Paper Citation Record · LEDGER

Regularizing quantum loss landscapes by noise injection

As of 17 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2505.08759.

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

pith.paper-citation-record.v1
2505.08759 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:56:01.186959Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:13:00.303758Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-20T22:29:09.544814Z

Reference resolution

50 of 50 outbound references displayed

verified exact8
verified fuzzy9
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External citation measurements

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Outbound references

Observation aaf84177-35c9-4a6f-84e4-2f31c6570cbd · outbound

This paper cites Variational Quantum Algorithms.

Regularizing quantum loss landscapes by noise injection Variational Quantum Algorithms

Reference 1

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Observation 9c1ce495-16ce-45cd-b0c5-e8e7cddece37 · outbound

This paper cites Quantum machine learning.

Regularizing quantum loss landscapes by noise injection Quantum machine learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:00.958308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b2a03d3-c159-40d1-a018-d7b0d8c362ba · outbound

This paper cites The effect of data encoding on the expressive power of variational quantum machine learning models.

Regularizing quantum loss landscapes by noise injection The effect of data encoding on the expressive power of variational quantum machine learning models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:00.964197Z

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Observation 15e9aa2a-6945-45fc-89f4-510bcc67a4d0 · outbound

This paper cites The theory of variational hybrid quantum-classical algorithms.

Regularizing quantum loss landscapes by noise injection The theory of variational hybrid quantum-classical algorithms

Reference 4

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Observation 3fc49899-eb70-4427-aa85-57544088b854 · outbound

This paper cites Barren Plateaus in Variational Quantum Computing.

Regularizing quantum loss landscapes by noise injection Barren Plateaus in Variational Quantum Computing

Reference 5

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Observation e5538d4c-348a-41a8-8273-4a8ca289c936 · outbound

This paper cites Cerezo, Samson Wang, Tyler Volkoff, Andrew T.

Regularizing quantum loss landscapes by noise injection Cerezo, Samson Wang, Tyler Volkoff, Andrew T

Reference 6

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Observation 6352801b-3364-4fef-968d-b33b30cc7be1 · outbound

This paper cites Does provable absence of barren plateaus imply classical simulability?.

Regularizing quantum loss landscapes by noise injection Does provable absence of barren plateaus imply classical simulability?

Reference 7

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Observation 4d98d2bd-79b3-4b56-8996-5ecad656e1ff · outbound

This paper cites Critical Points in Quantum Generative Models.

Regularizing quantum loss landscapes by noise injection Critical Points in Quantum Generative Models

Reference 8

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Observation d74ad7d0-047c-4d94-9fad-e8f8f72de84a · outbound

This paper cites Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps.

Regularizing quantum loss landscapes by noise injection Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps

Reference 9

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Observation 0895e8af-52be-4417-a8c3-c611393bc36f · outbound

This paper cites Training variational quantum algorithms is NP-hard.

Regularizing quantum loss landscapes by noise injection Training variational quantum algorithms is NP-hard

Reference 10

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Observation 8c42b4f0-75f2-4e2f-ba78-f0a10299ae50 · outbound

This paper cites Deep learning.

Regularizing quantum loss landscapes by noise injection Deep learning

Reference 11

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Observation 44a847d2-3676-4f78-8ee9-e0acdfaffb09 · outbound

This paper cites Visual recon- struction.

Regularizing quantum loss landscapes by noise injection Visual recon- struction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.189504Z

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Observation 2a8a4be2-88db-40ac-abc3-f0bceb10edda · outbound

This paper cites On the Link be- tween Gaussian Homotopy Continuation and Convex En- velopes.

Regularizing quantum loss landscapes by noise injection On the Link be- tween Gaussian Homotopy Continuation and Convex En- velopes

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.171191Z

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Observation f9b478da-b336-40fd-bd59-b00c1e63fe42 · outbound

This paper cites On Graduated Optimization for Stochastic Non-Convex Problems.

Regularizing quantum loss landscapes by noise injection On Graduated Optimization for Stochastic Non-Convex Problems

Reference 14

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Observation 5eba8198-23a0-40c2-b562-7a7862c34046 · outbound

This paper cites Stochastic Gradient Descent in the Viewpoint of Graduated Optimization.

Regularizing quantum loss landscapes by noise injection Stochastic Gradient Descent in the Viewpoint of Graduated Optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.026566Z

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Observation bc413181-4079-44d0-a5cb-846e81cb718c · outbound

This paper cites Explicit and Implicit Graduated Optimization in Deep Neural Networks.

Regularizing quantum loss landscapes by noise injection Explicit and Implicit Graduated Optimization in Deep Neural Networks

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.925732Z

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Observation 897014a0-5014-4bb7-86d1-fef0a7958c80 · outbound

This paper cites Fourier expansion in variational quantum al- gorithms.

Regularizing quantum loss landscapes by noise injection Fourier expansion in variational quantum al- gorithms

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.155190Z

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Observation 45802462-7d86-47cd-8ea3-50ec9e62987e · outbound

This paper cites Learning Unitaries by Gradient Descent.

Regularizing quantum loss landscapes by noise injection Learning Unitaries by Gradient Descent

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.042609Z

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Observation 5679c4fa-e135-4cab-ad1c-d0468036bd4a · outbound

This paper cites Training Saturation in Layerwise Quantum Approximate Optimisation.

Regularizing quantum loss landscapes by noise injection Training Saturation in Layerwise Quantum Approximate Optimisation

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.885987Z

Source-reported events for the cited work

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Observation 87dae78f-5bc5-432a-8b71-d3f66b2f0993 · outbound

This paper cites Efficient variational synthesis of quantum circuits with coherent multi-start optimization.

Regularizing quantum loss landscapes by noise injection Efficient variational synthesis of quantum circuits with coherent multi-start optimization

Reference 20

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Observation 1a0ff390-fe78-4cc6-afcd-fc60cb3d0bda · outbound

This paper cites An Empirical Review of Optimization Techniques for Quantum Variational Circuits.

Regularizing quantum loss landscapes by noise injection An Empirical Review of Optimization Techniques for Quantum Variational Circuits

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.057121Z

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Observation c0fff46f-fd6c-4002-8ddf-f2853ee94d7f · outbound

This paper cites Performance comparison of optimization methods on variational quantum algorithms.

Regularizing quantum loss landscapes by noise injection Performance comparison of optimization methods on variational quantum algorithms

Reference 22

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Observation 3f51f3ba-d8de-4cd1-afe3-591c6154a2bc · outbound

This paper cites Quantum Natural Gradient.

Regularizing quantum loss landscapes by noise injection Quantum Natural Gradient

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.067280Z

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Observation fb5a31c2-e49e-47d9-b919-cb358934c46c · outbound

This paper cites Avoiding local minima in variational quantum eigensolvers with the natural gradient optimizer.

Regularizing quantum loss landscapes by noise injection Avoiding local minima in variational quantum eigensolvers with the natural gradient optimizer

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.072217Z

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Observation 93864aa5-2fb3-4231-822c-0bcc148b51be · outbound

This paper cites Using Differential Evolution to avoid local minima in Variational Quantum Algorithms.

Regularizing quantum loss landscapes by noise injection Using Differential Evolution to avoid local minima in Variational Quantum Algorithms

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.787501Z

Source-reported events for the cited work

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Observation b80b1741-0b53-4d71-bca9-f26ebac4ea6e · outbound

This paper cites Diffusion-Enhanced Optimization of Variational Quan- tum Eigensolver for General Hamiltonians.

Regularizing quantum loss landscapes by noise injection Diffusion-Enhanced Optimization of Variational Quan- tum Eigensolver for General Hamiltonians

Reference 26

Resolution: verified exact; raw_fallback, observed 2026-08-15T21:56:01.766500Z

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Observation b0604cf0-d9b1-4a15-94dc-ac29ec03b962 · outbound

This paper cites Avoiding local minima in Variational Quantum Algorithms with Neural Networks.

Regularizing quantum loss landscapes by noise injection Avoiding local minima in Variational Quantum Algorithms with Neural Networks

Reference 27

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Observation d13ecdae-af2b-435a-aa0d-e90f220ba1ea · outbound

This paper cites Quantum Learning with Noise and Decoherence: A Robust Quantum Neural Network.

Regularizing quantum loss landscapes by noise injection Quantum Learning with Noise and Decoherence: A Robust Quantum Neural Network

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.676488Z

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Observation f29def85-d6b9-4ae7-9f79-55dfb19d692a · outbound

This paper cites Method for noise-induced regularization in quantum neural net- works.

Regularizing quantum loss landscapes by noise injection Method for noise-induced regularization in quantum neural net- works

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.095524Z

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Observation 092eaabc-1064-4661-9d58-0e09bed1d0c3 · outbound

This paper cites In [19] it was observed that a small amount of noise may prevent layer-wise training saturation in quan- tum approximate optimization algorithms.

Regularizing quantum loss landscapes by noise injection In [19] it was observed that a small amount of noise may prevent layer-wise training saturation in quan- tum approximate optimization algorithms

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.263272Z

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Observation b199f22a-aebb-49ac-b487-1bfbefde97d6 · outbound

This paper cites Stochastic noise can be helpful for variational quantum algorithms.

Regularizing quantum loss landscapes by noise injection Stochastic noise can be helpful for variational quantum algorithms

Reference 31

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Observation 5ed2b554-208d-454f-b56c-77be922888f8 · outbound

This paper cites Noisy Quantum Kernel Machines.

Regularizing quantum loss landscapes by noise injection Noisy Quantum Kernel Machines

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.099923Z

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Observation 68f5105d-147d-467e-9faa-2166a9ecda23 · outbound

This paper cites Low Rank Density Matrix Evolution for Noisy Quantum Circuits.

Regularizing quantum loss landscapes by noise injection Low Rank Density Matrix Evolution for Noisy Quantum Circuits

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.545663Z

Source-reported events for the cited work

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Observation 48f18265-3f61-4041-9459-b91d95c9dfe6 · outbound

This paper cites Classical simulations of noisy variational quantum circuits.

Regularizing quantum loss landscapes by noise injection Classical simulations of noisy variational quantum circuits

Reference 34

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Observation aa37207c-015a-42be-925a-460a357cc09f · outbound

This paper cites Simulating quantum circuit expectation values by Clifford perturbation theory.

Regularizing quantum loss landscapes by noise injection Simulating quantum circuit expectation values by Clifford perturbation theory

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.124824Z

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Observation 025bc704-13a0-4f73-9c89-086169e1aec3 · outbound

This paper cites Non-zero noise extrapolation: accu- rately simulating noisy quantum circuits with tensor net- works.

Regularizing quantum loss landscapes by noise injection Non-zero noise extrapolation: accu- rately simulating noisy quantum circuits with tensor net- works

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.120168Z

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Observation 51e98065-8b51-448b-8055-6594fad7cb7c · outbound

This paper cites Bagaev (2024).

Regularizing quantum loss landscapes by noise injection Bagaev (2024)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.139936Z

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Observation d12a91ee-6757-47fb-a981-9ba1ccc7ea3a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Regularizing quantum loss landscapes by noise injection Adam: A Method for Stochastic Optimization

Reference 38

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Observation f91aeefb-4948-4f5b-9463-8fe22da220a9 · outbound

This paper cites ORQVIZ: Visualizing High-Dimensional Landscapes in Variational Quantum Algorithms.

Regularizing quantum loss landscapes by noise injection ORQVIZ: Visualizing High-Dimensional Landscapes in Variational Quantum Algorithms

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.144271Z

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Observation 58e80867-a5eb-4b38-a0f2-c4ae18a01da6 · outbound

This paper cites A Quantum Approximate Optimization Algorithm.

Regularizing quantum loss landscapes by noise injection A Quantum Approximate Optimization Algorithm

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.138915Z

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Observation 6108639e-c910-430e-8298-9dac1eaa59db · outbound

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Regularizing quantum loss landscapes by noise injection Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:56:02.247835Z

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Observation 8dcdbeec-55aa-4386-bd98-1ed6f57ee902 · outbound

This paper cites Connecting the Hamiltonian structure to the QAOA energy and Fourier landscape structure.

Regularizing quantum loss landscapes by noise injection Connecting the Hamiltonian structure to the QAOA energy and Fourier landscape structure

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.149227Z

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Observation 76b7f2ea-9f2c-4eea-a30c-1d3c94db2f7f · outbound

This paper cites Quan- tum convolutional neural networks.

Regularizing quantum loss landscapes by noise injection Quan- tum convolutional neural networks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.124878Z

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Observation 6febed54-8bfa-4d5e-9284-7c4fd4ff3d93 · outbound

This paper cites Quantum Convolutional Neural Networks are Effectively Classically Simulable.

Regularizing quantum loss landscapes by noise injection Quantum Convolutional Neural Networks are Effectively Classically Simulable

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.158818Z

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Observation 4e7d6974-9b32-4384-ab7b-6545ac203b2f · outbound

This paper cites Kiani (2024).

Regularizing quantum loss landscapes by noise injection Kiani (2024)

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:56:02.109610Z

Source-reported events for the cited work

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Observation 87005f5f-4305-4970-bcb4-00e5fdefe24e · outbound

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

Regularizing quantum loss landscapes by noise injection Quantum Computing in the NISQ era and beyond

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.168227Z

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Observation 391057f9-1447-468d-98cb-8ae814d4742a · outbound

This paper cites Quantum computing at the quantum advantage threshold: a down-to-business review.

Regularizing quantum loss landscapes by noise injection Quantum computing at the quantum advantage threshold: a down-to-business review

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.173053Z

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Observation 612528cf-07de-468c-a355-e5ff5221027b · outbound

This paper cites Mitigating Quantum Gate Errors for Variational Eigensolvers Using Hardware-Inspired Zero-Noise Extrapolation.

Regularizing quantum loss landscapes by noise injection Mitigating Quantum Gate Errors for Variational Eigensolvers Using Hardware-Inspired Zero-Noise Extrapolation

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.273801Z

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Observation edfb7db0-2401-42a4-8a3f-3d4f13a118b0 · outbound

This paper cites Noise-Mitigated Variational Quantum Eigensolver with Pre-training and Zero-Noise Extrapolation.

Regularizing quantum loss landscapes by noise injection Noise-Mitigated Variational Quantum Eigensolver with Pre-training and Zero-Noise Extrapolation

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:56:01.250350Z

Source-reported events for the cited work

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Observation 13a35d66-cc1f-4a19-86e8-54f1090efe4a · outbound

This paper cites Myths around quantum computation before full fault tolerance: What no-go theorems rule out and what they don't.

Regularizing quantum loss landscapes by noise injection Myths around quantum computation before full fault tolerance: What no-go theorems rule out and what they don't

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T21:56:01.186959Z

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Pith citing papers

Observation ad06ad67-8d9b-4ca1-8206-aa23a2bb092e · inbound

QUBO-based training for VQAs on Quantum Annealers cites this paper.

QUBO-based training for VQAs on Quantum Annealers Regularizing quantum loss landscapes by noise injection

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T12:13:00.303758Z

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Observation 0edc2763-0bf0-4aa0-a748-f746fb1b0666 · inbound

Quantum Adversarial Machine Learning: From Classical Adaptations to Quantum-Native Methods cites this paper.

Quantum Adversarial Machine Learning: From Classical Adaptations to Quantum-Native Methods Regularizing quantum loss landscapes by noise injection

Reference 139

Resolution: verified exact; arxiv_id, observed 2026-06-09T02:06:03.288011Z

Source-reported events for the cited work

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