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Paper Citation Record · LEDGER

Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1907.07787.

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

pith.paper-citation-record.v1
1907.07787 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:47:27.717827Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-12T01:18:31.230899Z

Reference resolution

0 of 0 outbound references displayed

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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 503281e5-2428-4133-b38b-d77f405fda73 · inbound

Cosmological parameter estimation from large-scale structure deep learning cites this paper.

Cosmological parameter estimation from large-scale structure deep learning Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-14T10:47:27.717827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:47:27.717827Z digest=sha256:9b1622cd67342f70a405616207e8f19e90bd2933e7f9e79d0fd5bcf77c4b2b07

Observation 40b0943b-0cda-4a21-87f5-8bcc8cc424b2 · inbound

Deep Needlet: A CNN based full sky component separation method in Needlet space cites this paper.

Deep Needlet: A CNN based full sky component separation method in Needlet space Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T20:48:07.234756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:48:07.234756Z digest=sha256:49cfc3755780c972ce8472820b6a2634aae9d627ca0698bc9be87abb7a6ff658

Observation b9bf8579-b0fe-4c05-9076-a1b89672345e · inbound

An Alcock-Paczynski Test on Reionization Bubbles for Cosmology cites this paper.

An Alcock-Paczynski Test on Reionization Bubbles for Cosmology Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-09T11:42:48.575878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5053f7d2-9e71-4d5b-a4e5-56bc7ee60509 · inbound

CosmoUiT: A Vision Transformer-UNet Hybrid for Fast and Accurate Emulation of 21-cm Maps from the Epoch of Reionization cites this paper.

CosmoUiT: A Vision Transformer-UNet Hybrid for Fast and Accurate Emulation of 21-cm Maps from the Epoch of Reionization Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-04T13:15:32.174463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:15:32.174463Z digest=sha256:03eca8be17526708eb54f5844d7ea1f2f5094a8616a739542d386a52d9f8335a

Observation 290e20d3-5f09-4d63-ba27-04761990eeee · inbound

Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization cites this paper.

Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

Reference 183

Resolution
verified exact
local_arxiv, observed 2026-07-12T01:18:31.234538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-07-12T01:14:24.457057Z digest=sha256:8b6b7259321351768eeddb032eddb2d4c9a1761ad5e817d6f00e98f0027a40d6

Observation 65d1294c-bd05-4c91-b3a8-3fed3e8baba5 · inbound

The Rise and Fall of Acoustic Oscillations at Cosmic Dawn cites this paper.

The Rise and Fall of Acoustic Oscillations at Cosmic Dawn Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-14T15:06:13.177523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:06:13.177523Z digest=sha256:fd672e9c3ade85ea09ebc0d4d38ab44309b8a282f2ef10da5251674a91e25046