---
_id: '10834'
abstract:
- lang: eng
text: Hematopoietic-specific protein 1 (Hem1) is an essential subunit of the WAVE
regulatory complex (WRC) in immune cells. WRC is crucial for Arp2/3 complex activation
and the protrusion of branched actin filament networks. Moreover, Hem1 loss of
function in immune cells causes autoimmune diseases in humans. Here, we show that
genetic removal of Hem1 in macrophages diminishes frequency and efficacy of phagocytosis
as well as phagocytic cup formation in addition to defects in lamellipodial protrusion
and migration. Moreover, Hem1-null macrophages displayed strong defects in cell
adhesion despite unaltered podosome formation and concomitant extracellular matrix
degradation. Specifically, dynamics of both adhesion and de-adhesion as well as
concomitant phosphorylation of paxillin and focal adhesion kinase (FAK) were significantly
compromised. Accordingly, disruption of WRC function in non-hematopoietic cells
coincided with both defects in adhesion turnover and altered FAK and paxillin
phosphorylation. Consistently, platelets exhibited reduced adhesion and diminished
integrin αIIbβ3 activation upon WRC removal. Interestingly, adhesion phenotypes,
but not lamellipodia formation, were partially rescued by small molecule activation
of FAK. A full rescue of the phenotype, including lamellipodia formation, required
not only the presence of WRCs but also their binding to and activation by Rac.
Collectively, our results uncover that WRC impacts on integrin-dependent processes
in a FAK-dependent manner, controlling formation and dismantling of adhesions,
relevant for properly grabbing onto extracellular surfaces and particles during
cell edge expansion, like in migration or phagocytosis.
acknowledgement: We are grateful to Silvia Prettin, Ina Schleicher, and Petra Hagendorff
for expert technical assistance; David Dettbarn for animal keeping and breeding;
and Lothar Gröbe and Maria Höxter for cell sorting. We also thank Werner Tegge for
peptides and Giorgio Scita for antibodies. This work was supported, in part, by
the Deutsche Forschungsgemeinschaft (DFG), Priority Programm SPP1150 (to T.E.B.S.,
K.R., and M. Sixt), and by DFG grant GRK2223/1 (to K.R.). T.E.B.S. acknowledges
support by the Helmholtz Society through HGF impulse fund W2/W3-066 and M. Schnoor
by the Mexican Council for Science and Technology (CONACyT, 284292 ), Fund SEP-Cinvestav
( 108 ), and the Royal Society, UK (Newton Advanced Fellowship, NAF/R1/180017 ).
article_processing_charge: No
article_type: original
author:
- first_name: Stephanie
full_name: Stahnke, Stephanie
last_name: Stahnke
- first_name: Hermann
full_name: Döring, Hermann
last_name: Döring
- first_name: Charly
full_name: Kusch, Charly
last_name: Kusch
- first_name: David J.J.
full_name: de Gorter, David J.J.
last_name: de Gorter
- first_name: Sebastian
full_name: Dütting, Sebastian
last_name: Dütting
- first_name: Aleks
full_name: Guledani, Aleks
last_name: Guledani
- first_name: Irina
full_name: Pleines, Irina
last_name: Pleines
- first_name: Michael
full_name: Schnoor, Michael
last_name: Schnoor
- first_name: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-6620-9179
- first_name: Robert
full_name: Geffers, Robert
last_name: Geffers
- first_name: Manfred
full_name: Rohde, Manfred
last_name: Rohde
- first_name: Mathias
full_name: Müsken, Mathias
last_name: Müsken
- first_name: Frieda
full_name: Kage, Frieda
last_name: Kage
- first_name: Anika
full_name: Steffen, Anika
last_name: Steffen
- first_name: Jan
full_name: Faix, Jan
last_name: Faix
- first_name: Bernhard
full_name: Nieswandt, Bernhard
last_name: Nieswandt
- first_name: Klemens
full_name: Rottner, Klemens
last_name: Rottner
- first_name: Theresia E.B.
full_name: Stradal, Theresia E.B.
last_name: Stradal
citation:
ama: Stahnke S, Döring H, Kusch C, et al. Loss of Hem1 disrupts macrophage function
and impacts migration, phagocytosis, and integrin-mediated adhesion. Current
Biology. 2021;31(10):2051-2064.e8. doi:10.1016/j.cub.2021.02.043
apa: Stahnke, S., Döring, H., Kusch, C., de Gorter, D. J. J., Dütting, S., Guledani,
A., … Stradal, T. E. B. (2021). Loss of Hem1 disrupts macrophage function and
impacts migration, phagocytosis, and integrin-mediated adhesion. Current Biology.
Elsevier. https://doi.org/10.1016/j.cub.2021.02.043
chicago: Stahnke, Stephanie, Hermann Döring, Charly Kusch, David J.J. de Gorter,
Sebastian Dütting, Aleks Guledani, Irina Pleines, et al. “Loss of Hem1 Disrupts
Macrophage Function and Impacts Migration, Phagocytosis, and Integrin-Mediated
Adhesion.” Current Biology. Elsevier, 2021. https://doi.org/10.1016/j.cub.2021.02.043.
ieee: S. Stahnke et al., “Loss of Hem1 disrupts macrophage function and impacts
migration, phagocytosis, and integrin-mediated adhesion,” Current Biology,
vol. 31, no. 10. Elsevier, p. 2051–2064.e8, 2021.
ista: Stahnke S, Döring H, Kusch C, de Gorter DJJ, Dütting S, Guledani A, Pleines
I, Schnoor M, Sixt MK, Geffers R, Rohde M, Müsken M, Kage F, Steffen A, Faix J,
Nieswandt B, Rottner K, Stradal TEB. 2021. Loss of Hem1 disrupts macrophage function
and impacts migration, phagocytosis, and integrin-mediated adhesion. Current Biology.
31(10), 2051–2064.e8.
mla: Stahnke, Stephanie, et al. “Loss of Hem1 Disrupts Macrophage Function and Impacts
Migration, Phagocytosis, and Integrin-Mediated Adhesion.” Current Biology,
vol. 31, no. 10, Elsevier, 2021, p. 2051–2064.e8, doi:10.1016/j.cub.2021.02.043.
short: S. Stahnke, H. Döring, C. Kusch, D.J.J. de Gorter, S. Dütting, A. Guledani,
I. Pleines, M. Schnoor, M.K. Sixt, R. Geffers, M. Rohde, M. Müsken, F. Kage, A.
Steffen, J. Faix, B. Nieswandt, K. Rottner, T.E.B. Stradal, Current Biology 31
(2021) 2051–2064.e8.
date_created: 2022-03-08T07:51:04Z
date_published: 2021-05-24T00:00:00Z
date_updated: 2023-08-17T07:01:14Z
day: '24'
department:
- _id: MiSi
doi: 10.1016/j.cub.2021.02.043
external_id:
isi:
- '000654652200002'
pmid:
- '33711252'
intvolume: ' 31'
isi: 1
issue: '10'
keyword:
- General Agricultural and Biological Sciences
- General Biochemistry
- Genetics and Molecular Biology
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2020.03.24.005835
month: '05'
oa: 1
oa_version: Preprint
page: 2051-2064.e8
pmid: 1
publication: Current Biology
publication_identifier:
issn:
- 0960-9822
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Loss of Hem1 disrupts macrophage function and impacts migration, phagocytosis,
and integrin-mediated adhesion
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 31
year: '2021'
...
---
_id: '10838'
abstract:
- lang: eng
text: Combining hybrid zone analysis with genomic data is a promising approach to
understanding the genomic basis of adaptive divergence. It allows for the identification
of genomic regions underlying barriers to gene flow. It also provides insights
into spatial patterns of allele frequency change, informing about the interplay
between environmental factors, dispersal and selection. However, when only a single
hybrid zone is analysed, it is difficult to separate patterns generated by selection
from those resulting from chance. Therefore, it is beneficial to look for repeatable
patterns across replicate hybrid zones in the same system. We applied this approach
to the marine snail Littorina saxatilis, which contains two ecotypes, adapted
to wave-exposed rocks vs. high-predation boulder fields. The existence of numerous
hybrid zones between ecotypes offered the opportunity to test for the repeatability
of genomic architectures and spatial patterns of divergence. We sampled and phenotyped
snails from seven replicate hybrid zones on the Swedish west coast and genotyped
them for thousands of single nucleotide polymorphisms. Shell shape and size showed
parallel clines across all zones. Many genomic regions showing steep clines and/or
high differentiation were shared among hybrid zones, consistent with a common
evolutionary history and extensive gene flow between zones, and supporting the
importance of these regions for divergence. In particular, we found that several
large putative inversions contribute to divergence in all locations. Additionally,
we found evidence for consistent displacement of clines from the boulder–rock
transition. Our results demonstrate patterns of spatial variation that would not
be accessible without continuous spatial sampling, a large genomic data set and
replicate hybrid zones.
acknowledgement: "We thank everyone who helped with fieldwork, snail processing and
DNA extractions, particularly Laura Brettell, Mårten Duvetorp, Juan Galindo, Anne-Lise
Liabot, Mark Ravinet, Irena Senčić and Zuzanna Zagrodzka. We are also grateful to
Edinburgh Genomics for library preparation and sequencing, to Stuart Baird and Mark
Ravinet for helpful discussions, and to three anonymous reviewers for their constructive
comments. This work was supported by the Natural Environment Research Council (NE/K014021/1),
the European Research Council (AdG-693030-BARRIERS), Swedish Research Councils Formas
and Vetenskapsrådet through a Linnaeus grant to the Centre for Marine Evolutionary
Biology (217-2008-1719), the European Regional Development Fund (POCI-01-0145-FEDER-030628),
and the Fundação para a iência e a Tecnologia,\r\nPortugal (PTDC/BIA-EVL/\r\n30628/2017).
A.M.W. and R.F. were\r\nfunded by the European Union’s Horizon 2020 research and
innovation\r\nprogramme under Marie Skłodowska-Curie\r\ngrant agreements\r\nno.
754411/797747 and no. 706376, respectively."
article_processing_charge: No
article_type: original
author:
- first_name: Anja M
full_name: Westram, Anja M
id: 3C147470-F248-11E8-B48F-1D18A9856A87
last_name: Westram
orcid: 0000-0003-1050-4969
- first_name: Rui
full_name: Faria, Rui
last_name: Faria
- first_name: Kerstin
full_name: Johannesson, Kerstin
last_name: Johannesson
- first_name: Roger
full_name: Butlin, Roger
last_name: Butlin
citation:
ama: Westram AM, Faria R, Johannesson K, Butlin R. Using replicate hybrid zones
to understand the genomic basis of adaptive divergence. Molecular Ecology.
2021;30(15):3797-3814. doi:10.1111/mec.15861
apa: Westram, A. M., Faria, R., Johannesson, K., & Butlin, R. (2021). Using
replicate hybrid zones to understand the genomic basis of adaptive divergence.
Molecular Ecology. Wiley. https://doi.org/10.1111/mec.15861
chicago: Westram, Anja M, Rui Faria, Kerstin Johannesson, and Roger Butlin. “Using
Replicate Hybrid Zones to Understand the Genomic Basis of Adaptive Divergence.”
Molecular Ecology. Wiley, 2021. https://doi.org/10.1111/mec.15861.
ieee: A. M. Westram, R. Faria, K. Johannesson, and R. Butlin, “Using replicate hybrid
zones to understand the genomic basis of adaptive divergence,” Molecular Ecology,
vol. 30, no. 15. Wiley, pp. 3797–3814, 2021.
ista: Westram AM, Faria R, Johannesson K, Butlin R. 2021. Using replicate hybrid
zones to understand the genomic basis of adaptive divergence. Molecular Ecology.
30(15), 3797–3814.
mla: Westram, Anja M., et al. “Using Replicate Hybrid Zones to Understand the Genomic
Basis of Adaptive Divergence.” Molecular Ecology, vol. 30, no. 15, Wiley,
2021, pp. 3797–814, doi:10.1111/mec.15861.
short: A.M. Westram, R. Faria, K. Johannesson, R. Butlin, Molecular Ecology 30 (2021)
3797–3814.
date_created: 2022-03-08T11:28:32Z
date_published: 2021-08-01T00:00:00Z
date_updated: 2023-09-05T16:02:19Z
day: '01'
ddc:
- '570'
department:
- _id: BeVi
doi: 10.1111/mec.15861
external_id:
isi:
- '000669439700001'
pmid:
- '33638231'
file:
- access_level: open_access
checksum: d5611f243ceb63a0e091d6662ebd9cda
content_type: application/pdf
creator: dernst
date_created: 2022-03-08T11:31:30Z
date_updated: 2022-03-08T11:31:30Z
file_id: '10839'
file_name: 2021_MolecularEcology_Westram.pdf
file_size: 1726548
relation: main_file
success: 1
file_date_updated: 2022-03-08T11:31:30Z
has_accepted_license: '1'
intvolume: ' 30'
isi: 1
issue: '15'
keyword:
- Genetics
- Ecology
- Evolution
- Behavior and Systematics
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 3797-3814
pmid: 1
publication: Molecular Ecology
publication_identifier:
eissn:
- 1365-294X
issn:
- 0962-1083
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Using replicate hybrid zones to understand the genomic basis of adaptive divergence
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: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 30
year: '2021'
...
---
_id: '10847'
abstract:
- lang: eng
text: 'We study the two-player zero-sum extension of the partially observable stochastic
shortest-path problem where one agent has only partial information about the environment.
We formulate this problem as a partially observable stochastic game (POSG): given
a set of target states and negative rewards for each transition, the player with
imperfect information maximizes the expected undiscounted total reward until a
target state is reached. The second player with the perfect information aims for
the opposite. We base our formalism on POSGs with one-sided observability (OS-POSGs)
and give the following contributions: (1) we introduce a novel heuristic search
value iteration algorithm that iteratively solves depth-limited variants of the
game, (2) we derive the bound on the depth guaranteeing an arbitrary precision,
(3) we propose a novel upper-bound estimation that allows early terminations,
and (4) we experimentally evaluate the algorithm on a pursuit-evasion game.'
acknowledgement: "This research was supported by the Czech Science Foundation (no.
19-24384Y), by the OP VVV MEYS funded project CZ.02.1.01/0.0/0.0/16 019/0000765
“Research Center for Informatics”, by the ERC CoG 863818 (ForM-SMArt), and by the
Combat Capabilities Development Command Army Research Laboratory and was accomplished
under Cooperative\r\nAgreement Number W911NF-13-2-0045 (ARL Cyber Security CRA).
The views and conclusions contained in this document are those of the authors and
should not be interpreted as\r\nrepresenting the official policies, either expressed
or implied, of the Combat Capabilities Development Command Army Research Laboratory
or the U.S. Government. The U.S. Government is authorized to reproduce and distribute
reprints for Government purposes not withstanding any copyright notation here on. "
article_processing_charge: No
author:
- first_name: Petr
full_name: Tomášek, Petr
last_name: Tomášek
- first_name: Karel
full_name: Horák, Karel
last_name: Horák
- first_name: Aditya
full_name: Aradhye, Aditya
last_name: Aradhye
- first_name: Branislav
full_name: Bošanský, Branislav
last_name: Bošanský
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
citation:
ama: 'Tomášek P, Horák K, Aradhye A, Bošanský B, Chatterjee K. Solving partially
observable stochastic shortest-path games. In: 30th International Joint Conference
on Artificial Intelligence. International Joint Conferences on Artificial
Intelligence; 2021:4182-4189. doi:10.24963/ijcai.2021/575'
apa: 'Tomášek, P., Horák, K., Aradhye, A., Bošanský, B., & Chatterjee, K. (2021).
Solving partially observable stochastic shortest-path games. In 30th International
Joint Conference on Artificial Intelligence (pp. 4182–4189). Virtual, Online:
International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2021/575'
chicago: Tomášek, Petr, Karel Horák, Aditya Aradhye, Branislav Bošanský, and Krishnendu
Chatterjee. “Solving Partially Observable Stochastic Shortest-Path Games.” In
30th International Joint Conference on Artificial Intelligence, 4182–89.
International Joint Conferences on Artificial Intelligence, 2021. https://doi.org/10.24963/ijcai.2021/575.
ieee: P. Tomášek, K. Horák, A. Aradhye, B. Bošanský, and K. Chatterjee, “Solving
partially observable stochastic shortest-path games,” in 30th International
Joint Conference on Artificial Intelligence, Virtual, Online, 2021, pp. 4182–4189.
ista: 'Tomášek P, Horák K, Aradhye A, Bošanský B, Chatterjee K. 2021. Solving partially
observable stochastic shortest-path games. 30th International Joint Conference
on Artificial Intelligence. IJCAI: International Joint Conferences on Artificial
Intelligence Organization, 4182–4189.'
mla: Tomášek, Petr, et al. “Solving Partially Observable Stochastic Shortest-Path
Games.” 30th International Joint Conference on Artificial Intelligence,
International Joint Conferences on Artificial Intelligence, 2021, pp. 4182–89,
doi:10.24963/ijcai.2021/575.
short: P. Tomášek, K. Horák, A. Aradhye, B. Bošanský, K. Chatterjee, in:, 30th International
Joint Conference on Artificial Intelligence, International Joint Conferences on
Artificial Intelligence, 2021, pp. 4182–4189.
conference:
end_date: 2021-08-27
location: Virtual, Online
name: 'IJCAI: International Joint Conferences on Artificial Intelligence Organization'
start_date: 2021-08-19
date_created: 2022-03-13T23:01:47Z
date_published: 2021-09-01T00:00:00Z
date_updated: 2025-07-14T09:10:13Z
day: '01'
department:
- _id: KrCh
doi: 10.24963/ijcai.2021/575
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.24963/ijcai.2021/575
month: '09'
oa: 1
oa_version: Published Version
page: 4182-4189
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 30th International Joint Conference on Artificial Intelligence
publication_identifier:
isbn:
- '9780999241196'
issn:
- 1045-0823
publication_status: published
publisher: International Joint Conferences on Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Solving partially observable stochastic shortest-path games
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10852'
abstract:
- lang: eng
text: ' We review old and new results on the Fröhlich polaron model. The discussion
includes the validity of the (classical) Pekar approximation in the strong coupling
limit, quantum corrections to this limit, as well as the divergence of the effective
polaron mass.'
acknowledgement: This work was supported by the European Research Council (ERC) under
the Euro-pean Union’s Horizon 2020 research and innovation programme (grant agreementNo.
694227).
article_number: '2060012'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: Seiringer R. The polaron at strong coupling. Reviews in Mathematical Physics.
2021;33(01). doi:10.1142/s0129055x20600120
apa: Seiringer, R. (2021). The polaron at strong coupling. Reviews in Mathematical
Physics. World Scientific Publishing. https://doi.org/10.1142/s0129055x20600120
chicago: Seiringer, Robert. “The Polaron at Strong Coupling.” Reviews in Mathematical
Physics. World Scientific Publishing, 2021. https://doi.org/10.1142/s0129055x20600120.
ieee: R. Seiringer, “The polaron at strong coupling,” Reviews in Mathematical
Physics, vol. 33, no. 01. World Scientific Publishing, 2021.
ista: Seiringer R. 2021. The polaron at strong coupling. Reviews in Mathematical
Physics. 33(01), 2060012.
mla: Seiringer, Robert. “The Polaron at Strong Coupling.” Reviews in Mathematical
Physics, vol. 33, no. 01, 2060012, World Scientific Publishing, 2021, doi:10.1142/s0129055x20600120.
short: R. Seiringer, Reviews in Mathematical Physics 33 (2021).
date_created: 2022-03-18T08:11:34Z
date_published: 2021-02-01T00:00:00Z
date_updated: 2023-09-05T16:08:02Z
day: '01'
department:
- _id: RoSe
doi: 10.1142/s0129055x20600120
ec_funded: 1
external_id:
arxiv:
- '1912.12509'
isi:
- '000613313200013'
intvolume: ' 33'
isi: 1
issue: '01'
keyword:
- Mathematical Physics
- Statistical and Nonlinear Physics
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1912.12509
month: '02'
oa: 1
oa_version: Preprint
project:
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
publication: Reviews in Mathematical Physics
publication_identifier:
eissn:
- 1793-6659
issn:
- 0129-055X
publication_status: published
publisher: World Scientific Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: The polaron at strong coupling
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 33
year: '2021'
...
---
_id: '10853'
abstract:
- lang: eng
text: Dynamic Connectivity is a fundamental algorithmic graph problem, motivated
by a wide range of applications to social and communication networks and used
as a building block in various other algorithms, such as the bi-connectivity and
the dynamic minimal spanning tree problems. In brief, we wish to maintain the
connected components of the graph under dynamic edge insertions and deletions.
In the sequential case, the problem has been well-studied from both theoretical
and practical perspectives. However, much less is known about efficient concurrent
solutions to this problem. This is the gap we address in this paper. We start
from one of the classic data structures used to solve this problem, the Euler
Tour Tree. Our first contribution is a non-blocking single-writer implementation
of it. We leverage this data structure to obtain the first truly concurrent generalization
of dynamic connectivity, which preserves the time complexity of its sequential
counterpart, but is also scalable in practice. To achieve this, we rely on three
main techniques. The first is to ensure that connectivity queries, which usually
dominate real-world workloads, are non-blocking. The second non-trivial technique
expands the above idea by making all queries that do not change the connectivity
structure non-blocking. The third ingredient is applying fine-grained locking
for updating the connected components, which allows operations on disjoint components
to occur in parallel. We evaluate the resulting algorithm on various workloads,
executing on both real and synthetic graphs. The results show the efficiency of
each of the proposed optimizations; the most efficient variant improves the performance
of a coarse-grained based implementation on realistic scenarios up to 6x on average
and up to 30x when connectivity queries dominate.
article_processing_charge: No
arxiv: 1
author:
- first_name: Alexander
full_name: Fedorov, Alexander
last_name: Fedorov
- first_name: Nikita
full_name: Koval, Nikita
last_name: Koval
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Fedorov A, Koval N, Alistarh D-A. A scalable concurrent algorithm for dynamic
connectivity. In: Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms
and Architectures. Association for Computing Machinery; 2021:208-220. doi:10.1145/3409964.3461810'
apa: 'Fedorov, A., Koval, N., & Alistarh, D.-A. (2021). A scalable concurrent
algorithm for dynamic connectivity. In Proceedings of the 33rd ACM Symposium
on Parallelism in Algorithms and Architectures (pp. 208–220). Virtual, Online:
Association for Computing Machinery. https://doi.org/10.1145/3409964.3461810'
chicago: Fedorov, Alexander, Nikita Koval, and Dan-Adrian Alistarh. “A Scalable
Concurrent Algorithm for Dynamic Connectivity.” In Proceedings of the 33rd
ACM Symposium on Parallelism in Algorithms and Architectures, 208–20. Association
for Computing Machinery, 2021. https://doi.org/10.1145/3409964.3461810.
ieee: A. Fedorov, N. Koval, and D.-A. Alistarh, “A scalable concurrent algorithm
for dynamic connectivity,” in Proceedings of the 33rd ACM Symposium on Parallelism
in Algorithms and Architectures, Virtual, Online, 2021, pp. 208–220.
ista: 'Fedorov A, Koval N, Alistarh D-A. 2021. A scalable concurrent algorithm for
dynamic connectivity. Proceedings of the 33rd ACM Symposium on Parallelism in
Algorithms and Architectures. SPAA: Symposium on Parallelism in Algorithms and
Architectures, 208–220.'
mla: Fedorov, Alexander, et al. “A Scalable Concurrent Algorithm for Dynamic Connectivity.”
Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures,
Association for Computing Machinery, 2021, pp. 208–20, doi:10.1145/3409964.3461810.
short: A. Fedorov, N. Koval, D.-A. Alistarh, in:, Proceedings of the 33rd ACM Symposium
on Parallelism in Algorithms and Architectures, Association for Computing Machinery,
2021, pp. 208–220.
conference:
end_date: 2021-07-08
location: Virtual, Online
name: 'SPAA: Symposium on Parallelism in Algorithms and Architectures'
start_date: 2021-07-06
date_created: 2022-03-18T08:21:47Z
date_published: 2021-07-01T00:00:00Z
date_updated: 2022-03-18T08:45:46Z
day: '01'
department:
- _id: DaAl
doi: 10.1145/3409964.3461810
external_id:
arxiv:
- '2105.08098'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2105.08098
month: '07'
oa: 1
oa_version: Preprint
page: 208-220
publication: Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and
Architectures
publication_identifier:
isbn:
- '9781450380706'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: A scalable concurrent algorithm for dynamic connectivity
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10854'
abstract:
- lang: eng
text: "Consider a distributed task where the communication network is fixed but
the local inputs given to the nodes of the distributed system may change over
time. In this work, we explore the following question: if some of the local inputs
change, can an existing solution be updated efficiently, in a dynamic and distributed
manner?\r\nTo address this question, we define the batch dynamic CONGEST model
in which we are given a bandwidth-limited communication network and a dynamic
edge labelling defines the problem input. The task is to maintain a solution to
a graph problem on the labelled graph under batch changes. We investigate, when
a batch of alpha edge label changes arrive, - how much time as a function of alpha
we need to update an existing solution, and - how much information the nodes have
to keep in local memory between batches in order to update the solution quickly.\r\nOur
work lays the foundations for the theory of input-dynamic distributed network
algorithms. We give a general picture of the complexity landscape in this model,
design both universal algorithms and algorithms for concrete problems, and present
a general framework for lower bounds. The diverse time complexity of our model
spans from constant time, through time polynomial in alpha, and to alpha time,
which we show to be enough for any task."
acknowledgement: We thank Jukka Suomela for discussions. We also thank our shepherd
Mohammad Hajiesmaili and the reviewers for their time and suggestions on how to
improve the paper. This project has received funding from the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 805223 ScaleML), from the European Union’s Horizon 2020 research
and innovation programme under the Marie Skłodowska–Curie grant agreement No. 840605,
from the Vienna Science and Technology Fund (WWTF) project WHATIF, ICT19-045, 2020-2024,
and from the Austrian Science Fund (FWF) and netIDEE SCIENCE project P 33775-N.
article_processing_charge: No
arxiv: 1
author:
- first_name: Klaus-Tycho
full_name: Foerster, Klaus-Tycho
last_name: Foerster
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
- first_name: Ami
full_name: Paz, Ami
last_name: Paz
- first_name: Joel
full_name: Rybicki, Joel
id: 334EFD2E-F248-11E8-B48F-1D18A9856A87
last_name: Rybicki
orcid: 0000-0002-6432-6646
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
citation:
ama: 'Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed
algorithms for communication networks. In: Abstract Proceedings of the 2021
ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer
Systems. Association for Computing Machinery; 2021:71-72. doi:10.1145/3410220.3453923'
apa: 'Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021).
Input-dynamic distributed algorithms for communication networks. In Abstract
Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement
and Modeling of Computer Systems (pp. 71–72). Virtual, Online: Association
for Computing Machinery. https://doi.org/10.1145/3410220.3453923'
chicago: Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan
Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” In
Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference
on Measurement and Modeling of Computer Systems, 71–72. Association for Computing
Machinery, 2021. https://doi.org/10.1145/3410220.3453923.
ieee: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic
distributed algorithms for communication networks,” in Abstract Proceedings
of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling
of Computer Systems, Virtual, Online, 2021, pp. 71–72.
ista: 'Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic
distributed algorithms for communication networks. Abstract Proceedings of the
2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of
Computer Systems. SIGMETRICS: International Conference on Measurement and Modeling
of Computer Systems, 71–72.'
mla: Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication
Networks.” Abstract Proceedings of the 2021 ACM SIGMETRICS / International
Conference on Measurement and Modeling of Computer Systems, Association for
Computing Machinery, 2021, pp. 71–72, doi:10.1145/3410220.3453923.
short: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, in:, Abstract
Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement
and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp.
71–72.
conference:
end_date: 2021-06-18
location: Virtual, Online
name: 'SIGMETRICS: International Conference on Measurement and Modeling of Computer
Systems'
start_date: 2021-06-14
date_created: 2022-03-18T08:48:41Z
date_published: 2021-05-01T00:00:00Z
date_updated: 2023-09-26T10:40:55Z
day: '01'
department:
- _id: DaAl
doi: 10.1145/3410220.3453923
ec_funded: 1
external_id:
arxiv:
- '2005.07637'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2005.07637
month: '05'
oa: 1
oa_version: Preprint
page: 71-72
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
- _id: 26A5D39A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '840605'
name: Coordination in constrained and natural distributed systems
publication: Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference
on Measurement and Modeling of Computer Systems
publication_identifier:
isbn:
- '9781450380720'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
record:
- id: '10855'
relation: extended_version
status: public
scopus_import: '1'
status: public
title: Input-dynamic distributed algorithms for communication networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10855'
abstract:
- lang: eng
text: 'Consider a distributed task where the communication network is fixed but
the local inputs given to the nodes of the distributed system may change over
time. In this work, we explore the following question: if some of the local inputs
change, can an existing solution be updated efficiently, in a dynamic and distributed
manner? To address this question, we define the batch dynamic \congest model in
which we are given a bandwidth-limited communication network and a dynamic edge
labelling defines the problem input. The task is to maintain a solution to a graph
problem on the labeled graph under batch changes. We investigate, when a batch
of α edge label changes arrive, \beginitemize \item how much time as a function
of α we need to update an existing solution, and \item how much information the
nodes have to keep in local memory between batches in order to update the solution
quickly. \enditemize Our work lays the foundations for the theory of input-dynamic
distributed network algorithms. We give a general picture of the complexity landscape
in this model, design both universal algorithms and algorithms for concrete problems,
and present a general framework for lower bounds. In particular, we derive non-trivial
upper bounds for two selected, contrasting problems: maintaining a minimum spanning
tree and detecting cliques.'
acknowledgement: "We thank Jukka Suomela for discussions. We also thank our shepherd
Mohammad Hajiesmaili\r\nand the reviewers for their time and suggestions on how
to improve the paper. This project\r\nhas received funding from the European Research
Council (ERC) under the European Union’s\r\nHorizon 2020 research and innovation
programme (grant agreement No 805223 ScaleML), from the European Union’s Horizon
2020 research and innovation programme under the Marie\r\nSk lodowska–Curie grant
agreement No. 840605, from the Vienna Science and Technology Fund (WWTF) project
WHATIF, ICT19-045, 2020-2024, and from the Austrian Science Fund (FWF) and netIDEE
SCIENCE project P 33775-N."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Klaus-Tycho
full_name: Foerster, Klaus-Tycho
last_name: Foerster
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
- first_name: Ami
full_name: Paz, Ami
last_name: Paz
- first_name: Joel
full_name: Rybicki, Joel
id: 334EFD2E-F248-11E8-B48F-1D18A9856A87
last_name: Rybicki
orcid: 0000-0002-6432-6646
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
citation:
ama: Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed
algorithms for communication networks. Proceedings of the ACM on Measurement
and Analysis of Computing Systems. 2021;5(1):1-33. doi:10.1145/3447384
apa: Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021).
Input-dynamic distributed algorithms for communication networks. Proceedings
of the ACM on Measurement and Analysis of Computing Systems. Association for
Computing Machinery. https://doi.org/10.1145/3447384
chicago: Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan
Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” Proceedings
of the ACM on Measurement and Analysis of Computing Systems. Association for
Computing Machinery, 2021. https://doi.org/10.1145/3447384.
ieee: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic
distributed algorithms for communication networks,” Proceedings of the ACM
on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association
for Computing Machinery, pp. 1–33, 2021.
ista: Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic
distributed algorithms for communication networks. Proceedings of the ACM on Measurement
and Analysis of Computing Systems. 5(1), 1–33.
mla: Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication
Networks.” Proceedings of the ACM on Measurement and Analysis of Computing
Systems, vol. 5, no. 1, Association for Computing Machinery, 2021, pp. 1–33,
doi:10.1145/3447384.
short: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, Proceedings of
the ACM on Measurement and Analysis of Computing Systems 5 (2021) 1–33.
date_created: 2022-03-18T09:10:27Z
date_published: 2021-03-01T00:00:00Z
date_updated: 2023-09-26T10:40:55Z
day: '01'
department:
- _id: DaAl
doi: 10.1145/3447384
ec_funded: 1
external_id:
arxiv:
- '2005.07637'
intvolume: ' 5'
issue: '1'
keyword:
- Computer Networks and Communications
- Hardware and Architecture
- Safety
- Risk
- Reliability and Quality
- Computer Science (miscellaneous)
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2005.07637
month: '03'
oa: 1
oa_version: Preprint
page: 1-33
project:
- _id: 26A5D39A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '840605'
name: Coordination in constrained and natural distributed systems
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Proceedings of the ACM on Measurement and Analysis of Computing Systems
publication_identifier:
issn:
- 2476-1249
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
record:
- id: '10854'
relation: shorter_version
status: public
scopus_import: '1'
status: public
title: Input-dynamic distributed algorithms for communication networks
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 5
year: '2021'
...
---
_id: '10856'
abstract:
- lang: eng
text: "We study the properties of the maximal volume k-dimensional sections of the
n-dimensional cube [−1, 1]n. We obtain a first order necessary condition for a
k-dimensional subspace to be a local maximizer of the volume of such sections,
which we formulate in a geometric way. We estimate the length of the projection
of a vector of the standard basis of Rn onto a k-dimensional subspace that maximizes
the volume of the intersection. We \x1Cnd the optimal upper bound on the volume
of a planar section of the cube [−1, 1]n , n ≥ 2."
acknowledgement: "The authors acknowledge the support of the grant of the Russian
Government N 075-15-\r\n2019-1926. G.I.was supported also by the SwissNational Science
Foundation grant 200021-179133. The authors are very grateful to the anonymous reviewer
for valuable remarks."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Grigory
full_name: Ivanov, Grigory
id: 87744F66-5C6F-11EA-AFE0-D16B3DDC885E
last_name: Ivanov
- first_name: Igor
full_name: Tsiutsiurupa, Igor
last_name: Tsiutsiurupa
citation:
ama: Ivanov G, Tsiutsiurupa I. On the volume of sections of the cube. Analysis
and Geometry in Metric Spaces. 2021;9(1):1-18. doi:10.1515/agms-2020-0103
apa: Ivanov, G., & Tsiutsiurupa, I. (2021). On the volume of sections of the
cube. Analysis and Geometry in Metric Spaces. De Gruyter. https://doi.org/10.1515/agms-2020-0103
chicago: Ivanov, Grigory, and Igor Tsiutsiurupa. “On the Volume of Sections of the
Cube.” Analysis and Geometry in Metric Spaces. De Gruyter, 2021. https://doi.org/10.1515/agms-2020-0103.
ieee: G. Ivanov and I. Tsiutsiurupa, “On the volume of sections of the cube,” Analysis
and Geometry in Metric Spaces, vol. 9, no. 1. De Gruyter, pp. 1–18, 2021.
ista: Ivanov G, Tsiutsiurupa I. 2021. On the volume of sections of the cube. Analysis
and Geometry in Metric Spaces. 9(1), 1–18.
mla: Ivanov, Grigory, and Igor Tsiutsiurupa. “On the Volume of Sections of the Cube.”
Analysis and Geometry in Metric Spaces, vol. 9, no. 1, De Gruyter, 2021,
pp. 1–18, doi:10.1515/agms-2020-0103.
short: G. Ivanov, I. Tsiutsiurupa, Analysis and Geometry in Metric Spaces 9 (2021)
1–18.
date_created: 2022-03-18T09:25:14Z
date_published: 2021-01-29T00:00:00Z
date_updated: 2023-08-17T07:07:58Z
day: '29'
ddc:
- '510'
department:
- _id: UlWa
doi: 10.1515/agms-2020-0103
external_id:
arxiv:
- '2004.02674'
isi:
- '000734286800001'
file:
- access_level: open_access
checksum: 7e615ac8489f5eae580b6517debfdc53
content_type: application/pdf
creator: dernst
date_created: 2022-03-18T09:31:59Z
date_updated: 2022-03-18T09:31:59Z
file_id: '10857'
file_name: 2021_AnalysisMetricSpaces_Ivanov.pdf
file_size: 789801
relation: main_file
success: 1
file_date_updated: 2022-03-18T09:31:59Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '1'
keyword:
- Applied Mathematics
- Geometry and Topology
- Analysis
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 1-18
publication: Analysis and Geometry in Metric Spaces
publication_identifier:
issn:
- 2299-3274
publication_status: published
publisher: De Gruyter
quality_controlled: '1'
scopus_import: '1'
status: public
title: On the volume of sections of the cube
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 9
year: '2021'
...
---
_id: '10858'
abstract:
- lang: eng
text: The cost-effective conversion of low-grade heat into electricity using thermoelectric
devices requires developing alternative materials and material processing technologies
able to reduce the currently high device manufacturing costs. In this direction,
thermoelectric materials that do not rely on rare or toxic elements such as tellurium
or lead need to be produced using high-throughput technologies not involving high
temperatures and long processes. Bi2Se3 is an obvious possible Te-free alternative
to Bi2Te3 for ambient temperature thermoelectric applications, but its performance
is still low for practical applications, and additional efforts toward finding
proper dopants are required. Here, we report a scalable method to produce Bi2Se3
nanosheets at low synthesis temperatures. We studied the influence of different
dopants on the thermoelectric properties of this material. Among the elements
tested, we demonstrated that Sn doping resulted in the best performance. Sn incorporation
resulted in a significant improvement to the Bi2Se3 Seebeck coefficient and a
reduction in the thermal conductivity in the direction of the hot-press axis,
resulting in an overall 60% improvement in the thermoelectric figure of merit
of Bi2Se3.
acknowledgement: "M.L., Y.Z., T.Z. and K.X. thank the China Scholarship Council for
their scholarship\r\nsupport. Y.L. acknowledges funding from the European Union’s
Horizon 2020 research and\r\ninnovation program under the Marie Sklodowska-Curie
grant agreement No. 754411. J.L. thanks the ICREA Academia program and projects
MICINN/FEDER RTI2018-093996-B-C31 and G.C. 2017 SGR 128. ICN2 acknowledges funding
from the Generalitat de Catalunya 2017 SGR 327 and the Spanish MINECO ENE2017-85087-C3."
article_number: '1827'
article_processing_charge: No
article_type: original
author:
- first_name: Mengyao
full_name: Li, Mengyao
last_name: Li
- first_name: Yu
full_name: Zhang, Yu
last_name: Zhang
- first_name: Ting
full_name: Zhang, Ting
last_name: Zhang
- first_name: Yong
full_name: Zuo, Yong
last_name: Zuo
- first_name: Ke
full_name: Xiao, Ke
last_name: Xiao
- first_name: Jordi
full_name: Arbiol, Jordi
last_name: Arbiol
- first_name: Jordi
full_name: Llorca, Jordi
last_name: Llorca
- first_name: Yu
full_name: Liu, Yu
id: 2A70014E-F248-11E8-B48F-1D18A9856A87
last_name: Liu
orcid: 0000-0001-7313-6740
- first_name: Andreu
full_name: Cabot, Andreu
last_name: Cabot
citation:
ama: Li M, Zhang Y, Zhang T, et al. Enhanced thermoelectric performance of n-type
Bi2Se3 nanosheets through Sn doping. Nanomaterials. 2021;11(7). doi:10.3390/nano11071827
apa: Li, M., Zhang, Y., Zhang, T., Zuo, Y., Xiao, K., Arbiol, J., … Cabot, A. (2021).
Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping.
Nanomaterials. MDPI. https://doi.org/10.3390/nano11071827
chicago: Li, Mengyao, Yu Zhang, Ting Zhang, Yong Zuo, Ke Xiao, Jordi Arbiol, Jordi
Llorca, Yu Liu, and Andreu Cabot. “Enhanced Thermoelectric Performance of N-Type
Bi2Se3 Nanosheets through Sn Doping.” Nanomaterials. MDPI, 2021. https://doi.org/10.3390/nano11071827.
ieee: M. Li et al., “Enhanced thermoelectric performance of n-type Bi2Se3
nanosheets through Sn doping,” Nanomaterials, vol. 11, no. 7. MDPI, 2021.
ista: Li M, Zhang Y, Zhang T, Zuo Y, Xiao K, Arbiol J, Llorca J, Liu Y, Cabot A.
2021. Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through
Sn doping. Nanomaterials. 11(7), 1827.
mla: Li, Mengyao, et al. “Enhanced Thermoelectric Performance of N-Type Bi2Se3 Nanosheets
through Sn Doping.” Nanomaterials, vol. 11, no. 7, 1827, MDPI, 2021, doi:10.3390/nano11071827.
short: M. Li, Y. Zhang, T. Zhang, Y. Zuo, K. Xiao, J. Arbiol, J. Llorca, Y. Liu,
A. Cabot, Nanomaterials 11 (2021).
date_created: 2022-03-18T09:45:02Z
date_published: 2021-07-14T00:00:00Z
date_updated: 2023-08-17T07:08:30Z
day: '14'
ddc:
- '540'
department:
- _id: MaIb
doi: 10.3390/nano11071827
ec_funded: 1
external_id:
isi:
- '000676570000001'
file:
- access_level: open_access
checksum: f28a8b5cf80f5605828359bb398463b0
content_type: application/pdf
creator: dernst
date_created: 2022-03-18T09:53:15Z
date_updated: 2022-03-18T09:53:15Z
file_id: '10859'
file_name: 2021_Nanomaterials_Li.pdf
file_size: 4867547
relation: main_file
success: 1
file_date_updated: 2022-03-18T09:53:15Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
issue: '7'
keyword:
- General Materials Science
- General Chemical Engineering
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Nanomaterials
publication_identifier:
issn:
- 2079-4991
publication_status: published
publisher: MDPI
quality_controlled: '1'
scopus_import: '1'
status: public
title: Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn
doping
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
year: '2021'
...
---
_id: '10860'
abstract:
- lang: eng
text: A tight frame is the orthogonal projection of some orthonormal basis of Rn
onto Rk. We show that a set of vectors is a tight frame if and only if the set
of all cross products of these vectors is a tight frame. We reformulate a range
of problems on the volume of projections (or sections) of regular polytopes in
terms of tight frames and write a first-order necessary condition for local extrema
of these problems. As applications, we prove new results for the problem of maximization
of the volume of zonotopes.
acknowledgement: The author was supported by the Swiss National Science Foundation
grant 200021_179133. The author acknowledges the financial support from the Ministry
of Education and Science of the Russian Federation in the framework of MegaGrant
no. 075-15-2019-1926.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Grigory
full_name: Ivanov, Grigory
id: 87744F66-5C6F-11EA-AFE0-D16B3DDC885E
last_name: Ivanov
citation:
ama: Ivanov G. Tight frames and related geometric problems. Canadian Mathematical
Bulletin. 2021;64(4):942-963. doi:10.4153/s000843952000096x
apa: Ivanov, G. (2021). Tight frames and related geometric problems. Canadian
Mathematical Bulletin. Canadian Mathematical Society. https://doi.org/10.4153/s000843952000096x
chicago: Ivanov, Grigory. “Tight Frames and Related Geometric Problems.” Canadian
Mathematical Bulletin. Canadian Mathematical Society, 2021. https://doi.org/10.4153/s000843952000096x.
ieee: G. Ivanov, “Tight frames and related geometric problems,” Canadian Mathematical
Bulletin, vol. 64, no. 4. Canadian Mathematical Society, pp. 942–963, 2021.
ista: Ivanov G. 2021. Tight frames and related geometric problems. Canadian Mathematical
Bulletin. 64(4), 942–963.
mla: Ivanov, Grigory. “Tight Frames and Related Geometric Problems.” Canadian
Mathematical Bulletin, vol. 64, no. 4, Canadian Mathematical Society, 2021,
pp. 942–63, doi:10.4153/s000843952000096x.
short: G. Ivanov, Canadian Mathematical Bulletin 64 (2021) 942–963.
date_created: 2022-03-18T09:55:59Z
date_published: 2021-12-18T00:00:00Z
date_updated: 2023-09-05T12:43:09Z
day: '18'
department:
- _id: UlWa
doi: 10.4153/s000843952000096x
external_id:
arxiv:
- '1804.10055'
isi:
- '000730165300021'
intvolume: ' 64'
isi: 1
issue: '4'
keyword:
- General Mathematics
- Tight frame
- Grassmannian
- zonotope
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1804.10055
month: '12'
oa: 1
oa_version: Preprint
page: 942-963
publication: Canadian Mathematical Bulletin
publication_identifier:
eissn:
- 1496-4287
issn:
- 0008-4395
publication_status: published
publisher: Canadian Mathematical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Tight frames and related geometric problems
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 64
year: '2021'
...
---
_id: '10912'
abstract:
- lang: eng
text: Brain dynamics display collective phenomena as diverse as neuronal oscillations
and avalanches. Oscillations are rhythmic, with fluctuations occurring at a characteristic
scale, whereas avalanches are scale-free cascades of neural activity. Here we
show that such antithetic features can coexist in a very generic class of adaptive
neural networks. In the most simple yet fully microscopic model from this class
we make direct contact with human brain resting-state activity recordings via
tractable inference of the model's two essential parameters. The inferred model
quantitatively captures the dynamics over a broad range of scales, from single
sensor fluctuations, collective behaviors of nearly-synchronous extreme events
on multiple sensors, to neuronal avalanches unfolding over multiple sensors across
multiple time-bins. Importantly, the inferred parameters correlate with model-independent
signatures of "closeness to criticality", suggesting that the coexistence of scale-specific
(neural oscillations) and scale-free (neuronal avalanches) dynamics in brain activity
occurs close to a non-equilibrium critical point at the onset of self-sustained
oscillations.
acknowledgement: "FL acknowledges support from the European Union’s Horizon 2020 research
and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
GT\r\nacknowledges the support of the Austrian Science Fund (FWF) under Stand-Alone
Grant\r\nNo. P34015."
article_processing_charge: No
arxiv: 1
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Selver
full_name: Pepic, Selver
id: F93245C4-C3CA-11E9-B4F0-C6F4E5697425
last_name: Pepic
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Daniele
full_name: De Martino, Daniele
last_name: De Martino
citation:
ama: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. doi:10.48550/ARXIV.2108.06686
apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., & De Martino, D. (n.d.).
Quantifying the coexistence of neuronal oscillations and avalanches. arXiv. https://doi.org/10.48550/ARXIV.2108.06686
chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
De Martino. “Quantifying the Coexistence of Neuronal Oscillations and Avalanches.”
arXiv, n.d. https://doi.org/10.48550/ARXIV.2108.06686.
ieee: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Quantifying
the coexistence of neuronal oscillations and avalanches.” arXiv.
ista: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. 10.48550/ARXIV.2108.06686.
mla: Lombardi, Fabrizio, et al. Quantifying the Coexistence of Neuronal Oscillations
and Avalanches. arXiv, doi:10.48550/ARXIV.2108.06686.
short: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, (n.d.).
date_created: 2022-03-21T11:41:28Z
date_published: 2021-08-17T00:00:00Z
date_updated: 2022-03-22T07:53:18Z
day: '17'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.48550/ARXIV.2108.06686
ec_funded: 1
external_id:
arxiv:
- '2108.06686'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2108.06686
month: '08'
oa: 1
oa_version: Preprint
page: '37'
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication_status: submitted
publisher: arXiv
status: public
title: Quantifying the coexistence of neuronal oscillations and avalanches
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '11436'
abstract:
- lang: eng
text: Asynchronous distributed algorithms are a popular way to reduce synchronization
costs in large-scale optimization, and in particular for neural network training.
However, for nonsmooth and nonconvex objectives, few convergence guarantees exist
beyond cases where closed-form proximal operator solutions are available. As training
most popular deep neural networks corresponds to optimizing nonsmooth and nonconvex
objectives, there is a pressing need for such convergence guarantees. In this
paper, we analyze for the first time the convergence of stochastic asynchronous
optimization for this general class of objectives. In particular, we focus on
stochastic subgradient methods allowing for block variable partitioning, where
the shared model is asynchronously updated by concurrent processes. To this end,
we use a probabilistic model which captures key features of real asynchronous
scheduling between concurrent processes. Under this model, we establish convergence
with probability one to an invariant set for stochastic subgradient methods with
momentum. From a practical perspective, one issue with the family of algorithms
that we consider is that they are not efficiently supported by machine learning
frameworks, which mostly focus on distributed data-parallel strategies. To address
this, we propose a new implementation strategy for shared-memory based training
of deep neural networks for a partitioned but shared model in single- and multi-GPU
settings. Based on this implementation, we achieve on average1.2x speed-up in
comparison to state-of-the-art training methods for popular image classification
tasks, without compromising accuracy.
acknowledgement: Vyacheslav Kungurtsev was supported by the OP VVV project CZ.02.1.01/0.0/0.0/16
019/0000765 “Research Center for Informatics. Bapi Chatterjee was supported by the
European Union’s Horizon 2020 research and innovation programme under the Marie
Sklodowska-Curie grant agreement No. 754411 (ISTPlus). Dan Alistarh has received
funding from the European Research Council (ERC) under the European Union’s Horizon
2020 research and innovation programme (grant agreement No 805223 ScaleML).
article_processing_charge: No
arxiv: 1
author:
- first_name: Vyacheslav
full_name: Kungurtsev, Vyacheslav
last_name: Kungurtsev
- first_name: Malcolm
full_name: Egan, Malcolm
last_name: Egan
- first_name: Bapi
full_name: Chatterjee, Bapi
id: 3C41A08A-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. Asynchronous optimization
methods for efficient training of deep neural networks with guarantees. In: 35th
AAAI Conference on Artificial Intelligence, AAAI 2021. Vol 35. AAAI Press;
2021:8209-8216.'
apa: 'Kungurtsev, V., Egan, M., Chatterjee, B., & Alistarh, D.-A. (2021). Asynchronous
optimization methods for efficient training of deep neural networks with guarantees.
In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (Vol. 35,
pp. 8209–8216). Virtual, Online: AAAI Press.'
chicago: Kungurtsev, Vyacheslav, Malcolm Egan, Bapi Chatterjee, and Dan-Adrian Alistarh.
“Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks
with Guarantees.” In 35th AAAI Conference on Artificial Intelligence, AAAI
2021, 35:8209–16. AAAI Press, 2021.
ieee: V. Kungurtsev, M. Egan, B. Chatterjee, and D.-A. Alistarh, “Asynchronous optimization
methods for efficient training of deep neural networks with guarantees,” in 35th
AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual, Online, 2021,
vol. 35, no. 9B, pp. 8209–8216.
ista: 'Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. 2021. Asynchronous optimization
methods for efficient training of deep neural networks with guarantees. 35th AAAI
Conference on Artificial Intelligence, AAAI 2021. AAAI: Conference on Artificial
Intelligence vol. 35, 8209–8216.'
mla: Kungurtsev, Vyacheslav, et al. “Asynchronous Optimization Methods for Efficient
Training of Deep Neural Networks with Guarantees.” 35th AAAI Conference on
Artificial Intelligence, AAAI 2021, vol. 35, no. 9B, AAAI Press, 2021, pp.
8209–16.
short: V. Kungurtsev, M. Egan, B. Chatterjee, D.-A. Alistarh, in:, 35th AAAI Conference
on Artificial Intelligence, AAAI 2021, AAAI Press, 2021, pp. 8209–8216.
conference:
end_date: 2021-02-09
location: Virtual, Online
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2021-02-02
date_created: 2022-06-05T22:01:52Z
date_published: 2021-05-18T00:00:00Z
date_updated: 2022-06-07T06:53:36Z
day: '18'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '1905.11845'
intvolume: ' 35'
issue: 9B
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.1905.11845'
month: '05'
oa: 1
oa_version: Preprint
page: 8209-8216
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th AAAI Conference on Artificial Intelligence, AAAI 2021
publication_identifier:
eissn:
- 2374-3468
isbn:
- '9781713835974'
issn:
- 2159-5399
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Asynchronous optimization methods for efficient training of deep neural networks
with guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2021'
...
---
_id: '11452'
abstract:
- lang: eng
text: We study efficient distributed algorithms for the fundamental problem of principal
component analysis and leading eigenvector computation on the sphere, when the
data are randomly distributed among a set of computational nodes. We propose a
new quantized variant of Riemannian gradient descent to solve this problem, and
prove that the algorithm converges with high probability under a set of necessary
spherical-convexity properties. We give bounds on the number of bits transmitted
by the algorithm under common initialization schemes, and investigate the dependency
on the problem dimension in each case.
acknowledgement: We would like to thank the anonymous reviewers for helpful comments
and suggestions. We also thank Aurelien Lucchi and Antonio Orvieto for fruitful
discussions at an early stage of this work. FA is partially supported by the SNSF
under research project No. 192363 and conducted part of this work while at IST Austria
under the European Union’s Horizon 2020 research and innovation programme (grant
agreement No. 805223 ScaleML). PD partly conducted this work while at IST Austria
and was supported by the European Union’s Horizon 2020 programme under the Marie
Skłodowska-Curie grant agreement No. 754411.
article_processing_charge: No
arxiv: 1
author:
- first_name: Foivos
full_name: Alimisis, Foivos
last_name: Alimisis
- first_name: Peter
full_name: Davies, Peter
id: 11396234-BB50-11E9-B24C-90FCE5697425
last_name: Davies
orcid: 0000-0002-5646-9524
- first_name: Bart
full_name: Vandereycken, Bart
last_name: Vandereycken
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Alimisis F, Davies P, Vandereycken B, Alistarh D-A. Distributed principal
component analysis with limited communication. In: Advances in Neural Information
Processing Systems - 35th Conference on Neural Information Processing Systems.
Vol 4. Neural Information Processing Systems Foundation; 2021:2823-2834.'
apa: 'Alimisis, F., Davies, P., Vandereycken, B., & Alistarh, D.-A. (2021).
Distributed principal component analysis with limited communication. In Advances
in Neural Information Processing Systems - 35th Conference on Neural Information
Processing Systems (Vol. 4, pp. 2823–2834). Virtual, Online: Neural Information
Processing Systems Foundation.'
chicago: Alimisis, Foivos, Peter Davies, Bart Vandereycken, and Dan-Adrian Alistarh.
“Distributed Principal Component Analysis with Limited Communication.” In Advances
in Neural Information Processing Systems - 35th Conference on Neural Information
Processing Systems, 4:2823–34. Neural Information Processing Systems Foundation,
2021.
ieee: F. Alimisis, P. Davies, B. Vandereycken, and D.-A. Alistarh, “Distributed
principal component analysis with limited communication,” in Advances in Neural
Information Processing Systems - 35th Conference on Neural Information Processing
Systems, Virtual, Online, 2021, vol. 4, pp. 2823–2834.
ista: 'Alimisis F, Davies P, Vandereycken B, Alistarh D-A. 2021. Distributed principal
component analysis with limited communication. Advances in Neural Information
Processing Systems - 35th Conference on Neural Information Processing Systems.
NeurIPS: Neural Information Processing Systems vol. 4, 2823–2834.'
mla: Alimisis, Foivos, et al. “Distributed Principal Component Analysis with Limited
Communication.” Advances in Neural Information Processing Systems - 35th Conference
on Neural Information Processing Systems, vol. 4, Neural Information Processing
Systems Foundation, 2021, pp. 2823–34.
short: F. Alimisis, P. Davies, B. Vandereycken, D.-A. Alistarh, in:, Advances in
Neural Information Processing Systems - 35th Conference on Neural Information
Processing Systems, Neural Information Processing Systems Foundation, 2021, pp.
2823–2834.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-19T22:01:58Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-06-20T08:31:52Z
day: '01'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2110.14391'
intvolume: ' 4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/1680e9fa7b4dd5d62ece800239bb53bd-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 2823-2834
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Advances in Neural Information Processing Systems - 35th Conference on
Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Distributed principal component analysis with limited communication
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2021'
...
---
_id: '11453'
abstract:
- lang: eng
text: "Neuronal computations depend on synaptic connectivity and intrinsic electrophysiological
properties. Synaptic connectivity determines which inputs from presynaptic neurons
are integrated, while cellular properties determine how inputs are filtered over
time. Unlike their biological counterparts, most computational approaches to learning
in simulated neural networks are limited to changes in synaptic connectivity.
However, if intrinsic parameters change, neural computations are altered drastically.
Here, we include the parameters that determine the intrinsic properties,\r\ne.g.,
time constants and reset potential, into the learning paradigm. Using sparse feedback
signals that indicate target spike times, and gradient-based parameter updates,
we show that the intrinsic parameters can be learned along with the synaptic weights
to produce specific input-output functions. Specifically, we use a teacher-student
paradigm in which a randomly initialised leaky integrate-and-fire or resonate-and-fire
neuron must recover the parameters of a teacher neuron. We show that complex temporal
functions can be learned online and without backpropagation through time, relying
on event-based updates only. Our results are a step towards online learning of
neural computations from ungraded and unsigned sparse feedback signals with a
biologically inspired learning mechanism."
acknowledgement: We would like to thank Professor Dr. Henning Sprekeler for his valuable
suggestions and Dr. Andrew Saxe, Milan Klöwer and Anna Wallis for their constructive
feedback on the manuscript. Lukas Braun was supported by the Network of European
Neuroscience Schools through their NENS Exchange Grant program, by the European
Union through their European Community Action Scheme for the Mobility of University
Students, the Woodward Scholarship awarded by Wadham College, Oxford and the Medical
Research Council [MR/N013468/1]. Tim P. Vogels was supported by a Wellcome Trust
Senior Research Fellowship [214316/Z/18/Z].
article_processing_charge: No
author:
- first_name: Lukas
full_name: Braun, Lukas
last_name: Braun
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
citation:
ama: 'Braun L, Vogels TP. Online learning of neural computations from sparse temporal
feedback. In: Advances in Neural Information Processing Systems - 35th Conference
on Neural Information Processing Systems. Vol 20. Neural Information Processing
Systems Foundation; 2021:16437-16450.'
apa: 'Braun, L., & Vogels, T. P. (2021). Online learning of neural computations
from sparse temporal feedback. In Advances in Neural Information Processing
Systems - 35th Conference on Neural Information Processing Systems (Vol. 20,
pp. 16437–16450). Virtual, Online: Neural Information Processing Systems Foundation.'
chicago: Braun, Lukas, and Tim P Vogels. “Online Learning of Neural Computations
from Sparse Temporal Feedback.” In Advances in Neural Information Processing
Systems - 35th Conference on Neural Information Processing Systems, 20:16437–50.
Neural Information Processing Systems Foundation, 2021.
ieee: L. Braun and T. P. Vogels, “Online learning of neural computations from sparse
temporal feedback,” in Advances in Neural Information Processing Systems -
35th Conference on Neural Information Processing Systems, Virtual, Online,
2021, vol. 20, pp. 16437–16450.
ista: 'Braun L, Vogels TP. 2021. Online learning of neural computations from sparse
temporal feedback. Advances in Neural Information Processing Systems - 35th Conference
on Neural Information Processing Systems. NeurIPS: Neural Information Processing
Systems vol. 20, 16437–16450.'
mla: Braun, Lukas, and Tim P. Vogels. “Online Learning of Neural Computations from
Sparse Temporal Feedback.” Advances in Neural Information Processing Systems
- 35th Conference on Neural Information Processing Systems, vol. 20, Neural
Information Processing Systems Foundation, 2021, pp. 16437–50.
short: L. Braun, T.P. Vogels, in:, Advances in Neural Information Processing Systems
- 35th Conference on Neural Information Processing Systems, Neural Information
Processing Systems Foundation, 2021, pp. 16437–16450.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-19T22:01:59Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-06-20T07:12:58Z
day: '01'
department:
- _id: TiVo
intvolume: ' 20'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/88e1ce84f9feef5a08d0df0334c53468-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 16437-16450
project:
- _id: c084a126-5a5b-11eb-8a69-d75314a70a87
grant_number: 214316/Z/18/Z
name: What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent
neuronal networks.
publication: Advances in Neural Information Processing Systems - 35th Conference on
Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Online learning of neural computations from sparse temporal feedback
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2021'
...
---
_id: '11458'
abstract:
- lang: eng
text: 'The increasing computational requirements of deep neural networks (DNNs)
have led to significant interest in obtaining DNN models that are sparse, yet
accurate. Recent work has investigated the even harder case of sparse training,
where the DNN weights are, for as much as possible, already sparse to reduce computational
costs during training. Existing sparse training methods are often empirical and
can have lower accuracy relative to the dense baseline. In this paper, we present
a general approach called Alternating Compressed/DeCompressed (AC/DC) training
of DNNs, demonstrate convergence for a variant of the algorithm, and show that
AC/DC outperforms existing sparse training methods in accuracy at similar computational
budgets; at high sparsity levels, AC/DC even outperforms existing methods that
rely on accurate pre-trained dense models. An important property of AC/DC is that
it allows co-training of dense and sparse models, yielding accurate sparse–dense
model pairs at the end of the training process. This is useful in practice, where
compressed variants may be desirable for deployment in resource-constrained settings
without re-doing the entire training flow, and also provides us with insights
into the accuracy gap between dense and compressed models. The code is available
at: https://github.com/IST-DASLab/ACDC.'
acknowledged_ssus:
- _id: ScienComp
acknowledgement: This project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 805223 ScaleML), and a CNRS PEPS grant. This research was supported
by the Scientific Service Units (SSU) of IST Austria through resources provided
by Scientific Computing (SciComp). We would also like to thank Christoph Lampert
for his feedback on an earlier version of this work, as well as for providing hardware
for the Transformer-XL experiments.
article_processing_charge: No
arxiv: 1
author:
- first_name: Elena-Alexandra
full_name: Peste, Elena-Alexandra
id: 32D78294-F248-11E8-B48F-1D18A9856A87
last_name: Peste
- first_name: Eugenia B
full_name: Iofinova, Eugenia B
id: f9a17499-f6e0-11ea-865d-fdf9a3f77117
last_name: Iofinova
orcid: 0000-0002-7778-3221
- first_name: Adrian
full_name: Vladu, Adrian
last_name: Vladu
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed
training of deep neural networks. In: 35th Conference on Neural Information
Processing Systems. Vol 34. Curran Associates; 2021:8557-8570.'
apa: 'Peste, E.-A., Iofinova, E. B., Vladu, A., & Alistarh, D.-A. (2021). AC/DC:
Alternating Compressed/DeCompressed training of deep neural networks. In 35th
Conference on Neural Information Processing Systems (Vol. 34, pp. 8557–8570).
Virtual, Online: Curran Associates.'
chicago: 'Peste, Elena-Alexandra, Eugenia B Iofinova, Adrian Vladu, and Dan-Adrian
Alistarh. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural
Networks.” In 35th Conference on Neural Information Processing Systems,
34:8557–70. Curran Associates, 2021.'
ieee: 'E.-A. Peste, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating
Compressed/DeCompressed training of deep neural networks,” in 35th Conference
on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34,
pp. 8557–8570.'
ista: 'Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. 2021. AC/DC: Alternating Compressed/DeCompressed
training of deep neural networks. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 8557–8570.'
mla: 'Peste, Elena-Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed
Training of Deep Neural Networks.” 35th Conference on Neural Information Processing
Systems, vol. 34, Curran Associates, 2021, pp. 8557–70.'
short: E.-A. Peste, E.B. Iofinova, A. Vladu, D.-A. Alistarh, in:, 35th Conference
on Neural Information Processing Systems, Curran Associates, 2021, pp. 8557–8570.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-20T12:11:53Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2023-06-01T12:54:45Z
day: '6'
department:
- _id: GradSch
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2106.12379'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/48000647b315f6f00f913caa757a70b3-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 8557-8570
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
related_material:
record:
- id: '13074'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: 'AC/DC: Alternating Compressed/DeCompressed training of deep neural networks'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '11463'
abstract:
- lang: eng
text: "Efficiently approximating local curvature information of the loss function
is a key tool for optimization and compression of deep neural networks. Yet, most
existing methods to approximate second-order information have high computational\r\nor
storage costs, which limits their practicality. In this work, we investigate matrix-free,
linear-time approaches for estimating Inverse-Hessian Vector Products (IHVPs)
for the case when the Hessian can be approximated as a sum of rank-one matrices,
as in the classic approximation of the Hessian by the empirical Fisher matrix.
We propose two new algorithms: the first is tailored towards network compression
and can compute the IHVP for dimension d, if the Hessian is given as a sum of
m rank-one matrices, using O(dm2) precomputation, O(dm) cost for computing the
IHVP, and query cost O(m) for any single element of the inverse Hessian. The second
algorithm targets an optimization setting, where we wish to compute the product
between the inverse Hessian, estimated over a sliding window of optimization steps,
and a given gradient direction, as required for preconditioned SGD. We give an
algorithm with cost O(dm + m2) for computing the IHVP and O(dm + m3) for adding
or removing any gradient from the sliding window. These\r\ntwo algorithms yield
state-of-the-art results for network pruning and optimization with lower computational
overhead relative to existing second-order methods. Implementations are available
at [9] and [17]."
acknowledgement: We gratefully acknowledge funding the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme (grant
agreement No 805223 ScaleML), as well as computational support from Amazon Web Services
(AWS) EC2.
article_processing_charge: No
arxiv: 1
author:
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Frantar E, Kurtic E, Alistarh D-A. M-FAC: Efficient matrix-free approximations
of second-order information. In: 35th Conference on Neural Information Processing
Systems. Vol 34. Curran Associates; 2021:14873-14886.'
apa: 'Frantar, E., Kurtic, E., & Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free
approximations of second-order information. In 35th Conference on Neural Information
Processing Systems (Vol. 34, pp. 14873–14886). Virtual, Online: Curran Associates.'
chicago: 'Frantar, Elias, Eldar Kurtic, and Dan-Adrian Alistarh. “M-FAC: Efficient
Matrix-Free Approximations of Second-Order Information.” In 35th Conference
on Neural Information Processing Systems, 34:14873–86. Curran Associates,
2021.'
ieee: 'E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free
approximations of second-order information,” in 35th Conference on Neural Information
Processing Systems, Virtual, Online, 2021, vol. 34, pp. 14873–14886.'
ista: 'Frantar E, Kurtic E, Alistarh D-A. 2021. M-FAC: Efficient matrix-free approximations
of second-order information. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 14873–14886.'
mla: 'Frantar, Elias, et al. “M-FAC: Efficient Matrix-Free Approximations of Second-Order
Information.” 35th Conference on Neural Information Processing Systems,
vol. 34, Curran Associates, 2021, pp. 14873–86.'
short: E. Frantar, E. Kurtic, D.-A. Alistarh, in:, 35th Conference on Neural Information
Processing Systems, Curran Associates, 2021, pp. 14873–14886.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-26T22:01:35Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2022-06-27T07:05:12Z
day: '06'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2010.08222'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/7cfd5df443b4eb0d69886a583b33de4c-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 14873-14886
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'M-FAC: Efficient matrix-free approximations of second-order information'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '11464'
abstract:
- lang: eng
text: "We consider a standard distributed optimisation setting where N machines,
each holding a d-dimensional function\r\nfi, aim to jointly minimise the sum of
the functions ∑Ni=1fi(x). This problem arises naturally in large-scale distributed
optimisation, where a standard solution is to apply variants of (stochastic) gradient
descent. We focus on the communication complexity of this problem: our main result
provides the first fully unconditional bounds on total number of bits which need
to be sent and received by the N machines to solve this problem under point-to-point
communication, within a given error-tolerance. Specifically, we show that Ω(Ndlogd/Nε)
total bits need to be communicated between the machines to find an additive ϵ-approximation
to the minimum of ∑Ni=1fi(x). The result holds for both deterministic and randomised
algorithms, and, importantly, requires no assumptions on the algorithm structure.
The lower bound is tight under certain restrictions on parameter values, and is
matched within constant factors for quadratic objectives by a new variant of quantised
gradient descent, which we describe and analyse. Our results bring over tools
from communication complexity to distributed optimisation, which has potential
for further applications."
acknowledgement: We thank the NeurIPS reviewers for insightful comments that helped
us improve the positioning of our results, as well as for pointing out the subsampling
approach for complementing the randomised lower bound. We also thank Foivos Alimisis
and Peter Davies for useful discussions. This project has received funding from
the European Research Council (ERC) under the European Union’s Horizon 2020 research
and innovation programme (grant agreement No 805223 ScaleML).
article_processing_charge: No
arxiv: 1
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
citation:
ama: 'Alistarh D-A, Korhonen J. Towards tight communication lower bounds for distributed
optimisation. In: 35th Conference on Neural Information Processing Systems.
Vol 34. Curran Associates; 2021:7254-7266.'
apa: 'Alistarh, D.-A., & Korhonen, J. (2021). Towards tight communication lower
bounds for distributed optimisation. In 35th Conference on Neural Information
Processing Systems (Vol. 34, pp. 7254–7266). Virtual, Online: Curran Associates.'
chicago: Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication
Lower Bounds for Distributed Optimisation.” In 35th Conference on Neural Information
Processing Systems, 34:7254–66. Curran Associates, 2021.
ieee: D.-A. Alistarh and J. Korhonen, “Towards tight communication lower bounds
for distributed optimisation,” in 35th Conference on Neural Information Processing
Systems, Virtual, Online, 2021, vol. 34, pp. 7254–7266.
ista: 'Alistarh D-A, Korhonen J. 2021. Towards tight communication lower bounds
for distributed optimisation. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 7254–7266.'
mla: Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower
Bounds for Distributed Optimisation.” 35th Conference on Neural Information
Processing Systems, vol. 34, Curran Associates, 2021, pp. 7254–66.
short: D.-A. Alistarh, J. Korhonen, in:, 35th Conference on Neural Information Processing
Systems, Curran Associates, 2021, pp. 7254–7266.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-26T22:01:35Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2022-06-27T06:54:31Z
day: '06'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2010.08222'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/3b92d18aa7a6176dd37d372bc2f1eb71-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 7254-7266
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: Towards tight communication lower bounds for distributed optimisation
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '7883'
abstract:
- lang: eng
text: All vertebrates have a spinal cord with dimensions and shape specific to their
species. Yet how species‐specific organ size and shape are achieved is a fundamental
unresolved question in biology. The formation and sculpting of organs begins during
embryonic development. As it develops, the spinal cord extends in anterior–posterior
direction in synchrony with the overall growth of the body. The dorsoventral (DV)
and apicobasal lengths of the spinal cord neuroepithelium also change, while at
the same time a characteristic pattern of neural progenitor subtypes along the
DV axis is established and elaborated. At the basis of these changes in tissue
size and shape are biophysical determinants, such as the change in cell number,
cell size and shape, and anisotropic tissue growth. These processes are controlled
by global tissue‐scale regulators, such as morphogen signaling gradients as well
as mechanical forces. Current challenges in the field are to uncover how these
tissue‐scale regulatory mechanisms are translated to the cellular and molecular
level, and how regulation of distinct cellular processes gives rise to an overall
defined size. Addressing these questions will help not only to achieve a better
understanding of how size is controlled, but also of how tissue size is coordinated
with the specification of pattern.
acknowledgement: 'Austrian Academy of Sciences, Grant/Award Number: DOC fellowship
for Katarzyna Kuzmicz-Kowalska; Austrian Science Fund, Grant/Award Number: F78 (Stem
Cell Modulation); H2020 European Research Council, Grant/Award Number: 680037'
article_number: e383
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Katarzyna
full_name: Kuzmicz-Kowalska, Katarzyna
id: 4CED352A-F248-11E8-B48F-1D18A9856A87
last_name: Kuzmicz-Kowalska
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: 'Kuzmicz-Kowalska K, Kicheva A. Regulation of size and scale in vertebrate
spinal cord development. Wiley Interdisciplinary Reviews: Developmental Biology.
2021. doi:10.1002/wdev.383'
apa: 'Kuzmicz-Kowalska, K., & Kicheva, A. (2021). Regulation of size and scale
in vertebrate spinal cord development. Wiley Interdisciplinary Reviews: Developmental
Biology. Wiley. https://doi.org/10.1002/wdev.383'
chicago: 'Kuzmicz-Kowalska, Katarzyna, and Anna Kicheva. “Regulation of Size and
Scale in Vertebrate Spinal Cord Development.” Wiley Interdisciplinary Reviews:
Developmental Biology. Wiley, 2021. https://doi.org/10.1002/wdev.383.'
ieee: 'K. Kuzmicz-Kowalska and A. Kicheva, “Regulation of size and scale in vertebrate
spinal cord development,” Wiley Interdisciplinary Reviews: Developmental Biology.
Wiley, 2021.'
ista: 'Kuzmicz-Kowalska K, Kicheva A. 2021. Regulation of size and scale in vertebrate
spinal cord development. Wiley Interdisciplinary Reviews: Developmental Biology.,
e383.'
mla: 'Kuzmicz-Kowalska, Katarzyna, and Anna Kicheva. “Regulation of Size and Scale
in Vertebrate Spinal Cord Development.” Wiley Interdisciplinary Reviews: Developmental
Biology, e383, Wiley, 2021, doi:10.1002/wdev.383.'
short: 'K. Kuzmicz-Kowalska, A. Kicheva, Wiley Interdisciplinary Reviews: Developmental
Biology (2021).'
date_created: 2020-05-24T22:01:00Z
date_published: 2021-04-15T00:00:00Z
date_updated: 2024-03-07T15:03:00Z
day: '15'
ddc:
- '570'
department:
- _id: AnKi
doi: 10.1002/wdev.383
ec_funded: 1
external_id:
isi:
- '000531419400001'
pmid:
- '32391980'
file:
- access_level: open_access
checksum: f0a7745d48afa09ea7025e876a0145a8
content_type: application/pdf
creator: dernst
date_created: 2020-11-24T13:11:39Z
date_updated: 2020-11-24T13:11:39Z
file_id: '8800'
file_name: 2020_WIREs_DevBio_KuzmiczKowalska.pdf
file_size: 2527276
relation: main_file
success: 1
file_date_updated: 2020-11-24T13:11:39Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: 267AF0E4-B435-11E9-9278-68D0E5697425
name: The role of morphogens in the regulation of neural tube growth
- _id: 059DF620-7A3F-11EA-A408-12923DDC885E
grant_number: F07802
name: Morphogen control of growth and pattern in the spinal cord
publication: 'Wiley Interdisciplinary Reviews: Developmental Biology'
publication_identifier:
eissn:
- '17597692'
issn:
- '17597684'
publication_status: published
publisher: Wiley
quality_controlled: '1'
related_material:
record:
- id: '14323'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Regulation of size and scale in vertebrate spinal cord development
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: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '7900'
abstract:
- lang: eng
text: Hartree–Fock theory has been justified as a mean-field approximation for fermionic
systems. However, it suffers from some defects in predicting physical properties,
making necessary a theory of quantum correlations. Recently, bosonization of many-body
correlations has been rigorously justified as an upper bound on the correlation
energy at high density with weak interactions. We review the bosonic approximation,
deriving an effective Hamiltonian. We then show that for systems with Coulomb
interaction this effective theory predicts collective excitations (plasmons) in
accordance with the random phase approximation of Bohm and Pines, and with experimental
observation.
article_number: '2060009'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Niels P
full_name: Benedikter, Niels P
id: 3DE6C32A-F248-11E8-B48F-1D18A9856A87
last_name: Benedikter
orcid: 0000-0002-1071-6091
citation:
ama: Benedikter NP. Bosonic collective excitations in Fermi gases. Reviews in
Mathematical Physics. 2021;33(1). doi:10.1142/s0129055x20600090
apa: Benedikter, N. P. (2021). Bosonic collective excitations in Fermi gases. Reviews
in Mathematical Physics. World Scientific. https://doi.org/10.1142/s0129055x20600090
chicago: Benedikter, Niels P. “Bosonic Collective Excitations in Fermi Gases.” Reviews
in Mathematical Physics. World Scientific, 2021. https://doi.org/10.1142/s0129055x20600090.
ieee: N. P. Benedikter, “Bosonic collective excitations in Fermi gases,” Reviews
in Mathematical Physics, vol. 33, no. 1. World Scientific, 2021.
ista: Benedikter NP. 2021. Bosonic collective excitations in Fermi gases. Reviews
in Mathematical Physics. 33(1), 2060009.
mla: Benedikter, Niels P. “Bosonic Collective Excitations in Fermi Gases.” Reviews
in Mathematical Physics, vol. 33, no. 1, 2060009, World Scientific, 2021,
doi:10.1142/s0129055x20600090.
short: N.P. Benedikter, Reviews in Mathematical Physics 33 (2021).
date_created: 2020-05-28T16:47:55Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2023-09-05T16:07:40Z
day: '01'
department:
- _id: RoSe
doi: 10.1142/s0129055x20600090
ec_funded: 1
external_id:
arxiv:
- '1910.08190'
isi:
- '000613313200010'
intvolume: ' 33'
isi: 1
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1910.08190
month: '01'
oa: 1
oa_version: Preprint
project:
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
publication: Reviews in Mathematical Physics
publication_identifier:
eissn:
- 1793-6659
issn:
- 0129-055X
publication_status: published
publisher: World Scientific
quality_controlled: '1'
scopus_import: '1'
status: public
title: Bosonic collective excitations in Fermi gases
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 33
year: '2021'
...
---
_id: '7901'
abstract:
- lang: eng
text: We derive rigorously the leading order of the correlation energy of a Fermi
gas in a scaling regime of high density and weak interaction. The result verifies
the prediction of the random-phase approximation. Our proof refines the method
of collective bosonization in three dimensions. We approximately diagonalize an
effective Hamiltonian describing approximately bosonic collective excitations
around the Hartree–Fock state, while showing that gapless and non-collective excitations
have only a negligible effect on the ground state energy.
acknowledgement: We thank Christian Hainzl for helpful discussions and a referee for
very careful reading of the paper and many helpful suggestions. NB and RS were supported
by the European Research Council (ERC) under the European Union’s Horizon 2020 research
and innovation programme (grant agreement No. 694227). Part of the research of NB
was conducted on the RZD18 Nice–Milan–Vienna–Moscow. NB thanks Elliott H. Lieb and
Peter Otte for explanations about the Luttinger model. PTN has received funding
from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under
Germany’s Excellence Strategy (EXC-2111-390814868). MP acknowledges financial support
from the European Research Council (ERC) under the European Union’s Horizon 2020
research and innovation programme (ERC StG MaMBoQ, grant agreement No. 802901).
BS gratefully acknowledges financial support from the NCCR SwissMAP, from the Swiss
National Science Foundation through the Grant “Dynamical and energetic properties
of Bose-Einstein condensates” and from the European Research Council through the
ERC-AdG CLaQS (grant agreement No. 834782). All authors acknowledge support for
workshop participation from Mathematisches Forschungsinstitut Oberwolfach (Leibniz
Association). NB, PTN, BS, and RS acknowledge support for workshop participation
from Fondation des Treilles.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Niels P
full_name: Benedikter, Niels P
id: 3DE6C32A-F248-11E8-B48F-1D18A9856A87
last_name: Benedikter
orcid: 0000-0002-1071-6091
- first_name: Phan Thành
full_name: Nam, Phan Thành
last_name: Nam
- first_name: Marcello
full_name: Porta, Marcello
last_name: Porta
- first_name: Benjamin
full_name: Schlein, Benjamin
last_name: Schlein
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: Benedikter NP, Nam PT, Porta M, Schlein B, Seiringer R. Correlation energy
of a weakly interacting Fermi gas. Inventiones Mathematicae. 2021;225:885-979.
doi:10.1007/s00222-021-01041-5
apa: Benedikter, N. P., Nam, P. T., Porta, M., Schlein, B., & Seiringer, R.
(2021). Correlation energy of a weakly interacting Fermi gas. Inventiones Mathematicae.
Springer. https://doi.org/10.1007/s00222-021-01041-5
chicago: Benedikter, Niels P, Phan Thành Nam, Marcello Porta, Benjamin Schlein,
and Robert Seiringer. “Correlation Energy of a Weakly Interacting Fermi Gas.”
Inventiones Mathematicae. Springer, 2021. https://doi.org/10.1007/s00222-021-01041-5.
ieee: N. P. Benedikter, P. T. Nam, M. Porta, B. Schlein, and R. Seiringer, “Correlation
energy of a weakly interacting Fermi gas,” Inventiones Mathematicae, vol.
225. Springer, pp. 885–979, 2021.
ista: Benedikter NP, Nam PT, Porta M, Schlein B, Seiringer R. 2021. Correlation
energy of a weakly interacting Fermi gas. Inventiones Mathematicae. 225, 885–979.
mla: Benedikter, Niels P., et al. “Correlation Energy of a Weakly Interacting Fermi
Gas.” Inventiones Mathematicae, vol. 225, Springer, 2021, pp. 885–979,
doi:10.1007/s00222-021-01041-5.
short: N.P. Benedikter, P.T. Nam, M. Porta, B. Schlein, R. Seiringer, Inventiones
Mathematicae 225 (2021) 885–979.
date_created: 2020-05-28T16:48:20Z
date_published: 2021-05-03T00:00:00Z
date_updated: 2023-08-21T06:30:30Z
day: '03'
ddc:
- '510'
department:
- _id: RoSe
doi: 10.1007/s00222-021-01041-5
ec_funded: 1
external_id:
arxiv:
- '2005.08933'
isi:
- '000646573600001'
file:
- access_level: open_access
checksum: f38c79dfd828cdc7f49a34b37b83d376
content_type: application/pdf
creator: dernst
date_created: 2022-05-16T12:23:40Z
date_updated: 2022-05-16T12:23:40Z
file_id: '11386'
file_name: 2021_InventMath_Benedikter.pdf
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title: Correlation energy of a weakly interacting Fermi gas
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