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ac7bee01-3cca-4b2a-b4d9-c4c402734f41 | virtual diagnostics, where learned surrogate models provide
information about the state of an accelerator that would oth-
erwise be difficult or even impossible to acquire using a
physicaldiagnosticasinourcase. Theprovidedinformation
cangiveusefuldataaboutexperimentsandhelpoperators
tune the accelerator. Previous work ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 0 |
7bd06d1d-734e-4b4d-9236-e5435ca09a7f | dimensionalLPSattheEuXFELfromRFsettingsandthe
CRISP spectrum. In consideration of the limited amount of
LPSmeasurementsavailable,wedecidedtobasethetraining
of such model on simulated data.
METHODS AND RESULTS
Dataset Generation
In order to effectively train a surrogate model, large scale
simulated data is required. For... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 0 |
392ae252-b782-45ff-827a-dbccafeeebdb | scenariointhefirstbunchcompressor. Thelasttwoparame-
ters,theL1andL2chirps,controlthecompressionstrengths
inthesecondandthirdchicanesections. Preliminarystudies
were conducted in the past [ 9,10], where the RF settings
where adjusted with relatively small variations based on
the nominal design. The aim of this project ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 0 |
a511dc1b-5e7b-4d8b-a456-c4a677a0c262 | Figure 1: Schematiclayoutof the EuXFEL.
Table 1: The RF Parameter Input Features and the Values
Ranges Used in Simulations for the Dataset Generation
Parameter (unit) lower upper
bound bound
Injector chirp ( 1/𝑚) -10 -7
Injector curvature ( 1/𝑚2) -100 +300
Injector cubic coefficient ( 1/𝑚3) 0 30000
L1 chirp ( 1/𝑚) ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 1 |
e25bece1-ba7e-4bea-984a-c7b6d0f2be8d | ular framework for beam dynamics simulations allowing for
particle tracking, optics functions calculations, matching of
Twissparametersinamagneticlatticebyoptimizingasetof
variables. The Ocelot model of physical processes includes
collectiveeffectsasspacecharge,coherentsynchrotronra-
diation, wakefields and more.
Figur... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 1 |
b06c4574-b871-4ff9-960b-7cf1dbfa4a6a | model that is trained on data from a start-to-end beam dy-
namicssimulationtocombinescalarandspectralinforma-
tion in order to infer either the current profile or the two-
dimensional LPS. To this end, we construct a model that
receives two inputs: a 5D vector of RF settings and a 240-D
THz formfactor sampled from 0.7 ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 1 |
76bec8fa-7e00-4feb-94e0-2149735e4567 | ahigh-resolution(300×300)imageofthephasespace. To
ensure physical units, the network includes a secondary out-
put head that predicts the energy and spatial scales (ranges)
of the distribution. The model is trained in a supervised
setup to minimise the difference between the reconstructed
andthegroundtruthLPSimages. Th... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 1 |
4ceda728-b569-4253-b883-2a78bc798077 | be partially attributed to the inductive bias of the chosen
convolutionalarchitecture. The network’slayersinherently
prioritizethereconstructionofcontinuous,low-frequency
features,whichare more stableduring the gradient descent
process. Also the loss function might be responsible for
smearing the intensity over a certa... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 1 |
81b4ce00-b8ef-45d6-80e2-aed324813f58 | Figure 3: Three examplesfrom the validationset comparing ground truth and reconstructed 2D LPS images.
Operational Applications
The developed model serves a dual-purpose for machine
operations. Asa virtualdiagnostic ,ittakesreal-timeread-
backsofRFsettingsandmeasuredCRISPspectratoprovide
operators with an instantaneous... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 2 |
aa5f5c7e-c09e-417a-8670-1115736070fe | machine.
CONCLUSIONS AND OUTLOOK
In this paper, we demonstrated the first steps toward a
machine-learning-based virtual diagnostic for the longitu-
dinal phase space at the European XFEL. By leveraging
the Ocelot simulation toolkit, we generated a comprehen-
sive dataset validated against experimental injector mea-
sur... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 2 |
e63021be-9b4b-451e-88ab-b93f6d4b3c02 | variational autoencoders to sharpen the reconstructed im-
ages and recover the slice details. The corrected model willthenbeintegratedintotheEuXFELcontrolsystemviaaded-
icated graphical user interface, enabling livecomparisons
between predicted and measured beam properties during
facility operation.
This work lays the ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6156.pdf | 2 |
6294da65-4143-4c3c-ac3e-1fe6ee744557 | Maxwell computational resources operated at DESY.
REFERENCES
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059536a5-d4c1-4f41-be5e-1cf0e072b4d9 | GLOBAL START-TO-END OPTIMIZATION WITH
BAYESIAN OPTIMIZATION∗
B. Veglia†, B. Beutner, S. Tomin, S. D. Walker
Deutsches Elektronen-Synchrotron DESY, Hamburg, Germany
Abstract
Controlling the beam longitudinal phase space (LPS) dis-
tributioniscrucialforadvancedfree-electronlaseroperation
modes. AttheEuropeanXFEL,thistask... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
6c3020ef-96ac-4220-8bcf-d1ce2bddddfb | measured longitudinal phase space profiles.
INTRODUCTION
Precisecontroloverthelongitudinalphasespace(LPS)
distribution of electron bunches is fundamental to the op-
eration of modern X-ray free-electron lasers (FELs). At
facilities such as the European XFEL (EuXFEL), advanced
operating modes—including the generation of... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
b69496c6-7d3c-46ef-bf76-064e9552f973 | efficiently, minimizing the number of expensive ”black-box”
evaluations required to reach an optimal solution. Recent
advancesinmachinelearningandglobaloptimizationoffera
pathforward. Bayesianoptimization(BO)[ 1,2]hasemerged
as a particularlyeffectivetool for accelerator physics [ 3,4],
characterized byitssample effici... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
49b10f5d-7257-4553-bcbe-db40a5c224d9 | ing first on the task of model calibration. We show that
byautomatingthetuningofRFparameterswithinstart-to-
endsimulations,theBOframeworkcanefficientlyreconcile
∗Worksupported bythe EuXFEL R&D program.
†bianca.veglia@desy.dephysicsmodelswithexperimentalmeasurements, ensuring
thatsimulation-basedpredictionsaccuratelyref... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
7dbd8698-5466-46e3-bbef-cd3c0cfa1cb7 | where the beam compression was varied by scanning the
Linac L1 chirp from -12.4 to −4.4m−1in 9 steps. The chirp
is defined as−𝑘𝑉sin𝜑
𝐸0+𝑉cos𝜑, where𝜑and𝑉are the voltageand
phase of Linac L1, 𝐸0= 130 MeV is the initial energy of
thebeambeforeL1, and 𝑘 = 2𝜋𝑓/𝑐 ,𝑓 =1.3GHz. Details
abouttheEuropeanXFELthreest... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
12ae7c83-6f1c-412b-957b-96e3b1b3a212 | Voltage in L1 ± 5 MeV
Phase in L1 ± 0.3 deg
Voltage in L2 ± 15 MeV
Phase in L2 ± 0.5 deg
WeimplementedaBOframeworktotuneOCELOTsimu-
lations[9–11]byidentifyingtheoptimalparametersrequired
to reproduce the observed beam characteristics. The opti-
mizationparametersincludedtheRFsettingsfortheinjector
andlinacsL1andL2. The... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
99ddbf0e-a823-4009-838a-6cd44e04a87c | Mean Square Error (RMSE) between the reference and sim-
ulated current profiles. To ensure a robust comparison, a
cross-correlation function aligns the two curves by identify-
ing the temporal shift that maximizes their overlap.17th International Particle Accelerator Conference, Deauville, France JACoW Publishing
ISBN:... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 0 |
ad2aefaa-2d6a-4cfe-b5d1-f695a7446a5d | Figure 1: Comparison of optimized simulations vs current profiles measured with the CRISP spectrometer. Each plot
corresponds to a different value of the chirp in L1.
Table1detailstheoptimizedRFparametersandtheirtun-
ing ranges, defined relative to the initial machine read-outs
at the time of the experiment: at the inj... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 1 |
58976db6-2a95-497c-a1bf-887780087c17 | showed similar agreement (and closely resemble the curves
shown in the plot corresponding to L1 chirp = -7.4). Minor
discrepanciescanbeattributedtothefactthatmeasurements
weretakenwiththelaserheaterdeactivated. Theresulting
microbunching instabilities are not currently modeled in the
OCELOT tracking simulations, leadin... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 1 |
a7ab0185-4e0a-4ff5-8b9c-6124f22c48f8 | hardX-rayself-seeding(HXRSS)[ 12]whicharehighlysen-
sitive to the electron beam’s longitudinal distribution [ 13].
Figure2shows the performance of the BO when optimiz-
ing for different reference profiles. We observed that theconvergenceoftheoptimizerishighlysensitivetotheinitial
parametersandthechoiceofhyperparameters... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 1 |
ad9b999f-1d26-4e27-8aa3-d7c72747c0cf | experimental CRISP measurements by identifying small
butsignificantoffsetsinRFparameters. Furthermore,the
frameworkprovedcapableof”reverse-engineering”machine
configurationstomatchspecific,user-definedlongitudinal
current profiles, including Gaussian, flat-top, and triangular
distributions.
Looking forward, we intend t... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 1 |
765ae748-2968-4350-ab35-9121417afd81 | discrepancies,newmeasurement campaigns areplanned in
whichthemicrobunchinginstability(MBI)willbefullysup-
pressed using the laser heater. This will facilitate a more
direct comparison with numerical models and provide a17th International Particle Accelerator Conference, Deauville, France JACoW Publishing
ISBN: 978-3-95... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 1 |
c770c0c8-b009-47d1-bc7a-8b7578e96e2d | (a) Gaussian
(b) Flat top
(c) Left triangle
(d) Right triangle
Figure2: Examplesofsimulationsoptimizedtofitreference
profiles.clearer understanding of the underlying longitudinal dynam-
ics.
ACKNOWLEDGEMENTS
The authors are thankful for the support through the
Maxwell computational resources operated at DESY.
REFERENCE... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 2 |
70a31558-fefa-46f9-89c3-03d3c98f8cc5 | [3]R. Roussel et al., “Bayesian Optimization Algorithms for
AcceleratorPhysics”, Phys.Rev.Accel.Beams ,vol.27,no.8,
p. 084801, 2024.
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[4]F.Jietal.,“Multi-objectiveBayesianactivelearningforMeV-
ultrafastelectrondiffraction”, NatureCommun. ,vol.15... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 2 |
4bbb2442-f1fd-4866-8673-00015e4f40f1 | Rev. Accel. Beams , vol. 22, no. 2, p. 024401, Feb. 2019.
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[7]S.Wesch,B.Schmidt,C.Behrens,H.Delsim-Hashemi,andP.
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for femtosecond electron bunch diagnostics by single-shot
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277232cd-d8ca-45ea-b02e-777a00710ec3 | [9]S. Tomin, I. Agapov, M. Dohlus, and I. Zagorodnov,
“OCELOT as a Framework for Beam Dynamics Simulations
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[10]I. Agapov, G. Geloni, S. Tomin, and I. Zagorodnov,
“OCELOT: A softw... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 2 |
2ecfba44-b69c-49a7-b7b3-739b5014fd8b | [11]I.Zagorodnov,S.Tomin,Y.Chen,andF.Brinker,“Experi-
mental validation of collective effects modeling at injector
section of X-ray free-electron laser”, Nucl. Instrum. Methods
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[12]S.Liuetal.,“Updatesonthehardx-ra... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 3 |
c7546eff-a50d-40df-a2fc-b3cc427113a0 | ISBN: 978-3-95450-252-3 ISSN: 2673-5350 doi: 10.18429/JACoW-IPAC2026-WEP6157
MC6.T33: Online Modelling and Software Tools 2899WEP: Poster session WEP6157
Content from this work may be used under the terms of the CC BY 4.0 licence (© 2026). Any distribution of this work must maintain attribution to the author(s), title ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6157.pdf | 3 |
265552ad-ca3b-42d8-a445-2a2ce5f9f4ef | TURNING LOGBOOK DATA INTO OPERATIONAL INSIGHT
WITH A NEW STATISTICS SERVICE AT GSI AND FAIR
H. Stemmler∗, A. Bloch-Späth, M. Stein, O. Geithner, S. Reimann
GSI Helmholtz Centre for Heavy Ion Research, Darmstadt, Germany
Abstract
Itiscommonpracticeduringacceleratoroperationtocon-
tinuouslydocumentallrelevantmachinestate... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
2f459d25-06e1-4dcf-8352-04d5e4404937 | search(FAIR)as its operations graduallycommence in the
upcoming beamtimes. This service is built as twolayers: a
backend layer using the Micronaut framework, which com-
municates with the database to retrieve logbook entries and
calculatestatistics,andafrontendlayerusingtheAngular
framework,whichhandlesuserrequestsandp... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
b9b7f4d2-279a-4515-9b13-cdb424ae3b48 | allteams,whichallowsforthemaintenanceofefficientcom-
municationbetweencomplex,interactingareassuchasbeam
diagnosticsandphysics,technicalinfrastructure,andcontrol
systems.
At GSI, shift crew operators use OLOG [ 2], an electronic
logbook tool developed in-house to continuously record
events that may influence beam deliv... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
2e3e01ef-df03-4c3b-a8b0-63c54c0946d4 | performanceassessmentatGSIhasrecentlybeenintroduced
in Ref. [3]. Resultsare presented in Ref.[ 4].
In addition, documentation becomes increasingly impor-
tantasfacilitiesexpand. Withthegradualdevelopmentof
the Facility for Antiproton and Ion Research (FAIR) [ 5], the
complexity and scale of accelerator operations will ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
7c0abbce-0c43-456a-b81e-2e0f3a5b86ca | logbook. Upuntilitslastversion,theOLOGwebapplication
includedafeatureforgeneratingstatisticalsummaries. Users
were able to export tables containing calculated statistics
basedonthelogbookentriesstoredinthedatabase. Theseta-
bleswouldprovideinformationabouteventsasdocumented
bytheoperators. However,concatenationofstatis... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
7b0f3b7a-57e2-468c-99ed-bb06cc323cbb | systemisdesignedtoallowuserstorequestspecificstatistics
for a chosen time range and immediately receive both the
calculated results and the underlying data.
Onceastatisticisselected,theservicerunsthroughsev-
eral steps to first retrieve the necessary entries from the
OLOG database. Next, the system processes the data a... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
6e6dacce-fb27-4c20-82a0-16df8bdb7ce6 | Requirements Asidefromensuringaccurateandreli-
ablestatisticalcalculation,thedesignofthenewserviceis
guided by three main objectives.
First,thesystemmustbeeasytouse. Thewebinterface
mustremainintuitiveandrequireminimaltraining,enabling
both technical and non-technical users to extract statistics
with minimal effort.17t... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 0 |
73c24671-0134-4e28-8e6e-b032203123b4 | Figure 1: User interfaceof OLOG, the electronic logbook system used at GSI and FAIR to document operational data.
Second, loading and computation times must remain low
despite large data volumes, ensuring results are generated
within seconds.
Third,the systemshould producehigh-qualitygraphical
outputs. Clear and custom... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 1 |
6cde9a1e-f297-4966-9154-d2fa9e08b1eb | datastructures. Thislimitsthehistoricalrangeofpossible
analyses.
Additionally, much of the data in the OLOG system is
documented manually by operators. While this allows for
detaileddescriptionsofevents,italsointroducespotentialin-
consistencies, as naming conventions or classification meth-
ods may have changed over t... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 1 |
457b7697-098e-4f61-a109-3d67f6be3f59 | work is widely used for building responsive and dynamic
webapplications. It providesa robustenvironmentforhan-
dlinguserinteractions,andisalreadybeingusedindevel-
opment of many other web applications at GSI.
Figure2: StaticAngularcomponenthandlingstatisticand
timerangeselectionwiththedisplayofselectedtimeranges
stampe... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 1 |
f9cb925f-6d89-46ed-aa28-77bb03e07453 | section.
Upon receiving a response from the backend layer,
thefrontendgeneratesgraphicalrepresentationsusingthe
D3[11] package from the data. Figure 3shows the graphic
generated by D3 for the selected statistic and time range
specified in Fig. 2. Every graph is configured to display
the corresponding statistic as accur... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 1 |
0f24cf8d-9a10-4e95-a6bd-eb9856bea809 | ISBN: 978-3-95450-252-3 ISSN: 2673-5350 doi: 10.18429/JACoW-IPAC2026-WEP6158
MC6.T33: Online Modelling and Software Tools 2901WEP: Poster session WEP6158
Content from this work may be used under the terms of the CC BY 4.0 licence (© 2026). Any distribution of this work must maintain attribution to the author(s), title ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 1 |
b75e3d36-b4e7-4453-b269-2a7698043390 | Figure 3: D3 generated SVG graphic of chosen statistic and
time range as specified in Fig. 2.
As the backend layer receives requests from the frontend
specifyingtheselectedstatisticandthedesiredtimerange,
the service then retrieves the corresponding logbook entries
fromtheOLOGdatabase. Thebackendthenprocessesthe
data e... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
6e33fb7f-8e98-4d0b-b800-cdacef263e1a | at first sight. As such, the response objects are converted
into JSON files, that have the relevant information at first or
second level, while the raw data the statistic was calculated
from is then provided in deeper levels to the finest detail.
Data
All calculations are based on event entries manually doc-
umentedinO... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
dd00d3ae-7f90-42e7-85b4-319f596df1ab | error as some entries are made during hectic in-shift mo-
ments. Duringweeklymeetings,eventsdocumentedsince
the previous meeting are reviewed and potentially revised
to better reflect the reported incident in light of hindsight.
This reduces errors and inaccuracies but does not guarantee
complete correctness.
RESULTS
I... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
f8165828-99dc-4549-9ac5-629a34df9a1e | usefulness as a diagnostic resource.
Anothernotableresultisthesystem’sperformance. De-
spite retrieving thousands of logbook entries spanning over
tenyears,theserviceachievesloadingtimesofonlyafew
seconds. This gives confidence that expanding the database
and the service with further development of FAIR won’t
have a bi... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
18f12649-198c-45f4-b465-4277f178dd06 | at GSI. By combining automated data retrieval, statistical
analysis,andgraphicalvisualization,thesystemsignificantly
improves the accessibility and usability of operational data.
The service also demonstrates strong performance and scal-
ability, enabling the analysis of large datasets with minimal
waiting time.
Future... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
52b84cd5-c817-4a33-abf0-45da96820a9c | www.gsi.de/en/start/news
[2]P.Schuett etal.,“TheGSIOperationLogbookOLog”,pre-
sentedatthe7thInt.WorkshoponAccel.Oper.(WAO’10),
Daejeon,Korea,Apr.2010, https://www-conf.kek.jp/
wao/WAO2/zero.alt41/zero.alt4/PDF/O-17.pdf
[3]O. Geithner et al., “Introduction of key performance indi-
cators for the GSI accelerator facility... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
7d635a40-e6e7-4883-bdb6-1be1cac5cd5d | Taiwan, Jun. 2025, pp. 2495–2498.
doi:1/zero.alt4.18429/JACoW-IPAC2/zero.alt425-THBN217th International Particle Accelerator Conference, Deauville, France JACoW Publishing
ISBN: 978-3-95450-252-3 ISSN: 2673-5350 doi: 10.18429/JACoW-IPAC2026-WEP6158
2902 MC6.T33: Online Modelling and Software ToolsWEP6158 WEP: Poster se... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 2 |
ddc79bc8-02c1-433d-a364-3c4bf15aa5c7 | [6]M. Vossberg, K. Berkl, S. Reimann, P. Schuett, R. J. Stein-
hagen, and G. Stephan, “FAIR Control Centre (FCC) - Con-
cepts and Interim Options for the Existing GSI Main Control
Room”,in Proc.8thInt.Part.Accel.Conf.(IPAC’17) ,Copen-
hagen, Denmark, May 2017, pp. 1791–1794.
doi:1/zero.alt4.18429/JACoW-IPAC2/zero.alt41... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 3 |
f47962c0-cb5c-4824-b638-c05f0e2a1f18 | [9]Angular, https://angular.dev/
[10]Micronaut, https://micronaut.io/
[11]D3,https://d3js.org/
[12]P. Duval, R. Bacher, H. Ehrlichmann, D. Haupt, M. Lom-
perski, and J. Bobnar, “Automating Operation Statistics at
PETRA-3”,in Proc.16thInt. Conf. Accel.LargeExp. Phys.
ControlSyst.(ICALEPCS’17) , Barcelona, Spain, Oct. 20... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6158.pdf | 3 |
f9a3ff58-07a9-46f5-b927-35d3381b7d76 | INOVESALIB: A MODULAR VLASOV-FOKKER-PLANCK SOLVER
FRAMEWORK
F. Donoso∗, M. Brosi, E. Bründermann, M. Frank, S. Funkner, J. Gethmann,
A.-S. Müller, P. Schreiber,
Karlsruhe Institute of Technology, Karlsruhe, Germany
Abstract
The numerical solution of the Vlasov–Fokker–Planck
(VFP) equation is a well-established method t... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
ab5517cd-c9cc-4495-bec5-34e3d8dc605e | providesaPythonwrapperforseamlessintegrationintouser
workflows. Inovesalib decouples the solver core from appli-
cationlogicandoffersapluginarchitecturethatallowsusers
to implement custom algorithms without modifying the un-
derlyingsolver. TheredesignedstructureturnsInovesafrom
a standalone application into a flexible... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
e1add9bb-0f90-4cdf-9da9-3bdb01aeec09 | throughwakefields[1],orequivalently,throughthebeam
couplingimpedance. Theseinteractionsgiverisetophenom-
enasuchascoherentsynchrotronradiation(CSR)andmicro-
bunchinginstabilities,whichcansignificantlydegradebeam
quality, reduce beam lifetime, and limit the performance of
synchrotronradiationfacilities[2,3]. Specificall... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
9be287e6-87a4-4fcc-b8f2-c837e176e263 | ∗felipe.donoso@kit.eduTosolvethisequationefficientlyinpractice,Inovesawas
developed as a runtime-efficient VFPE solver for desktop-
classhardware. Theoriginalcodebase,developedbySchön-
feldtat KIT[5],combinedadiscretized longitudinalphase
space model with optimized numerical operators and paral-
lelization, making syst... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
619cd238-c1a5-481f-8bbe-baedf9d77847 | chronous phase shift at KARA, connecting the solver to an
experimentally accessible machine observable. In a related
study,Funkneret al.[8]developedanon-destructivelongitu-
dinal phase space density tomography method, qualitatively
validating their reconstructed dynamics against Inovesa sim-
ulations driven by KARA mac... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
9883a544-6601-450d-bda3-42dfceb843a0 | et al. [11] utilized Inovesa as a primary VFP solver in a
cross-code comparison between SOLEIL and KARA. Most
recently,Brosiet al.[12]applieditatMAXIVtoinvestigate
microwave instabilities under varying intra-beam scatter-
ing (IBS) conditions, finding good qualitative agreement
between simulation and experiment. These ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
114a9c8f-3f38-45a2-9017-006d1e9169e4 | how these effects depend on bunch length conditions in low
momentum compaction operation [14]. Wanget al.[15]
usedInovesaastheCSRsimulationenvironmentforaccel-
erateddeepreinforcementlearningaimedatfastfeedback17th International Particle Accelerator Conference, Deauville, France JACoW Publishing
ISBN: 978-3-95450-252-3... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 0 |
19491298-f8e8-43fa-ae8c-b05e47b100bd | of beam dynamics at KARA, showing that Inovesa can also
serveasasimulationbackendforlowlatencycontrolsystem
development.
The original Inovesa software was primarily organized
as an application, which is suitable for batch runs and
command-linestudiesbutrestrictivewhenthesolvermust
be embedded into other software. Moder... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
959f7912-1c35-44a5-8c92-c215197b132f | and algorithms via plugin loading. In practical terms, the
samephysicalproblemcannowbesolvedthroughacompact
C++API,dynamicallyloadedalgorithmimplementations,
or Python bindings, making the solver easier to integrate,
extend, and maintain.
ARCHITECTURE
Inovesalibisorganizedasamodularscientificsoftware
frameworkbuiltarou... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
af032cb3-36ca-4835-9cb9-dafaa9993b1a | pattern that preserves the validated Inovesa numerical work-
flow while exposing it through a compact object interface
for external applications, analysis pipelines, and Python-
basedworkflows. Inthisway,theestablishedsolverkernel
is reorganized into a form with explicit and reusable state
management, runtime control, ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
1ff9fd82-9f6d-46a1-99ff-4bcb13d154e2 | runtime, so that controller-driven parameter changes can
updatetheaffectednumericalmapswithoutrebuildingthe
full solver instance.Parameter models
Inovesalibintroducesanexplicitparametermodellayer
that separates simulation parameter configuration from
solverexecution. Inthissoftwarecontext,amodelisnotthe
physicaldynamic... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
4aabaa9f-ee1a-455a-a02a-d425b0fb664d | eter schema and the parameter values. Here, the schema
denotesthemetadatathatdescribestheavailableparameters,
suchastheirnames,mutability,units,grouping,andvalue
types. Themethod describeAttributes() publishesthis
schema, whereas the actual parameter values remain stored
in the concrete model instance and are accessed ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
0a159100-63b6-4fec-ab10-b06923c2967e | whichprovidestheminimalpolymorphicinterfaceusedto
attachoutput-sidecomponentstothesolver. Thisseparation
preventssimulationcodefrombeingentangledwithfileI/O,
visualization, benchmarking, or communication back-ends,
andmakesitpossibletocombineseveraloutputpathways
with the same solver run.
Severalobserverfamiliesarealre... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
9b062b58-0f17-4dfd-bc87-6ec3c18a97ac | purposeisnottoconsumeoutput,buttomodifythemodelor
trigger solver updates while the simulation is running. This
is particularly relevant for interactive steering, parameter
scanswithfeedback,andfuturehardware-orientedoronline
applications.
The main controller currently implemented in Inovesalib
is the ZMQ model control.... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 1 |
d1fb2695-14c2-4e6b-ab1b-7c3a0f3dd09d | schema, and applies accepted updates during iteration.
These changes can selectively refresh the RF, drift, Fokker-
Planck, or wake operators, depending on which parameters
havebeenmodified. Thisarchitecturekeepsruntimesteer-
ingoutside thenumericalcore whilepreserving consistency
between the model state and the active... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 2 |
befa57a5-57fb-40bd-8435-fb4825b7e3a6 | can optionally develop plugins to introduce entirely new
types of algorithms, such as novel numerical schemes, data-
driven methods, or alternative physics models, expanding
the library’s capabilities without ever modifying the core
codebase.
Thisdesignfollowsthestrategypattern: atruntime,the
framework selects and inst... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 2 |
8f9f6d87-71b9-42f6-90a5-c82e9c502d91 | ing how models, solvers, observers, and related components
interact in typical workflows.
C++
The first example illustrates the high-level usage path,
where an Inovesa instance is created from a configured
model, observers and controllers are attached, and the simu-
lation is executed. This reflects the most direct app... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 2 |
daaa5b87-6cfa-4702-86eb-c3a4618675a4 | at construction time through SolverVFP , emphasizing howtheexecutionstrategyischosenindependentlyfrommodel
and observers.
Listing 2: Algorithm-oriented workflow with explicit strat-
egy selection.
#include"inovesalib/Inovesalib.h"
intmain() {
inovesalib::InovesaModel param_model;
vector<inovesalib::ObserverBase*> obser... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 2 |
8a30c257-9bff-47ee-a83c-360024751fb5 | attached, and the simulation is executed. The snippet below
shows a practical workflow.
Listing 3: Minimal Python example.
importinovesalibasinl
param_model = inl.model("InovesaLegacy")
param_model.grid_size = 256
param_model.beam_current = 8.5e-4
solver = inl.Inovesa(param_model)
observer = inl.InovesaLegacyObserver()... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 2 |
62993d5a-8606-4fe6-b940-3362fd98a76c | physics studies while enabling new forms of integration
throughacompactuserinterfaceandapluginmechanism
for developers. Ongoing work focuses on a differentiable
VFPsolverthatsupportsbothforwardsimulationandgra-
dient propagation for inverse problems and optimization
workflows. Access to the Inovesalib codebase is avail... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 2 |
4468295e-2c77-4661-9266-6bfe70e341c7 | REFERENCES
[1]M. Dohlus and R. Wanzenberg, “An introduction to wake
fields and impedances”,CERN Yellow Rep. School Proc.,
vol. 3, p. 15, 2017.doi:10.23730/CYRSP-2017-003.15
[2]M. Brosi, “Overview of the micro-bunching instability in
electron storage rings and evolving diagnostics”, inProc.
IPAC’21, Campinas, SP, Brazil... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 3 |
c13d9083-313d-4f9e-8f49-7013b825cf7a | Stanford, CA, USA, Rep. SLAC-PUB-8404, 2000.
doi:10.2172/753322
[5]P. Schönfeldt, M. Brosi, M. Schwarz, J. L. Steinmann, and
A.-S. Müller, “Parallelized Vlasov–Fokker–Planck solver
for desktop personal computers”,Phys. Rev. Accel. Beams,
vol. 20, no. 3, p. 030704, 2017.
doi:10.1103/PhysRevAccelBeams.20.030704
[6]J. L. ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 3 |
1aafd8e9-c429-41ea-adaf-9ec784d7cbe8 | tomography”,Sci. Rep., vol. 13, no. 1, p. 4618, 2023.
doi:10.1038/s41598-023-31196-5
[9]M. Brosiet al., “Studies of the micro-bunching instability
inthepresenceofadampingwiggler”,J. Phys.: Conf. Ser.,
vol. 1067, p. 062017, 2018.
doi:10.1088/1742-6596/1067/6/062017[10]T. Boltzet al., “Perturbation of synchrotron motion ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 3 |
c5acf33e-bb8d-4cbe-bdaf-ceacad903ad1 | Taipei, Taiwan, pp. 2207–2210, Jun. 2025.
doi:10.18429/JACoW-IPAC2025-WEPM099
[13]S. Maieret al., “Simulation of the effect of corrugated struc-
tures on the longitudinal beam dynamics at KARA”, inProc.
IPAC’22, Bangkok, Thailand, pp. 2241–2244, Jun. 2022.
doi:10.18429/JACoW-IPAC2022-WEPOMS006
[14]S. Maieret al., “Simu... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 3 |
b74b0201-a612-4376-8ad7-d60081e50cb7 | of ultra-short electron bunch profiles for the generation of
coherent THz radiation”, Ph.D. thesis, Karlsruhe Institute of
Technology, Karlsruhe, Germany, 2018.
doi:10.5445/IR/1000084466
[17]F.Donosoet al.,“Longitudinalphasespacedensitytomog-
raphy constrained by the Vlasov–Fokker–Planck equation”,
inProc. IPAC’24, Nas... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 3 |
c2670add-f4f1-477b-960d-9c4fcc060e7d | ISBN: 978-3-95450-252-3 ISSN: 2673-5350 doi: 10.18429/JACoW-IPAC2026-WEP6163
MC6.T33: Online Modelling and Software Tools 2907WEP: Poster session WEP6163
Content from this work may be used under the terms of the CC BY 4.0 licence (© 2026). Any distribution of this work must maintain attribution to the author(s), title ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6163.pdf | 3 |
35af40d6-b50d-405d-a905-945bc18fe9fe | PROVIDING REPRODUCIBILITY AND ACCESSIBILITY OF RESEARCH
SOFTWARE DEVELOPMENT FOR ACCELERATOR PHYSICS AT KARA
F. Donoso∗, E. Bründermann, M. Frank, S. Funkner, J. Gethmann,
S. Masoumi, A.-S. Müller
Karlsruhe Institute of Technology, Karlsruhe, Germany
Abstract
Modernacceleratorfacilitiesgenerateheterogeneousdata
fromdia... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
971ce173-deea-47d2-8044-436e87cdebad | C++andPythonthatinterfaceswiththeKadi4Mat(Kadi)
virtual research environment. BenchTune records metadata
for each algorithm run, compiler information, parameters,
metrics and stores it in Kadi as portable, traceable research
artifacts. Aproject-viewplugininKadivisualizestheevo-
lution of a research project, linking cod... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
0e739a90-6a51-41a9-9bd1-2251b4d71b92 | isacceleratorresearchattheKarlsruheResearchAccelerator
(KARA),usingitasatestfacilityforstudieswithelectron
beams, beam diagnostics, and related developments such as
magnet systems.
KARAservesasacriticaltestbedfornoveldiagnostics,
beamdynamicsstudies,and advancedlightsourceapplica-
tions,generatinglargeandheterogeneouss... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
715fe593-90b2-4ca3-af90-0df2178e34cb | andprocesseddataisalreadytreatedasacentralconcernand
is addressed according to established FAIR principles [ 1].
At IBPT, this process has recently been strengthened by the
∗felipe.donoso@kit.eduadoption of Kadi4Mat [ 2] (Kadi), a virtual research envi-
ronment that supports the structured organization of data,
metadat... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
8d63ef64-9fa2-4125-9dd0-e44958269f73 | in long-term repositories such as Zenodo, the provenance
of individual software executions is rarely preserved as a
research object in its own right [ 7]. Such execution-level
provenanceextendsbeyondthesourcecodeandincludesthe
scientificliteraturemotivatingtheimplementation,metadata
describingtheexecutionenvironment,co... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
e3cd573b-bcae-474f-be8c-e9664d2d4783 | this, a scientist attempting to reproduce the results at a later
stage may still fail. The code in the repository may have
changed since the plots were originally produced, the ex-
act runtime parameters mayneverhavebeen documented,
and the computation itself may have relied on a specific
compiler version, build config... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
e532987f-796e-43c0-a653-3f7926adf06b | software execution, runtime environment, and configuration
has not been properly persisted [ 8].
Softwareprovenanceisparticularlyimportant inacceler-
atorphysics,wheremanybeampropertiescannot bemea-
sureddirectlybutmustbereconstructedfromheterogeneous
diagnosticdata. Manyquantitiesofscientificinterestareob-
tainedonlyt... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 0 |
7c57133b-e980-48bf-bf8c-9d796a2410cb | Figure1: OverviewoftheKARAresearchstack,illustrating
thepipelinefrominitialsensordataandmetadataacquisition
to the persistence of algorithm execution RUNs and their
visualization via the Kadi Project View.
isreconstructedthroughcode,thescientificsoftwareoften
evolves iteratively alongside the research questions. Sim-
u... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
27b2ee11-a733-4ac4-a7dd-3d8b049d0afd | The work presented in this paper addresses this gap by
extendingprovenancetrackingbeyondtraditionaldataand
metadata records to individual software execution instances,
hereafterdenotedasRUNs. Inthisnotation,RUNreferstoa
research object representing one execution of research soft-
ware. Our approach persists both the re... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
fee77657-f9a1-452b-958d-438aa04608e5 | Tune,whichsendsrunmetadatadirectlytoKadi,and Kadi
ProjectView ,avisualmanagementextensionfororganizing
and exploring these relationships.
Byintegratingthesetools,weprovideaframeworkthat
isintendedtomakeresearchsoftwareatKARAastraceable
and reproducible as the physical experiments themselves.
KARA RESEARCH STACK
During ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
2c907bc7-b1d6-4abc-b472-086a9183cb2f | Facility (LSDF), or temporarily saved on local researcher
workstations.
Inthisheterogeneousenvironment,dataandmetadataare
notautomaticallytransferredtoKadi. Instead,researchers
decide which artifacts should be persisted in the local Kadi
instance,whichisitselfconnectedtotheLSDFinfrastruc-
ture. For experimental dataset... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
96116247-6ffb-4711-91b0-8d5e451a0284 | tion, simulation, and benchmarking, and therefore forms an
essential part of the scientific workflow [ 8].
Tocapturetheprovenanceofthesecomputationalsteps,
the metadata and outputs produced during individual RUNs
of research software are transferred to Kadi through the
BenchTunelibrary. Inthisway,eachrunbecomesatraceab... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
392e9c29-5bcc-40aa-b23a-6e5e65f5ef23 | Project View plugin developed for Kadi, these relationships
can be explored visually, allowing researchers to analyze,
preserve, and communicate the evolution of a project in a
more intuitive and structured way.
BENCHTUNE: RUNs TELEMETRY
BenchTune is a telemetry and reporting layer for C++
and Python that captures syst... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
6efb8767-3c43-47b3-ba36-31860a1c78dd | effort. Onceenabled,itautomaticallygathersmetadatafrom
the execution environment, including kernel, storage, CPU,
compiler, virtualization, distribution, memory, executable
information, and user-defined parameter values provided by
thecodeitself. Thisallowseachexecutiontobedocumented17th International Particle Accelera... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 1 |
025a26bf-06d7-48e6-8b73-58787d683a0d | Figure 2: Kadi project viewcanvasexample.
/vskip2mm
asatraceablerunenrichedwithrelevantcomputationalcon-
text.
Thefollowingcode snippet showsan exampleof Bench-
Tune usage in a C++ program.
Listing 1: BenchTuneC++ use example.
#include <BenchTuneManager.hpp>
using namespace BenchTune;
BenchTuneConfig cfg;
cfg.name = "R... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 2 |
76ed0e4e-3af4-431f-b1c6-f0c1369be7cb | benchtune->add("model/parameter", model->parameter);
benchtune->add("magic_number", 42);
// Write file and sent to kadi (if kadi available)
benchtune->close();
KADI PROJECT VIEW
Kadi Project View extends the Kadi environment with
an interactive visual workspace in which researchers can
organize records, collections, an... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 2 |
9f3ab6cf-5163-4c40-bbd4-f3671797539c | making the evolution of datasets, record versions, and their
interconnections easier to inspect and communicate.
Beyond visualization, Kadi Project View also introduces
analysis-oriented functionality directly into the project can-
vas. Records can be enriched with attached analysis tools
that expose relevant metadata ... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 2 |
2f809578-b88a-474a-b2f5-6e1642ad8a8b | class research artifacts within Kadi, through BenchTune
and Kadi Project View, advances the implementation of
FAIR4RSprinciplesat KARA. Toservethe broader scien-
tificcommunity,futureworkwilldeeplyintegratetheProject
ViewintotheKadiecosystemandexpandBenchTunetosup-
port additional programming languages.
ACKNOWLEDGEMENT... | D:\Daily_ihep\Conferences\IPAC2026\WEP\WEP6164.pdf | 2 |
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