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Electron correlation dynamics of strong-field double ionization of atoms below recollision threshold

Journal of physics: Conference Series 2011年第1期276卷

作者： Yunquan Liu Difa Ye Jie Liu A Rudenko S Tschuch M Dürr M Siegel U Morgner Qihuang Gong R Moshammer J Ullrich Department of Physics and State Key Laboratory for Mesoscopic Physics Peking University Beijing 100871 People's Republic of China Max-Planck-Institut für Kernphysik D-69117 Heidelberg Germany Center for Applied Physics and Technology Peking University 100084 Beijing People's Republic of China Institute of Applied Physics and Computational Mathematics 100088 Beijing People's Republic of China Max-Planck Advanced Study Group at CFEL 22607 Hamburg Germany Leibniz Universität Hannover Welfengarten 1 D-30167 Hannover Germany

In recent combined experimental and theoretical study we have explored nonsequential double ionization of neon and argon atoms in the infrared light field (800nm) below the recollision threshold. We find that the two-electron correlation dynamics depends on atomic structure- 'side-by-side emission' (correlation) for Ne and 'back-to-back emission' (anticorrelation) for argon atoms. This can be explained theoretically within our three dimensional classical model calculation including tunnelling effect. The multiple recollisions as well as recollision-induced-excitation-tunnelling (RIET) effect dominate the anticorrelation of argon, whereas the laser-assisted instantaneous recollision dominates the correlation of neon.

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Position: Bayesian deep learning is needed in the age of large-scale AI 24

Position: Bayesian deep learning is needed in the age of lar...

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Proceedings of the 41st International Conference on Machine Learning

作者： Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel David Dunson Maurizio Filippone Vincent Fortuin Philipp Hennig José Miguel Hernández-Lobato Aliaksandr Hubin Alexander Immer Theofanis Karaletsos Mohammad Emtiyaz Khan Agustinus Kristiadi Yingzhen Li Stephan Mandt Christopher Nemeth Michael A. Osborne Tim G. J. Rudner David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang Department of Mathematics The University of Manchester Manchester UK Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge Spotify London UK Computational Neuroscience Unit University of Bristol Bristol UK Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany and Department of Computer Science Technical University of Munich Munich Germany and Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge UK Department of Mathematics University of Oslo Oslo Norway and Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative California Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London UK Department of Computer Science UC Irvine Irvine Department of Mathematics and Statistics Lancaster University Lancaster UK Department of Engineering Science University of Oxford Oxford UK Center for Data Science New York University New York Munich Center for Machine Learning Munich Germany and Department of Statistics LMU Munich Munich Germany DeepMind London UK and Department of Statistics University of Oxford Oxford UK Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences and Center for Data Science Computer Science Department New York University New York Department of Computer Science Purdue University West Lafayette

In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective reveals a multitude of overlooked metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data, that demand attention. Bayesian deep learning (BDL) constitutes a promising avenue, offering advantages across these diverse settings. This paper posits that BDL can elevate the capabilities of deep learning. It revisits the strengths of BDL, acknowledges existing challenges, and highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential.

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Criterion and principles of easily-modified program

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IOP Conference Series: Materials Science and Engineering 2021年第1期1027卷

作者： A Prutzkow Department of Computational and Applied Mathematics Ryazan State Radio Engineering University named after V. F. Utkin 59/1 Gagarina str. Ryazan 390005 Russian Federation Department of Mathematics Physics and Medical Computer Sciences Ryazan State Medical University named after I. P. Pavlov 9 Vysokovoltnaya str. Ryazan 390026 Russian Federation

Ease of modifying is one of the characteristics of the program. The existing approaches do not clarify this concept. These approaches are clean code and maintainability. We formulate simple and explicit criterion and principles of easily-modified programs. The criterion is an E.W. Dijkstra's criterion. The principles are (1) the names of the elements should reflect their purpose in the program; (2) use indentation for nested statements and blank lines; (3) one program element must have one assignment and one assignment must correspond to only one element; (4) optimize dependencies between program elements. We introduce a metric for easily-modified programs as well. It's a number of commands in methods and static blocks in a class.

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Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel’dovich effect

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Physical Review D 2020年第2期102卷 023534-023534页

作者： Mathew S. Madhavacheril J. Colin Hill Sigurd Næss Graeme E. Addison Simone Aiola Taylor Baildon Nicholas Battaglia Rachel Bean J. Richard Bond Erminia Calabrese Victoria Calafut Steve K. Choi Omar Darwish Rahul Datta Mark J. Devlin Joanna Dunkley Rolando Dünner Simone Ferraro Patricio A. Gallardo Vera Gluscevic Mark Halpern Dongwon Han Matthew Hasselfield Matt Hilton Adam D. Hincks Renée Hložek Shuay-Pwu Patty Ho Kevin M. Huffenberger John P. Hughes Brian J. Koopman Arthur Kosowsky Martine Lokken Thibaut Louis Marius Lungu Amanda MacInnis Loïc Maurin Jeffrey J. McMahon Kavilan Moodley Federico Nati Michael D. Niemack Lyman A. Page Bruce Partridge Naomi Robertson Neelima Sehgal Emmanuel Schaan Alessandro Schillaci Blake D. Sherwin Cristóbal Sifón Sara M. Simon David N. Spergel Suzanne T. Staggs Emilie R. Storer Alexander van Engelen Eve M. Vavagiakis Edward J. Wollack Zhilei Xu Centre for the Universe Perimeter Institute for Theoretical Physics Waterloo Ontario Canada N2L 2Y5 Department of Astrophysical Sciences Princeton University 4 Ivy Lane Princeton New Jersey 08544 USA Department of Physics Columbia University 550 West 120th Street New York New York 10027 USA Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New York New York 10010 USA School of Natural Sciences Institute for Advanced Study Princeton New Jersey 08540 USA Department of Physics and Astronomy Johns Hopkins University Baltimore Maryland 21218 USA Department of Physics University of Michigan Ann Arbor Michigan 48103 USA Department of Astronomy Cornell University Ithaca New York 14853 USA Canadian Institute for Theoretical Astrophysics University of Toronto 60 St. George St. Toronto Ontario M5S 3H8 Canada School of Physics and Astronomy Cardiff University The Parade Cardiff CF24 3AA United Kingdom Department of Applied Mathematics and Theoretical Physics University of Cambridge Wilberforce Road Cambridge CB3 0WA United Kingdom Department of Physics and Astronomy University of Pennsylvania 209 South 33rd Street Philadelphia Pennsylvania 19104 USA Joseph Henry Laboratories of Physics Jadwin Hall Princeton University Princeton New Jersey 08544 USA Instituto de Astrofísica and Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 7820436 Macul Santiago Chile Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics Cornell University 109 Clark Hall Ithaca New York 14853 USA Department of Physics and Astronomy University of Southern California Los Angeles California 90089-0484 USA Department of Physics and Astronomy University of British Columbia Vancouver British Columbia Canada V6T 1Z1 Physics and Astronomy Department Stony Brook University Stony Brook New York 11794 USA Astrophysics & Cosmology Research Unit Sc

Optimal analyses of many signals in the cosmic microwave background (CMB) require map-level extraction of individual components in the microwave sky, rather than measurements at the power spectrum level alone. To date, nearly all map-level component separation in CMB analyses has been performed exclusively using satellite data. In this paper, we implement a component separation method based on the internal linear combination (ILC) approach which we have designed to optimally account for the anisotropic noise (in the 2D Fourier domain) often found in ground-based CMB experiments. Using this method, we combine multifrequency data from the Planck satellite and the Atacama Cosmology Telescope Polarimeter (ACTPol) to construct the first wide-area (≈2100 sq. deg.), arcminute-resolution component-separated maps of the CMB temperature anisotropy and the thermal Sunyaev-Zel’dovich (tSZ) effect sourced by the inverse-Compton scattering of CMB photons off hot, ionized gas. Our ILC pipeline allows for explicit deprojection of various contaminating signals, including a modified blackbody approximation of the cosmic infrared background (CIB) spectral energy distribution. The cleaned CMB maps will be a useful resource for CMB lensing reconstruction, kinematic SZ cross-correlations, and primordial non-Gaussianity studies. The tSZ maps will be used to study the pressure profiles of galaxies, groups, and clusters through cross-correlations with halo catalogs, with dust contamination controlled via CIB deprojection. The data products described in this paper are available on LAMBDA.

关键词： Cosmic microwave background Cosmology

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Picosecond volume expansion drives a later-time insulator-metal transition in a nano-textured Mott Insulator

arXiv

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arXiv 2023年

作者： Verma, Anita Golež, Denis Gorobtsov, Oleg Yu. Kaj, Kelson Russell, Ryan Kaaret, Jeffrey Z. Lamb, Erik Khalsa, Guru Nair, Hari P. Sun, Yifei Bouck, Ryan Schreiber, Nathaniel Ruf, Jacob P. Ramaprasad, Varun Kubota, Yuya Togashi, Tadashi Stoica, Vladimir A. Padmanabhan, Hari Freeland, John W. Benedek, Nicole A. Shpyrko, Oleg Harter, John W. Averitt, Richard D. Schlom, Darrell G. Shen, Kyle M. Millis, Andrew J. Singer, Andrej Department of Materials Science and Engineering Cornell University IthacaNY14853 United States Jozef Stefan Institute Jamova 39 LjubljanaSI-1000 Slovenia Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 Ljubljana1000 Slovenia Department of Physics University of California San Diego La Jolla CA92093 United States Materials Department University of California Santa BarbaraCA93106 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Physics Department Cornell University IthacaNY14853 United States Riken SPring-8 Center 1-1-1 Kouto Sayo-cho Sayo-gun Hyogo679-5148 Japan Japan Synchrotron Radiation Research Institute 1-1-1 Kouto Sayo-cho Sayo-gun Hyogo679-5198 Japan Department of Materials Science and Engineering Pennsylvania State University University ParkPA United States X-ray Science Division Argonne National Laboratory ArgonneIL60439 United States Kavli Institute at Cornell for Nanoscale Science Cornell University IthacaNY14853 United States Leibniz-Institut für Kristallzüchtung Max-Born-Straße 2 Berlin12489 Germany Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Department of Physics Columbia University 538 West 120th Street New YorkNY10027 United States

Technology moves towards ever faster switching between different electronic and magnetic states of matter. Manipulating properties at terahertz rates requires accessing the intrinsic timescales of electrons (femtoseconds) and associated phonons (10s of femtoseconds to few picoseconds), which is possible with short-pulse photoexcitation. Yet, in many Mott insulators, the electronic transition is accompanied by the nucleation and growth of percolating domains of the changed lattice structure, leading to empirical time scales dominated by slow coarsening dynamics. Here, we use time-resolved X-ray diffraction and reflectivity measurements to investigate the photoinduced insulator-to-metal transition in an epitaxially strained thin film Mott insulator Ca2RuO4. The dynamical transition occurs without observable domain formation and coarsening effects, allowing the study of the intrinsic electronic and lattice dynamics. Above a fluence threshold, the initial electronic excitation drives a fast lattice rearrangement, followed by a slower electronic evolution into a metastable non-equilibrium state. Microscopic calculations based on time-dependent dynamical mean-field theory and semiclassical lattice dynamics within a recently published equilibrium energy landscape picture explain the threshold-behavior and elucidate the delayed onset of the electronic phase transition in terms of kinematic constraints on recombination. Analysis of satellite scattering peaks indicates the persistence of a strain-induced nano-texture in the photoexcited film. This work highlights the importance of combined electronic and structural studies to unravel the physics of dynamic transitions and elucidates the role of strain in tuning the timescales of photoinduced processes. © 2023, CC BY.

关键词： Mott insulators

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Evaluation of Beam Matching in Commissioning a Halcyon Accelerator

SSRN

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SSRN 2023年

作者： Tai, Duong Thanh Tuan, Hoang Duc Hai, Nguyen Xuan Anh, Nguyen Ngoc Sulieman, Abdelmoneim Bradley, David Andrew Sandwall, Peter Chow, James Department of Medical Physics Faculty of Medicine Nguyen Tat Thanh University 298-300A Nguyen Tat Thanh Street Ward 13 District 4 Ho Chi Minh City Viet Nam Department of Radiation Oncology University Medical Shing Mark Hospital Dong Nai810000 Viet Nam Dalat Nuclear Research Institute Dalat City Viet Nam Faculty of Fundamental Science PHENIKAA University Yen Nghia Ha Dong Hanoi12116 Viet Nam A&A Green Phoenix Group JSC No.167 Hoang Ngan Trung Hoa Cau Giay Hanoi11313 Viet Nam Department of Radiology and Medical Imaging Sciences College of Applied Medical Sciences Prince Sattam bin Abdulaziz University P.O. Box 422 Alkharj11942 Saudi Arabia Centre for Applied Physics and Radiation Technologies Sunway University PJ 46150 Malaysia School of Mathematics and Physics University of Surrey GuildfordGU2 7XH United Kingdom Department of Radiation Oncology OhioHealth Mansfield OH United States Radiation Medicine Program Princess Margaret Cancer Centre University Health Network TorontoONM5G 1X6 Canada Department of Radiation Oncology University of Toronto TorontoONM5T 1P5 Canada

Purpose: This study aims to serve as a methods paper demonstrating the evaluation and validation of manufacturer reference data, commonly referred to as "Golden Beam Data" (GBD). This data has been used during the commissioning of a Halcyon linear accelerator Analyses of gamma index and relative dose difference were performed in the *** and Methods: For the Halcyon accelerator, dosimetric data were acquired including percentage depth doses, dose profiles and output factors, use being made of a 3D-scanning water tank and various ionization chambers. The GBD was exported from the treatment planning system and compared with measurements. Gamma index and relative dose difference analyses were performed to assess agreement between GBD and ***: For field sizes greater than 4×4 cm2, percentage depth doses and beam profiles, the gamma index between GBD and measurements was less than 1%/1 mm. The gamma indices were found to be slightly greater for the field sizes 2×2 cm2 and 4×4 cm2, remaining within 2%/2 mm, satisfying the AAPM Medical physics Practice Guideline 5 for commissioning and QA of MV photon beams. Between GBD and measurements, output factor deviations were not significant, remaining within 1%.Conclusion: The GBD data was validated in the commissioning of a Halcyon linear accelerator, analyses being made of gamma index and relative dose difference. The gamma index analysis is shown to be an effective method for comprehensively evaluating deviations between the GBD and measurements in the beam matching process. © 2023, The Authors. All rights reserved.

关键词： Photons

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Introduction to the theory of stochastic processes: Studying the basic concepts

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AIP Conference Proceedings 2022年第1期2647卷

作者： Elena Kuznetsova Natalia Zhbanova Tatyana Fomina Faina Golovaneva Tatyana Glushakova 1Department of Automation and Informatics Lipetsk State Technical University Lipetsk Russia 2Department of Mathematics and Physics Lipetsk State Pedagogical University named after P. P. Semenov-Tyan-Shansky Lipetsk Russia 3Department of Partial Differential Equation Studies and Relativity Theory Voronezh State University Voronezh Russia 4Department of Computational Mathematics and Applied Information Technologies Voronezh State University Voronezh Russia

Models of stochastic processes describe many phenomena in nature, technology, and economics. However, STEM and economics students usually do not have enough time to study this topic. When developing a course on stochastic processes, a teacher faces some challenges. The task is to present sophisticated educational material, combining the mathematical severity of presentation and ease of understanding. Throughout several lessons, students should get a holistic understanding of the subject so that they can correctly and meaningfully apply models of stochastic processes in the field of their professional activities. The complicated nature of stochastic processes models requires understanding their multidimensionality, facilitated by various representation methods: formulas, tables, graphs, and computer simulation. The article discusses applying these techniques on the example of the formation of the concepts "stochastic process" "mathematical expectation and variance of a stochastic process."

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The Atacama Cosmology Telescope: Probing the baryon content of SDSS DR15 galaxies with the thermal and kinematic Sunyaev-Zel’dovich effects

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Physical Review D 2021年第4期104卷 043503-043503页

作者： E. M. Vavagiakis P. A. Gallardo V. Calafut S. Amodeo S. Aiola J. E. Austermann N. Battaglia E. S. Battistelli J. A. Beall R. Bean J. R. Bond E. Calabrese S. K. Choi N. F. Cothard M. J. Devlin C. J. Duell S. M. Duff A. J. Duivenvoorden J. Dunkley R. Dunner S. Ferraro Y. Guan J. C. Hill G. C. Hilton M. Hilton R. Hložek Z. B. Huber J. Hubmayr K. M. Huffenberger J. P. Hughes B. J. Koopman A. Kosowsky Y. Li M. Lokken M. Madhavacheril J. McMahon K. Moodley S. Naess F. Nati L. B. Newburgh M. D. Niemack L. A. Page B. Partridge E. Schaan A. Schillaci C. Sifón D. N. Spergel S. T. Staggs J. N. Ullom L. R. Vale A. Van Engelen J. Van Lanen E. J. Wollack Z. Xu Department of Physics Cornell University Ithaca New York 14853 USA Department of Astronomy Cornell University Ithaca New York 14853 USA Center for Computational Astrophysics Flatiron Institute New York New York 10010 USA NIST Quantum Sensors Group 325 Broadway Boulder Colorado 80305 USA Physics Department Sapienza University of Rome Piazzale Aldo Moro 5 I-00185 Rome Italy Canadian Institute for Theoretical Astrophysics University of Toronto Toronto Ontario M5S 3H8 Canada School of Physics and Astronomy Cardiff University The Parade Cardiff CF24 3AA United Kingdom Department of Applied and Engineering Physics Cornell University Ithaca New York 14853 USA Department of Physics and Astronomy University of Pennsylvania 209 South 33rd Street Philadelphia Pennsylvania 19104 USA Joseph Henry Laboratories of Physics Jadwin Hall Princeton University Princeton New Jersey 08544 USA Department of Astrophysical Sciences Peyton Hall Princeton University Princeton New Jersey 08544 USA Instituto de Astrofísica and Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Avenida Vicuña Mackenna 4860 7820436 Macul Santiago Chile Lawrence Berkeley National Laboratory One Cyclotron Road Berkeley California 94720 USA Berkeley Center for Cosmological Physics UC Berkeley California 94720 USA Department of Physics and Astronomy University of Pittsburgh Pittsburgh Pennsylvania 15260 USA Department of Physics Columbia University New York New York 10027 USA Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban 4041 South Africa David A. Dunlap Department of Astronomy and Astrophysics University of Toronto 50 St. George Street Toronto Ontario M5S 3H4 Canada Dunlap Institute for Astronomy and Astrophysics University of Toronto 50 St. George Street Toronto Ontario M5S 3H4 Canada Department of Physics Florida State University Tallahassee Florida 32306 USA Department of Physics and Astronomy Rutgers Th

We present measurements of the average thermal Sunyaev Zel’dovich (tSZ) effect from optically selected galaxy groups and clusters at high signal-to-noise (up to 12σ) and estimate their baryon content within a 2.1′ radius aperture. Sources from the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey DR15 catalog overlap with 3,700 sq deg of sky observed by the Atacama Cosmology Telescope (ACT) from 2008 to 2018 at 150 and 98 GHz (ACT DR5), and 2,089 sq deg of internal linear combination component-separated maps combining ACT and Planck data (ACT DR4). The corresponding optical depths τ¯, which depend on the baryon content of the halos, are estimated using results from cosmological hydrodynamic simulations assuming an active galactic nuclei feedback radiative cooling model. We estimate the mean mass of the halos in multiple luminosity bins, and compare the tSZ-based τ¯ estimates to theoretical predictions of the baryon content for a Navarro-Frenk-White profile. We do the same for τ¯ estimates extracted from fits to pairwise baryon momentum measurements of the kinematic Sunyaev-Zel’dovich effect (kSZ) for the same dataset obtained in a companion paper. We find that the τ¯ estimates from the tSZ measurements in this work and the kSZ measurements in the companion paper agree within 1σ for two out of the three disjoint luminosity bins studied, while they differ by 2–3σ in the highest luminosity bin. The optical depth estimates account for one-third to all of the theoretically predicted baryon content in the halos across luminosity bins. Potential systematic uncertainties are discussed. The tSZ and kSZ measurements provide a step toward empirical Compton-y¯−τ¯ relationships to provide new tests of cluster formation and evolution models.

关键词： Cosmic microwave background Cosmological parameters Cosmology Large scale structure of the Universe

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Leveraging randomized compiling for the QITE algorithm

arXiv

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arXiv 2021年

作者： Ville, Jean-Loup Morvan, Alexis Hashim, Akel Naik, Ravi K. Lu, Marie Mitchell, Bradley Kreikebaum, John-Mark O’Brien, Kevin P. Wallman, Joel J. Hincks, Ian Emerson, Joseph Smith, Ethan Younis, Ed Iancu, Costin Santiago, David I. Siddiqi, Irfan Quantum Nanoelectronics Laboratory Dept. of Physics University of California at Berkeley BerkeleyCA94720 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Inst. for Quantum Computing Dept. of Applied Mathematics University of Waterloo WaterlooONN2L 3G1 Canada Quantum Benchmark Inc. KitchenerONN2H 5G5 Canada

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary Time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary Time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices. © 2021, CC BY.

关键词： Benchmarking

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Interpretation of gravity satellite data to delineate structural features connected to geothermal resources at Bur Ni Geureudong geothermal field

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IOP Conference Series: Earth and Environmental Science 2019年第1期364卷

作者： D R Putri M Nanda S Rizal R Idroes N Ismail Doctoral Program of Mathematics and Applied Science Universitas Syiah Kuala Banda Aceh 23111 Indonesia Marine Sciences Department Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Department of Pharmacy Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Department of Physics Faculty of Mathematics and Natural Science Universitas Syiah Kuala Banda Aceh 23111 Indonesia

The gravity method is broadly used in analyzing potential geothermal studies. The method can be used for determining potential areas, reservoir locations, and geological structure investigation. In this paper, satellite gravity data was applied for better understand the geological conditions connected with the geothermal system of Bur Ni Geureudong geothermal field, Bener Meriah District, Aceh, Indonesia. Open access Free Air anomaly data were provided by satellite geodesy information with 1 minute-grid. The data were reduced to obtain Bouguer anomaly distribution in the study area. Tilt derivative (TDR) technique was applied to Bouguer anomaly to enhance linear trends of geological structures. The aim of this analytical technique is able to clearly display faults correlated with geothermal manifestations around the Bur Ni Geureudong geothermal field. The complete Bouguer anomaly range of 20 mGal up to 170 mGal covers Bur Ni Geureudong volcano complex. A low Bouguer anomaly is located in all summits of volcanoes that are included in Bur Ni Geureudong Volcano Complex; those are summits of Bur Geureudong volcano, Bur Ni Telong Volcano, Pepanji Mountain, and Salah Nama Mountain. The low Bouguer anomaly is associated with the andesitic flow and volcanic ashes. The higher Bouguer Anomaly is reflected in high-density basement rock in the west of Geureudong Volcano. Tilt derivative (TDR) shows geological structures more detail, particularly, the tilt derivative (TDR) clearly detects two fault structures over the study area presented by a tilt value of zero. The results will be useful as basic information in exploration study of Bur Ni Geureudong geothermal field.

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