Paper Citation Record · LEDGER

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

As of 11 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 5 inbound Pith citation observations for arXiv:2412.17675.

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

pith.paper-citation-record.v1
2412.17675 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:20:33.960952Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:08:52.971831Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T10:26:52.332045Z

Reference resolution

50 of 50 outbound references displayed

verified exact8
verified fuzzy5
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External citation measurements

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Outbound references

Observation 8df99cff-19a4-436a-9d73-23f10f6b861d · outbound

This paper cites Brein, Adaptive scanning—a proposal how to scan theoretical predictions over a multi-dimensional parameter space efficiently, Computer Physics Communications 170 (1) (2005) 42–48.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Brein, Adaptive scanning—a proposal how to scan theoretical predictions over a multi-dimensional parameter space efficiently, Computer Physics Communications 170 (1) (2005) 42–48

Reference 1

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 2

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Observation d008824a-3036-4add-8766-7ed221f6cb79 · outbound

This paper cites A comparison of Bayesian sampling algorithms for high-dimensional particle physics and cosmology applications.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology A comparison of Bayesian sampling algorithms for high-dimensional particle physics and cosmology applications

Reference 3

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Observation c333fe48-0397-4a8d-a802-298a1cc8bb5b · outbound

This paper cites A Conceptual Introduction to Markov Chain Monte Carlo Methods.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology A Conceptual Introduction to Markov Chain Monte Carlo Methods

Reference 4

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Observation 78b0a6f6-3c2a-4b67-bd13-476970ef196f · outbound

This paper cites A Living Review of Machine Learning for Particle Physics.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology A Living Review of Machine Learning for Particle Physics

Reference 5

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Observation f80b9261-239c-4b9d-be32-f6d44f6719f3 · outbound

This paper cites Baruah, S.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Baruah, S

Reference 6

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 7

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Observation 66165894-ad6f-4ea0-9505-4097a652bca7 · outbound

This paper cites Hammad, M.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Hammad, M

Reference 8

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Observation e0017cc4-6dee-45e0-9829-845fb3c7bb11 · outbound

This paper cites Fast multilabel classification of HEP constraints with deep learning.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Fast multilabel classification of HEP constraints with deep learning

Reference 9

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Observation b757f348-9109-4a06-9a37-af9c49d454bc · outbound

This paper cites Hollingsworth, M.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Hollingsworth, M

Reference 10

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Observation f0d4e806-2d18-4d10-90f1-f2fec36642db · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 11

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 12

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Observation d33eb9c8-8b92-4e2b-be1c-0bcb6abdeeb3 · outbound

This paper cites Abreu de Souza, M.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Abreu de Souza, M

Reference 13

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Observation eb53c993-3c6e-4463-96c4-beab3acd566f · outbound

This paper cites Combining Evolutionary Strategies and Novelty Detection to go Beyond the Alignment Limit of the $Z_3$ 3HDM.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Combining Evolutionary Strategies and Novelty Detection to go Beyond the Alignment Limit of the $Z_3$ 3HDM

Reference 14

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Observation 7b5ee832-d30e-4be6-b759-250b4da8fd34 · outbound

This paper cites Bal ´azs, M.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Bal ´azs, M

Reference 15

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Observation 35e639e5-990a-4a8f-bfc8-a7e2c00a92d1 · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 16

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Observation 16340996-1e04-47bf-abf1-d2eed64ebdc3 · outbound

This paper cites A tool box for implementing supersymmetric models.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology A tool box for implementing supersymmetric models

Reference 17

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Observation 70d34142-7a07-4b8f-a4b8-83ad56226e0b · outbound

This paper cites xBIT: an easy to use scanning tool with machine learning abilities.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology xBIT: an easy to use scanning tool with machine learning abilities

Reference 18

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Observation 82a3f777-592f-4fef-b77e-a9421dc66c0c · outbound

This paper cites EasyScan_HEP: a tool for connecting programs to scan the parameter space of physics models.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology EasyScan_HEP: a tool for connecting programs to scan the parameter space of physics models

Reference 19

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Observation 71aeeccc-4708-4150-b165-f0b4ffa75107 · outbound

This paper cites BSMArt: simple and fast parameter space scans.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology BSMArt: simple and fast parameter space scans

Reference 20

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Observation 64a06d6b-29bc-4429-9970-08c8e20f3963 · outbound

This paper cites Sarah.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Sarah

Reference 21

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Observation f89595de-985e-4b9e-845b-26ba23c881fc · outbound

This paper cites Staub, Sarah 4: A tool for (not only susy) model builders, Computer Physics Communications 185 (6) (2014) 1773–1790.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Staub, Sarah 4: A tool for (not only susy) model builders, Computer Physics Communications 185 (6) (2014) 1773–1790

Reference 22

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Observation deb81e10-4258-46ee-97df-3b6293a3c7be · outbound

This paper cites Garnett, Y.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Garnett, Y

Reference 23

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Observation 7a5fea1c-e315-4ee9-9fcf-57d4f8d21843 · outbound

This paper cites pandas development team, pandas-dev /pandas: Pandas (Feb.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology pandas development team, pandas-dev /pandas: Pandas (Feb

Reference 24

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Observation 601d010c-bbe0-40e9-b96d-5502315a5226 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 25

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Observation 941512b9-50b2-4e8f-80b7-f404bcd51808 · outbound

This paper cites Di-photon decay of a light Higgs state in the BLSSM.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Di-photon decay of a light Higgs state in the BLSSM

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T05:20:33.869362Z

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Observation dc62412d-2be2-4c8f-9aa4-aab4fc99b12f · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 27

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Observation 1989ed50-cc3c-4837-8a6d-3c3cfd4516ca · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 28

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Observation 90d9cd79-b172-44c9-a716-75fc5650cab9 · outbound

This paper cites Porod, F.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Porod, F

Reference 29

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Bechtle, O

Reference 30

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Bechtle, S

Reference 31

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Observation 3512cb43-edfe-47f6-9344-2dd52d25a52d · outbound

This paper cites The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T05:20:33.892326Z

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Observation ea5af10a-dbe4-4735-a310-1046e4c38296 · outbound

This paper cites Malkomes, B.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Malkomes, B

Reference 33

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Observation 42fdd66c-cc9e-4517-a669-26c2cf774d10 · outbound

This paper cites Metropolis, A.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Metropolis, A

Reference 34

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

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Observation d6d74bd9-3513-4890-b0bf-8568d6814c1f · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology SUSY Les Houches Accord 2

Reference 36

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology UFO 2.0 -- The Universal Feynman Output format

Reference 37

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Observation d1539f0c-7ca0-4bd0-bda6-efe2096af0fa · outbound

This paper cites rep., CERN, Geneva (2022).

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology rep., CERN, Geneva (2022)

Reference 38

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Observation e44633ec-556d-4047-9f79-74643c102e2a · outbound

This paper cites Search for the Standard Model Higgs Boson at LEP.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Search for the Standard Model Higgs Boson at LEP

Reference 39

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Observation a859548d-c86b-4277-9d4c-db9cff272096 · outbound

This paper cites Aad, et al., Observation of a new particle in the search for the standard model higgs boson with the atlas detector at the lhc, Physics Letters B 716 (1) (2012) 1–29.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Aad, et al., Observation of a new particle in the search for the standard model higgs boson with the atlas detector at the lhc, Physics Letters B 716 (1) (2012) 1–29

Reference 40

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This paper cites Chatrchyan, et al., Observation of a new boson at a mass of 125 gev with the cms experiment at the lhc, Physics Letters B 716 (1) (2012) 30–61.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Chatrchyan, et al., Observation of a new boson at a mass of 125 gev with the cms experiment at the lhc, Physics Letters B 716 (1) (2012) 30–61

Reference 41

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Observation fcf3f266-3fe1-487b-85ae-dace9312ec9e · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology HiggsTools: BSM scalar phenomenology with new versions of HiggsBounds and HiggsSignals

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T05:20:33.931429Z

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Observation 18efd3ea-d39e-405d-8a9d-347a05e781f9 · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology SUSY Les Houches Accord: Interfacing SUSY Spectrum Calculators, Decay Packages, and Event Generators

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T05:20:33.934935Z

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology PySLHA: a Pythonic interface to SUSY Les Houches Accord data

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:20:34.171064Z

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Observation 563808a3-7046-4525-84df-0bd854e8a17a · outbound

This paper cites Staub, xslha: An les houches accord reader for python and mathematica, Computer Physics Communications 241 (2019) 132–138.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Staub, xslha: An les houches accord reader for python and mathematica, Computer Physics Communications 241 (2019) 132–138

Reference 45

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Observation 43e01840-7ec2-4dca-8684-a4beb06aac30 · outbound

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Unresolved cited work

Reference 46

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hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Yadan, J

Reference 47

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This paper cites BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T05:20:33.953602Z

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Observation 2d3bffd9-0bf8-42da-b4e6-75fb70708351 · outbound

This paper cites Gardner, G.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Gardner, G

Reference 49

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Observation c06515bf-9a47-4461-8ff9-1be038be6b16 · outbound

This paper cites Akiba, S.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Akiba, S

Reference 50

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Pith citing papers

Observation 01386b67-d532-4f75-8d97-00008dbd23aa · inbound

DLScanner: A parameter space scanner package assisted by deep learning methods cites this paper.

DLScanner: A parameter space scanner package assisted by deep learning methods hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

Reference 19

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Observation 208eec65-d7c6-43f7-b02a-7712ad9bda3b · inbound

Normalizing Flow-Assisted Nested Sampling on Type-II Seesaw Model cites this paper.

Normalizing Flow-Assisted Nested Sampling on Type-II Seesaw Model hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

Reference 16

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Observation db9b25f1-6f64-46ef-a2fe-67a20d3dcead · inbound

Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics cites this paper.

Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

Reference 101

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:56:12.651114Z

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Observation bd837081-8e43-4286-a624-de375475740c · inbound

BSMArt 2: simpler and faster parameter space scans cites this paper.

BSMArt 2: simpler and faster parameter space scans hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-02T10:26:52.333542Z

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Observation 8d206889-c07b-430a-865e-808dfa036c2d · inbound

EasyScan_HEP 2: Agent-Ready Parameter Scans for High-Energy Physics cites this paper.

EasyScan_HEP 2: Agent-Ready Parameter Scans for High-Energy Physics hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:45:42.200671Z

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