Pith. sign in

Paper Citation Record · LEDGER

A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1903.09204.

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

pith.paper-citation-record.v1
1903.09204 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:57:54.309215Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:46:32.063617Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2f48b608-e586-4756-8c42-0b38dc57c72c · inbound

AthenaK simulations of the binary black hole merger GW150914 cites this paper.

AthenaK simulations of the binary black hole merger GW150914 A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T05:57:54.309215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:57:54.309215Z digest=sha256:776f235f66c5ccacebafed806ed19e999ff2b93a58520b187d16d44a23fe6954

Observation af57ccaa-3ad0-48f3-ba7a-fc1eca069902 · inbound

Chase Orbits, not Time: A Scalable Paradigm for Long-Duration Eccentric Gravitational-Wave Surrogates cites this paper.

Chase Orbits, not Time: A Scalable Paradigm for Long-Duration Eccentric Gravitational-Wave Surrogates A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-04T13:34:57.560308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:34:57.560308Z digest=sha256:d192279edb49dc08730e526ff2733e29b8bcfd66dfd11f36afabe9f7d824a3f7

Observation 96cd0512-2975-4b05-92f7-47b6bf4c09e4 · inbound

Advancing the Effective-One-Body Framework in the Test-Mass Limit cites this paper.

Advancing the Effective-One-Body Framework in the Test-Mass Limit A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-15T14:26:35.666160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T14:26:35.666160Z digest=sha256:3a697aaa56d4e40168ac56835bd36edf70f9776bc007e9bf852182078376866d

Observation 13dcb86d-6cc3-4dbe-813e-6f5f84ac5b56 · inbound

Fast neural network surrogate for multimodal effective-one-body gravitational waveforms from generically precessing compact binaries cites this paper.

Fast neural network surrogate for multimodal effective-one-body gravitational waveforms from generically precessing compact binaries A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:46:32.079354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T12:36:17.507439Z digest=sha256:5240f41254ef26810d55825835912a42fba2d1a86a15b18e9a4e95460042e4cf

Observation 6e1013a6-5436-44ab-bd49-f35ce9d32fa1 · inbound

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms cites this paper.

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach

Reference 101

Resolution
unresolved
no resolver link, observed 2026-07-31T04:58:16.982169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T04:58:16.982169Z digest=sha256:6d88f9ca96c8fd21a849c643be3860b30ba36e6dc754a8c7463e7ec023009f25