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Institution

Moscow Institute of Physics and Technology

EducationDolgoprudnyy, Russia
About: Moscow Institute of Physics and Technology is a education organization based out in Dolgoprudnyy, Russia. It is known for research contribution in the topics: Laser & Large Hadron Collider. The organization has 8594 authors who have published 16968 publications receiving 246551 citations. The organization is also known as: MIPT & Moscow Institute of Physics and Technology (State University).


Papers
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Journal ArticleDOI
13 Nov 2015-Science
TL;DR: A multidimensional approach, based on the measurement and accurate theoretical description of both even and odd harmonic orders, enabled us to reconstruct both quantum amplitudes and phases of the electronic states with a resolution of ~100 attoseconds.
Abstract: The ultrafast motion of electrons and holes after light-matter interaction is fundamental to a broad range of chemical and biophysical processes. We advanced high-harmonic spectroscopy to resolve spatially and temporally the migration of an electron hole immediately after ionization of iodoacetylene while simultaneously demonstrating extensive control over the process. A multidimensional approach, based on the measurement and accurate theoretical description of both even and odd harmonic orders, enabled us to reconstruct both quantum amplitudes and phases of the electronic states with a resolution of ~100 attoseconds. We separately reconstructed quasi-field-free and laser-controlled charge migration as a function of the spatial orientation of the molecule and determined the shape of the hole created by ionization. Our technique opens the prospect of laser control over electronic primary processes.

448 citations

Journal ArticleDOI
TL;DR: The use of an intense collimated beam of protons produced by a high-intensity laser pulse interacting with a plasma for the proton treatment of oncological diseases is discussed and the generation of high quality proton beams is proved with particle in cell simulations.

446 citations

Journal ArticleDOI
TL;DR: In this paper, the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment, are highlighted, highlighting how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as searches for physics beyond the Standard Model.
Abstract: We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.

433 citations

Proceedings Article
03 Dec 2018
TL;DR: This paper presents the key algorithmic techniques behind CatBoost, a new gradient boosting toolkit and provides a detailed analysis of this problem and demonstrates that proposed algorithms solve it effectively, leading to excellent empirical results.
Abstract: This paper presents the key algorithmic techniques behind CatBoost, a new gradient boosting toolkit. Their combination leads to CatBoost outperforming other publicly available boosting implementations in terms of quality on a variety of datasets. Two critical algorithmic advances introduced in CatBoost are the implementation of ordered boosting, a permutation-driven alternative to the classic algorithm, and an innovative algorithm for processing categorical features. Both techniques were created to fight a prediction shift caused by a special kind of target leakage present in all currently existing implementations of gradient boosting algorithms. In this paper, we provide a detailed analysis of this problem and demonstrate that proposed algorithms solve it effectively, leading to excellent empirical results.

431 citations

Journal ArticleDOI
Betsy A. Read1, Jessica Kegel2, Mary J. Klute3, Alan Kuo4, Stephane C. Lefebvre5, Florian Maumus6, Christoph Mayer7, John P. Miller8, Adam Monier9, Asaf Salamov4, Jeremy R. Young10, María Aguilar3, Jean-Michel Claverie11, Stephan Frickenhaus2, Karina Gonzalez12, Emily K. Herman3, Yao-Cheng Lin13, Johnathan A. Napier14, Hiroyuki Ogata11, Analissa F. Sarno1, Jeremy Shmutz4, Declan C. Schroeder, Colomban de Vargas15, Frédéric Verret16, Peter von Dassow17, Klaus Valentin2, Yves Van de Peer13, Glen L. Wheeler18, Joel B. Dacks3, Charles F. Delwiche8, Sonya T. Dyhrman2, Sonya T. Dyhrman19, Sonya T. Dyhrman20, Gernot Glöckner21, Uwe John2, Thomas A. Richards22, Alexandra Z. Worden9, Xiaoyu Zhang1, Igor V. Grigoriev23, Andrew E. Allen24, Kay D. Bidle25, Kay D. Bidle11, Mark Borodovsky11, Chris Bowler15, Colin Brownlee26, Colin Brownlee1, J. Mark Cock12, Marek Eliáš27, Vadim N. Gladyshev28, Marco Groth1, Chittibabu Guda, Ahmad R. Hadaegh29, M. D. Iglesias-Rodriguez30, Jerry Jenkins16, Bethan M. Jones31, Tracy Lawson32, Florian Leese33, Erika Lindquist34, Alexei Lobanov27, Alexandre Lomsadze25, Shehre-Banoo Malik35, Mary E. Marsh36, Luke C. M. Mackinder15, Thomas Mock11, Bernd Mueller-Roeber37, António Pagarete38, Micaela S. Parker39, Ian Probert11, Hadi Quesneville15, Christine A. Raines31, Stefan A. Rensing2, Stefan A. Rensing15, Diego Mauricio Riaño-Pachón40, Sophie Richier40, Sophie Richier41, Sebastian D. Rokitta42, Yoshihiro Shiraiwa43, Darren M. Soanes42, Mark van der Giezen39, Thomas M. Wahlund41, Bryony A. P. Williams44, Willie Wilson43, Gordon Wolfe41, Louie L. Wurch40, Louie L. Wurch42 
11 Jul 2013-Nature
TL;DR: Comparisons across strains demonstrate that E. huxleyi, which has long been considered a single species, harbours extensive genome variability reflected in different metabolic repertoires, and reveals a pan genome (core genes plus genes distributed variably between strains) probably supported by an atypical complement of repetitive sequence in the genome.
Abstract: Coccolithophores have influenced the global climate for over 200 million years(1). These marine phytoplankton can account for 20 per cent of total carbon fixation in some systems(2). They form blooms that can occupy hundreds of thousands of square kilometres and are distinguished by their elegantly sculpted calcium carbonate exoskeletons (coccoliths), rendering them visible from space(3). Although coccolithophores export carbon in the form of organic matter and calcite to the sea floor, they also release CO2 in the calcification process. Hence, they have a complex influence on the carbon cycle, driving either CO2 production or uptake, sequestration and export to the deep ocean(4). Here we report the first haptophyte reference genome, from the coccolithophore Emiliania huxleyi strain CCMP1516, and sequences from 13 additional isolates. Our analyses reveal a pan genome (core genes plus genes distributed variably between strains) probably supported by an atypical complement of repetitive sequence in the genome. Comparisons across strains demonstrate that E. huxleyi, which has long been considered a single species, harbours extensive genome variability reflected in different metabolic repertoires. Genome variability within this species complex seems to underpin its capacity both to thrive in habitats ranging from the equator to the subarctic and to form large-scale episodic blooms under a wide variety of environmental conditions.

430 citations


Authors

Showing all 8797 results

NameH-indexPapersCitations
Dominique Pallin132113188668
Vladimir N. Uversky13195975342
Lee Sawyer130134088419
Dmitry Novikov12734883093
Simon Lin12675469084
Zeno Dixon Greenwood126100277347
Christian Ohm12687369771
Alexey Myagkov10958645630
Stanislav Babak10730866226
Alexander Zaitsev10345348690
Vladimir Popov102103050257
Alexander Vinogradov9641040879
Gueorgui Chelkov9332141816
Igor Pshenichnov8336222699
Vladimir Popov8337026390
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202368
2022238
20211,774
20202,246
20192,112
20181,902