Paper Citation Record · LEDGER

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 4 inbound Pith citation observations for arXiv:2412.00826.

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

pith.paper-citation-record.v1
2412.00826 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: arxiv_reference, observed 2026-07-03T06:27:41.714632Z

Reference resolution

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External citation measurements

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Outbound references

Observation 2745d1a2-149d-4400-b425-bce716159694 · outbound

This paper cites an unresolved cited work.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

Reference 1

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This paper cites an unresolved cited work.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

Reference 2

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Observation 0add3258-9147-4e1c-a692-58b7af9a2911 · outbound

This paper cites Constructing Exact Confidence Regions on Parameter Manifolds of Non-Linear Models.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Constructing Exact Confidence Regions on Parameter Manifolds of Non-Linear Models

Reference 3

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Observation 8939aee2-8af5-4b78-ad9b-aedad47f3a29 · outbound

This paper cites 2023, Phys.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2023, Phys

Reference 4

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Observation 597e1a5e-a815-4ab4-838d-0a36553a8a16 · outbound

This paper cites & Reichardt, C.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation & Reichardt, C

Reference 5

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Observation 9a63a951-258d-4349-90f8-947b4d88925d · outbound

This paper cites 2018, JAX: composable transformations of Python+NumPy programs.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2018, JAX: composable transformations of Python+NumPy programs

Reference 6

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Observation 83f7336d-4604-45b1-8178-9468d28f219a · outbound

This paper cites A., Battaglia, N., et al.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation A., Battaglia, N., et al

Reference 7

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This paper cites 2023, The Open Journal of Astrophysics, 6, 15.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2023, The Open Journal of Astrophysics, 6, 15

Reference 8

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Observation ef26ce92-949e-4920-8206-04432022a72e · outbound

This paper cites E., Ade, P.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation E., Ade, P

Reference 9

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Observation df2f6d40-47f4-4d61-b39f-0b6f4e1809ae · outbound

This paper cites CMB-S4 Science Case, Reference Design, and Project Plan.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation CMB-S4 Science Case, Reference Design, and Project Plan

Reference 10

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Observation 67de03bb-bf94-4e98-9e9f-a299b2d9e5e9 · outbound

This paper cites & Schneider, M.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation & Schneider, M

Reference 11

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

Reference 12

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

Reference 13

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Observation 9bb295b9-542a-48e0-9d50-6540c078d44e · outbound

This paper cites Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data

Reference 14

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Observation e889938c-c897-41c5-b0b4-d879acda3189 · outbound

This paper cites 2007, A&A, 464, 399.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2007, A&A, 464, 399

Reference 15

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This paper cites F., Seikel, M., Nord, B.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation F., Seikel, M., Nord, B

Reference 16

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Observation b7d52297-8649-41ec-85f2-5b49b07f34ab · outbound

This paper cites W., Sayre, J.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation W., Sayre, J

Reference 17

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Observation 02f27480-91dc-4c03-871d-e7f3c28c0586 · outbound

This paper cites The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo

Reference 18

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

Reference 19

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Observation 9cc2b37d-f6d7-445e-a843-48e25cac76f8 · outbound

This paper cites 2014, Phys.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2014, Phys

Reference 20

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This paper cites 2001, SciPy: Open source scientific tools for Python, [Online; accessed 2014-10-22].

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2001, SciPy: Open source scientific tools for Python, [Online; accessed 2014-10-22]

Reference 21

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Observation 826290d3-6606-4f6b-ad4d-b2d620d6972a · outbound

This paper cites G., Ade, P.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation G., Ade, P

Reference 22

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Observation f54342ec-1ece-4f64-b2ed-08d2f31307b0 · outbound

This paper cites The Cosmic Microwave Background and its Polarization,.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation The Cosmic Microwave Background and its Polarization,

Reference 23

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Observation 944e2051-67f6-49a5-8312-ba63624d30b0 · outbound

This paper cites 2000, ApJ, 538, 473.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2000, ApJ, 538, 473

Reference 24

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This paper cites S., Qu, F.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation S., Qu, F

Reference 25

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This paper cites 2014, Phys.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2014, Phys

Reference 26

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This paper cites M., Crawford, T.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation M., Crawford, T

Reference 27

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation & Wright, S

Reference 29

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation Unresolved cited work

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This paper cites J., Friedrich, O., Sellentin, E., & Heavens, A.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation J., Friedrich, O., Sellentin, E., & Heavens, A

Reference 31

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation & Spurio Mancini, A

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This paper cites A foreground-marginalized 'BK-lite' likelihood for the tensor-to-scalar ratio.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation A foreground-marginalized 'BK-lite' likelihood for the tensor-to-scalar ratio

Reference 33

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation J., Sherwin, B

Reference 34

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This paper cites 2014, MNRAS, 441, 1831 Simons Observatory Collaboration, Ade, P., Aguirre, J., et al.

Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation 2014, MNRAS, 441, 1831 Simons Observatory Collaboration, Ade, P., Aguirre, J., et al

Reference 35

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation W., Amiri, M., et al

Reference 36

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation & Lewis, A

Reference 37

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Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation E., et al

Reference 38

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Pith citing papers

Observation d4dceadc-2c6a-4497-85c9-a32396513613 · inbound

The Status of Gravitational Vector Perturbations with Recent CMB Data cites this paper.

The Status of Gravitational Vector Perturbations with Recent CMB Data Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation

Reference 44

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Observation 3940ea48-54f8-40e5-8f2f-dc6392958931 · inbound

Effective Bayesian ranking of low order monomial potentials in low temperature warm inflation cites this paper.

Effective Bayesian ranking of low order monomial potentials in low temperature warm inflation Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation

Reference 51

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Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization cites this paper.

Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation

Reference 135

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Observation 9defdac9-5063-468d-b477-28763e70a439 · inbound

Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization cites this paper.

Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization Compressed 'CMB-lite' Likelihoods Using Automatic Differentiation

Reference 135

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