---
OA_place: publisher
OA_type: gold
_id: '20817'
abstract:
- lang: eng
text: We present Mechanistic PDE Networks -- a model for discovery of governing
partial differential equations from data. Mechanistic PDE Networks represent spatiotemporal
data as space-time dependent linear partial differential equations in neural network
hidden representations. The represented PDEs are then solved and decoded for specific
tasks. The learned PDE representations naturally express the spatiotemporal dynamics
in data in neural network hidden space, enabling increased modeling power. Solving
the PDE representations in a compute and memory-efficient way, however, is a significant
challenge. We develop a native, GPU-capable, parallel, sparse and differentiable
multigrid solver specialized for linear partial differential equations that acts
as a module in Mechanistic PDE Networks. Leveraging the PDE solver we propose
a discovery architecture that can discovers nonlinear PDEs in complex settings,
while being robust to noise. We validate PDE discovery on a number of PDEs including
reaction-diffusion and Navier-Stokes equations.
acknowledgement: "AP. This project has received funding from the European Union’s
Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie
Grant Agreement No. 101034413.\r\nFL. This research was funded in whole or in part
by the Austrian Science Fund (FWF) 10.55776/COE12. For open access purposes, the
author has applied a CC BY public\r\ncopyright license to any author accepted manuscript
version arising from this submission."
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Adeel A
full_name: Pervez, Adeel A
id: fca6d90c-d47f-11ee-bc87-93ff51604981
last_name: Pervez
- first_name: Efstratios
full_name: Gavves, Efstratios
last_name: Gavves
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Pervez AA, Gavves E, Locatello F. Mechanistic PDE networks for discovery of
governing equations. In: 42nd International Conference on Machine Learning.
Vol 267. ML Research Press; 2025:48962-48973.'
apa: 'Pervez, A. A., Gavves, E., & Locatello, F. (2025). Mechanistic PDE networks
for discovery of governing equations. In 42nd International Conference on Machine
Learning (Vol. 267, pp. 48962–48973). Vancouver, Canada: ML Research Press.'
chicago: Pervez, Adeel A, Efstratios Gavves, and Francesco Locatello. “Mechanistic
PDE Networks for Discovery of Governing Equations.” In 42nd International Conference
on Machine Learning, 267:48962–73. ML Research Press, 2025.
ieee: A. A. Pervez, E. Gavves, and F. Locatello, “Mechanistic PDE networks for discovery
of governing equations,” in 42nd International Conference on Machine Learning,
Vancouver, Canada, 2025, vol. 267, pp. 48962–48973.
ista: 'Pervez AA, Gavves E, Locatello F. 2025. Mechanistic PDE networks for discovery
of governing equations. 42nd International Conference on Machine Learning. ICML:
International Conference on Machine Learning, PMLR, vol. 267, 48962–48973.'
mla: Pervez, Adeel A., et al. “Mechanistic PDE Networks for Discovery of Governing
Equations.” 42nd International Conference on Machine Learning, vol. 267,
ML Research Press, 2025, pp. 48962–73.
short: A.A. Pervez, E. Gavves, F. Locatello, in:, 42nd International Conference
on Machine Learning, ML Research Press, 2025, pp. 48962–48973.
conference:
end_date: 2025-07-19
location: Vancouver, Canada
name: 'ICML: International Conference on Machine Learning'
start_date: 2025-07-13
corr_author: '1'
date_created: 2025-12-14T23:02:04Z
date_published: 2025-05-01T00:00:00Z
date_updated: 2026-09-16T07:17:18Z
day: '01'
ddc:
- '000'
department:
- _id: FrLo
ec_funded: 1
external_id:
arxiv:
- '2502.18377'
file:
- access_level: open_access
checksum: 933cb673fb41416f537278fb990df6c3
content_type: application/pdf
creator: dernst
date_created: 2025-12-16T12:21:49Z
date_updated: 2025-12-16T12:21:49Z
file_id: '20827'
file_name: 2025_ICML_Pervez.pdf
file_size: 993381
relation: main_file
success: 1
file_date_updated: 2025-12-16T12:21:49Z
has_accepted_license: '1'
intvolume: ' 267'
language:
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month: '05'
oa: 1
oa_version: Published Version
page: 48962-48973
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
- _id: a392d8f0-b034-11f1-b88e-d3025c6734f6
grant_number: COE12
name: Bilateral Artificial Intelligence (Locatello)
publication: 42nd International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/ alpz/mech-nn-discovery-pde
scopus_import: '1'
status: public
title: Mechanistic PDE networks for discovery of governing equations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 267
year: '2025'
...
---
APC_amount: 3003,56 EUR
OA_place: publisher
OA_type: hybrid
_id: '20857'
abstract:
- lang: eng
text: 'Evolutionary games provide a flexible mathematical framework for many problems
in biology and social evolution. Prisoners’ dilemma, and in particular, the important
special case of donation games, represents social dilemmas where cooperation is
mutually beneficial, yet defection is preferred by selfish agents. In evolutionary
games on networks, the agents interact over a population structure. The existence
of population structures that promote cooperative behavior is a fascinating and
active research topic. Previous research establishes structures promoting cooperation
in the limit of weak selection where the benefit-to-cost ratio β exceeds 1.5.
The existence of such structures for medium and strong selection for 1 < ß < 2
and for weak selection for 1 < ß < 1.5 has been a long-standing open question.
First, we answer the open questions in the affirmative: For every selection strength
and every ß > 1, we construct networks promoting cooperation. Second, we present
a robustness result with respect to β and selection strength: Our structures promote
cooperation for a range of these parameter values rather than specific parameter
values. Finally, we supplement our theoretical results with simulation results
on small population structures that show the effectiveness of our construction
over well-studied population structures.'
acknowledgement: J.S. and K.C. were supported by the European Research Council CoG
863818 (ForM-SMArt) and Austrian Science Fund (FWF) 10.55776/COE12.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
citation:
ama: Svoboda J, Chatterjee K. Promoters of cooperation in evolutionary games. Proceedings
of the National Academy of Sciences. 2025;122(51):e2524109122. doi:10.1073/pnas.2524109122
apa: Svoboda, J., & Chatterjee, K. (2025). Promoters of cooperation in evolutionary
games. Proceedings of the National Academy of Sciences. National Academy
of Sciences. https://doi.org/10.1073/pnas.2524109122
chicago: Svoboda, Jakub, and Krishnendu Chatterjee. “Promoters of Cooperation in
Evolutionary Games.” Proceedings of the National Academy of Sciences. National
Academy of Sciences, 2025. https://doi.org/10.1073/pnas.2524109122.
ieee: J. Svoboda and K. Chatterjee, “Promoters of cooperation in evolutionary games,”
Proceedings of the National Academy of Sciences, vol. 122, no. 51. National
Academy of Sciences, p. e2524109122, 2025.
ista: Svoboda J, Chatterjee K. 2025. Promoters of cooperation in evolutionary games.
Proceedings of the National Academy of Sciences. 122(51), e2524109122.
mla: Svoboda, Jakub, and Krishnendu Chatterjee. “Promoters of Cooperation in Evolutionary
Games.” Proceedings of the National Academy of Sciences, vol. 122, no.
51, National Academy of Sciences, 2025, p. e2524109122, doi:10.1073/pnas.2524109122.
short: J. Svoboda, K. Chatterjee, Proceedings of the National Academy of Sciences
122 (2025) e2524109122.
corr_author: '1'
date_created: 2025-12-28T23:01:26Z
date_published: 2025-12-15T00:00:00Z
date_updated: 2026-09-16T07:20:45Z
day: '15'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1073/pnas.2524109122
ec_funded: 1
external_id:
pmid:
- '41397136'
file:
- access_level: open_access
checksum: dd50b62a1efc28c0133fe9c11dbee53c
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creator: dernst
date_created: 2025-12-29T09:36:50Z
date_updated: 2025-12-29T09:36:50Z
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file_size: 2308124
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success: 1
file_date_updated: 2025-12-29T09:36:50Z
fulldoi: https://doi.org/10.1073/pnas.2524109122
has_accepted_license: '1'
intvolume: ' 122'
issue: '51'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: e2524109122
pmid: 1
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee
grant_number: COE12
name: Bilateral Artificial Intelligence (Chatterjee)
publication: Proceedings of the National Academy of Sciences
publication_identifier:
eissn:
- 1091-6490
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Promoters of cooperation in evolutionary games
tmp:
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short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 122
year: '2025'
...
---
OA_place: publisher
_id: '20607'
acknowledged_ssus:
- _id: Bio
- _id: SSU
- _id: LifeSc
- _id: M-Shop
acknowledgement: "I gratefully acknowledge the support of the ISTA Graduate School
and the Scientific Service Units of\r\nISTA, whose resources made this work possible—especially
the Imaging & Optics Facility, the Lab\r\nSupport Facility, and the Miba Machine
Shop. I would like to thank two staff scientists in particular:\r\nRobert Hauschild
(Imaging & Optics Facility) and Daniel Balazs (Lab Support Facility), for their\r\nassistance
and advice. My PhD was partially funded by the Austrian Science Fund (FWF)\r\n(10.55776/P37169
and 10.55776/COE5)."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Soumyadip
full_name: Mondal, Soumyadip
id: d25d21ef-dc8d-11ea-abe3-ec4576307f48
last_name: Mondal
citation:
ama: 'Mondal S. Oxygen and sulfur redox: Conversion kinetics and phase equilibria.
2025. doi:10.15479/AT-ISTA-20607'
apa: 'Mondal, S. (2025). Oxygen and sulfur redox: Conversion kinetics and phase
equilibria. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20607'
chicago: 'Mondal, Soumyadip. “Oxygen and Sulfur Redox: Conversion Kinetics and Phase
Equilibria.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20607.'
ieee: 'S. Mondal, “Oxygen and sulfur redox: Conversion kinetics and phase equilibria,”
Institute of Science and Technology Austria, 2025.'
ista: 'Mondal S. 2025. Oxygen and sulfur redox: Conversion kinetics and phase equilibria.
Institute of Science and Technology Austria.'
mla: 'Mondal, Soumyadip. Oxygen and Sulfur Redox: Conversion Kinetics and Phase
Equilibria. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20607.'
short: 'S. Mondal, Oxygen and Sulfur Redox: Conversion Kinetics and Phase Equilibria,
Institute of Science and Technology Austria, 2025.'
corr_author: '1'
das_tickbox: '1'
date_created: 2025-11-07T12:40:54Z
date_published: 2025-09-19T00:00:00Z
date_updated: 2026-09-16T07:07:04Z
day: '19'
ddc:
- '541'
- '543'
- '542'
degree_awarded: PhD
department:
- _id: GradSch
- _id: StFr
doi: 10.15479/AT-ISTA-20607
doi_confirm: '1'
file:
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content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: smondal
date_created: 2025-11-13T16:47:47Z
date_updated: 2025-11-13T16:47:47Z
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file_name: 2025_Mondal_Soumyadip_Thesis.docx
file_size: 32589295
relation: source_file
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creator: smondal
date_created: 2025-11-13T16:47:46Z
date_updated: 2025-11-13T16:47:46Z
embargo: 2026-11-13
embargo_to: open_access
file_id: '20645'
file_name: 2025_Mondal_Soumyadip_Thesis.pdf
file_size: 5007370
relation: main_file
file_date_updated: 2025-11-13T16:47:47Z
fulldoi: https://doi.org/10.15479/AT-ISTA-20607
has_accepted_license: '1'
language:
- iso: eng
month: '09'
oa_version: Published Version
page: '71'
project:
- _id: 8df062be-16d5-11f0-9cad-f559b6612c7e
grant_number: P37169
name: Singlet oxygen in non-aqueous oxygen redox chemistry
- _id: 5eaf4378-b033-11f1-b276-f928018a46c1
grant_number: COE05
name: Materials for Energy Conversion and Storage (Freunberger)
publication_identifier:
isbn:
- 978-3-99078-071-8
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '12065'
relation: part_of_dissertation
status: public
- id: '13044'
relation: part_of_dissertation
status: public
- id: '20437'
relation: part_of_dissertation
status: deleted
- id: '14687'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Stefan Alexander
full_name: Freunberger, Stefan Alexander
id: A8CA28E6-CE23-11E9-AD2D-EC27E6697425
last_name: Freunberger
orcid: 0000-0003-2902-5319
title: 'Oxygen and sulfur redox: Conversion kinetics and phase equilibria'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: dissertation
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21320'
abstract:
- lang: eng
text: "Prophet inequalities are a central object of study in optimal stopping theory.
In the iid model, a gambler sees values in an online fashion, sampled independently
from a given distribution. Upon observing each value, the gambler either accepts
it as a reward, or irrevocably rejects it and proceeds to observe the next value.
The goal of the gambler, who cannot see the future, is to maximise the expected
value of the reward while competing against the expectation of a prophet (the
offline maximum). In other words, one seeks to maximise the gambler-to-prophet
ratio of the expectations. \r\nThis model has been studied with infinite, finite
and unknown number of values. When the gambler faces a random number of values,
the model is said to have a random horizon. We consider the model in which the
gambler is given a priori knowledge of the horizon’s distribution. Alijani et
al. (2020) designed a single-threshold algorithm achieving a ratio of 1/2 when
the random horizon has an increasing hazard rate and is independent of the values.
We prove that with a single threshold, a ratio of 1/2 is actually achievable for
several larger classes of horizon distributions, with the largest being known
as the \U0001D4A2 class in reliability theory. Moreover, we show that this does
not extend to its dual, the ̅\U0001D4A2 class (which includes the decreasing
hazard rate class), while it can be extended to low-variance horizons. Finally,
we construct the first example of a family of horizons, for which multiple thresholds
are necessary to achieve a nonzero ratio. We establish that the Secretary Problem
optimal stopping rule provides one such algorithm, paving the way towards the
study of the model beyond single-threshold algorithms."
acknowledgement: 'We would like to thank José Correa for his precious advice, Bruno
Ziliotto and Vasilis Livanos for early conversations. Giambartolomei, Giordano:
EPSRC grants EP/W005573/1 and EP/X021696/1. Mallmann-Trenn, Frederik: EPSRC grant
EP/W005573/1. Saona, Raimundo: ERC grant CoG 863818 (ForM-SMArt), ANID Chile grant
ACT210005, French Agence Nationale de la Recherche (ANR) grant ANR-21-CE40-0020
(CONVERGENCE), and Austrian Science Fund (FWF) grant 10.55776/COE12.'
alternative_title:
- LIPIcs
article_processing_charge: No
arxiv: 1
author:
- first_name: Giordano
full_name: Giambartolomei, Giordano
last_name: Giambartolomei
- first_name: Frederik
full_name: Mallmann-Trenn, Frederik
last_name: Mallmann-Trenn
- first_name: Raimundo J
full_name: Saona Urmeneta, Raimundo J
id: BD1DF4C4-D767-11E9-B658-BC13E6697425
last_name: Saona Urmeneta
orcid: 0000-0001-5103-038X
citation:
ama: 'Giambartolomei G, Mallmann-Trenn F, Saona Urmeneta RJ. IID prophet inequality
with random horizon: Going beyond increasing hazard rates. In: 52nd International
Colloquium on Automata, Languages, and Programming. Vol 334. Schloss Dagstuhl
- Leibniz-Zentrum für Informatik; 2025. doi:10.4230/LIPIcs.ICALP.2025.87'
apa: 'Giambartolomei, G., Mallmann-Trenn, F., & Saona Urmeneta, R. J. (2025).
IID prophet inequality with random horizon: Going beyond increasing hazard rates.
In 52nd International Colloquium on Automata, Languages, and Programming
(Vol. 334). Aarhus, Denmark: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.
https://doi.org/10.4230/LIPIcs.ICALP.2025.87'
chicago: 'Giambartolomei, Giordano, Frederik Mallmann-Trenn, and Raimundo J Saona
Urmeneta. “IID Prophet Inequality with Random Horizon: Going beyond Increasing
Hazard Rates.” In 52nd International Colloquium on Automata, Languages, and
Programming, Vol. 334. Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2025. https://doi.org/10.4230/LIPIcs.ICALP.2025.87.'
ieee: 'G. Giambartolomei, F. Mallmann-Trenn, and R. J. Saona Urmeneta, “IID prophet
inequality with random horizon: Going beyond increasing hazard rates,” in 52nd
International Colloquium on Automata, Languages, and Programming, Aarhus,
Denmark, 2025, vol. 334.'
ista: 'Giambartolomei G, Mallmann-Trenn F, Saona Urmeneta RJ. 2025. IID prophet
inequality with random horizon: Going beyond increasing hazard rates. 52nd International
Colloquium on Automata, Languages, and Programming. ICALP: Automata, Languages
and Programming, LIPIcs, vol. 334.'
mla: 'Giambartolomei, Giordano, et al. “IID Prophet Inequality with Random Horizon:
Going beyond Increasing Hazard Rates.” 52nd International Colloquium on Automata,
Languages, and Programming, vol. 334, Schloss Dagstuhl - Leibniz-Zentrum für
Informatik, 2025, doi:10.4230/LIPIcs.ICALP.2025.87.'
short: G. Giambartolomei, F. Mallmann-Trenn, R.J. Saona Urmeneta, in:, 52nd International
Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum
für Informatik, 2025.
conference:
end_date: 2025-07-11
location: Aarhus, Denmark
name: 'ICALP: Automata, Languages and Programming'
start_date: 2025-07-08
date_created: 2026-02-18T10:44:14Z
date_published: 2025-06-30T00:00:00Z
date_updated: 2026-09-16T07:25:05Z
day: '30'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.ICALP.2025.87
ec_funded: 1
external_id:
arxiv:
- '2407.11752'
file:
- access_level: open_access
checksum: 960110956c26a5cefadde8e47888bfbe
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T07:41:55Z
date_updated: 2026-02-19T07:41:55Z
file_id: '21331'
file_name: 2025_ICALP_Giambartolomei.pdf
file_size: 876167
relation: main_file
success: 1
file_date_updated: 2026-02-19T07:41:55Z
fulldoi: https://doi.org/10.4230/LIPIcs.ICALP.2025.87
has_accepted_license: '1'
intvolume: ' 334'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee
grant_number: COE12
name: Bilateral Artificial Intelligence (Chatterjee)
publication: 52nd International Colloquium on Automata, Languages, and Programming
publication_identifier:
isbn:
- '9783959773720'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
status: public
title: 'IID prophet inequality with random horizon: Going beyond increasing hazard
rates'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 334
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21326'
abstract:
- lang: eng
text: 'Neural Collapse is a phenomenon where the last-layer representations of a
well-trained neural network converge to a highly structured geometry. In this
paper, we focus on its first (and most basic) property, known as NC1: the within-class
variability vanishes. While prior theoretical studies establish the occurrence
of NC1 via the data-agnostic unconstrained features model, our work adopts a data-specific
perspective, analyzing NC1 in a three-layer neural network, with the first two
layers operating in the mean-field regime and followed by a linear layer. In particular,
we establish a fundamental connection between NC1 and the loss landscape: we prove
that points with small empirical loss and gradient norm (thus, close to being
stationary) approximately satisfy NC1, and the closeness to NC1 is controlled
by the residual loss and gradient norm. We then show that (i) gradient flow on
the mean squared error converges to NC1 solutions with small empirical loss, and
(ii) for well-separated data distributions, both NC1 and vanishing test loss are
achieved simultaneously. This aligns with the empirical observation that NC1 emerges
during training while models attain near-zero test error. Overall, our results
demonstrate that NC1 arises from gradient training due to the properties of the
loss landscape, and they show the co-occurrence of NC1 and small test error for
certain data distributions.'
acknowledgement: "This research was funded in whole or in part by the Austrian Science
Fund (FWF) 10.55776/COE12. For the purpose of open access, the authors have applied
a CC BY public\r\ncopyright license to any Author Accepted Manuscript version arising
from this submission. The authors would like to thank Peter Sukenık for general
helpful discussions and for pointing out that all the stationary points are approximately
proportional in the case without entropic regularization. "
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Diyuan
full_name: Wu, Diyuan
id: 1a5914c2-896a-11ed-bdf8-fb80621a0635
last_name: Wu
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
citation:
ama: 'Wu D, Mondelli M. Neural collapse beyond the unconstrained features model:
Landscape, dynamics, and generalization in the mean-field regime. In: Proceedings
of the 42nd International Conference on Machine Learning. Vol 267. ML Research
Press; 2025:67499-67536.'
apa: 'Wu, D., & Mondelli, M. (2025). Neural collapse beyond the unconstrained
features model: Landscape, dynamics, and generalization in the mean-field regime.
In Proceedings of the 42nd International Conference on Machine Learning
(Vol. 267, pp. 67499–67536). Vancouver, Canada: ML Research Press.'
chicago: 'Wu, Diyuan, and Marco Mondelli. “Neural Collapse beyond the Unconstrained
Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime.”
In Proceedings of the 42nd International Conference on Machine Learning,
267:67499–536. ML Research Press, 2025.'
ieee: 'D. Wu and M. Mondelli, “Neural collapse beyond the unconstrained features
model: Landscape, dynamics, and generalization in the mean-field regime,” in Proceedings
of the 42nd International Conference on Machine Learning, Vancouver, Canada,
2025, vol. 267, pp. 67499–67536.'
ista: 'Wu D, Mondelli M. 2025. Neural collapse beyond the unconstrained features
model: Landscape, dynamics, and generalization in the mean-field regime. Proceedings
of the 42nd International Conference on Machine Learning. ICML: International
Conference on Machine Learning, PMLR, vol. 267, 67499–67536.'
mla: 'Wu, Diyuan, and Marco Mondelli. “Neural Collapse beyond the Unconstrained
Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime.”
Proceedings of the 42nd International Conference on Machine Learning, vol.
267, ML Research Press, 2025, pp. 67499–536.'
short: D. Wu, M. Mondelli, in:, Proceedings of the 42nd International Conference
on Machine Learning, ML Research Press, 2025, pp. 67499–67536.
conference:
end_date: 2025-07-19
location: Vancouver, Canada
name: 'ICML: International Conference on Machine Learning'
start_date: 2025-07-13
corr_author: '1'
date_created: 2026-02-18T12:02:45Z
date_published: 2025-07-30T00:00:00Z
date_updated: 2026-09-16T07:25:42Z
day: '30'
ddc:
- '000'
department:
- _id: MaMo
external_id:
arxiv:
- '2501.19104'
file:
- access_level: open_access
checksum: c5ce8b1c83e33dc3a11122f4910deb67
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T08:28:22Z
date_updated: 2026-02-19T08:28:22Z
file_id: '21337'
file_name: 2025_ICML_Wu.pdf
file_size: 3994385
relation: main_file
success: 1
file_date_updated: 2026-02-19T08:28:22Z
has_accepted_license: '1'
intvolume: ' 267'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 67499-67536
project:
- _id: 74caaef7-b034-11f1-8f2d-e0e993bb422e
grant_number: COE12
name: Bilateral Artificial Intelligence (Mondelli)
publication: Proceedings of the 42nd International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: 'Neural collapse beyond the unconstrained features model: Landscape, dynamics,
and generalization in the mean-field regime'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
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type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 267
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21268'
abstract:
- lang: eng
text: "We consider multiple-environment Markov decision processes (MEMDP), which
consist of a finite set of MDPs over the same state space, representing different
scenarios of transition structure and probability. The value of a strategy is
the probability to satisfy the objective, here a parity objective, in the worst-case
scenario, and the value of an MEMDP is the supremum of the values achievable by
a strategy.\r\nWe show that deciding whether the value is 1 is a PSPACE-complete
problem, and even in P when the number of environments is fixed, along with new
insights to the almost-sure winning problem, which is to decide if there exists
a strategy with value 1. Pure strategies are sufficient for theses problems, whereas
randomization is necessary in general when the value is smaller than 1. We present
an algorithm to approximate the value, running in double exponential space. Our
results are in contrast to the related model of partially-observable MDPs where
all these problems are known to be undecidable."
acknowledgement: "Krishnendu Chatterjee: ERC CoG 863818 (ForM-SMArt) and Austrian
Science Fund\r\n(FWF) 10.55776/COE12. Jean-François Raskin: PDR Weave project FORM-LEARN-POMDP
funded by FNRS and DFG, and the support of the Fondation ULB. Ocan Sankur: ANR BisoUS
(ANR-22-CE48-0012) and ANR EpiRL (ANR-22-CE23-0029)."
alternative_title:
- LIPIcs
article_number: '150'
article_processing_charge: No
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Laurent
full_name: Doyen, Laurent
last_name: Doyen
- first_name: Jean-Francois
full_name: Raskin, Jean-Francois
last_name: Raskin
- first_name: Ocan
full_name: Sankur, Ocan
last_name: Sankur
citation:
ama: 'Chatterjee K, Doyen L, Raskin J-F, Sankur O. The value problem for multiple-environment
MDPs with parity objective. In: 52nd International Colloquium on Automata,
Languages, and Programming. Schloss Dagstuhl - Leibniz-Zentrum für Informatik;
2025. doi:10.4230/LIPIcs.ICALP.2025.150'
apa: 'Chatterjee, K., Doyen, L., Raskin, J.-F., & Sankur, O. (2025). The value
problem for multiple-environment MDPs with parity objective. In 52nd International
Colloquium on Automata, Languages, and Programming. Aarhus, Denmark: Schloss
Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2025.150'
chicago: Chatterjee, Krishnendu, Laurent Doyen, Jean-Francois Raskin, and Ocan Sankur.
“The Value Problem for Multiple-Environment MDPs with Parity Objective.” In 52nd
International Colloquium on Automata, Languages, and Programming. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2025. https://doi.org/10.4230/LIPIcs.ICALP.2025.150.
ieee: K. Chatterjee, L. Doyen, J.-F. Raskin, and O. Sankur, “The value problem for
multiple-environment MDPs with parity objective,” in 52nd International Colloquium
on Automata, Languages, and Programming, Aarhus, Denmark, 2025.
ista: 'Chatterjee K, Doyen L, Raskin J-F, Sankur O. 2025. The value problem for
multiple-environment MDPs with parity objective. 52nd International Colloquium
on Automata, Languages, and Programming. ICALP: Automata, Languages and Programming,
LIPIcs, , 150.'
mla: Chatterjee, Krishnendu, et al. “The Value Problem for Multiple-Environment
MDPs with Parity Objective.” 52nd International Colloquium on Automata, Languages,
and Programming, 150, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025,
doi:10.4230/LIPIcs.ICALP.2025.150.
short: K. Chatterjee, L. Doyen, J.-F. Raskin, O. Sankur, in:, 52nd International
Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum
für Informatik, 2025.
conference:
end_date: 2025-07-11
location: Aarhus, Denmark
name: 'ICALP: Automata, Languages and Programming'
start_date: 2025-07-08
corr_author: '1'
date_created: 2026-02-17T07:49:17Z
date_published: 2025-07-30T00:00:00Z
date_updated: 2026-09-16T07:23:50Z
day: '30'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.ICALP.2025.150
ec_funded: 1
external_id:
arxiv:
- '2504.15960'
file:
- access_level: open_access
checksum: 4477a7fd4fbf0ba6c8e9b15683b5a6b8
content_type: application/pdf
creator: dernst
date_created: 2026-02-18T07:50:56Z
date_updated: 2026-02-18T07:50:56Z
file_id: '21313'
file_name: 2025_LIPIcs_Chatterjee.pdf
file_size: 1075724
relation: main_file
success: 1
file_date_updated: 2026-02-18T07:50:56Z
fulldoi: https://doi.org/10.4230/LIPIcs.ICALP.2025.150
has_accepted_license: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee
grant_number: COE12
name: Bilateral Artificial Intelligence (Chatterjee)
publication: 52nd International Colloquium on Automata, Languages, and Programming
publication_identifier:
isbn:
- '9783959773720'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: The value problem for multiple-environment MDPs with parity objective
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21076'
abstract:
- lang: eng
text: In many scientific experiments, the data annotating cost constraints the pace
for testing novel hypotheses. Yet, modern machine learning pipelines offer a promising
solution—provided their predictions yield correct conclusions. We focus on Prediction-Powered
Causal Inferences (PPCI), i.e., estimating the treatment effect in an unlabeled
target experiment, relying on training data with the same outcome annotated but
potentially different treatment or effect modifiers. We first show that conditional
calibration guarantees valid PPCI at population level. Then, we introduce a sufficient
representation constraint transferring validity across experiments, which we propose
to enforce in practice in Deconfounded Empirical Risk Minimization, our new model-agnostic
training objective. We validate our method on synthetic and real-world scientific
data, solving impossible problem instances for Empirical Risk Minimization even
with standard invariance constraints. In particular, for the first time, we achieve
valid causal inference on a scientific experiment with complex recording and no
human annotations, fine-tuning a foundational model on our similar annotated experiment.
acknowledgement: We thank the Causal Learning and Artificial Intelligence group at
ISTA for the continuous feedback on the project and valuable discussions. We thank
the Social Immunity group at ISTA, particularly Jinook Oh, for the annotation program
and Michaela Hoenigsberger for supporting our ecological experiment. Riccardo Cadei
is supported by a Google Research Scholar Award and a Google Initiated Gift to Francesco
Locatello. This research was funded in part by the Austrian Science Fund (FWF) 10.55776/COE12).
It was further partially supported by the ISTA Interdisciplinary Project Committee
for the collaborative project “ALED” between Francesco Locatello and Sylvia Cremer.
For open access purposes, the author has applied a CC BY public copyright license
to any author accepted manuscript version arising from this submission.
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
author:
- first_name: Riccardo
full_name: Cadei, Riccardo
id: 0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b
last_name: Cadei
- first_name: Ilker
full_name: Demirel, Ilker
last_name: Demirel
- first_name: Piersilvio
full_name: De Bartolomeis, Piersilvio
last_name: De Bartolomeis
- first_name: Lukas
full_name: Lindorfer, Lukas
id: 85f0e6d3-06b3-11ec-8982-8c5049fa4455
last_name: Lindorfer
- first_name: Sylvia
full_name: Cremer, Sylvia
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
- first_name: Cordelia
full_name: Schmid, Cordelia
last_name: Schmid
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Cadei R, Demirel I, De Bartolomeis P, et al. Prediction-powered causal inferences.
In: 39th Annual Conference on Neural Information Processing Systems. Vol
38. Neural Information Processing Systems Foundation; 2025.'
apa: 'Cadei, R., Demirel, I., De Bartolomeis, P., Lindorfer, L., Cremer, S., Schmid,
C., & Locatello, F. (2025). Prediction-powered causal inferences. In 39th
Annual Conference on Neural Information Processing Systems (Vol. 38). San
Diego, CA, United States: Neural Information Processing Systems Foundation.'
chicago: Cadei, Riccardo, Ilker Demirel, Piersilvio De Bartolomeis, Lukas Lindorfer,
Sylvia Cremer, Cordelia Schmid, and Francesco Locatello. “Prediction-Powered Causal
Inferences.” In 39th Annual Conference on Neural Information Processing Systems,
Vol. 38. Neural Information Processing Systems Foundation, 2025.
ieee: R. Cadei et al., “Prediction-powered causal inferences,” in 39th
Annual Conference on Neural Information Processing Systems, San Diego, CA,
United States, 2025, vol. 38.
ista: 'Cadei R, Demirel I, De Bartolomeis P, Lindorfer L, Cremer S, Schmid C, Locatello
F. 2025. Prediction-powered causal inferences. 39th Annual Conference on Neural
Information Processing Systems. NeurIPS: Neural Information Processing Systems,
Advances in Neural Information Processing Systems, vol. 38.'
mla: Cadei, Riccardo, et al. “Prediction-Powered Causal Inferences.” 39th Annual
Conference on Neural Information Processing Systems, vol. 38, Neural Information
Processing Systems Foundation, 2025.
short: R. Cadei, I. Demirel, P. De Bartolomeis, L. Lindorfer, S. Cremer, C. Schmid,
F. Locatello, in:, 39th Annual Conference on Neural Information Processing Systems,
Neural Information Processing Systems Foundation, 2025.
conference:
end_date: 2025-12-07
location: San Diego, CA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2025-12-02
das_tickbox: '1'
date_created: 2026-01-29T14:35:11Z
date_published: 2025-12-15T00:00:00Z
date_updated: 2026-09-16T07:22:52Z
day: '15'
ddc:
- '000'
department:
- _id: FrLo
- _id: SyCr
file:
- access_level: open_access
checksum: 92467fa566cd36671a6a3b9e71ae0f71
content_type: application/pdf
creator: flocatel
date_created: 2026-01-29T14:35:02Z
date_updated: 2026-01-29T14:35:02Z
file_id: '21077'
file_name: 17546_Prediction_Powered_Causa.pdf
file_size: 8489023
relation: main_file
success: 1
file_date_updated: 2026-01-29T14:35:02Z
has_accepted_license: '1'
intvolume: ' 38'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: a392d8f0-b034-11f1-b88e-d3025c6734f6
grant_number: COE12
name: Bilateral Artificial Intelligence (Locatello)
publication: 39th Annual Conference on Neural Information Processing Systems
publication_identifier:
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
status: public
title: Prediction-powered causal inferences
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21068'
abstract:
- lang: eng
text: "Causal reasoning and discovery, two fundamental tasks of causal analysis,\r\noften
face challenges in applications due to the complexity, noisiness, and highdimensionality
of real-world data. Despite recent progress in identifying latent\r\ncausal structures
using causal representation learning (CRL), what makes learned\r\nrepresentations
useful for causal downstream tasks and how to evaluate them are\r\nstill not well
understood. In this paper, we reinterpret CRL using a measurement\r\nmodel framework,
where the learned representations are viewed as proxy measurements of the latent
causal variables. Our approach clarifies the conditions under\r\nwhich learned
representations support downstream causal reasoning and provides\r\na principled
basis for quantitatively assessing the quality of representations using\r\na new
Test-based Measurement EXclusivity (T-MEX) score. We validate T-MEX\r\nacross
diverse causal inference scenarios, including numerical simulations and\r\nreal-world
ecological video analysis, demonstrating that the proposed framework\r\nand corresponding
score effectively assess the identification of learned representations and their
usefulness for causal downstream tasks. Reproducible code can\r\nbe found at https://github.com/shimenghuang/a-measurement-perspective-of-crl."
acknowledgement: "This research was funded in whole or in part by the Austrian Science
Fund (FWF) 10.55776/COE12. For open access purposes, the author has applied a CC
BY public copyright license to any accepted manuscript version arising from this
submission.\r\n"
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Dingling
full_name: Yao, Dingling
id: d3e02e50-48a8-11ee-8f62-c108061797fa
last_name: Yao
- first_name: Shimeng
full_name: Huang, Shimeng
id: 989c2a06-fb4e-11ef-a992-ab766442255b
last_name: Huang
orcid: 0000-0001-6919-821X
- first_name: Riccardo
full_name: Cadei, Riccardo
id: 0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b
last_name: Cadei
- first_name: Kun
full_name: Zhang, Kun
last_name: Zhang
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Yao D, Huang S, Cadei R, Zhang K, Locatello F. The third pillar of causal
analysis? A measurement perspective on causal representations. In: 39th Annual
Conference on Neural Information Processing Systems. Vol 38. Neural Information
Processing Systems Foundation; 2025.'
apa: 'Yao, D., Huang, S., Cadei, R., Zhang, K., & Locatello, F. (2025). The
third pillar of causal analysis? A measurement perspective on causal representations.
In 39th Annual Conference on Neural Information Processing Systems (Vol.
38). San Diego, CA, United States: Neural Information Processing Systems Foundation.'
chicago: Yao, Dingling, Shimeng Huang, Riccardo Cadei, Kun Zhang, and Francesco
Locatello. “The Third Pillar of Causal Analysis? A Measurement Perspective on
Causal Representations.” In 39th Annual Conference on Neural Information Processing
Systems, Vol. 38. Neural Information Processing Systems Foundation, 2025.
ieee: D. Yao, S. Huang, R. Cadei, K. Zhang, and F. Locatello, “The third pillar
of causal analysis? A measurement perspective on causal representations,” in 39th
Annual Conference on Neural Information Processing Systems, San Diego, CA,
United States, 2025, vol. 38.
ista: 'Yao D, Huang S, Cadei R, Zhang K, Locatello F. 2025. The third pillar of
causal analysis? A measurement perspective on causal representations. 39th Annual
Conference on Neural Information Processing Systems. NeurIPS: Neural Information
Processing Systems, Advances in Neural Information Processing Systems, vol. 38.'
mla: Yao, Dingling, et al. “The Third Pillar of Causal Analysis? A Measurement Perspective
on Causal Representations.” 39th Annual Conference on Neural Information Processing
Systems, vol. 38, Neural Information Processing Systems Foundation, 2025.
short: D. Yao, S. Huang, R. Cadei, K. Zhang, F. Locatello, in:, 39th Annual Conference
on Neural Information Processing Systems, Neural Information Processing Systems
Foundation, 2025.
conference:
end_date: 2025-12-07
location: San Diego, CA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2025-12-02
corr_author: '1'
das_tickbox: '1'
date_created: 2026-01-29T14:24:56Z
date_published: 2025-12-15T00:00:00Z
date_updated: 2026-09-16T07:21:47Z
day: '15'
ddc:
- '000'
department:
- _id: FrLo
external_id:
arxiv:
- '2505.17708'
has_accepted_license: '1'
intvolume: ' 38'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2505.17708
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: a392d8f0-b034-11f1-b88e-d3025c6734f6
grant_number: COE12
name: Bilateral Artificial Intelligence (Locatello)
publication: 39th Annual Conference on Neural Information Processing Systems
publication_identifier:
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/shimenghuang/a-measurement-perspective-of-crl
status: public
title: The third pillar of causal analysis? A measurement perspective on causal representations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21070'
abstract:
- lang: eng
text: 'Deep learning systems deployed in real-world applications often encounter
data that is different from their in-distribution (ID). A reliable model should
ideally abstain from making decisions in this out-of-distribution (OOD) setting.
Existing state-of-the-art methods primarily focus on feature distances, such as
k-th nearest neighbors and distances to decision boundaries, either overlooking
or ineffectively using in-distribution statistics. In this work, we propose a
novel angle-based metric for OOD detection that is computed relative to the in-distribution
structure. We demonstrate that the angles between feature representations and
decision boundaries, viewed from the mean of in-distribution features, serve as
an effective discriminative factor between ID and OOD data. We evaluate our method
on nine ImageNet-pretrained models. Our approach achieves the lowest FPR in 5
out of 9 ImageNet models, obtains the best average FPR overall, and consistently
ranking among the top 3 across all evaluated models. Furthermore, we highlight
the benefits of contrastive representations by showing strong performance with
ResNet SCL and CLIP architectures. Finally, we demonstrate that the scale-invariant
nature of our score enables an ensemble strategy via simple score summation. '
acknowledgement: "This research was funded in whole or in part by the Austrian Science
Fund (FWF) 10.55776/COE12. For open access purposes, the author has applied a CC
BY public copyright license to any accepted manuscript version arising from this
submission.\r\n"
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Berker
full_name: Demirel, Berker
id: 8b4bc47f-3200-11ee-973b-8f0e7be21a9f
last_name: Demirel
- first_name: 'Marco '
full_name: 'Fumero, Marco '
last_name: Fumero
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Demirel B, Fumero M, Locatello F. Out-of-Distribution detection with relative
angles. In: 39th Annual Conference on Neural Information Processing Systems.
Vol 38. Neural Information Processing Systems Foundation; 2025.'
apa: 'Demirel, B., Fumero, M., & Locatello, F. (2025). Out-of-Distribution detection
with relative angles. In 39th Annual Conference on Neural Information Processing
Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing
Systems Foundation.'
chicago: Demirel, Berker, Marco Fumero, and Francesco Locatello. “Out-of-Distribution
Detection with Relative Angles.” In 39th Annual Conference on Neural Information
Processing Systems, Vol. 38. Neural Information Processing Systems Foundation,
2025.
ieee: B. Demirel, M. Fumero, and F. Locatello, “Out-of-Distribution detection with
relative angles,” in 39th Annual Conference on Neural Information Processing
Systems, San Diego, CA, United States, 2025, vol. 38.
ista: 'Demirel B, Fumero M, Locatello F. 2025. Out-of-Distribution detection with
relative angles. 39th Annual Conference on Neural Information Processing Systems.
NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, vol. 38.'
mla: Demirel, Berker, et al. “Out-of-Distribution Detection with Relative Angles.”
39th Annual Conference on Neural Information Processing Systems, vol. 38,
Neural Information Processing Systems Foundation, 2025.
short: B. Demirel, M. Fumero, F. Locatello, in:, 39th Annual Conference on Neural
Information Processing Systems, Neural Information Processing Systems Foundation,
2025.
conference:
end_date: 2025-12-07
location: San Diego, CA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2025-12-02
corr_author: '1'
das_tickbox: '1'
date_created: 2026-01-29T14:26:47Z
date_published: 2025-12-01T00:00:00Z
date_updated: 2026-09-16T07:22:16Z
day: '01'
ddc:
- '000'
department:
- _id: FrLo
external_id:
arxiv:
- '2410.04525'
has_accepted_license: '1'
intvolume: ' 38'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2410.04525
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: a392d8f0-b034-11f1-b88e-d3025c6734f6
grant_number: COE12
name: Bilateral Artificial Intelligence (Locatello)
publication: 39th Annual Conference on Neural Information Processing Systems
publication_identifier:
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/berkerdemirel/ORA-OOD-Detection-with-Relative-Angles
status: public
title: Out-of-Distribution detection with relative angles
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21412'
abstract:
- lang: eng
text: "Payment channel networks (PCNs) are a promising technology that alleviates
blockchain scalability by shifting the transaction load from the blockchain to
the PCN. Nevertheless, the network topology has to be carefully designed to maximise
the transaction throughput in PCNs. Additionally, users in PCNs also have to make
optimal decisions on which transactions to forward and which to reject to prolong
the lifetime of their channels. In this work, we consider an input sequence of
transactions over p parties. Each transaction consists of a transaction size,
source, and target, and can be either accepted or rejected (entailing a cost).
The goal is to design a PCN topology among the p cooperating parties, along with
the channel capacities, and then output a decision for each transaction in the
sequence to minimise the cost of creating and augmenting channels, as well as
the cost of rejecting transactions. Our main contribution is an \U0001D4AA(p)
approximation algorithm for the problem with p parties. We further show that with
some assumptions on the distribution of transactions, we can reduce the approximation
ratio to \U0001D4AA(√p). We complement our theoretical analysis with an empirical
study of our assumptions and approach in the context of the Lightning Network."
acknowledgement: "Chatterjee, Krishnendu: European Research Council CoG 863818 (ForM-SMArt)
and Austrian Science Fund 10.55776/COE12.\r\nKřišťan, Jan Matyáš: Czech Science
Foundation Grant no. 24-12046S.\r\nSchmid, Stefan: German Research Foundation (DFG)
project ReNO (SPP 2378) from 2023-2027.\r\nSvoboda, Jakub: European Research Council
CoG 863818 (ForM-SMArt) and Austrian Science Fund 10.55776/COE12.\r\nYeo, Michelle:
MOE-T2EP20122-0014 (Data-Driven Distributed Algorithms)."
alternative_title:
- LIPIcs
article_number: '23'
article_processing_charge: No
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Jan Matyáš
full_name: Křišťan, Jan Matyáš
last_name: Křišťan
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Michelle X
full_name: Yeo, Michelle X
id: 2D82B818-F248-11E8-B48F-1D18A9856A87
last_name: Yeo
orcid: 0009-0001-3676-4809
citation:
ama: 'Chatterjee K, Křišťan JM, Schmid S, Svoboda J, Yeo MX. Boosting payment channel
network liquidity with topology optimization and transaction selection. In: 39th
International Symposium on Distributed Computing. Vol 356. Schloss Dagstuhl
- Leibniz-Zentrum für Informatik; 2025. doi:10.4230/LIPIcs.DISC.2025.23'
apa: 'Chatterjee, K., Křišťan, J. M., Schmid, S., Svoboda, J., & Yeo, M. X.
(2025). Boosting payment channel network liquidity with topology optimization
and transaction selection. In 39th International Symposium on Distributed Computing
(Vol. 356). Berlin, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.
https://doi.org/10.4230/LIPIcs.DISC.2025.23'
chicago: Chatterjee, Krishnendu, Jan Matyáš Křišťan, Stefan Schmid, Jakub Svoboda,
and Michelle X Yeo. “Boosting Payment Channel Network Liquidity with Topology
Optimization and Transaction Selection.” In 39th International Symposium on
Distributed Computing, Vol. 356. Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2025. https://doi.org/10.4230/LIPIcs.DISC.2025.23.
ieee: K. Chatterjee, J. M. Křišťan, S. Schmid, J. Svoboda, and M. X. Yeo, “Boosting
payment channel network liquidity with topology optimization and transaction selection,”
in 39th International Symposium on Distributed Computing, Berlin, Germany,
2025, vol. 356.
ista: 'Chatterjee K, Křišťan JM, Schmid S, Svoboda J, Yeo MX. 2025. Boosting payment
channel network liquidity with topology optimization and transaction selection.
39th International Symposium on Distributed Computing. DISC: Symposium on Distributed
Computing, LIPIcs, vol. 356, 23.'
mla: Chatterjee, Krishnendu, et al. “Boosting Payment Channel Network Liquidity
with Topology Optimization and Transaction Selection.” 39th International Symposium
on Distributed Computing, vol. 356, 23, Schloss Dagstuhl - Leibniz-Zentrum
für Informatik, 2025, doi:10.4230/LIPIcs.DISC.2025.23.
short: K. Chatterjee, J.M. Křišťan, S. Schmid, J. Svoboda, M.X. Yeo, in:, 39th International
Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2025.
conference:
end_date: 2025-10-31
location: Berlin, Germany
name: 'DISC: Symposium on Distributed Computing'
start_date: 2025-10-27
cryptoeprintid: 1
date_created: 2026-03-08T23:01:46Z
date_published: 2025-10-22T00:00:00Z
date_updated: 2026-09-16T07:27:09Z
day: '22'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.DISC.2025.23
ec_funded: 1
external_id:
arxiv:
- '2508.14524'
cryptoeprintid:
- 2025/1484
file:
- access_level: open_access
checksum: 8e3d1594365df60163d9df22158a37b1
content_type: application/pdf
creator: dernst
date_created: 2026-03-09T11:51:59Z
date_updated: 2026-03-09T11:51:59Z
file_id: '21418'
file_name: 2025_DISC_Chatterjee.pdf
file_size: 1130069
relation: main_file
success: 1
file_date_updated: 2026-03-09T11:51:59Z
fulldoi: https://doi.org/10.4230/LIPIcs.DISC.2025.23
has_accepted_license: '1'
intvolume: ' 356'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee
grant_number: COE12
name: Bilateral Artificial Intelligence (Chatterjee)
publication: 39th International Symposium on Distributed Computing
publication_identifier:
isbn:
- '9783959774024'
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Boosting payment channel network liquidity with topology optimization and transaction
selection
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 356
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '20819'
abstract:
- lang: eng
text: "Clustering is a cornerstone of data analysis that is particularly suited
to identifying coherent subgroups or substructures in unlabeled data, as are generated
continuously in large amounts these days. However, in many cases traditional clustering
methods are not applicable, because data are increasingly being produced and stored
in a distributed way, e.g. on edge devices, and privacy concerns prevent it from
being transferred to a central server. To address this challenge, we present FedDP-KMeans,
a new algorithm for \r\n-means clustering that is fully-federated as well as differentially
private. Our approach leverages (potentially small and out-of-distribution) server-side
data to overcome the primary challenge of differentially private clustering methods:
the need for a good initialization. Combining our initialization with a simple
federated DP-Lloyds algorithm we obtain an algorithm that achieves excellent results
on synthetic and real-world benchmark tasks. We also provide a theoretical analysis
of our method that provides bounds on the convergence speed and cluster identification
success."
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "This research was funded in part by the Austrian Science Fund (FWF)
[10.55776/COE12] and supported by the Scientific Service Units (SSU) of ISTA through
resources provided by Scientific Computing (SciComp).\r\n"
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Jonathan A
full_name: Scott, Jonathan A
id: e499926b-f6e0-11ea-865d-9c63db0031e8
last_name: Scott
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: David
full_name: Saulpic, David
id: f8e48cf0-b0ff-11ed-b0e9-b4c35598f964
last_name: Saulpic
citation:
ama: 'Scott JA, Lampert C, Saulpic D. Differentially private federated k-means clustering
with server-side data. In: 42nd International Conference on Machine Learning.
Vol 267. ML Research Press; 2025:53757-53790.'
apa: 'Scott, J. A., Lampert, C., & Saulpic, D. (2025). Differentially private
federated k-means clustering with server-side data. In 42nd International Conference
on Machine Learning (Vol. 267, pp. 53757–53790). Vancouver, Canada: ML Research
Press.'
chicago: Scott, Jonathan A, Christoph Lampert, and David Saulpic. “Differentially
Private Federated K-Means Clustering with Server-Side Data.” In 42nd International
Conference on Machine Learning, 267:53757–90. ML Research Press, 2025.
ieee: J. A. Scott, C. Lampert, and D. Saulpic, “Differentially private federated
k-means clustering with server-side data,” in 42nd International Conference
on Machine Learning, Vancouver, Canada, 2025, vol. 267, pp. 53757–53790.
ista: 'Scott JA, Lampert C, Saulpic D. 2025. Differentially private federated k-means
clustering with server-side data. 42nd International Conference on Machine Learning.
ICML: International Conference on Machine Learning, PMLR, vol. 267, 53757–53790.'
mla: Scott, Jonathan A., et al. “Differentially Private Federated K-Means Clustering
with Server-Side Data.” 42nd International Conference on Machine Learning,
vol. 267, ML Research Press, 2025, pp. 53757–90.
short: J.A. Scott, C. Lampert, D. Saulpic, in:, 42nd International Conference on
Machine Learning, ML Research Press, 2025, pp. 53757–53790.
conference:
end_date: 2025-07-19
location: Vancouver, Canada
name: 'ICML: International Conference on Machine Learning'
start_date: 2025-07-13
corr_author: '1'
date_created: 2025-12-14T23:02:05Z
date_published: 2025-05-01T00:00:00Z
date_updated: 2026-09-16T07:26:12Z
day: '01'
ddc:
- '000'
department:
- _id: ChLa
- _id: MoHe
external_id:
arxiv:
- '2506.05408'
file:
- access_level: open_access
checksum: 815b32b463023ca21e569c2158745c15
content_type: application/pdf
creator: dernst
date_created: 2025-12-16T12:38:29Z
date_updated: 2025-12-16T12:38:29Z
file_id: '20829'
file_name: 2025_ICML_Scott.pdf
file_size: 746612
relation: main_file
success: 1
file_date_updated: 2025-12-16T12:38:29Z
has_accepted_license: '1'
intvolume: ' 267'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
page: 53757-53790
project:
- _id: d8f03aaa-b035-11f1-8588-d5147fa879e0
grant_number: COE12
name: Bilateral Artificial Intelligence (Lampert)
publication: 42nd International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
related_material:
record:
- id: '21198'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Differentially private federated k-means clustering with server-side data
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 267
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21207'
abstract:
- lang: eng
text: Personalized federated learning has emerged as a popular approach to training
on devices holding statistically heterogeneous data, known as clients. However,
most existing approaches require a client to have labeled data for training or
finetuning in order to obtain their own personalized model. In this paper we address
this by proposing FLowDUP, a novel method that is able to generate a personalized
model using only a forward pass with unlabeled data. The generated model parameters
reside in a low-dimensional subspace, enabling efficient communication and computation.
FLowDUP's learning objective is theoretically motivated by our new transductive
multi-task PAC-Bayesian generalization bound, that provides performance guarantees
for unlabeled clients. The objective is structured in such a way that it allows
both clients with labeled data and clients with only unlabeled data to contribute
to the training process. To supplement our theoretical results we carry out a
thorough experimental evaluation of FLowDUP, demonstrating strong empirical performance
on a range of datasets with differing sorts of statistically heterogeneous clients.
Through numerous ablation studies, we test the efficacy of the individual components
of the method.
article_number: '2505.15579'
article_processing_charge: No
author:
- first_name: Hossein
full_name: Zakerinia, Hossein
id: 653bd8b6-f394-11eb-9cf6-c0bbf6cd78d4
last_name: Zakerinia
orcid: 0009-0007-3977-6462
- first_name: Jonathan A
full_name: Scott, Jonathan A
id: e499926b-f6e0-11ea-865d-9c63db0031e8
last_name: Scott
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Zakerinia H, Scott JA, Lampert C. Federated learning with unlabeled clients:
Personalization can happen in low dimensions. arXiv. doi:10.48550/ARXIV.2505.15579'
apa: 'Zakerinia, H., Scott, J. A., & Lampert, C. (n.d.). Federated learning
with unlabeled clients: Personalization can happen in low dimensions. arXiv.
https://doi.org/10.48550/ARXIV.2505.15579'
chicago: 'Zakerinia, Hossein, Jonathan A Scott, and Christoph Lampert. “Federated
Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.”
ArXiv, n.d. https://doi.org/10.48550/ARXIV.2505.15579.'
ieee: 'H. Zakerinia, J. A. Scott, and C. Lampert, “Federated learning with unlabeled
clients: Personalization can happen in low dimensions,” arXiv. .'
ista: 'Zakerinia H, Scott JA, Lampert C. Federated learning with unlabeled clients:
Personalization can happen in low dimensions. arXiv, 2505.15579.'
mla: 'Zakerinia, Hossein, et al. “Federated Learning with Unlabeled Clients: Personalization
Can Happen in Low Dimensions.” ArXiv, 2505.15579, doi:10.48550/ARXIV.2505.15579.'
short: H. Zakerinia, J.A. Scott, C. Lampert, ArXiv (n.d.).
corr_author: '1'
das_tickbox: '1'
date_created: 2026-02-10T08:20:59Z
date_published: 2025-05-21T00:00:00Z
date_updated: 2026-09-16T07:26:12Z
day: '21'
department:
- _id: ChLa
doi: 10.48550/ARXIV.2505.15579
fulldoi: https://doi.org/10.48550/ARXIV.2505.15579
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2505.15579
month: '05'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: draft
related_material:
record:
- id: '21198'
relation: dissertation_contains
status: public
status: public
title: 'Federated learning with unlabeled clients: Personalization can happen in low
dimensions'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '22823'
abstract:
- lang: eng
text: This position paper argues that setting the privacy budget in differential
privacy should not be viewed as an important limitation of differential privacy
compared to alternative methods for privacy-preserving machine learning. The so-called
problem of interpreting the privacy budget is often presented as a major hindrance
to the wider adoption of differential privacy in real-world deployments and is
sometimes used to promote alternative mitigation techniques for data protection.
We believe this misleads decision-makers into choosing unsafe methods. We argue
that the difficulty in interpreting privacy budgets does not stem from the definition
of differential privacy itself, but from the intrinsic difficulty of estimating
privacy risks in context, a challenge that any rigorous method for privacy risk
assessment face. Moreover, we claim that any sound method for estimating privacy
risks should, given the current state of research, be expressible within the differential
privacy framework or justify why it cannot.
acknowledgement: "This research was funded in whole by the Austrian Science Fund (FWF)
10.55776/COE12. I thank\r\nAlberto Naibo for the discussion and his invitation to
\"Logique, droit, IA : penser les algorithmes\"\r\ncolloquium. I thank Simone Bombari
for the discussions. I thank EurIPS for the active poster session."
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
author:
- first_name: Edwige Audrey Lucienne
full_name: Cyffers, Edwige Audrey Lucienne
id: 20d4c299-977a-11ef-ae55-98b15ac64a57
last_name: Cyffers
citation:
ama: 'Cyffers EAL. Setting ε is not the issue in differential privacy. In: 39th
Conference on Neural Information Processing Systems. Vol 38. Neural Information
Processing Systems Foundation; 2025:159016-159028. doi:10.52202/085713-4798'
apa: 'Cyffers, E. A. L. (2025). Setting ε is not the issue in differential privacy.
In 39th Conference on Neural Information Processing Systems (Vol. 38, pp.
159016–159028). San Diego, CA, United States: Neural Information Processing Systems
Foundation. https://doi.org/10.52202/085713-4798'
chicago: Cyffers, Edwige Audrey Lucienne. “Setting ε Is Not the Issue in Differential
Privacy.” In 39th Conference on Neural Information Processing Systems,
38:159016–28. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-4798.
ieee: E. A. L. Cyffers, “Setting ε is not the issue in differential privacy,” in
39th Conference on Neural Information Processing Systems, San Diego, CA,
United States, 2025, vol. 38, pp. 159016–159028.
ista: 'Cyffers EAL. 2025. Setting ε is not the issue in differential privacy. 39th
Conference on Neural Information Processing Systems. NeurIPS: Neural Information
Processing Systems, Advances in Neural Information Processing Systems, vol. 38,
159016–159028.'
mla: Cyffers, Edwige Audrey Lucienne. “Setting ε Is Not the Issue in Differential
Privacy.” 39th Conference on Neural Information Processing Systems, vol.
38, Neural Information Processing Systems Foundation, 2025, pp. 159016–28, doi:10.52202/085713-4798.
short: E.A.L. Cyffers, in:, 39th Conference on Neural Information Processing Systems,
Neural Information Processing Systems Foundation, 2025, pp. 159016–159028.
conference:
end_date: 2025-12-07
location: San Diego, CA, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2025-12-02
corr_author: '1'
das_tickbox: '0'
date_created: 2026-09-06T22:01:59Z
date_published: 2025-12-02T00:00:00Z
date_updated: 2026-09-16T07:40:20Z
day: '02'
department:
- _id: ChLa
doi: 10.52202/085713-4798
fulldoi: https://doi.org/10.52202/085713-4798
intvolume: ' 38'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.52202/085713-4798
month: '12'
oa: 1
oa_version: Published Version
page: 159016-159028
project:
- _id: d8f03aaa-b035-11f1-8588-d5147fa879e0
grant_number: COE12
name: Bilateral Artificial Intelligence (Lampert)
publication: 39th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9798331338275'
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: yes
title: Setting ε is not the issue in differential privacy
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2025'
...
---
OA_place: publisher
OA_type: free access
_id: '22828'
abstract:
- lang: eng
text: 'We propose Joint Moment Estimation (JME), a method for continually and privately
estimating both the first and second moments of a data stream with reduced noise
compared to naive approaches. JME supports the matrix mechanism and exploits a
joint sensitivity analysis to identify a privacy regime in which the second-moment
estimation incurs no additional privacy cost, thereby improving accuracy while
maintaining privacy. We demonstrate JME’s effectiveness in two applications: estimating
the running mean and covariance matrix for Gaussian density estimation and model
training with DP-Adam.'
acknowledgement: "We thank Monika Henzinger for her valuable feedback and insightful
discussions on earlier versions\r\nof this draft. We are also grateful to Mher Safaryan
for his contributions to discussions on DP-Adam.\r\nAdditionally, we thank Ryan
McKenna for suggesting Joint Clipping as a baseline.\r\nJalaj Upadhyay’s research
was funded by the Rutgers Decanal Grant no. 302918, NSF CNS 2433628,\r\nGoogle Research
Scholar Award, and Google Seed Fund Grant. A part of this work was done while\r\nvisiting
the Institute of Science and Technology Austria (ISTA).\r\nNikita Kalinin’s research
was funded in part by the Austrian Science Fund (FWF) [10.55776/COE12]"
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
author:
- first_name: Nikita
full_name: Kalinin, Nikita
id: 4b14526e-14d2-11ed-ba64-c14c9553d137
last_name: Kalinin
- first_name: Jalaj
full_name: Upadhyay, Jalaj
last_name: Upadhyay
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Kalinin N, Upadhyay J, Lampert C. Continual release moment estimation with
differential privacy. In: Advances in Neural Information Processing Systems.
Vol 38. Neural Information Processing Systems Foundation; 2025:64002-64047. doi:10.52202/085713-1924'
apa: 'Kalinin, N., Upadhyay, J., & Lampert, C. (2025). Continual release moment
estimation with differential privacy. In Advances in Neural Information Processing
Systems (Vol. 38, pp. 64002–64047). San Diego, CA, United States: Neural Information
Processing Systems Foundation. https://doi.org/10.52202/085713-1924'
chicago: Kalinin, Nikita, Jalaj Upadhyay, and Christoph Lampert. “Continual Release
Moment Estimation with Differential Privacy.” In Advances in Neural Information
Processing Systems, 38:64002–47. Neural Information Processing Systems Foundation,
2025. https://doi.org/10.52202/085713-1924.
ieee: N. Kalinin, J. Upadhyay, and C. Lampert, “Continual release moment estimation
with differential privacy,” in Advances in Neural Information Processing Systems,
San Diego, CA, United States, 2025, vol. 38, pp. 64002–64047.
ista: 'Kalinin N, Upadhyay J, Lampert C. 2025. Continual release moment estimation
with differential privacy. Advances in Neural Information Processing Systems.
NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, vol. 38, 64002–64047.'
mla: Kalinin, Nikita, et al. “Continual Release Moment Estimation with Differential
Privacy.” Advances in Neural Information Processing Systems, vol. 38, Neural
Information Processing Systems Foundation, 2025, pp. 64002–47, doi:10.52202/085713-1924.
short: N. Kalinin, J. Upadhyay, C. Lampert, in:, Advances in Neural Information
Processing Systems, Neural Information Processing Systems Foundation, 2025, pp.
64002–64047.
conference:
location: San Diego, CA, United States
name: 'NeurIPS: Neural Information Processing Systems'
corr_author: '1'
das_tickbox: '0'
date_created: 2026-09-06T22:02:00Z
date_published: 2025-12-02T00:00:00Z
date_updated: 2026-09-16T07:40:56Z
day: '02'
department:
- _id: GradSch
- _id: ChLa
doi: 10.52202/085713-1924
fulldoi: https://doi.org/10.52202/085713-1924
intvolume: ' 38'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.52202/085713-1924
month: '12'
oa: 1
oa_version: Published Version
page: 64002-64047
project:
- _id: d8f03aaa-b035-11f1-8588-d5147fa879e0
grant_number: COE12
name: Bilateral Artificial Intelligence (Lampert)
publication: Advances in Neural Information Processing Systems
publication_identifier:
isbn:
- '9798331338275'
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Continual release moment estimation with differential privacy
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2025'
...
---
OA_place: publisher
OA_type: diamond
_id: '19841'
abstract:
- lang: eng
text: "Context. The blue supergiant (BSG) domain contains a large variety of stars
whose past and future evolutionary paths are still highly uncertain. Since binary
interaction plays a crucial role in the fate of massive stars, investigating the
multiplicity among BSGs helps shed light on the fate of such objects.\r\nAims.
We aim to estimate the binary fraction of a large sample of BSGs in the Small
Magellanic Cloud (SMC) within the Binarity at LOw Metallicity (BLOeM) survey.
In total, we selected 262 targets with spectral types B0-B3 and luminosity classes
I-II.\r\n\r\nMethods. This work is based on spectroscopic data collected by the
FLAMES instrument, mounted on the Very Large Telescope, which gathered nine epochs
over three months. Our spectroscopic analysis for each target includes the individual
and peak-to-peak radial velocity measurements, an investigation of the line profile
variability, and a periodogram analysis to search for possible short- and long-period
binaries.\r\n\r\nResults. By applying a 20 km s−1 threshold on the peak-to-peak
radial velocities above which we would consider the star to be binary, the resulting
observed spectroscopic binary fraction for our BSG sample is 23 ± 3%. An independent
analysis of line profile variability reveals 11 (plus 5 candidates) double-lined
spectroscopic binaries and 32 (plus 41 candidates) single-lined spectroscopic
binaries. Based on these results, we estimated the overall observed binary fraction
in this sample to be 34 ± 3%, which is close to the computed intrinsic binary
fraction of 40 ± 4%. In addition, we derived reliable orbital periods for 41 spectroscopic
binaries and potential binary candidates, among which there are 17 eclipsing binaries,
including 20 SB1 and SB2 systems with periods of less than 10 days. We reported
a significant drop in the binary fraction of BSGs with spectral types later than
B2 and effective temperatures less than 18 kK, which could indicate the end of
the main sequence phase in this temperature regime. We found no metallicity dependence
in the binary fraction of BSGs, compared to existing spectroscopic surveys of
the Galaxy and Large Magellanic Cloud."
acknowledgement: 'We thank the anonymous referee for helpful comments that have improved
the manuscript. This project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement 101164755/METAL) and was supported by the Israel Science Foundation
(ISF) under grant number 2434/24. NB acknowledges support from the Belgian federal
government grant for Ukrainian postdoctoral researchers (contract UF/2022/10). TS
acknowledges support by the Israel Science Foundation (ISF) under grant number 0603225041.
DP acknowledges financial support from the Deutsches Zentrum für Luft und Raumfahrt
(DLR) grant FKZ 50OR2005 and the FWO junior postdoctoral fellowship No. 1256225N.
DMB gratefully acknowledges UK Research and Innovation (UKRI) in the form of a Frontier
Research grant under the UK government’s ERC Horizon Europe funding guarantee (SYMPHONY;
PI Bowman; grant number: EP/Y031059/1), and a Royal Society University Research
Fellowship (PI Bowman; grant number: URF\R1\231631). KS is funded by the National
Science Center (NCN), Poland, under grant number OPUS 2021/41/B/ST9/00757. IM acknowledges
support from the Australian Research Council (ARC) Centre of Excellence for Gravitational
Wave Discovery (OzGav), through project number CE230100016. JIV acknowledges support
from the European Research Council through ERC Advanced Grant No. 101054731. SS-D,
and GH acknowledge support from the Spanish Ministry of Science and Innovation and
Universities (MICIU) through the Spanish State Research Agency (AEI) through grants
PID2021-122397NB-C21, and the Severo Ochoa Program 2020-2023 (CEX2019-000920-S).'
article_number: A40
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: N.
full_name: Britavskiy, N.
last_name: Britavskiy
- first_name: L.
full_name: Mahy, L.
last_name: Mahy
- first_name: D. J.
full_name: Lennon, D. J.
last_name: Lennon
- first_name: L. R.
full_name: Patrick, L. R.
last_name: Patrick
- first_name: H.
full_name: Sana, H.
last_name: Sana
- first_name: J. I.
full_name: Villaseñor, J. I.
last_name: Villaseñor
- first_name: T.
full_name: Shenar, T.
last_name: Shenar
- first_name: J.
full_name: Bodensteiner, J.
last_name: Bodensteiner
- first_name: M.
full_name: Bernini-Peron, M.
last_name: Bernini-Peron
- first_name: S. R.
full_name: Berlanas, S. R.
last_name: Berlanas
- first_name: D. M.
full_name: Bowman, D. M.
last_name: Bowman
- first_name: P. A.
full_name: Crowther, P. A.
last_name: Crowther
- first_name: S. E.
full_name: De Mink, S. E.
last_name: De Mink
- first_name: C. J.
full_name: Evans, C. J.
last_name: Evans
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: G.
full_name: Holgado, G.
last_name: Holgado
- first_name: C.
full_name: Johnston, C.
last_name: Johnston
- first_name: Z.
full_name: Keszthelyi, Z.
last_name: Keszthelyi
- first_name: J.
full_name: Klencki, J.
last_name: Klencki
- first_name: N.
full_name: Langer, N.
last_name: Langer
- first_name: I.
full_name: Mandel, I.
last_name: Mandel
- first_name: A.
full_name: Menon, A.
last_name: Menon
- first_name: M.
full_name: Moe, M.
last_name: Moe
- first_name: L. M.
full_name: Oskinova, L. M.
last_name: Oskinova
- first_name: D.
full_name: Pauli, D.
last_name: Pauli
- first_name: M.
full_name: Pawlak, M.
last_name: Pawlak
- first_name: V.
full_name: Ramachandran, V.
last_name: Ramachandran
- first_name: M.
full_name: Renzo, M.
last_name: Renzo
- first_name: A. A.C.
full_name: Sander, A. A.C.
last_name: Sander
- first_name: F. R.N.
full_name: Schneider, F. R.N.
last_name: Schneider
- first_name: A.
full_name: Schootemeijer, A.
last_name: Schootemeijer
- first_name: K.
full_name: Sen, K.
last_name: Sen
- first_name: S.
full_name: Simón-Díaz, S.
last_name: Simón-Díaz
- first_name: J. T.
full_name: Van Loon, J. T.
last_name: Van Loon
- first_name: J. S.
full_name: Vink, J. S.
last_name: Vink
citation:
ama: 'Britavskiy N, Mahy L, Lennon DJ, et al. Binarity at LOw Metallicity (BLOeM):
Multiplicity of early B-type supergiants in the Small Magellanic Cloud. Astronomy
& Astrophysics. 2025;698. doi:10.1051/0004-6361/202452963'
apa: 'Britavskiy, N., Mahy, L., Lennon, D. J., Patrick, L. R., Sana, H., Villaseñor,
J. I., … Vink, J. S. (2025). Binarity at LOw Metallicity (BLOeM): Multiplicity
of early B-type supergiants in the Small Magellanic Cloud. Astronomy &
Astrophysics. EDP Sciences. https://doi.org/10.1051/0004-6361/202452963'
chicago: 'Britavskiy, N., L. Mahy, D. J. Lennon, L. R. Patrick, H. Sana, J. I. Villaseñor,
T. Shenar, et al. “Binarity at LOw Metallicity (BLOeM): Multiplicity of Early
B-Type Supergiants in the Small Magellanic Cloud.” Astronomy & Astrophysics.
EDP Sciences, 2025. https://doi.org/10.1051/0004-6361/202452963.'
ieee: 'N. Britavskiy et al., “Binarity at LOw Metallicity (BLOeM): Multiplicity
of early B-type supergiants in the Small Magellanic Cloud,” Astronomy &
Astrophysics, vol. 698. EDP Sciences, 2025.'
ista: 'Britavskiy N, Mahy L, Lennon DJ, Patrick LR, Sana H, Villaseñor JI, Shenar
T, Bodensteiner J, Bernini-Peron M, Berlanas SR, Bowman DM, Crowther PA, De Mink
SE, Evans CJ, Götberg YLL, Holgado G, Johnston C, Keszthelyi Z, Klencki J, Langer
N, Mandel I, Menon A, Moe M, Oskinova LM, Pauli D, Pawlak M, Ramachandran V, Renzo
M, Sander AAC, Schneider FRN, Schootemeijer A, Sen K, Simón-Díaz S, Van Loon JT,
Vink JS. 2025. Binarity at LOw Metallicity (BLOeM): Multiplicity of early B-type
supergiants in the Small Magellanic Cloud. Astronomy & Astrophysics. 698,
A40.'
mla: 'Britavskiy, N., et al. “Binarity at LOw Metallicity (BLOeM): Multiplicity
of Early B-Type Supergiants in the Small Magellanic Cloud.” Astronomy &
Astrophysics, vol. 698, A40, EDP Sciences, 2025, doi:10.1051/0004-6361/202452963.'
short: N. Britavskiy, L. Mahy, D.J. Lennon, L.R. Patrick, H. Sana, J.I. Villaseñor,
T. Shenar, J. Bodensteiner, M. Bernini-Peron, S.R. Berlanas, D.M. Bowman, P.A.
Crowther, S.E. De Mink, C.J. Evans, Y.L.L. Götberg, G. Holgado, C. Johnston, Z.
Keszthelyi, J. Klencki, N. Langer, I. Mandel, A. Menon, M. Moe, L.M. Oskinova,
D. Pauli, M. Pawlak, V. Ramachandran, M. Renzo, A.A.C. Sander, F.R.N. Schneider,
A. Schootemeijer, K. Sen, S. Simón-Díaz, J.T. Van Loon, J.S. Vink, Astronomy &
Astrophysics 698 (2025).
das_tickbox: '1'
date_created: 2025-06-15T22:01:29Z
date_published: 2025-06-01T00:00:00Z
date_updated: 2026-09-16T09:10:41Z
day: '01'
ddc:
- '520'
department:
- _id: YlGo
doi: 10.1051/0004-6361/202452963
external_id:
arxiv:
- '2502.12239'
isi:
- '001497903100019'
file:
- access_level: open_access
checksum: 53a9f290cb1f468895e0d4446e0020f0
content_type: application/pdf
creator: dernst
date_created: 2025-06-25T08:38:02Z
date_updated: 2025-06-25T08:38:02Z
file_id: '19901'
file_name: 2025_AstronomyAstrophysics_Britavskiy.pdf
file_size: 7106568
relation: main_file
success: 1
file_date_updated: 2025-06-25T08:38:02Z
fulldoi: https://doi.org/10.1051/0004-6361/202452963
has_accepted_license: '1'
intvolume: ' 698'
isi: 1
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: Astronomy & Astrophysics
publication_identifier:
eissn:
- 1432-0746
issn:
- 0004-6361
publication_status: published
publisher: EDP Sciences
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: 'Binarity at LOw Metallicity (BLOeM): Multiplicity of early B-type supergiants
in the Small Magellanic Cloud'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 698
year: '2025'
...
---
OA_place: publisher
OA_type: diamond
_id: '19797'
abstract:
- lang: eng
text: Stars stripped of their hydrogen-rich envelopes through binary interaction
are thought to be responsible for both hydrogen-poor supernovae and the hard ionizing
radiation observed in low-Z galaxies. A population of these stars was recently
observed for the first time, but their prevalence remains unknown. In preparation
for such measurements, we estimate the mass distribution of hot, stripped stars
using a population synthesis code that interpolates over detailed single and binary
stellar evolution tracks. We predict that for a constant star formation rate of
1 M⊙/yr and regardless of metallicity, a scalable model population contains ∼30
000 stripped stars with mass Mstrip > 1 M⊙ and ∼4000 stripped stars that are sufficiently
massive to explode (Mstrip > 2.6 M⊙). Below Mstrip = 5 M⊙, the distribution is
metallicity-independent and can be described by a power law with the exponent
α ∼ −2. At higher masses and lower metallicity (Z ≲ 0.002), the mass distribution
exhibits a drop. This originates from the prediction, frequently seen in evolutionary
models, that massive low-metallicity stars do not expand substantially until central
helium burning or later and therefore cannot form long-lived stripped stars. With
weaker line-driven winds at low metallicity, this suggests that neither binary
interaction nor wind mass loss can efficiently strip massive stars at low metallicity.
As a result, a “helium-star desert” emerges around Mstrip = 15 M⊙ at Z = 0.002,
covering an increasingly large mass range with decreasing metallicity. We note
that these high-mass stars are those that potentially boost a galaxy’s He+-ionizing
radiation and that participate in the formation of merging black holes. This “helium-star
desert” therefore merits further study.
acknowledgement: We thank the anonymous referee for providing a constructive report.
We thank Tomer Shenar and Selma de Mink for the interesting discussions that helped
us improve the content of Sect. 4. Thank you to Jorick Vink and Andreas Sander for
helpful discussions about wind driving. BHA thanks the Caltech Summer Undergraduate
Research Fellowship (SURF) program and Peter Adams for supporting this project in
memory of Alain Porter and Arthur R. Adams. BHA thanks Gwen Rudie for organizing
the Carnegie Astrophysics Summer Student Internship (CASSI) program and all the
staff at Carnegie Observatories who help to support this program. BHA also thanks
Laura Jaliff, Sal Wanying Fu, Ivanna Escala, Johanna Teske, Tony Piro, Brian Lorenz,
and Peter Senchyna for their mentorship during this project. Computing resources
used for this work were made possible by a grant from the Ahmanson Foundation. We
thank the Observatories of the Carnegie Institution for Science for support, including
Chris Burns for help with computations. This work used computing resources provided
by Northwestern University and the Center for Interdisciplinary Exploration and
Research in Astrophysics (CIERA). This research was supported in part through the
computational resources and staff contributions provided for the Quest high performance
computing facility at Northwestern University which is jointly supported by the
Office of the Provost, the Office for Research, and Northwestern University Information
Technology. MRD acknowledges support from the NSERC through grant RGPIN-2019-06186,
the Canada Research Chairs Program, and the Dunlap Institute at the University of
Toronto. BHA is supported by the National Science Foundation Graduate Research Fellowship
under Grant No. DGE-2234667.
article_number: A239
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: B.
full_name: Hovis-Afflerbach, B.
last_name: Hovis-Afflerbach
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: A.
full_name: Schootemeijer, A.
last_name: Schootemeijer
- first_name: J.
full_name: Klencki, J.
last_name: Klencki
- first_name: A. L.
full_name: Strom, A. L.
last_name: Strom
- first_name: B. A.
full_name: Ludwig, B. A.
last_name: Ludwig
- first_name: M. R.
full_name: Drout, M. R.
last_name: Drout
citation:
ama: 'Hovis-Afflerbach B, Götberg YLL, Schootemeijer A, et al. The mass distribution
of stars stripped in binaries: The effect of metallicity. Astronomy & Astrophysics.
2025;697. doi:10.1051/0004-6361/202453185'
apa: 'Hovis-Afflerbach, B., Götberg, Y. L. L., Schootemeijer, A., Klencki, J., Strom,
A. L., Ludwig, B. A., & Drout, M. R. (2025). The mass distribution of stars
stripped in binaries: The effect of metallicity. Astronomy & Astrophysics.
EDP Sciences. https://doi.org/10.1051/0004-6361/202453185'
chicago: 'Hovis-Afflerbach, B., Ylva Louise Linsdotter Götberg, A. Schootemeijer,
J. Klencki, A. L. Strom, B. A. Ludwig, and M. R. Drout. “The Mass Distribution
of Stars Stripped in Binaries: The Effect of Metallicity.” Astronomy &
Astrophysics. EDP Sciences, 2025. https://doi.org/10.1051/0004-6361/202453185.'
ieee: 'B. Hovis-Afflerbach et al., “The mass distribution of stars stripped
in binaries: The effect of metallicity,” Astronomy & Astrophysics,
vol. 697. EDP Sciences, 2025.'
ista: 'Hovis-Afflerbach B, Götberg YLL, Schootemeijer A, Klencki J, Strom AL, Ludwig
BA, Drout MR. 2025. The mass distribution of stars stripped in binaries: The effect
of metallicity. Astronomy & Astrophysics. 697, A239.'
mla: 'Hovis-Afflerbach, B., et al. “The Mass Distribution of Stars Stripped in Binaries:
The Effect of Metallicity.” Astronomy & Astrophysics, vol. 697, A239,
EDP Sciences, 2025, doi:10.1051/0004-6361/202453185.'
short: B. Hovis-Afflerbach, Y.L.L. Götberg, A. Schootemeijer, J. Klencki, A.L. Strom,
B.A. Ludwig, M.R. Drout, Astronomy & Astrophysics 697 (2025).
corr_author: '1'
das_tickbox: '0'
date_created: 2025-06-08T22:01:22Z
date_published: 2025-05-01T00:00:00Z
date_updated: 2026-09-16T09:06:06Z
day: '01'
ddc:
- '520'
department:
- _id: YlGo
doi: 10.1051/0004-6361/202453185
external_id:
arxiv:
- '2412.05356'
isi:
- '001494033100007'
file:
- access_level: open_access
checksum: caa92beb22ab3146a75c5b03e926de1f
content_type: application/pdf
creator: dernst
date_created: 2025-06-10T07:00:38Z
date_updated: 2025-06-10T07:00:38Z
file_id: '19799'
file_name: 2025_AstronomyAstrophysics_HovisAfflerbach.pdf
file_size: 6378030
relation: main_file
success: 1
file_date_updated: 2025-06-10T07:00:38Z
fulldoi: https://doi.org/10.1051/0004-6361/202453185
has_accepted_license: '1'
intvolume: ' 697'
isi: 1
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
publication: Astronomy & Astrophysics
publication_identifier:
eissn:
- 1432-0746
issn:
- 0004-6361
publication_status: published
publisher: EDP Sciences
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: 'The mass distribution of stars stripped in binaries: The effect of metallicity'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 697
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '22933'
abstract:
- lang: eng
text: "The HST spectra obtained for MWC656 and spectral data used for comparison
in the publication.\r\nThis DOI is provided by the MAST archive at Space Telescope
Science Institute"
article_processing_charge: No
author:
- first_name: Johanna
full_name: Mueller-Horn, Johanna
last_name: Mueller-Horn
citation:
ama: Mueller-Horn J. MWC656 Analysis. 2025. doi:10.17909/cfms-dg96
apa: Mueller-Horn, J. (2025). MWC656 Analysis. Repository. https://doi.org/10.17909/cfms-dg96
chicago: Mueller-Horn, Johanna. “MWC656 Analysis.” Repository, 2025. https://doi.org/10.17909/cfms-dg96.
ieee: J. Mueller-Horn, “MWC656 Analysis.” Repository, 2025.
ista: Mueller-Horn J. 2025. MWC656 Analysis, Repository, 10.17909/cfms-dg96.
mla: Mueller-Horn, Johanna. MWC656 Analysis. Repository, 2025, doi:10.17909/cfms-dg96.
short: J. Mueller-Horn, (2025).
date_created: 2026-09-16T08:51:40Z
date_published: 2025-07-05T00:00:00Z
date_updated: 2026-09-16T08:56:13Z
day: '05'
ddc:
- '520'
department:
- _id: YlGo
doi: 10.17909/cfms-dg96
fulldoi: https://doi.org/10.17909/cfms-dg96
main_file_link:
- open_access: '1'
url: https://doi.org/10.17909/cfms-dg96
month: '07'
oa: 1
oa_version: None
publisher: Repository
related_material:
record:
- id: '22816'
relation: used_in_publication
status: public
status: public
title: MWC656 Analysis
type: research_data_reference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
year: '2025'
...
---
OA_place: publisher
OA_type: diamond
_id: '19844'
abstract:
- lang: eng
text: "Context. Rapidly rotating classical OBe stars have been proposed as the products
of binary interactions, and the fraction of Be stars with compact companions implies
that at least some are. However, to constrain the interaction physics spinning
up the OBe stars, a large sample of homogeneously analyzed OBe stars with well-determined
binary characteristics and orbital parameters are required.\r\n\r\nAims. We investigated
the multiplicity properties of a sample of 18 Oe, 62 Be, and two Of?p stars observed
within the BLOeM survey in the Small Magellanic Cloud. We analyzed the first nine
epochs of spectroscopic observations obtained over approximately three months
in 2023.\r\n\r\nMethods. Radial velocities (RVs) of all stars were measured using
cross-correlation based on different sets of absorption and emission lines. Applying
commonly used binarity criteria, we classified objects as binaries, binary candidates,
and apparently single (RV stable) objects. We further inspected the spectra for
double-lined spectroscopic binaries and cross-matched with catalogs of X-ray sources
and photometric binaries.\r\n\r\nResults. We classify 14 OBe stars as binaries,
and an additional 11 as binary candidates. The two Of?p stars are apparently single.
We find two more objects that are most likely currently interacting binaries.
Without those, the observed binary fraction for the remaining OBe sample of 78
stars is fobs+candOBe = 0.18 ± 0.04 (fobs+candOBe = 0.32±0.05 including candidates).
This binary fraction is less than half of that measured for OB stars in BLOeM.
Combined with the lower fraction of SB2s, this suggests that OBe stars do indeed
have fundamentally different present-day binary properties than OB stars. We find
no evidence for OBe binaries with massive compact companions, in contrast to expectations
from binary population synthesis.\r\n\r\nConclusions. Our results support the
binary scenario as an important formation channel for OBe stars, as post-interaction
binaries may have been disrupted or the stripped companions of OBe stars are harder
to detect. Further observations are required to characterize the detected binaries,
their orbital parameters, and the nature of their companions."
acknowledgement: 'The research leading to these results has received funding from
the European Research Council (ERC) under the European Union’s Horizon 2020 and
Horizon Europe research and innovation programme (grant agreement numbers 772225:
MULTIPLES, and 945806) and is supported by the Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation) under Germany’s Excellence Strategy EXC 2181/1-390900948
(the Heidelberg STRUCTURES Excellence Cluster). DMB gratefully acknowledges funding
from UK Research and Innovation (UKRI) in the form of a Frontier Research grant
under the UK government’s ERC Horizon Europe funding guarantee (SYMPHONY; grant
number: EP/Y031059/1), and a Royal Society University Research Fellowship (URF;
grant number: URF\R1\231631). RGI is funded by STFC grant ST/Y002350/1 as part of
the BRIDGCE UK network, and thanks IReNA colleagues for stimulating discussions.
Z.K. acknowledges support from JSPS Kakenhi Grant-in-Aid for Scientific Research
(23K19071). IM acknowledges support from the Australian Research Council (ARC) Centre
of Excellence for GravitationalWave Discovery (OzGrav), through project number CE230100016.
DP acknowledges financial support by the Deutsches Zentrum für Luft und Raumfahrt
(DLR) grant FKZ 50OR2005. DFR is thankful for the support of CAPES-Br and FAPERJ/DSC-10
(SEI-260003/001630/2023). AACS and VR are supported by the German Deutsche Forschungsgemeinschaft
(DFG) under Project-ID 445674056 (Emmy Noether Research Group SA4064/1-1, PI Sander).
AACS and VR are further supported by funding from the Federal Ministry of Education
and Research (BMBF) and the Baden-Württemberg Ministry of Science as part of the
Excellence Strategy of the German Federal and State Governments. JIV acknowledges
support from the European Research Council for the ERC Advanced Grant 101054731.
LRP acknowledges support from grant PID2022-140483NB-C22 funded by MCIN/AEI/10.13039/501100011033.
GH acknowledges support from grants PID2021-122397NB-C21/PID2022-136640NB-C22 funded
by MCIN/AEI/FEDER/10.13039/501100011033. J.K. thanks for the support of a grant
GA CR 22-34467S. This project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement 101164755/METAL) and was supported by the Israel Science Foundation
(ISF) under grant number 2434/24.'
article_number: A38
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: J.
full_name: Bodensteiner, J.
last_name: Bodensteiner
- first_name: T.
full_name: Shenar, T.
last_name: Shenar
- first_name: H.
full_name: Sana, H.
last_name: Sana
- first_name: N.
full_name: Britavskiy, N.
last_name: Britavskiy
- first_name: P. A.
full_name: Crowther, P. A.
last_name: Crowther
- first_name: N.
full_name: Langer, N.
last_name: Langer
- first_name: D. J.
full_name: Lennon, D. J.
last_name: Lennon
- first_name: L.
full_name: Mahy, L.
last_name: Mahy
- first_name: L. R.
full_name: Patrick, L. R.
last_name: Patrick
- first_name: J. I.
full_name: Villaseñor, J. I.
last_name: Villaseñor
- first_name: M.
full_name: Abdul-Masih, M.
last_name: Abdul-Masih
- first_name: D. M.
full_name: Bowman, D. M.
last_name: Bowman
- first_name: A.
full_name: De Koter, A.
last_name: De Koter
- first_name: S. E.
full_name: De Mink, S. E.
last_name: De Mink
- first_name: K.
full_name: Deshmukh, K.
last_name: Deshmukh
- first_name: M.
full_name: Fabry, M.
last_name: Fabry
- first_name: A.
full_name: Gilkis, A.
last_name: Gilkis
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: G.
full_name: Holgado, G.
last_name: Holgado
- first_name: R. G.
full_name: Izzard, R. G.
last_name: Izzard
- first_name: S.
full_name: Janssens, S.
last_name: Janssens
- first_name: V. M.
full_name: Kalari, V. M.
last_name: Kalari
- first_name: Z.
full_name: Keszthelyi, Z.
last_name: Keszthelyi
- first_name: J.
full_name: Kubát, J.
last_name: Kubát
- first_name: I.
full_name: Mandel, I.
last_name: Mandel
- first_name: G.
full_name: Maravelias, G.
last_name: Maravelias
- first_name: L. M.
full_name: Oskinova, L. M.
last_name: Oskinova
- first_name: D.
full_name: Pauli, D.
last_name: Pauli
- first_name: V.
full_name: Ramachandran, V.
last_name: Ramachandran
- first_name: D. F.
full_name: Rocha, D. F.
last_name: Rocha
- first_name: M.
full_name: Renzo, M.
last_name: Renzo
- first_name: A. A.C.
full_name: Sander, A. A.C.
last_name: Sander
- first_name: F. R.N.
full_name: Schneider, F. R.N.
last_name: Schneider
- first_name: A.
full_name: Schootemeijer, A.
last_name: Schootemeijer
- first_name: K.
full_name: Sen, K.
last_name: Sen
- first_name: M.
full_name: Stoop, M.
last_name: Stoop
- first_name: S.
full_name: Toonen, S.
last_name: Toonen
- first_name: J. T.
full_name: Van Loon, J. T.
last_name: Van Loon
- first_name: R.
full_name: Valli, R.
last_name: Valli
- first_name: A.
full_name: Vigna-Gómez, A.
last_name: Vigna-Gómez
- first_name: J. S.
full_name: Vink, J. S.
last_name: Vink
- first_name: C.
full_name: Wang, C.
last_name: Wang
- first_name: X. T.
full_name: Xu, X. T.
last_name: Xu
citation:
ama: 'Bodensteiner J, Shenar T, Sana H, et al. Binarity at LOw Metallicity (BLOeM):
Multiplicity properties of Oe and Be stars. Astronomy & Astrophysics.
2025;698. doi:10.1051/0004-6361/202452623'
apa: 'Bodensteiner, J., Shenar, T., Sana, H., Britavskiy, N., Crowther, P. A., Langer,
N., … Xu, X. T. (2025). Binarity at LOw Metallicity (BLOeM): Multiplicity properties
of Oe and Be stars. Astronomy & Astrophysics. EDP Sciences. https://doi.org/10.1051/0004-6361/202452623'
chicago: 'Bodensteiner, J., T. Shenar, H. Sana, N. Britavskiy, P. A. Crowther, N.
Langer, D. J. Lennon, et al. “Binarity at LOw Metallicity (BLOeM): Multiplicity
Properties of Oe and Be Stars.” Astronomy & Astrophysics. EDP Sciences,
2025. https://doi.org/10.1051/0004-6361/202452623.'
ieee: 'J. Bodensteiner et al., “Binarity at LOw Metallicity (BLOeM): Multiplicity
properties of Oe and Be stars,” Astronomy & Astrophysics, vol. 698.
EDP Sciences, 2025.'
ista: 'Bodensteiner J, Shenar T, Sana H, Britavskiy N, Crowther PA, Langer N, Lennon
DJ, Mahy L, Patrick LR, Villaseñor JI, Abdul-Masih M, Bowman DM, De Koter A, De
Mink SE, Deshmukh K, Fabry M, Gilkis A, Götberg YLL, Holgado G, Izzard RG, Janssens
S, Kalari VM, Keszthelyi Z, Kubát J, Mandel I, Maravelias G, Oskinova LM, Pauli
D, Ramachandran V, Rocha DF, Renzo M, Sander AAC, Schneider FRN, Schootemeijer
A, Sen K, Stoop M, Toonen S, Van Loon JT, Valli R, Vigna-Gómez A, Vink JS, Wang
C, Xu XT. 2025. Binarity at LOw Metallicity (BLOeM): Multiplicity properties of
Oe and Be stars. Astronomy & Astrophysics. 698, A38.'
mla: 'Bodensteiner, J., et al. “Binarity at LOw Metallicity (BLOeM): Multiplicity
Properties of Oe and Be Stars.” Astronomy & Astrophysics, vol. 698,
A38, EDP Sciences, 2025, doi:10.1051/0004-6361/202452623.'
short: J. Bodensteiner, T. Shenar, H. Sana, N. Britavskiy, P.A. Crowther, N. Langer,
D.J. Lennon, L. Mahy, L.R. Patrick, J.I. Villaseñor, M. Abdul-Masih, D.M. Bowman,
A. De Koter, S.E. De Mink, K. Deshmukh, M. Fabry, A. Gilkis, Y.L.L. Götberg, G.
Holgado, R.G. Izzard, S. Janssens, V.M. Kalari, Z. Keszthelyi, J. Kubát, I. Mandel,
G. Maravelias, L.M. Oskinova, D. Pauli, V. Ramachandran, D.F. Rocha, M. Renzo,
A.A.C. Sander, F.R.N. Schneider, A. Schootemeijer, K. Sen, M. Stoop, S. Toonen,
J.T. Van Loon, R. Valli, A. Vigna-Gómez, J.S. Vink, C. Wang, X.T. Xu, Astronomy
& Astrophysics 698 (2025).
das_tickbox: '1'
date_created: 2025-06-15T22:01:30Z
date_published: 2025-06-01T00:00:00Z
date_updated: 2026-09-16T09:14:49Z
day: '01'
ddc:
- '520'
department:
- _id: YlGo
doi: 10.1051/0004-6361/202452623
external_id:
arxiv:
- '2502.02641'
isi:
- '001497903100011'
file:
- access_level: open_access
checksum: 51d79c82f6030180fb7c5d7ba01b2da8
content_type: application/pdf
creator: dernst
date_created: 2025-06-23T07:54:57Z
date_updated: 2025-06-23T07:54:57Z
file_id: '19866'
file_name: 2025_AstronomyAstrophysics_Bodensteiner.pdf
file_size: 2404827
relation: main_file
success: 1
file_date_updated: 2025-06-23T07:54:57Z
fulldoi: https://doi.org/10.1051/0004-6361/202452623
has_accepted_license: '1'
intvolume: ' 698'
isi: 1
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: Astronomy & Astrophysics
publication_identifier:
eissn:
- 1432-0746
issn:
- 0004-6361
publication_status: published
publisher: EDP Sciences
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: yes
title: 'Binarity at LOw Metallicity (BLOeM): Multiplicity properties of Oe and Be
stars'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 698
year: '2025'
...
---
OA_place: publisher
OA_type: diamond
_id: '19842'
abstract:
- lang: eng
text: Given the uncertain evolutionary status of blue supergiant stars, their multiplicity
properties hold vital clues to better understand their origin and evolution. As
part of The Binarity at LOw Metallicity (BLOeM) campaign in the Small Magellanic
Cloud, we present a multi-epoch spectroscopic survey of 128 supergiant stars of
spectral type B5–F5, which roughly correspond to initial masses in the 6–30 M⊙
range. The observed binary fraction for the B5–9 supergiants is 25 ± 6% (10 ±
4%) and 5 ± 2% (0%) for the A–F stars, which were found using a radial-velocity
(RV) variability threshold of 5 km s−1 (10 km s−1) as a criterion for binarity.
Accounting for observational biases, we find an intrinsic multiplicity fraction
of less than 18% for the B5–9 stars and 8−7+9% for the AF stars, for the orbital
periods up to 103.5 days and mass ratios (q) in the 0.1 < q < 1 range. The large
stellar radii of these supergiant stars prevent short orbital periods, but we
demonstrate that this effect alone cannot explain our results. We assessed the
spectra and RV time series of the detected binary systems and find that only a
small fraction display convincing solutions. We conclude that the multiplicity
fractions are compromised by intrinsic stellar variability, such that the true
multiplicity fraction may be significantly smaller. Our main conclusions from
comparing the multiplicity properties of the B5–9- and AF-type supergiants to
that of their less evolved counterparts is that such stars cannot be explained
by a direct evolution from the main sequence. Furthermore, by comparing their
multiplicity properties to red supergiant stars, we conclude that the AF supergiant
stars are neither progenitors nor descendants of red supergiants.
acknowledgement: 'We thank Sipra Hota for kindly sharing the SMC UVIT catalogue prior
to publication. LRP, FN. and FT acknowledge support by grants PID2019-105552RB-C41
and PID2022-137779OB-C41 funded by MCIN/AEI/10.13039/501100011033 by “ERDF A way
of making Europe”. LRP acknowledges support from grant PID2022-140483NB-C22 funded
by MCIN/AEI/10.13039/501100011033. TS acknowledges support by the Israel Science
Foundation (ISF) under grant number 0603225041. The research leading to these results
has received funding from the European Research Council (ERC) under the European
Union’s Horizon 2020 research and innovation programme (grant agreement numbers
772225: MULTIPLES). DMB gratefully acknowledges support from UK Research and Innovation
(UKRI) in the form of a Frontier Research grant under the UK government’s ERC Horizon
Europe funding guarantee (SYMPHONY; grant number: EP/Y031059/1), and a Royal Society
University Research Fellowship (grant number: URF\R1\231631). GGT is supported by
the German Deutsche Forschungsgemeinschaft (DFG) under Project-ID 496854903 (SA4064/2-1,
PI Sander). AACS is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research
Foundation) in the form of an Emmy Noether Research Group – Project-ID 445674056
(SA4064/1-1, PI Sander). GGT and AACS further acknowledges support from the Federal
Ministry of Education and Research (BMBF) and the Baden-Württemberg Ministry of
Science as part of the Excellence Strategy of the German Federal and State Governments.
This paper benefited from discussions at the International Space Science Institute
(ISSI) in Bern through ISSI International Team project 512 (Multiwavelength View
on Massive Stars in the Era of Multimessenger Astronomy). DP acknowledges financial
support by the Deutsches Zentrum für Luft und Raumfahrt (DLR) grant FKZ 50OR2005.
JIV acknowledges support from the European Research Council for the ERC Advanced
Grant 101054731. PAC is supported by the Science and Technology Facilities Council
research grant ST/V000853/1 (PI. V. Dhillon). JSV is supported by Science and Technology
Facilities Council funding under grant number ST/V000233/1. DFR is thankful for
the support of the CAPES-Br and FAPERJ/DSC-10 (SEI-260003/001630/2023). This work
has received funding from the European Research Council (ERC) under the European
Union’s Horizon 2020 research and innovation programme (Grant agreement No. 945806)
and is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
under Germany’s Excellence Strategy EXC 2181/1-390900948 (the Heidelberg STRUCTURES
Excellence Cluster).'
article_number: A39
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: L. R.
full_name: Patrick, L. R.
last_name: Patrick
- first_name: D. J.
full_name: Lennon, D. J.
last_name: Lennon
- first_name: F.
full_name: Najarro, F.
last_name: Najarro
- first_name: T.
full_name: Shenar, T.
last_name: Shenar
- first_name: J.
full_name: Bodensteiner, J.
last_name: Bodensteiner
- first_name: H.
full_name: Sana, H.
last_name: Sana
- first_name: P. A.
full_name: Crowther, P. A.
last_name: Crowther
- first_name: N.
full_name: Britavskiy, N.
last_name: Britavskiy
- first_name: N.
full_name: Langer, N.
last_name: Langer
- first_name: A.
full_name: Schootemeijer, A.
last_name: Schootemeijer
- first_name: C. J.
full_name: Evans, C. J.
last_name: Evans
- first_name: L.
full_name: Mahy, L.
last_name: Mahy
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: S. E.
full_name: De Mink, S. E.
last_name: De Mink
- first_name: F. R.N.
full_name: Schneider, F. R.N.
last_name: Schneider
- first_name: A. J.G.
full_name: O’Grady, A. J.G.
last_name: O’Grady
- first_name: J. I.
full_name: Villaseñor, J. I.
last_name: Villaseñor
- first_name: M.
full_name: Bernini-Peron, M.
last_name: Bernini-Peron
- first_name: D. M.
full_name: Bowman, D. M.
last_name: Bowman
- first_name: A.
full_name: De Koter, A.
last_name: De Koter
- first_name: K.
full_name: Deshmukh, K.
last_name: Deshmukh
- first_name: A.
full_name: Gilkis, A.
last_name: Gilkis
- first_name: G.
full_name: González-Torà, G.
last_name: González-Torà
- first_name: V. M.
full_name: Kalari, V. M.
last_name: Kalari
- first_name: Z.
full_name: K̃Eszthelyi, Z.
last_name: K̃Eszthelyi
- first_name: I.
full_name: Mandel, I.
last_name: Mandel
- first_name: A.
full_name: Menon, A.
last_name: Menon
- first_name: M.
full_name: Moe, M.
last_name: Moe
- first_name: L. M.
full_name: Oskinova, L. M.
last_name: Oskinova
- first_name: D.
full_name: Pauli, D.
last_name: Pauli
- first_name: M.
full_name: Renzo, M.
last_name: Renzo
- first_name: A. A.C.
full_name: Sander, A. A.C.
last_name: Sander
- first_name: K.
full_name: Sen, K.
last_name: Sen
- first_name: M.
full_name: Stoop, M.
last_name: Stoop
- first_name: J. T.
full_name: Van Loon, J. T.
last_name: Van Loon
- first_name: S.
full_name: Toonen, S.
last_name: Toonen
- first_name: F.
full_name: Tramper, F.
last_name: Tramper
- first_name: J. S.
full_name: Vink, J. S.
last_name: Vink
- first_name: C.
full_name: Wang, C.
last_name: Wang
citation:
ama: 'Patrick LR, Lennon DJ, Najarro F, et al. Binarity at LOw Metallicity (BLOeM):
The multiplicity properties and evolution of BAF-type supergiants. Astronomy
& Astrophysics. 2025;698. doi:10.1051/0004-6361/202452949'
apa: 'Patrick, L. R., Lennon, D. J., Najarro, F., Shenar, T., Bodensteiner, J.,
Sana, H., … Wang, C. (2025). Binarity at LOw Metallicity (BLOeM): The multiplicity
properties and evolution of BAF-type supergiants. Astronomy & Astrophysics.
EDP Sciences. https://doi.org/10.1051/0004-6361/202452949'
chicago: 'Patrick, L. R., D. J. Lennon, F. Najarro, T. Shenar, J. Bodensteiner,
H. Sana, P. A. Crowther, et al. “Binarity at LOw Metallicity (BLOeM): The Multiplicity
Properties and Evolution of BAF-Type Supergiants.” Astronomy & Astrophysics.
EDP Sciences, 2025. https://doi.org/10.1051/0004-6361/202452949.'
ieee: 'L. R. Patrick et al., “Binarity at LOw Metallicity (BLOeM): The multiplicity
properties and evolution of BAF-type supergiants,” Astronomy & Astrophysics,
vol. 698. EDP Sciences, 2025.'
ista: 'Patrick LR, Lennon DJ, Najarro F, Shenar T, Bodensteiner J, Sana H, Crowther
PA, Britavskiy N, Langer N, Schootemeijer A, Evans CJ, Mahy L, Götberg YLL, De
Mink SE, Schneider FRN, O’Grady AJG, Villaseñor JI, Bernini-Peron M, Bowman DM,
De Koter A, Deshmukh K, Gilkis A, González-Torà G, Kalari VM, K̃Eszthelyi Z, Mandel
I, Menon A, Moe M, Oskinova LM, Pauli D, Renzo M, Sander AAC, Sen K, Stoop M,
Van Loon JT, Toonen S, Tramper F, Vink JS, Wang C. 2025. Binarity at LOw Metallicity
(BLOeM): The multiplicity properties and evolution of BAF-type supergiants. Astronomy
& Astrophysics. 698, A39.'
mla: 'Patrick, L. R., et al. “Binarity at LOw Metallicity (BLOeM): The Multiplicity
Properties and Evolution of BAF-Type Supergiants.” Astronomy & Astrophysics,
vol. 698, A39, EDP Sciences, 2025, doi:10.1051/0004-6361/202452949.'
short: L.R. Patrick, D.J. Lennon, F. Najarro, T. Shenar, J. Bodensteiner, H. Sana,
P.A. Crowther, N. Britavskiy, N. Langer, A. Schootemeijer, C.J. Evans, L. Mahy,
Y.L.L. Götberg, S.E. De Mink, F.R.N. Schneider, A.J.G. O’Grady, J.I. Villaseñor,
M. Bernini-Peron, D.M. Bowman, A. De Koter, K. Deshmukh, A. Gilkis, G. González-Torà,
V.M. Kalari, Z. K̃Eszthelyi, I. Mandel, A. Menon, M. Moe, L.M. Oskinova, D. Pauli,
M. Renzo, A.A.C. Sander, K. Sen, M. Stoop, J.T. Van Loon, S. Toonen, F. Tramper,
J.S. Vink, C. Wang, Astronomy & Astrophysics 698 (2025).
das_tickbox: '1'
date_created: 2025-06-15T22:01:29Z
date_published: 2025-06-01T00:00:00Z
date_updated: 2026-09-16T09:11:14Z
day: '01'
ddc:
- '520'
department:
- _id: YlGo
doi: 10.1051/0004-6361/202452949
external_id:
arxiv:
- '2502.02644'
isi:
- '001497903100028'
file:
- access_level: open_access
checksum: 93a907bf48da7e2ba7d75b53ea6011f5
content_type: application/pdf
creator: dernst
date_created: 2025-06-23T07:09:38Z
date_updated: 2025-06-23T07:09:38Z
file_id: '19863'
file_name: 2025_AstronomyAstrophysics_Patrick.pdf
file_size: 2130448
relation: main_file
success: 1
file_date_updated: 2025-06-23T07:09:38Z
fulldoi: https://doi.org/10.1051/0004-6361/202452949
has_accepted_license: '1'
intvolume: ' 698'
isi: 1
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: Astronomy & Astrophysics
publication_identifier:
eissn:
- 1432-0746
issn:
- 0004-6361
publication_status: published
publisher: EDP Sciences
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: 'Binarity at LOw Metallicity (BLOeM): The multiplicity properties and evolution
of BAF-type supergiants'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 698
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '20352'
abstract:
- lang: eng
text: "At high metallicity, a majority of massive stars have at least one close
stellar companion. The evolution of such binaries is subject to strong interaction
processes, which heavily impact the characteristics of their life-ending supernova
and compact remnants. For the low-metallicity environments of high-redshift galaxies,
constraints on the multiplicity properties of massive stars over the separation
range leading to binary interaction are crucially missing. Here we show that the
presence of massive stars in close binaries is ubiquitous, even at low metallicity.
Using the Very Large Telescope, we obtained multi-epoch radial velocity measurements
of a representative sample of 139 massive O-type stars across the Small Magellanic
Cloud, which has a metal content of about one-fifth of the solar value. We find
that 45% of them show radial velocity variations that demonstrate that they are
members of close binary systems, and predominantly have orbital periods shorter
than 1 year. Correcting for observational biases indicates that at least 70+11−6
% of the O stars in our sample are in close binaries, and that at least 68+7\r\n−8%
of all O stars interact with a companion star during their lifetime. We found
no evidence supporting a statistically significant trend of the multiplicity properties
with metallicity. Our results indicate that multiplicity and binary interactions
govern the evolution of massive stars and determine their cosmic feedback and
explosive fates."
acknowledgement: 'Based on data collected at the European Southern Observatory (ESO)
under programme ID 112.25R7. The research leading to these results has received
funding from the European Research Council (ERC) under the European Union’s Horizon
2020 and Horizon Europe research and innovation programme (grant agreement numbers
772225: MULTIPLES, 772086: ASSESS and 945806: TEL-STARS, ADG101054731: Stellar-BHs-SDSS-V,
and 101164755: METAL). This research was supported by the Israel Science Foundation
(ISF) under grant number 0603225041. We acknowledge support from the Science and
Technology Facilities Council (research grant ST/V000853/1 and ST/V000233/1), UK
Research and Innovation (UKRI) and the UK government’s ERC Horizon Europe funding
guarantee (grant number EP/Y031059/1), a Royal Society University Research Fellowship
(grant number URF\R1\231631), a Royal Society–Science Foundation Ireland University
Research Fellowship, the German Deutsche Forschungsgemeinschaft (Project-ID 496854903,
445674056 and 443790621, Germany’s Excellence Strategy EXC 2181/1-390900948), the
Klaus Tschira Foundation, the JSPS Kakenhi Grant-in-Aid for Scientific Research
(23K19071) and international fellowships (at the Graduate school of Science, Tokyo
University), the Australian Research Council (ARC) Centre of Excellence for Gravitational
Wave Discovery (OzGrav; project number CE230100016), the Deutsches Zentrum für Luft
und Raumfahrt (DLR) grants FKZ 50OR2005 and 50OR2306, Agencia Española de Investigación
(AEI) of the Spanish Ministerio de Ciencia Innovación y Universidades (MICIU) and
the European Regional Development Fund, FEDER and Severo Ochoa Programme (grants
PID2021-122397NB-C21 and CEX2019-000920-S), the NextGeneration EU/PRTR and MIU (UNI/551/2021)
trough grant Margarita Salas-UL, the CAPES-Br and FAPERJ/DSC-10 (SEI-260003/001630/2023),
MCIN/AEI/10.13039/501100011033 by ‘ERDF A way of making Europe’ (grants PID2019-105552RB-C41
and PID2022-137779OB-C41, PID2021-125485NB-C22, CEX2019-000918-M) funded by MCIN/AEI/10.13039/501100011033
(State Agency for Research of the Spanish Ministry of Science and Innovation) and
SGR-2021-01069 (AGAUR), the Spanish Government Ministerio de Ciencia e Innovación
and Agencia Estatal de Investigación (10.13 039/501 100 011 033; grant PID2022-136
640 NB-C22), the Consejo Superior de Investigaciones Científicas (CSIC; grant 2022-AEP
005), the Polish National Agency for Academic Exchange (BEKKER fellowship BPN/BEK/2022/1/00106)
and National Science Center (NCN, Poland; grant number OPUS 2021/41/B/ST9/00757),
the ‘La Caixa’ Foundation (ID 100010434) under the fellowship code LCF/BQ/PI23/11970035,
the Research foundation Flanders (FWO) PhD fellowship under project 11E1721N and
senior postdoctoral fellowship under number 12ZY523N, and the Netherlands Research
Council NWO (VIDI 203.061 grant).'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: H.
full_name: Sana, H.
last_name: Sana
- first_name: T.
full_name: Shenar, T.
last_name: Shenar
- first_name: J.
full_name: Bodensteiner, J.
last_name: Bodensteiner
- first_name: N.
full_name: Britavskiy, N.
last_name: Britavskiy
- first_name: N.
full_name: Langer, N.
last_name: Langer
- first_name: D. J.
full_name: Lennon, D. J.
last_name: Lennon
- first_name: L.
full_name: Mahy, L.
last_name: Mahy
- first_name: I.
full_name: Mandel, I.
last_name: Mandel
- first_name: S. E.
full_name: De Mink, S. E.
last_name: De Mink
- first_name: L. R.
full_name: Patrick, L. R.
last_name: Patrick
- first_name: J. I.
full_name: Villaseñor, J. I.
last_name: Villaseñor
- first_name: M.
full_name: Dirickx, M.
last_name: Dirickx
- first_name: M.
full_name: Abdul-Masih, M.
last_name: Abdul-Masih
- first_name: L. A.
full_name: Almeida, L. A.
last_name: Almeida
- first_name: F.
full_name: Backs, F.
last_name: Backs
- first_name: S. R.
full_name: Berlanas, S. R.
last_name: Berlanas
- first_name: M.
full_name: Bernini-Peron, M.
last_name: Bernini-Peron
- first_name: D. M.
full_name: Bowman, D. M.
last_name: Bowman
- first_name: V. A.
full_name: Bronner, V. A.
last_name: Bronner
- first_name: P. A.
full_name: Crowther, P. A.
last_name: Crowther
- first_name: K.
full_name: Deshmukh, K.
last_name: Deshmukh
- first_name: C. J.
full_name: Evans, C. J.
last_name: Evans
- first_name: M.
full_name: Fabry, M.
last_name: Fabry
- first_name: M.
full_name: Gieles, M.
last_name: Gieles
- first_name: A.
full_name: Gilkis, A.
last_name: Gilkis
- first_name: G.
full_name: González-Torà, G.
last_name: González-Torà
- first_name: G.
full_name: Gräfener, G.
last_name: Gräfener
- first_name: Ylva Louise Linsdotter
full_name: Götberg, Ylva Louise Linsdotter
id: d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d
last_name: Götberg
orcid: 0000-0002-6960-6911
- first_name: C.
full_name: Hawcroft, C.
last_name: Hawcroft
- first_name: V.
full_name: Hénault-Brunet, V.
last_name: Hénault-Brunet
- first_name: A.
full_name: Herrero, A.
last_name: Herrero
- first_name: G.
full_name: Holgado, G.
last_name: Holgado
- first_name: R. G.
full_name: Izzard, R. G.
last_name: Izzard
- first_name: A.
full_name: De Koter, A.
last_name: De Koter
- first_name: S.
full_name: Janssens, S.
last_name: Janssens
- first_name: C.
full_name: Johnston, C.
last_name: Johnston
- first_name: J.
full_name: Josiek, J.
last_name: Josiek
- first_name: S.
full_name: Justham, S.
last_name: Justham
- first_name: V. M.
full_name: Kalari, V. M.
last_name: Kalari
- first_name: J.
full_name: Klencki, J.
last_name: Klencki
- first_name: J.
full_name: Kubát, J.
last_name: Kubát
- first_name: B.
full_name: Kubátová, B.
last_name: Kubátová
- first_name: R. R.
full_name: Lefever, R. R.
last_name: Lefever
- first_name: J. Th
full_name: Van Loon, J. Th
last_name: Van Loon
- first_name: B.
full_name: Ludwig, B.
last_name: Ludwig
- first_name: J.
full_name: Mackey, J.
last_name: Mackey
- first_name: J.
full_name: Maíz Apellániz, J.
last_name: Maíz Apellániz
- first_name: G.
full_name: Maravelias, G.
last_name: Maravelias
- first_name: P.
full_name: Marchant, P.
last_name: Marchant
- first_name: T.
full_name: Mazeh, T.
last_name: Mazeh
- first_name: A.
full_name: Menon, A.
last_name: Menon
- first_name: M.
full_name: Moe, M.
last_name: Moe
- first_name: F.
full_name: Najarro, F.
last_name: Najarro
- first_name: L. M.
full_name: Oskinova, L. M.
last_name: Oskinova
- first_name: R.
full_name: Ovadia, R.
last_name: Ovadia
- first_name: D.
full_name: Pauli, D.
last_name: Pauli
- first_name: M.
full_name: Pawlak, M.
last_name: Pawlak
- first_name: V.
full_name: Ramachandran, V.
last_name: Ramachandran
- first_name: M.
full_name: Renzo, M.
last_name: Renzo
- first_name: D. F.
full_name: Rocha, D. F.
last_name: Rocha
- first_name: A. A.C.
full_name: Sander, A. A.C.
last_name: Sander
- first_name: F. R.N.
full_name: Schneider, F. R.N.
last_name: Schneider
- first_name: A.
full_name: Schootemeijer, A.
last_name: Schootemeijer
- first_name: E. C.
full_name: Schösser, E. C.
last_name: Schösser
- first_name: C.
full_name: Schürmann, C.
last_name: Schürmann
- first_name: K.
full_name: Sen, K.
last_name: Sen
- first_name: S.
full_name: Shahaf, S.
last_name: Shahaf
- first_name: S.
full_name: Simón-Díaz, S.
last_name: Simón-Díaz
- first_name: L. A.C.
full_name: Van Son, L. A.C.
last_name: Van Son
- first_name: M.
full_name: Stoop, M.
last_name: Stoop
- first_name: S.
full_name: Toonen, S.
last_name: Toonen
- first_name: F.
full_name: Tramper, F.
last_name: Tramper
- first_name: R.
full_name: Valli, R.
last_name: Valli
- first_name: A.
full_name: Vigna-Gómez, A.
last_name: Vigna-Gómez
- first_name: J. S.
full_name: Vink, J. S.
last_name: Vink
- first_name: C.
full_name: Wang, C.
last_name: Wang
- first_name: R.
full_name: Willcox, R.
last_name: Willcox
citation:
ama: Sana H, Shenar T, Bodensteiner J, et al. A high fraction of close massive binary
stars at low metallicity. Nature Astronomy. 2025;9:1337-1346. doi:10.1038/s41550-025-02610-x
apa: Sana, H., Shenar, T., Bodensteiner, J., Britavskiy, N., Langer, N., Lennon,
D. J., … Willcox, R. (2025). A high fraction of close massive binary stars at
low metallicity. Nature Astronomy. Springer Nature. https://doi.org/10.1038/s41550-025-02610-x
chicago: Sana, H., T. Shenar, J. Bodensteiner, N. Britavskiy, N. Langer, D. J. Lennon,
L. Mahy, et al. “A High Fraction of Close Massive Binary Stars at Low Metallicity.”
Nature Astronomy. Springer Nature, 2025. https://doi.org/10.1038/s41550-025-02610-x.
ieee: H. Sana et al., “A high fraction of close massive binary stars at low
metallicity,” Nature Astronomy, vol. 9. Springer Nature, pp. 1337–1346,
2025.
ista: Sana H, Shenar T, Bodensteiner J, Britavskiy N, Langer N, Lennon DJ, Mahy
L, Mandel I, De Mink SE, Patrick LR, Villaseñor JI, Dirickx M, Abdul-Masih M,
Almeida LA, Backs F, Berlanas SR, Bernini-Peron M, Bowman DM, Bronner VA, Crowther
PA, Deshmukh K, Evans CJ, Fabry M, Gieles M, Gilkis A, González-Torà G, Gräfener
G, Götberg YLL, Hawcroft C, Hénault-Brunet V, Herrero A, Holgado G, Izzard RG,
De Koter A, Janssens S, Johnston C, Josiek J, Justham S, Kalari VM, Klencki J,
Kubát J, Kubátová B, Lefever RR, Van Loon JT, Ludwig B, Mackey J, Maíz Apellániz
J, Maravelias G, Marchant P, Mazeh T, Menon A, Moe M, Najarro F, Oskinova LM,
Ovadia R, Pauli D, Pawlak M, Ramachandran V, Renzo M, Rocha DF, Sander AAC, Schneider
FRN, Schootemeijer A, Schösser EC, Schürmann C, Sen K, Shahaf S, Simón-Díaz S,
Van Son LAC, Stoop M, Toonen S, Tramper F, Valli R, Vigna-Gómez A, Vink JS, Wang
C, Willcox R. 2025. A high fraction of close massive binary stars at low metallicity.
Nature Astronomy. 9, 1337–1346.
mla: Sana, H., et al. “A High Fraction of Close Massive Binary Stars at Low Metallicity.”
Nature Astronomy, vol. 9, Springer Nature, 2025, pp. 1337–46, doi:10.1038/s41550-025-02610-x.
short: H. Sana, T. Shenar, J. Bodensteiner, N. Britavskiy, N. Langer, D.J. Lennon,
L. Mahy, I. Mandel, S.E. De Mink, L.R. Patrick, J.I. Villaseñor, M. Dirickx, M.
Abdul-Masih, L.A. Almeida, F. Backs, S.R. Berlanas, M. Bernini-Peron, D.M. Bowman,
V.A. Bronner, P.A. Crowther, K. Deshmukh, C.J. Evans, M. Fabry, M. Gieles, A.
Gilkis, G. González-Torà, G. Gräfener, Y.L.L. Götberg, C. Hawcroft, V. Hénault-Brunet,
A. Herrero, G. Holgado, R.G. Izzard, A. De Koter, S. Janssens, C. Johnston, J.
Josiek, S. Justham, V.M. Kalari, J. Klencki, J. Kubát, B. Kubátová, R.R. Lefever,
J.T. Van Loon, B. Ludwig, J. Mackey, J. Maíz Apellániz, G. Maravelias, P. Marchant,
T. Mazeh, A. Menon, M. Moe, F. Najarro, L.M. Oskinova, R. Ovadia, D. Pauli, M.
Pawlak, V. Ramachandran, M. Renzo, D.F. Rocha, A.A.C. Sander, F.R.N. Schneider,
A. Schootemeijer, E.C. Schösser, C. Schürmann, K. Sen, S. Shahaf, S. Simón-Díaz,
L.A.C. Van Son, M. Stoop, S. Toonen, F. Tramper, R. Valli, A. Vigna-Gómez, J.S.
Vink, C. Wang, R. Willcox, Nature Astronomy 9 (2025) 1337–1346.
das_tickbox: '1'
date_created: 2025-09-14T22:01:32Z
date_published: 2025-09-02T00:00:00Z
date_updated: 2026-09-16T10:03:32Z
day: '02'
department:
- _id: YlGo
doi: 10.1038/s41550-025-02610-x
external_id:
arxiv:
- '2509.12488'
isi:
- '001568077900001'
fulldoi: https://doi.org/10.1038/s41550-025-02610-x
intvolume: ' 9'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2509.12488
month: '09'
oa: 1
oa_version: Preprint
page: 1337-1346
publication: Nature Astronomy
publication_identifier:
eissn:
- 2397-3366
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: A high fraction of close massive binary stars at low metallicity
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 9
year: '2025'
...