cometadata/test-preprints-extracted-funding huggingface dataset:
We are grateful to the High Performance Computing (HPC) facility at IISER Bhopal, where largescale calculations in this project were run. P.D. is grateful to IISERB for the PhD fellowship. A.S acknowledges financial support from SERB via the grant (File Number: CRG/2019/003447), and from DST via the DST-INSPIRE Faculty Award [DST/INSPIRE/04/2014/002461].
Grant NOs. 12005266 and 12305127, the International Partnership Program of the Chinese Academy of Sciences under the Grant NO. 016GJHZ2022054FN, and the Strategic Priority Research Program of Chinese Academy of Sciences under the Grant NO. XDB34030301.
We thank Dr. Qin-Tao SONG for the fruitful discussions and comments. This work is supported by the National Natural Science Foundation of China under the
This work is partly supported by the National Natural Science Foundation of China under Grant No. 11975083 and No. 12365019, and by the Central Government Guidance Funds
for Local Scientific and Technological Development, China (No. Guike ZY22096024). R. M. acknowledges support from the CIDEGENT program with Ref. CIDEGENT/2019/015, the Spanish Ministerio de Economia y Competitividad and European Union (NextGenerationEU/PRTR) by the grant with Ref. CNS2022-13614. This work is also partly supported by the Spanish Ministerio de Economia y Competitividad (MINECO) and European FEDER funds under Contracts No. FIS2017-84038-C2-1-P B, PID2020-112777GB-I00, and by Generalitat Valenciana under contract PROMETEO/2020/023. This project has received funding from the European Union Horizon 2020 research and innovation programme under the program H2020-INFRAIA-2018-1, grant agreement No. 824093 of the STRONG-2020 project.
Acknowledgements. We thank Alexis Lavail and the ESO User Support team for their help in reducing this very early CRIRES + data. This work has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 325594231, FOR 2634 / 2. T. H. and D.S. acknowledge support from the European Research Council under the Horizon 2020 Framework Program via the ERC Advanced Grant Origins 83 24 28 (PI: Th. Henning). C.F.M. is funded by the European Union (ERC, WANDA, 101039452). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
This work was primarily funded by the US Department of Energy in the program '4D Camera Distillery: From Massive Electron Microscopy Scattering Data to Useful Information with AI/ML.' Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This research used Theory and Computation resources of the Center for Functional Nanomaterials (CFN), which is a U.S. Department of Energy Office of Science User Facility, at Brookhaven National Laboratory under Contract No. DE-SC0012704. The training and instrumentation support necessary to operate the TEAM I microscope and acquire the experimental EELS data presented in this work was provided by Dr Chengyu Song.
We are grateful to Micaela Oertel for several useful comments and suggestions. We also thank Tim Dietrich, Wolfgang Kastaun and other members of the LVK Extreme Matter working group for comments during a presentation of this work. We are grateful to Andreas Bauswein for providing the EoS tables used in this study and to Christos Charmousis for comments. The research leading to these results has received funding from the European Union's Horizon 2020 Programme under the AHEAD2020 project (grant agreement n. 871158). B.B. acknowledges the support from the Knut and Alice Wallenberg Foundation under grant Dnr. KAW 2019.0112 and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2121 'Quantum Universe' - 390833306. Calculations were performed on the facilities of the North-German Supercomputing Alliance (HLRN) and at the SUNRISE HPC facility supported by the Technical Division at the Department of Physics, Stockholm University. Virgo is funded through the European Gravitational Observatory (EGO), by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale di Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by institutions from Belgium, Germany, Greece, Hungary, Ireland, Japan, Monaco, Poland, Portugal, Spain.
Manuscript received: April 10, 2024; Accepted: September 11, 2024. This article was recommended for publication by Associate Editor P. V. K. Borges and Editor C. Cadena Lerma upon evaluation of the reviewers' comments. This work was supported by the United States Department of Agriculture (USDA) under USDA-ARS CRIS #6034-21000-018-000-D, #606621310-006-000-D, and USDA-ARS Non-Assistance Cooperative Agreement #6066-21310-005-061-S. (Jordan A. James and Heather K. Manching contributed equally to this work.) (Corresponding author: William J. Beksi .)
JQS and ALW also acknowledge Turing Fellowships from the Turing Institute; and CJD and JQS would like to thank the Isaac Newton Institute for Mathematical Sciences for support and hospitality during the programme Mathematical and Statistical Foundations of Data Driven Engineering when work on this paper was undertaken (supported by EPSRC Grant Number EP/R014604/1), associated with which CJD was partially supported by a grant from the Simons Foundation. CJD further acknowledges a grant from the International Centre for Mathematical Sciences under its Knowledge Exchange Catalyst scheme to work with the Global Power System Transformation consortium.
We would like to thank the anonymous referee for the comments and suggestions. The Swedish 1-m Solar Telescope is operated on the island of La Palma by the Institute for Solar Physics of Stockholm University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrof´ ısica de Canarias. The Institute for Solar Physics is supported by a grant for research infrastructures of national importance from the Swedish Research Council (registration number 202100169). We acknowledge support from NASA LWS NNH17ZDA001N, NASA LWS 80NSSC19K0070, NASA ECIP 80NSSC19K0910, NASA HSR NNH21ZDA001 and NSF CAREER award SPVKK1RC2MZ3 (R.Y. and M.D.K.). Resources supporting this work were provided by the NASA HighEnd Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. This work utilized the Alpine high performance computing resource at the University of Colorado Boulder. Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, Colorado State University, and the National Science Foundation (award 2201538). This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (SUNMAG, grant agreement 759548). We acknowledge the use of the visualization software VAPOR (Li et al. 2019) for generating relevant graphics. Data and images are courtesy of NASA/SDO and the HMI and AIA science teams. This research has made use of NASA's Astrophysics Data System. We acknowledge the community effort devoted to the development of the following open-source packages that were used in this work: NumPy (numpy.org), matplotlib (matplotlib.org) and SunPy (sunpy.org).
Arthur Hoarau, Jean-Christophe Dubois, Yolande Le Gall and Arnaud Martin received research support from the University of Rennes, the IRISA laboratory and the DRUID team. Vincent Lemaire received research support from Orange SA.
This work is funded by the Brittany region and the Cˆ otes-d'Armor department. The authors also received funding from IRISA, the University of Rennes, DRUID and Orange SA.
This research used resources of the 'Plateforme Technologique de Calcul Intensif (PTCI)' (http://www.ptci.unamur.be) located at the University of Namur, Belgium, which is supported by the FNRS-FRFC, the Walloon Region, and the University of Namur (Conventions No. 2.5020.11, GEQ U.G006.15, 1610468, RW/GEQ2016 et U.G011.22). The PTCI is a member of the 'Consortium des ´ Equipements de Calcul Intensif (C ´ ECI)'.
We thank E. Bannai and H. Kurihara for the inspiring discussions and for sharing with us a draft of [10] before its publication. PAB and MZ hold an Alexander-Graham-Bell scholarship from the Natural Sciences and Engineering Research Council of Canada (NSERC). NC is partially supported by Agence Nationale de la Recherche Projet AHA ANR-18-CE40-0001 and by the IRP AAPT of CNRS. The research of LV is supported by a Discovery Grant from NSERC.
We thank Anastasios Angelopoulos, Ying Jin, and Asher Spector for helpful suggestions and feedback on a draft on this manuscript, and Aditya Ghosh for catching and fixing a typo in a previous version of the manuscript. We also thank the reviewers for helping us clarify and improve the paper's exposition. T.Z. was supported by Stanford Data Science through the Fellowship program. E.J.C. was supported by the Office of Naval Research grant N00014-20-1-2157, the National Science Foundation grant DMS-2032014, the Simons Foundation under award 814641, and the ARO grant 2003514594.
WeacknowledgefundingfromtheNationalInstitutesofHealth(NIH)grantsU54CA268084, U54CA261694, R01CA228272, R01CA224911, R01CA225002, T32GM142604, NSF grant EFMA-1830961, and philanthropic support from K. Hudson and R. Goldman, S. Brice and J. Esteve, M. E. Holliday and I. Schneider, the Christina Carinato Charitable Foundation, and D. Sachs. Luay Almassalha acknowledge the support of NIH training grant T32AI083216.
- We can reformulate the problem in a different way. How big should be the flux n p to have at least one atom in the beam to get excited? The answer is obviously n atom ∼ e 10 9 for the last case. Too humongous to be achievable at present time even though luminosity of accelerators is increasing rather rapidly. - May be then one can hope to see the effect on the hyperfine structure of the atomic energy levels, where the energy difference is 10 -6 smaller than between the regular atomic levels. That makes n atom ∼ e 10 3 . However, in this case the main mistake for the effect that we consider will come from the fact that particles in the beam are thermalized during non-homogeneous acceleration periods and are not in the vacuum state. Even though for the NICA experiment the effective temperature of Sokolov-Ternov effect is tiny T NICA ST ∼ 10 -4 K , for the CERN experiment it is T CERN ST ∼ 10 K , that can be of the same order as the temperature of in the beam. Furthermore, the Sokolov-Ternov effect may play role in the crystalline ion beams [11] where the temperature is of order T ∼ 10 -3 K . 3. We would like to thank Pavel Pakhlov for valuable comments. This work is supported by the Foundation for the Advancement of Theoretical Physics and Mathematics 'BASIS' grant, by RFBR grant 19-02-00815 and joint RFBR- MOST grant 21-52-52004 MNT a, and by Russian Ministry of education and science.
MGM and SKC acknowledge financial support from Engineering and Physical Sciences Research Council (EPSRC) [Grant No. EP/X018989/1]. TG and VZ acknowledge support from EPSRC [DTP, Grant No. EP/T518050/1]. ATI-based authors would like to thank the UK National Ion Beam Centre [EPSRC, Grant No. EP/X015491/1] and UCL-based authors were financially supported by EPSRC [Grant No. EP/W000520/1, EP/R034540/1 and EP/V027700/1]. NK thanks the EPSRC Centre for Doctoral Training in Advanced Characterisation of Materials [Grant No. EP/S023259/1]. PGE acknowledges support from the U.S. Department of Energy Office of Basic Energy Sciences through contract DE-FG02-04ER46147. EDX analysis was supported by EPSRC [Grant No. EP/V036327/1].
The authors would like to thank Steve Furlanetto and Sahil Hegde for constructive conversations and feedback. C.E.W. acknowledges the support of the National Science Foundation Graduate Research Fellowship and the University of California, Los Angeles. C.E.W., W.L., S.N., Y.S.C, B.B., F.M., and M.V. thank the support of NASA grant No. 80NSSC20K0500 and the XSEDE/ACCESS AST180056 allocation, as well as, the UCLA cluster Hoffman2 for computational resources. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-2034835. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
† Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, CA 94720 (yingcui@berkeley.edu). The author is partially supported by the National Science Foundation under grants CCF-2153352 and DMS-2309729, and the National Institutes of Health under grant R01CA287413-01.
‡ Department of Mathematics, University of California San Diego, La Jolla, CA 92093 (njw@math.ucsd.edu). The author is partially supported by the National Science Foundation under grant DMS-2110780.
This work was partially supported by NeuroSys, which as part of the initiative 'Clusters4Future' is funded by the Federal Ministry of Education and Research BMBF (03ZU1106DA), and by the project RESCALE within the program AI Lighthouse Projects for the Environment, Climate, Nature and Resources funded by the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV), funding ID: 67KI32006A.
SB was supported by a COST Action CaLISTA grant (reference number E-COST-GRANT-CA211091cd88727). Further support was given by the Czech Science Foundation (GACR) grant GA22-00091S and the Operational Programme Research Development and Education Project No. CZ.02.01.01/00/22-010/0007541. SB would also like to acknowledge the UiT Department of Mathematics and Statistics for their gracious hospitality. DM is supported by the Norwegian Financial Mechanism 2014-2021 (project registration number 2019/34/H/ST1/00636).
This work is supported by the National Natural Science Foundation of China (Project 62271434), Shenzhen Science and Technology Program (Project JCYJ20210324120011032), Guangdong Basic and Applied Basic Research Foundation (Project 2021B1515120008), Shenzhen Key Lab of Crowd Intelligence Empowered Low-Carbon Energy Network (No. ZDSYS20220606100601002), and the Shenzhen Institute of Artificial Intelligence and Robotics for Society. The work of Pengchao Han is supported by Guangdong Basic and Applied Basic Research Foundation under Grants 2022A1515110056.
FIG. 11. (a) Experimental setup for spatially separated beam geometry. (b) The transmission of infrared light in channel B for a given beam separation D . Reported transmission is normalized to the peak steady-state EIT transmission experimentally observed using only the infrared and blue beams of channel B (channel A blocked).(c) The experimentally measured EIT peak height as a function of beam separation, as compared with the results predicted by our theoretical model. There are no free parameters in our theoretical result. The validity of our model is supported by the close correspondence between theoretical and experimental transmission curves.
This work has been funded by the project PCI2022-134990-2 (MARTINI) of the CHISTERA IV Cofund 2021 program, funded by MCIN/AEI/10.13039/501100011033 and by the 'European Union NextGenerationEU/PRTR'; by the research project DisTrack: Tracking disinformation in Online Social Networks through Deep Natural Language Processing, granted by Mobile World Capital Foundation; by the Spanish Ministry of Science and Innovation under FightDIS (PID2020-117263GB-I00); by MCIN/AEI/10.13039/501100011033/ and European Union NextGenerationEU/PRTR for XAI-Disinfodemics (PLEC2021-007681) grant, by Comunidad Autónoma de Madrid under S2018/TCS-4566 grant, by European Comission under IBERIFIER - Iberian Digital Media Research and Fact-Checking Hub (2020-EU-IA-0252); and by "Convenio Plurianual with the Universidad Politécnica de Madrid in the actuation line of Programa de Excelencia para el Profesorado Universitario".
Acknowledgments: We thank many colleagues at IFISC, C. Granell, A. Arenas and A. Raya for useful discussions. We acknowledge funding from project DYNDEEP (EUR2021-122007) from the Agencia Estatal de Investigacion MCIN/AEI/10.13039/501100011033. LL additionally acknowledges funding from project MISLAND (PID2020-114324GB-C22), and Mar´ ıa de Maeztu project CEX2021-001164-M.
This research received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreements No. 945539 (Human Brain Project SGA3) to GP, No. 952215 (TAILOR) to GP, and No. 951910 (MAIA) to IPS; the European Research Council under the Grant Agreement No. 820213 (ThinkAhead) to GP the Wellcome Centre for Human Neuroimaging (Ref: 205103/Z/16/Z) to KF, a CanadaUK Artificial Intelligence Initiative (Ref: ES/T01279X/1) to KF, and the MUR projects PE0000013-FAIR to GP, IR0000011-EBRAINS-Italy to GP and PRIN 2017KZNZLN to IPS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This work was supported by Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0006G04), National Key Research and Development Program of China (Grant No. 2020YFC0833406), Key Research and Development and Transformation Plan of Science and Technology Program for Tibet Autonomous Region China (No. XZ201901-GB-16), Famous teachers workshop project of Tibet University China, Central government China supports the reform and development of local universities of Tibet University in 2020. The code is available at https://github.com/ExplorerLu1024/MIMAD-GAN
J.C.L.D and J.C. are supported by CONAHCyT/DCF-320821. I. D. S is supported by CONAHCyT/Estancias Posdoctorales por México. C.M.R. was supported by CONAHCyT PhD scholarship program. It is a pleasure to thank Antonio Pérez Cortés for his important contribution to the early stages of this project.
This work was supported in part by MOST Major Research and Development Project under Grant 2021YFB2900204; in part by the Sichuan Major R&amp;D Project under Grant 22QYCX0168; in part by the Sichuan Science and Technology Program under Grant 2022YFH0022 and Grant 2023NSFSC1375; in part by the Natural Science Foundation of China under Grant 62132004, Grant 61971102 and Grant 62301122; in part by the Stable Supporting Fund of National Key Laboratory of Underwater Acoustic Technology; and in part by the Key Research and Development Program of Zhejiang Province under Grant 2022C01093. ( Corresponding Author: Jie Hu. )
Funding : This work was done within the Exascale Catalytic Chemistry (ECC) Project, which is supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences and Biosciences Division, as part of the Computational Chemistry Sciences Program. This article has been authored by employees of National Technology &amp; Engineering Solutions of Sandia, LLC under Contract No. DE-NA0003525 with the U.S. Department of Energy (DOE). The employees co-own right, title and interest in and to the article and are responsible for its contents. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this article or allow others to do so, for United States Government purposes. The DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan https://www.energy.gov/downloads/doe-public-access-plan.
We thank Alex Drlica-Wanger, Ben Lillard, Ethan Nadler, Jesus Perez-R´ ıos, and Benjamin Safdi for helpful discussions. A.P. acknowledges support from the Princeton Center for Theoretical Science postdoctoral fellowship. The work of C.B. was supported in part by NASA through the NASA Hubble Fellowship Program grant HST-HF2-51451.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. The work of I.H. and Y.K. was supported in part by DOE grant DE-SC0015655. Part of this work was done the Aspen Center for Physics, which is supported by National Science Foundation grant PHY-1607611.
The authors thank their advisor, Prof. Evelyn N. Wang, for her guidance on this work until the date of her confirmation (12/22/2022) by the U.S. Senate to serve as director of the Advanced Research Projects Agency-Energy (ARPA-E). The authors thank the Office of Energy Efficiency and Renewable Energy for funding under Grant No. DE-EE0009679. G.G. acknowledges funding by the Swiss National Science Foundation via a Postdoc Mobility grant (P400P2_194367). C.D.D. gratefully acknowledges the MIT Martin Family Society of Fellows for Sustainability. We thank Dr. Geoffrey Vaartstra, Dr. Bachir El Fil and Mr. Yang Zhong for fruitful discussions.
Acknowledgments. A. S. R. acknowledges support via a Miller Research Fellowship from the Miller Institute for Basic Research in Science, University of California, Berkeley. A. S. K. acknowledges support from Laboratory Directed Research and Development (LDRD) funding under Contract Number DE-AC0205CH11231. D. R. and J. E. G. acknowledge gifts from Anyscale, Astronomer, Google, IBM, Intel, Lacework, Microsoft, Mohamed Bin Zayed University of Artificial Intelligence, Samsung SDS, Uber, and VMware.
VL acknowledges the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES scholarship through the grants 88882.427898/2019-01. SBR acknowledges support from Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq. RRdC aknowledges the financial support from FAPESP through the grant 2020 / 15245 -2.
We are grateful to the anonymous referee for providing constructive feedback. It is a pleasure to acknowledge Eliot Quataert and Daniel Kasen for helpful discussions on the simulation setup. We thank Shengtai Li for assistance with utilizing the HPC resources, and Adam M. Dempsey for helpful discussions. AK acknowledges support from the Director's postdoctoral fellowship funded by LANL LDRD project No. 20220808PRD4. AK, HL and BRR gratefully acknowledge the support by LANL LDRD program under project No. 20220087DR. Computational resources for this project was provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the U.S. Department of Energy National Nuclear Security Administration under contract No. 89233218CNA000001. This research also used resources of the National Energy Research Scientific Computing Center (NERSC) and the Texas Advanced Computing Center (TACC). NERSC is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This manuscript has been assigned a document release number LA-UR-23-31757.
We would like to acknowledge C. G. Van de Walle, S. T. Pantelides, R. D. Schrimpf, and D. M. Fleetwood for their support and especially for their contributions to our work on GaN. We acknowledge also the computational support of the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing high-performance computing. This work has been supported by the Air Force Office of Scientific Research: Award FA9550-23-1-0549, and through the Center of Excellence in Radiation Effects: Award FA9550-22-1-0012.
We would like to thank Tracy Slatyer for valuable discussions. The work of CV is supported by a grant from the Simons Foundation (602883,CV), the DellaPietra Foundation, and by the NSF grant PHY2013858. CD is partially supported by the Department of Energy (DOE) Grant No. DE-SC0020223. EG is supported in part by the NSF grants PHY2013988 and PHY1748958. The work of GO work is supported by a Leverhulme Trust International Professorship grant number LIP-202-014. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.