Paper Citation Record · LEDGER

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference

As of 14 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 2 inbound Pith citation observations for arXiv:2601.02336.

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

pith.paper-citation-record.v1
2601.02336 v2

Coverage vector

measured 54 of 54 reference resolution

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One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T12:51:48.815349Z

measured 1 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

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Outbound references

Observation 5af84d7c-8b58-42a3-a3a9-4200d3b3ec44 · outbound

This paper cites Advanced LIGO.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Advanced LIGO

Reference 1

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Observation ae6a293b-e71f-4525-96a6-47af5d8701c0 · outbound

This paper cites Advanced Virgo: a 2nd generation interferometric gravitational wave detector.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Advanced Virgo: a 2nd generation interferometric gravitational wave detector

Reference 2

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Unresolved cited work

Reference 3

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Observation a0fc31b5-c5ba-4738-a027-bcb8b94d7111 · outbound

This paper cites An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models

Reference 4

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Observation e29f6cc4-b01c-49c9-855e-e3ca40e23fb4 · outbound

This paper cites GWTC-4.0: Population Properties of Merging Compact Binaries.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference GWTC-4.0: Population Properties of Merging Compact Binaries

Reference 5

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This paper cites GWTC-4.0: Constraints on the Cosmic Expansion Rate and Modified Gravitational-wave Propagation.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference GWTC-4.0: Constraints on the Cosmic Expansion Rate and Modified Gravitational-wave Propagation

Reference 6

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Observation 09757ccd-20cf-4d5a-8847-f8fc6cb028f8 · outbound

This paper cites Tests of General Relativity with GWTC-3.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Tests of General Relativity with GWTC-3

Reference 7

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Observation 1762e37e-2252-414a-93d0-4acb41225a6e · outbound

This paper cites Skilling, J.: Nested sampling for gen- eral Bayesian computation.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Skilling, J.: Nested sampling for gen- eral Bayesian computation

Reference 8

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Nested sampling for physical scientists

Reference 9

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This paper cites GWTC-4.0: Methods for Identifying and Characterizing Gravitational-wave Transients.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference GWTC-4.0: Methods for Identifying and Characterizing Gravitational-wave Transients

Reference 10

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This paper cites & Jasra, A.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference & Jasra, A

Reference 11

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This paper cites A., Nabergoj, D.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference A., Nabergoj, D

Reference 12

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This paper cites J., Karamanis, M., Luo, Y.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference J., Karamanis, M., Luo, Y

Reference 13

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This paper cites Accelerated Sequential Posterior Inference via Reuse for Gravitational-Wave Analyses.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Accelerated Sequential Posterior Inference via Reuse for Gravitational-Wave Analyses

Reference 14

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference F., Drovandi, C

Reference 15

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Observation 1aeffe2f-8abe-46e7-a067-735fdfaec6c9 · outbound

This paper cites inHandbook of Markov Chain Monte Carlo113–162 (2011).

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference inHandbook of Markov Chain Monte Carlo113–162 (2011)

Reference 16

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This paper cites Robust parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Robust parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library

Reference 18

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This paper cites Rapid and accurate parameter inference for coalescing, precessing compact binaries.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Rapid and accurate parameter inference for coalescing, precessing compact binaries

Reference 20

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference S., Tono- lini, F

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This paper cites Learning Bayesian posteriors with neural networks for gravitational-wave inference.

The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Learning Bayesian posteriors with neural networks for gravitational-wave inference

Reference 24

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Fast gravitational wave parameter estimation without compromises

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Rapid Parameter Estimation of Gravitational Waves from Binary Neutron Star Coalescence using Focused Reduced Order Quadrature

Reference 27

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Accelerating parameter estimation of gravitational waves from compact binary coalescence using adaptive frequency resolutions

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference arXiv:2312

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Nested Sampling with Normalising Flows for Gravitational-Wave Inference

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo

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The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference Bayesian inference for compact binary coalescences with BILBY: Validation and application to the first LIGO--Virgo gravitational-wave transient catalogue

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Reliable model selection in the presence of parameter non-identifiability cites this paper.

Reliable model selection in the presence of parameter non-identifiability The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference

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Ab Initio Real-Time Gravitational-Wave Parameter Estimation cites this paper.

Ab Initio Real-Time Gravitational-Wave Parameter Estimation The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference

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