free Recursive QAOA for the Binary Paint Shop Problem For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 64
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T04:27:03.805016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e091312f-2adf-4080-8d59-ff1d3d3e1f9e · inbound
Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms cites this paper.
Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T15:36:34.790627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f4e68343-7d31-4a9e-9365-2456ba1fad4c · inbound
Going off Pattern? QAOA Parameter Heuristics and Potentials of Parsimony cites this paper.
Going off Pattern? QAOA Parameter Heuristics and Potentials of Parsimony For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T09:22:30.447371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation da265a73-1d6a-4ff9-824b-4340fda17570 · inbound
Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning cites this paper.
Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T09:39:16.946463Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f950b504-64ea-4f8b-975a-97c2ae21d041 · inbound
Mind the gaps: The fraught road to quantum advantage cites this paper.
Mind the gaps: The fraught road to quantum advantage For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 133
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T01:51:39.787899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 398a0e1b-0709-4c24-93b2-a4554f759a3a · inbound
Mind the gaps: The fraught road to quantum advantage cites this paper.
Mind the gaps: The fraught road to quantum advantage For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 133
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T13:11:35.001656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 68f43647-8431-4769-b9b9-7d68b9f3d2b1 · inbound
Reductions of QAOA Induced by Classical Symmetries: Theoretical Insights and Practical Implications cites this paper.
Reductions of QAOA Induced by Classical Symmetries: Theoretical Insights and Practical Implications For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T21:56:40.694698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 098f742c-37af-4d59-80a4-3b9befe02901 · inbound
Landscape-Similarity-Guided Optimization in Divide-and-Conquer QAOA cites this paper.
Landscape-Similarity-Guided Optimization in Divide-and-Conquer QAOA For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T21:01:13.674551Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16f4798d-0d99-4a8a-9bed-a786f1014a3e · inbound
Tensor network surrogate models for variational quantum computation cites this paper.
Tensor network surrogate models for variational quantum computation For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T00:54:48.726052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 12291d86-fa06-4aff-8e0e-4ab320595bb2 · inbound
Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Regions cites this paper.
Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Regions For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T00:04:25.702915Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 873ff411-1f7d-44f0-86ed-50e188491e2d · inbound
Graph-Conditioned Meta-Optimizer for QAOA Parameter Generation on Multiple Problem Classes cites this paper.
Graph-Conditioned Meta-Optimizer for QAOA Parameter Generation on Multiple Problem Classes For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:31:16.009743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fd162693-148f-4eb9-82a0-7dad866128ae · inbound
QAOA Parameter Transfer for Hypergraphs cites this paper.
QAOA Parameter Transfer for Hypergraphs For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:36:40.137814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 482d2923-2745-4f7b-9e42-92965135601d · inbound
Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Problem cites this paper.
Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Problem For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 37
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T09:51:28.439240Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 834c6150-15c0-40b1-9ead-1cdefe14edf2 · inbound
SCALAR: A Neurosymbolic Framework for Automated Conjecture and Reasoning in Quantum Circuit Analysis cites this paper.
SCALAR: A Neurosymbolic Framework for Automated Conjecture and Reasoning in Quantum Circuit Analysis For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T05:31:25.951371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dd4f2e8b-98c2-4455-a295-f16a31a5e7c4 · inbound
Efficient Fourier-Based Linear Combination of Unitaries and Applications in Quantum Optimization cites this paper.
Efficient Fourier-Based Linear Combination of Unitaries and Applications in Quantum Optimization For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 61
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:48:13.036786Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e1db2116-6fab-4d87-86a4-ce28221a57f0 · inbound
Mechanism of Efficacy in QAOA for Random k-SAT: From Adiabatic Manifold to Sublinear Parameter Optimization cites this paper.
Mechanism of Efficacy in QAOA for Random k-SAT: From Adiabatic Manifold to Sublinear Parameter Optimization For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T02:29:24.985437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ae0fb470-7b3d-4263-8713-001f73fbe88d · inbound
SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation cites this paper.
SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 27
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-25T04:30:20.231121Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6961d370-5e1c-49a9-8748-ab77629de83d · inbound
SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation cites this paper.
SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T13:24:18.046425Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f3179e2-585d-4f49-8ef6-680763600b31 · inbound
Setting angles in quantum approximate optimization at utility-scale cites this paper.
Setting angles in quantum approximate optimization at utility-scale For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 73
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T09:16:49.161933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2e856853-4d1f-49d4-ac3e-2948d1b2f19b · inbound
Hamiltonian-Guided Leverage Embedding: Robust Subspace Compression for Efficient QAOA Parameter Estimation cites this paper.
Hamiltonian-Guided Leverage Embedding: Robust Subspace Compression for Efficient QAOA Parameter Estimation For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T19:17:18.475563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6f49c18f-f44a-40de-9cfb-44a4bc9c66ba · inbound
Challenges in Barren Plateau Mitigation with Dynamic Parameterized Quantum Circuits cites this paper.
Challenges in Barren Plateau Mitigation with Dynamic Parameterized Quantum Circuits For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T10:49:45.581505Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ae24bf67-83bd-4128-afaa-45adb7c7d095 · inbound
Challenges in Barren Plateau Mitigation with Dynamic Parameterized Quantum Circuits cites this paper.
Challenges in Barren Plateau Mitigation with Dynamic Parameterized Quantum Circuits For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T04:45:05.513719Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cfe55714-8017-4e94-be96-7da3a599c7e4 · inbound
Feasibility-driven QAOA with penalty scheduling cites this paper.
Feasibility-driven QAOA with penalty scheduling For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T17:50:00.477455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5b5c5001-24d0-4d7f-a4f4-e18bf2461d14 · inbound
Quantum machine learning models for graphs cites this paper.
Quantum machine learning models for graphs For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 62
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T12:16:56.390053Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6e00c933-1374-42eb-9354-7df6661dbf9b · inbound
Quantum-Informed Portfolio Selection: An End-to-End Pipeline Validated on Trapped-Ion Hardware with Real Market Data cites this paper.
Quantum-Informed Portfolio Selection: An End-to-End Pipeline Validated on Trapped-Ion Hardware with Real Market Data For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 51
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T11:56:54.880400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b7ad035b-4a7c-42f0-8249-62c3598a6fdb · inbound
Quantum-Informed Portfolio Selection: An End-to-End Pipeline Validated on Trapped-Ion Hardware with Real Market Data cites this paper.
Quantum-Informed Portfolio Selection: An End-to-End Pipeline Validated on Trapped-Ion Hardware with Real Market Data For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T16:49:25.319923Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3aa555cd-0d83-476b-a94f-9e9f3e1bee31 · inbound
Measurements Number Scaling in the Quantum Approximate Optimization Algorithm for MaxCut: A Statistical Analysis cites this paper.
Measurements Number Scaling in the Quantum Approximate Optimization Algorithm for MaxCut: A Statistical Analysis For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T03:11:29.824055Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 430be862-9a08-43bf-bf18-d902d9424ca5 · inbound
Weak Poincar\'e Inequalities via Approximate Stochastic Localization: Application to Sampling the Sherrington-Kirkpatrick Model cites this paper.
Weak Poincar\'e Inequalities via Approximate Stochastic Localization: Application to Sampling the Sherrington-Kirkpatrick Model For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 37
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-10T12:17:03.990289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 386db9e8-2ac0-49c6-ae9f-5e2bf30d58aa · inbound
Transferred QAOA Parameters Remember the Penalty Scale: A $\lambda$-Resonance Law for Constrained Quantum Optimization cites this paper.
Transferred QAOA Parameters Remember the Penalty Scale: A $\lambda$-Resonance Law for Constrained Quantum Optimization For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T14:33:18.384595Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.