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Paper Citation Record · LEDGER

Combining Machine Learning with Recurrence Analysis for resonance detection

As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2412.19683.

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

pith.paper-citation-record.v1
2412.19683 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:06:48.633994Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T00:06:49.310326Z

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation 23516bc7-04ea-42f2-bce1-b8a14feef7db · outbound

This paper cites With d degrees of freedom, it consists of • generalized coordinates qi, i= 1,.

Combining Machine Learning with Recurrence Analysis for resonance detection With d degrees of freedom, it consists of • generalized coordinates qi, i= 1,

Reference 1

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Observation a77a7786-3268-49cf-960c-421cc13c2f94 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 2

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Observation 6c287c97-b495-464e-96fa-e07c79c0714c · outbound

This paper cites The initial conditions are taken along the pr = 0 line on the Poincar´ e section in r ∈ [6.36M, 6.43M ] spaced at 0.001M.

Combining Machine Learning with Recurrence Analysis for resonance detection The initial conditions are taken along the pr = 0 line on the Poincar´ e section in r ∈ [6.36M, 6.43M ] spaced at 0.001M

Reference 3

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Observation 680daf1b-bc03-4aa6-844d-3a84812545b7 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 4

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Observation 220d4147-d0bd-4691-b607-4c7b8b9de37e · outbound

This paper cites Knowledge of their locations will allow us to properly model the qual- itatively distinct behavior of the passage through these resonances.

Combining Machine Learning with Recurrence Analysis for resonance detection Knowledge of their locations will allow us to properly model the qual- itatively distinct behavior of the passage through these resonances

Reference 5

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Observation 0998d4da-60a7-463b-8fa9-fbf11a7102b6 · outbound

This paper cites Lukes-Gerakopoulos and V.

Combining Machine Learning with Recurrence Analysis for resonance detection Lukes-Gerakopoulos and V

Reference 6

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Observation d4f33661-94c4-4e4c-8776-5546535e12b4 · outbound

This paper cites However, already in a system with 3 degrees of freedom, the Poincar´ e section becomes 4-dimensional and these simple methods are no longer applicable.

Combining Machine Learning with Recurrence Analysis for resonance detection However, already in a system with 3 degrees of freedom, the Poincar´ e section becomes 4-dimensional and these simple methods are no longer applicable

Reference 7

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Observation b12b2139-a049-410a-9745-cbb0828e788f · outbound

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Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 8

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Observation d0efcb1f-3d96-4d11-ae96-38ca0f59e6b0 · outbound

This paper cites Combining Machine Learning with Recurrence Analysis for resonance detection.

Combining Machine Learning with Recurrence Analysis for resonance detection Combining Machine Learning with Recurrence Analysis for resonance detection

Reference 9

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Observation d795aa53-218a-429d-9d18-d9204ef2591d · outbound

This paper cites 8 shows the result of the basic network applied to the Poincar´ e section of a test particle following a geodesic in the Johannsen-Psaltis spacetime metric (see Sec.

Combining Machine Learning with Recurrence Analysis for resonance detection 8 shows the result of the basic network applied to the Poincar´ e section of a test particle following a geodesic in the Johannsen-Psaltis spacetime metric (see Sec

Reference 10

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Observation ad2fd049-1119-4699-92ef-65a0b995ffe1 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 11

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Observation d39a44cd-57ec-4ad7-bf89-6dd3dab1134b · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 12

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Observation decf37f2-6388-40cb-be96-2de7bf7322c2 · outbound

This paper cites Resonance crossing of a charged body in a magnetized Kerr background: an analogue of extreme mass ratio inspiral.

Combining Machine Learning with Recurrence Analysis for resonance detection Resonance crossing of a charged body in a magnetized Kerr background: an analogue of extreme mass ratio inspiral

Reference 13

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Observation 6f4e2f6e-ede2-41c9-bf87-42f1dfab5c9d · outbound

This paper cites Zelenka, G.

Combining Machine Learning with Recurrence Analysis for resonance detection Zelenka, G

Reference 14

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Observation 809cee2f-7aaf-4f26-915a-d156fda642c6 · outbound

This paper cites Relativistic Dynamics and Extreme Mass Ratio Inspirals.

Combining Machine Learning with Recurrence Analysis for resonance detection Relativistic Dynamics and Extreme Mass Ratio Inspirals

Reference 15

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Observation cfd7729f-694f-441d-ae04-73a8e7858e10 · outbound

This paper cites Astrophysics with the Laser Interferometer Space Antenna.

Combining Machine Learning with Recurrence Analysis for resonance detection Astrophysics with the Laser Interferometer Space Antenna

Reference 16

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Observation 86bc5ecb-00cc-4be9-aebc-839537de981b · outbound

This paper cites Free motion around black holes with discs or rings: between integrability and chaos - III.

Combining Machine Learning with Recurrence Analysis for resonance detection Free motion around black holes with discs or rings: between integrability and chaos - III

Reference 17

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Observation 6b567a60-4016-4c7d-8748-1a1d87087bec · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 18

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Observation 8e7484ec-faf2-4e01-a0f6-8605ba0eb179 · outbound

This paper cites Marwan, M.

Combining Machine Learning with Recurrence Analysis for resonance detection Marwan, M

Reference 19

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Observation b47427bb-4db9-4724-8ee3-b8af0225cf83 · outbound

This paper cites A Metric for Rapidly Spinning Black Holes Suitable for Strong-Field Tests of the No-Hair Theorem.

Combining Machine Learning with Recurrence Analysis for resonance detection A Metric for Rapidly Spinning Black Holes Suitable for Strong-Field Tests of the No-Hair Theorem

Reference 20

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Observation a8241158-7f91-4d3d-a6de-fbb42129513d · outbound

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Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 21

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Observation 6240a8fd-9101-4ed3-8a5b-431a9dbdad67 · outbound

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Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 22

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Observation 8114042d-1ee5-49a4-b679-6dce0a64897c · outbound

This paper cites Moser, Nachrichten der Akademie der Wissenschaften in G¨ ottingen.

Combining Machine Learning with Recurrence Analysis for resonance detection Moser, Nachrichten der Akademie der Wissenschaften in G¨ ottingen

Reference 23

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Observation fb235b0c-8372-4c8a-9b43-0f06bd14a686 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 24

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Observation bf78dab6-0aaf-40a0-91fb-5c8a01de0ce0 · outbound

This paper cites How to avoid potential pitfalls in recurrence plot based data analysis.

Combining Machine Learning with Recurrence Analysis for resonance detection How to avoid potential pitfalls in recurrence plot based data analysis

Reference 25

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Observation 7a5328c8-c637-4fdf-82ca-304014d156e1 · outbound

This paper cites Recurrence Analysis as a tool to study chaotic dynamics of extreme mass ratio inspiral in signal with noise.

Combining Machine Learning with Recurrence Analysis for resonance detection Recurrence Analysis as a tool to study chaotic dynamics of extreme mass ratio inspiral in signal with noise

Reference 26

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Observation b2bb4344-5eea-4c34-ad02-0a69d502e482 · outbound

This paper cites Transition from Regular to Chaotic Circulation in Magnetized Coronae near Compact Objects.

Combining Machine Learning with Recurrence Analysis for resonance detection Transition from Regular to Chaotic Circulation in Magnetized Coronae near Compact Objects

Reference 27

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Observation 6afd78a7-57a5-4f9c-92f0-ae6936c4c5c7 · outbound

This paper cites Takens, in Dynamical Systems and Turbulence, War- wick 1980, edited by D.

Combining Machine Learning with Recurrence Analysis for resonance detection Takens, in Dynamical Systems and Turbulence, War- wick 1980, edited by D

Reference 28

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Observation 395d7628-b97d-409d-8752-bfae383b2a58 · outbound

This paper cites Hochreiter and J.

Combining Machine Learning with Recurrence Analysis for resonance detection Hochreiter and J

Reference 29

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Observation db475c41-8197-4523-a69c-80a0e2aa4b1b · outbound

This paper cites Long Short-Term Memory for Early Warning Detection of Gravitational Waves.

Combining Machine Learning with Recurrence Analysis for resonance detection Long Short-Term Memory for Early Warning Detection of Gravitational Waves

Reference 30

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 08864628-220f-474d-8995-fcdd925b02c1 · outbound

This paper cites an unresolved cited work.

Combining Machine Learning with Recurrence Analysis for resonance detection Unresolved cited work

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 79cc8923-4dd8-4ca0-90cc-9ab5b623d66a · outbound

This paper cites Morbidelli, Modern celestial mechanics: aspects of solar system dynamics , 1st ed.

Combining Machine Learning with Recurrence Analysis for resonance detection Morbidelli, Modern celestial mechanics: aspects of solar system dynamics , 1st ed

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a758e7f0-0ffa-403a-be39-939dcb2f6d25 · outbound

This paper cites Reichl, The Transition to Chaos: Conservative Clas- sical Systems and Quantum Manifestations , Institute for Nonlinear Science (Springer, 2004).

Combining Machine Learning with Recurrence Analysis for resonance detection Reichl, The Transition to Chaos: Conservative Clas- sical Systems and Quantum Manifestations , Institute for Nonlinear Science (Springer, 2004)

Reference 33

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 22b39090-8601-4bd9-bcfe-0e06e1e5776e · outbound

This paper cites Chaotic motion in the Johannsen-Psaltis spacetime.

Combining Machine Learning with Recurrence Analysis for resonance detection Chaotic motion in the Johannsen-Psaltis spacetime

Reference 34

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verified exact
local_arxiv, observed 2026-08-11T00:06:48.910738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 345f318f-222c-41ac-94c0-4a9a9d687893 · outbound

This paper cites Lukes-Gerakopoulos, N.

Combining Machine Learning with Recurrence Analysis for resonance detection Lukes-Gerakopoulos, N

Reference 35

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a5587e73-d196-475d-8280-b525d9a6eb11 · outbound

This paper cites Froeschl´ e, M.

Combining Machine Learning with Recurrence Analysis for resonance detection Froeschl´ e, M

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.395518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.820234Z digest=sha256:6c341e33c4fc99cc1e31eaea7a14298e056740ed84d87931684e9cac26ad4e31

Observation b222eadb-1480-4ece-9c5c-8db596fe775c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Combining Machine Learning with Recurrence Analysis for resonance detection Adam: A Method for Stochastic Optimization

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T00:06:48.825399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:06:48.825399Z digest=sha256:3cf5b326df840cc2514974f6c331e9d584d608d85fc991a0b4ff5f1eff0fb25c

Observation 47b87d5c-644b-4ba7-a0e0-0003bad91c1c · outbound

This paper cites Sukov´ a, M.

Combining Machine Learning with Recurrence Analysis for resonance detection Sukov´ a, M

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.378657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.830380Z digest=sha256:5e4d2f77c5a8e9bb356d3e19fb6d9d929352dae2377d7fcb9c1152033cddf4ce

Observation 58b99189-6581-4172-ae08-cd48c23d0f25 · outbound

This paper cites Hegger, H.

Combining Machine Learning with Recurrence Analysis for resonance detection Hegger, H

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.363206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.835227Z digest=sha256:28cf8d9137bec8e1dced3af965314cd1cf5f9cf14b00600203702fccb503aea9

Observation 59880a56-da3a-4ced-85a1-98bd4b4bba16 · outbound

This paper cites Marwan, Commandline recurrence plots (2006), https://tocsy.pik-potsdam.de/commandline-rp.

Combining Machine Learning with Recurrence Analysis for resonance detection Marwan, Commandline recurrence plots (2006), https://tocsy.pik-potsdam.de/commandline-rp

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.347559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.840011Z digest=sha256:6662b50dff54ae4e5f1e838f0602aecba099ba63eb87ce108825ca39b8ace1b3

Observation ac0d24bf-97b3-4ebe-8684-6a0a85b45163 · outbound

This paper cites Marwan, Recurrence plots and cross recurrence plots (2024), http://www.recurrence-plot.tk.

Combining Machine Learning with Recurrence Analysis for resonance detection Marwan, Recurrence plots and cross recurrence plots (2024), http://www.recurrence-plot.tk

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:06:49.332112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.844673Z digest=sha256:230295984c3a29d120675d3bd0d8847d253798221495eb6cca5b39fdb0292077

Pith citing papers

Observation d0efcb1f-3d96-4d11-ae96-38ca0f59e6b0 · inbound

Combining Machine Learning with Recurrence Analysis for resonance detection cites this paper.

Combining Machine Learning with Recurrence Analysis for resonance detection Combining Machine Learning with Recurrence Analysis for resonance detection

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:06:49.315940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:06:48.633994Z digest=sha256:78cc04bd93ad2391b6ac404b46ad917c79a2370f209f8d7829242d4a21b04532