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Paper Citation Record · LEDGER

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization

As of 12 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.08476.

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

pith.paper-citation-record.v1
2507.08476 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:22:13.873407Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation 2cedca79-4395-4cb6-b119-138f1257cd75 · outbound

This paper cites It is a 6D tracking prob- lem of 5000 particles over a FODO cell with space-charge effects[26].

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization It is a 6D tracking prob- lem of 5000 particles over a FODO cell with space-charge effects[26]

Reference 1

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Observation 1e4215c3-b083-4ada-9ccd-1ec86247da0d · outbound

This paper cites To slightly reduce the computational cost of each cell, we reduce the number of integration steps of a half slice from 20 to 5.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization To slightly reduce the computational cost of each cell, we reduce the number of integration steps of a half slice from 20 to 5

Reference 2

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Observation 89eab0a6-7c0f-402b-8b29-cfeceded1f34 · outbound

This paper cites 4: Ratio of execution times: FD over AD – GPU.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization 4: Ratio of execution times: FD over AD – GPU

Reference 3

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Observation 60662332-769e-4b24-b254-2b8ea5852753 · outbound

This paper cites an unresolved cited work.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 4

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Observation 28b8f10e-e46f-416c-92b7-e71a5f9dd531 · outbound

This paper cites Here, as in most computational machines, we consider a DAG of unary or binary operations, although the same could be done for any arity.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Here, as in most computational machines, we consider a DAG of unary or binary operations, although the same could be done for any arity

Reference 5

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Observation 19faeedd-743e-4f9c-a9c0-f0961b8d3d5a · outbound

This paper cites Iselin, The mad program, in Computing in Accelerator Design and Operation , edited by W.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Iselin, The mad program, in Computing in Accelerator Design and Operation , edited by W

Reference 6

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Observation 7cd4b5bc-e307-4066-93aa-543de79114f3 · outbound

This paper cites Ramjiawan, S.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Ramjiawan, S

Reference 7

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Observation 27d9952e-4545-43e9-9ab8-61e9de3878b5 · outbound

This paper cites Remta, F.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Remta, F

Reference 8

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Observation defc7e6d-d441-4d7f-8c28-4402fc6d7a23 · outbound

This paper cites an unresolved cited work.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 9

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Observation f4307176-513f-4a95-ae64-d92bc57bda17 · outbound

This paper cites Deniau et al., MethodicalAcceleratorDesign/MAD-X: 5.09.01 (2023).

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Deniau et al., MethodicalAcceleratorDesign/MAD-X: 5.09.01 (2023)

Reference 10

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Observation 92156243-1dcd-4008-b4b9-1157b5c19859 · outbound

This paper cites an unresolved cited work.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 11

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Observation e640b866-6dcf-4a53-9b7b-c7bd83ee0573 · outbound

This paper cites Xsuite: an integrated beam physics simulation framework.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Xsuite: an integrated beam physics simulation framework

Reference 12

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Observation f997e1ad-97d8-4ed8-b6c1-602aeb57ac86 · outbound

This paper cites Hansen, A.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Hansen, A

Reference 13

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Observation 787612c1-eabd-43b2-a485-6f6b8833d883 · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 14

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Observation c8f846f3-0584-4321-8be7-41b45a496908 · outbound

This paper cites Jameson, Aerodynamic design via control theory, Jour- nal of Scientific Computing 3, 233 (1988).

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Jameson, Aerodynamic design via control theory, Jour- nal of Scientific Computing 3, 233 (1988)

Reference 15

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Observation 130f8852-d2cb-4d40-8660-8264571635e7 · outbound

This paper cites Magri, Adjoint methods as design tools in thermoa- coustics, Applied Mechanics Reviews 71, 020801 (2019).

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Magri, Adjoint methods as design tools in thermoa- coustics, Applied Mechanics Reviews 71, 020801 (2019)

Reference 16

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Observation 78ce4610-33fa-4255-a3e4-bd57fd1eb0e8 · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 17

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Observation 21bd36c9-f88d-4025-9b78-4879264d54f8 · outbound

This paper cites Ansel, E.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Ansel, E

Reference 18

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Observation 8b8f83cc-fc90-4ad6-b36f-b61355fec1d5 · outbound

This paper cites Abadi, A.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Abadi, A

Reference 19

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Observation 3bb5cd20-de5e-4304-b2c2-c4d046989454 · outbound

This paper cites Bradbury, R.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Bradbury, R

Reference 20

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Observation b4d2dd7e-fe48-4cd6-b087-7c167b8ce8a7 · outbound

This paper cites Gonzalez-Aguilera, Y.-K.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Gonzalez-Aguilera, Y.-K

Reference 21

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Observation d48d9a98-f831-4bae-848e-1ffe5c4bbf4e · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Kaiser, C

Reference 22

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Observation 4e6741cb-c510-4741-b1ea-52c36e69667c · outbound

This paper cites JuTrack: a Julia package for auto-differentiable accelerator modeling and particle tracking.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization JuTrack: a Julia package for auto-differentiable accelerator modeling and particle tracking

Reference 23

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Observation 39a6dbfd-aaee-450f-8365-e9e8dfc4ae00 · outbound

This paper cites MAD-NG, a standalone multiplatform tool for linear and non-linear optics design and optimisation.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization MAD-NG, a standalone multiplatform tool for linear and non-linear optics design and optimisation

Reference 24

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Observation c787190f-717c-4c8e-b47d-bc1e9a73726e · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 25

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Observation faa9e8ff-baf3-4512-90a0-bc1f89e31090 · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 26

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization CD = 2CP

Reference 27

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Observation 99dc09dd-4d12-40c5-8317-74a8d7fde806 · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 28

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 29

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 30

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 31

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 32

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 33

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

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Observation c3f2c28e-0da3-493c-b74d-7fdd9f2bbc6a · outbound

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Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 35

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e5d34a2a-b3ac-447a-ad6e-735d4e4c04de · outbound

This paper cites 2a vs Fig.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization 2a vs Fig

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:22:14.058202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-06T18:22:13.854347Z digest=sha256:6c0f27568bf6327c9e297acc16a268d149eb5a6ebe71198634d5459a6b8bf4b3

Observation 67de5484-d6a3-4d9a-b537-65b39725b39b · outbound

This paper cites Kraft, Algorithm 733: Tomp–fortran modules for op- timal control calculations, ACM Transactions on Mathe- matical Software 20, 262–281 (1994).

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Kraft, Algorithm 733: Tomp–fortran modules for op- timal control calculations, ACM Transactions on Mathe- matical Software 20, 262–281 (1994)

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:22:14.041998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-06T18:22:13.859891Z digest=sha256:4a8e170a434b03b1983965d3c2c52c43e43620d6924b1cedea2925a54a6656b1

Observation 3346d009-4cb2-469d-8cfa-dc55a84ffc6f · outbound

This paper cites an unresolved cited work.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:22:14.022713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-06T18:22:13.864208Z digest=sha256:c492d6e313ea6af5f3d5739a28c1bf83692ab874a70bfc489e2175fa32fdd152

Observation fb5284b6-2584-4c07-8125-a68fed86992b · outbound

This paper cites an unresolved cited work.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:22:14.004215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-06T18:22:13.868734Z digest=sha256:d2b1efa3980799d89ca440f05285999a00e063cb0dba80fe0612dfe4c46c939b

Observation 29b6647b-baf5-4459-b22e-c5bbd071e56b · outbound

This paper cites Roussel, J.

Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization Roussel, J

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:22:13.987532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-06T18:22:13.873407Z digest=sha256:853434713a99f36917350aba12d3091e8f782138d531210247a6d296f2c733b6

Pith citing papers

No inbound Pith citation observations are available.