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Gammapy: A Python package for gamma-ray astronomy

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arXiv 2023年

作者： Donath, Axel Terrier, Régis Remy, Quentin Sinha, Atreyee Nigro, Cosimo Pintore, Fabio Khélifi, Bruno Olivera-Nieto, Laura Ruiz, Jose Enrique Brügge, Kai Linhoff, Maximilian Contreras, Jose Luis Acero, Fabio Aguasca-Cabot, Arnau Berge, David Bhattacharjee, Pooja Buchner, Johannes Boisson, Catherine Fidalgo, David Carreto Chen, Andrew de Lavergne, Mathieu de Bony de Miranda Cardoso, José Vinícius Deil, Christoph Füßling, Matthias Funk, Stefan Giunti, Luca Hinton, Jim Jouvin, Léa King, Johannes Lefaucheur, Julien Lemoine-Goumard, Marianne Lenain, Jean-Philippe López-Coto, Rubén Mohrmann, Lars Morcuende, Daniel Panny, Sebastian Regeard, Maxime Saha, Lab Siejkowski, Hubert Siemiginowska, Aneta Sipőcz, Brigitta M. Unbehaun, Tim van Eldik, Christopher Vuillaume, Thomas Zanin, Roberta Center for Astrophysics Harvard and Smithsonian United States Université de Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France Max-Planck-Institut für Kernphysik P.O. Box 103980 HeidelbergD 69029 Germany IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain INAF/IASF Palermo Via U. La Malfa 153 PA Palermo90146 Italy Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Point8 GmbH Germany Astroparticle Physics Department of Physics TU Dortmund University Otto-Hahn-Str. 4a DortmundD-44227 Germany Université Paris-Saclay Université Paris Cité CEA CNRS AIM Gif-sur-YvetteF-91191 France c. Martí i Franqués 1 Barcelona08028 Spain c. Martí i Franqués 1 Barcelona08028 Spain c. Gran Capità 2-4 Barcelona08034 Spain Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain ZeuthenD-15738 Germany Institute of physics Humboldt-University of Berlin BerlinD-12489 Germany Université Savoie Mont Blanc CNRS Laboratoire d’Annecy de Physique des Particules - IN2P3 Annecy74000 France Max Planck Institute for extraterrestrial Physics Giessenbachstrasse Garching85748 Germany Laboratoire Univers et Théories Observatoire de Paris Université PSL Université Paris Cité CNRS MeudonF-92190 France Max Planck Computing and Data Facility Gießenbachstraße 2 Garching85748 Germany School of Physics University of the Witwatersrand 1 Jan Smuts Avenue Braamfontein Johannesburg2050 South Africa The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Saupfercheckweg Heidelberg1 69117 Germany Friedrich-Alexander-Universität Erlangen-Nürnberg Nikolaus-Fiebiger Strasse 2 Erlangen91058 Germany IRFU CEA Université Pa

Context. Traditionally, TeV-γ-ray astronomy has been conducted by experiments employing proprietary data and analysis software. However, the next generation of γ-ray instruments, such as the Cherenkov Telescope Array Observatory (CTAO), will be operated as open observatories. Alongside the data, they will also make the associated software tools available to a wider community. This necessity prompted the development of open, high-level, astronomical software customized for high-energy astrophysics. Aims. In this article, we present Gammapy, an open-source Python package for the analysis of astronomical γ-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different γ-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages. Methods. Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting γ-ray instruments. After the data are binned, the flux and morphology of one or more γ-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported. Results. After describing the structure of the package, we show, using publicly available gamma-ray data, the capabilities of Gammapy in multiple traditional and novel γ-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexib

关键词： Gamma rays

Author Correction: The landscape of viral associations in human cancers

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Nature genetics 2023年第6期55卷 1077页

作者： Marc Zapatka Ivan Borozan Daniel S Brewer Murat Iskar Adam Grundhoff Malik Alawi Nikita Desai Holger Sültmann Holger Moch Colin S Cooper Roland Eils Vincent Ferretti Peter Lichter Division of Molecular Genetics German Cancer Research Center (DKFZ) Heidelberg Germany. Informatics and Bio-computing Program Ontario Institute for Cancer Research Toronto Ontario Canada. Norwich Medical School University of East Anglia Norwich UK. Earlham Institute Norwich UK. Heinrich-Pette-Institute Leibniz Institute for Experimental Virology Hamburg Germany. German Center for Infection Research (DZIF) Partner Site Hamburg-Borstel-Lübeck-Riems Hamburg Germany. Bioinformatics Core University Medical Center Hamburg-Eppendorf Hamburg Germany. Bioinformatics Group Department of Computer Science University College London London UK. Biomedical Data Science Laboratory Francis Crick Institute London UK. National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany. Division of Cancer Genome Research German Cancer Research Center (DKFZ) Heidelberg Germany. German Cancer Consortium (DKTK) Heidelberg Germany. Department of Pathology and Molecular Pathology University and University Hospital Zürich Zurich Switzerland. Institute of Cancer Research London UK. University of East Anglia Norwich UK. Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Bioinformatics and Functional Genomics Institute of Pharmacy and Molecular Biotechnology Heidelberg University and BioQuant Center Heidelberg Germany. Center for Digital Health Berlin Institute of Health and Charité Universitätsmedizin Berlin Berlin Germany. Ontario Institute for Cancer Research MaRS Centre Toronto Ontario Canada. Department of Biochemistry and Molecular Medicine University of Montreal Montreal Québec Canada. Division of Molecular Genetics German Cancer Research Center (DKFZ) Heidelberg Germany. peter.lichter@dkfz-heidelberg.de. German Cancer Consortium (DKTK) Heidelberg Germany. peter.lichter@dkfz-heidelberg.de.

A note on "quantum algorithm for linear systems of equations"

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arXiv 2018年

作者： Xu, Yong-Zhen Huang, Yifan Ye, Zekun Li, Lvzhou Institute of Computer Science Theory School of Data and Computer Science Sun Yat-sen University Guangzhou510006 China Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Ministry of Education Guangzhou510006 China

Recently, an efficient quantum algorithm for linear systems of equations introduced by Harrow, Hassidim, and Lloyd, has received great concern from the academic community. However, the error and complexity analysis for this algorithm seems so complicated that it may not be applicable to other filter functions for other tasks. In this note, a concise proof is proposed. We hope that it may inspire some novel HHL-based algorithms that can compute F(A)|bi for any computable F. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum theory

Structured decomposition for reversible Boolean functions

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arXiv 2018年

作者： Jiang, Jiaqing Sun, Xiaoming Sun, Yuan Wu, Kewen Xia, Zhiyu CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China

Reversible Boolean function is a one-to-one function which maps n-bit input to n-bit output. Reversible logic synthesis has been widely studied due to its relationship with low-energy computation as well as quantum computation. In this work, we give a structured decomposition for even reversible Boolean functions (RBF). Specifically, for n ≥ 6, any even n-bit RBF can be decomposed to 7 blocks of (n − 1)-bit RBF, where 7 is a constant independent of n;and the positions of those blocks have large degree of freedom. Moreover, if the (n − 1)-bit RBFs are required to be even as well, we show for n ≥ 10, n-bit RBF can be decomposed to 10 even (n − 1)-bit RBFs. For simplicity, we say our decomposition has block depth 7 and even block depth 10. Our result improves Selinger’s work in block depth model, by reducing the constant from 9 to 7;and from 13 to 10 when the blocks are limited to be even. We emphasize that our setting is a bit different from Selinger’s. In Selinger’s constructive proof, each block is one of two specific positions and thus the decomposition has an alternating structure. We relax this restriction and allow each block to act on arbitrary (n − 1) bits. This relaxation keeps the block structure and provides more candidates when choosing positions of blocks. Copyright © 2018, The Authors. All rights reserved.

关键词： Logic gates

SNe Ia from double detonations: Impact of core-shell mixing on the carbon ignition mechanism

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arXiv 2020年

作者： Gronow, Sabrina Collins, Christine Ohlmann, Sebastian T. Pakmor, Rüdiger Kromer, Markus Seitenzahl, Ivo R. Sim, Stuart A. Röpke, Friedrich K. Heidelberger Institut für Theoretische Studien Schloss-Wolfsbrunnenweg 35 Heidelberg69118 Germany Zentrum für Astronomie der Universität Heidelberg Astronomisches Rechen-Institut Mönchhofstr. 12-14 Heidelberg69120 Germany Astrophysics Research Center School of Mathematics and Physics Queen's University Belfast Belfast Northern IrelandBT7 1NN United Kingdom Max Planck Computing and Data Facility Gießenbachstraße 2 Garching85748 Germany Max Planck Institute for Astrophysics Karl-Schwarzschild-Straße 1 Garching85748 Germany Zentrum für Astronomie der Universität Heidelberg Institut für Theoretische Astrophysik Philosophenweg 12 Heidelberg69120 Germany School of Science University of New South Wales Australian Defence Force Academy CanberraACT2600 Australia

Sub-Chandrasekhar mass white dwarfs accreting a helium shell on a carbon-oxygen core are potential progenitors of normal Type Ia supernovae. This work focuses on the details of the onset of the carbon detonation in the double detonation sub-Chandrasekhar model. In order to simulate the influence of core-shell mixing on the carbon ignition mechanism, the helium shell and its detonation are followed with an increased resolution compared to the rest of the star treating the propagation of the detonation wave more accurately. This significantly improves the predictions of the nucleosynthetic yields from the helium burning. The simulations were carried out with the Arepo code. A carbon-oxygen core with a helium shell was set up in one dimension and mapped to three dimensions. We ensured the stability of the white dwarf with a relaxation step before the hydrodynamic detonation simulation started. Synthetic observables were calculated with the radiative transfer code Artis. An ignition mechanism of the carbon detonation was observed, which received little attention before. In this "scissors mechanism", the impact the helium detonation wave has on unburnt material when converging opposite to its ignition spot is strong enough to ignite a carbon detonation. This is possible in a carbon enriched transition region between the core and shell. The detonation mechanism is found to be sensitive to details of the core-shell transition and our models illustrate the need to consider core-shell mixing taking place during the accretion process. Even though the detonation ignition mechanism differs form the converging shock mechanism, the differences in the synthetic observables are not significant. Though they do not fit observations better than previous simulations, they illustrate the need for multi-dimensional simulations. Copyright © 2020, The Authors. All rights reserved.

关键词： Hydrodynamics

Method for the calculation of the Hamaker constants of organic materials by the Lifshitz macroscopic approach with DFT

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arXiv 2019年

作者： Takagishi, Hideyuki Masuda, Takashi Shimoda, Tatsuya Maezono, Ryo Hongo, Kenta School of Materials Science JAIST Asahidai 1-1 Nomi Ishikawa923-1292 Japan School of Information Science JAIST Asahidai 1-1 Nomi Ishikawa923-1292 Japan Computational Engineering Applications Unit RIKEN 2-1 Hirosawa Wako Saitama351-0198 Research Center for Advanced Computing Infrastructure JAIST Asahidai 1-1 Nomi Ishikawa923-1292 Japan Center for Materials Research by Information Integration Research Services Division of Materials Data and Integrated System National Institute for Materials Science Tsukuba305-0047 PRESTO Japan Science and Technology Agency 4-1-8 Honcho Kawaguchi-shi Saitama322-0012 Japan

The Hamaker constants, which are coefficients providing quantitative information on intermolecular forces, were calculated for a number of different materials according to the Lifshitz theory via simple DFT calculations without any experimental measurements being performed. The physical properties (polarizability, dipole moment, molecular volume, and vibrational frequency) of organic molecules were calculated using the B3LYP density functional and the aug-cc-pVDZ basis set. Values for the Hamaker constants were obtained using the approximation of the Lorentz-Lorenz equation and Onsager's equation with these properties. It was found that, in the case of 'non-associative' materials, like hydrocarbons, ethers, ketones, aldehydes, carboxylic acids, esters, nitriles, and hydrosilanes, and halides, the calculated Hamaker constants were similar in value to their experimentally determined counterparts. Moreover, with this calculation method, it is easy to create the molecular model and the CPU time can be shortened. Copyright © 2019, The Authors. All rights reserved.

关键词： Ketones

Angular triplet-center loss for multi-view 3D shape retrieval

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arXiv 2018年

作者： Li, Zhaoqun Xu, Cheng Leng, Biao School of Computer Science and Engineering Beihang University Beijing100191 Research Institute of Beihang University in Shenzhen Shenzhen518057 Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191

How to obtain the desirable representation of a 3D shape, which is discriminative across categories and polymerized within classes, is a significant challenge in 3D shape retrieval. Most existing 3D shape retrieval methods focus on capturing strong discriminative shape representation with softmax loss for the classification task, while the shape feature learning with metric loss is neglected for 3D shape retrieval. In this paper, we address this problem based on the intuition that the cosine distance of shape embeddings should be close enough within the same class and far away across categories. Since most of 3D shape retrieval tasks use cosine distance of shape features for measuring shape similarity, we propose a novel metric loss named angular triplet-center loss, which directly optimizes the cosine distances between the features. It inherits the triplet-center loss property to achieve larger inter-class distance and smaller intra-class distance simultaneously. Unlike previous metric loss utilized in 3D shape retrieval methods, where Euclidean distance is adopted and the margin design is difficult, the proposed method is more convenient to train feature embeddings and more suitable for 3D shape retrieval. Moreover, the angle margin is adopted to replace the cosine margin in order to provide more explicit discriminative constraints on an embedding space. Extensive experimental results on two popular 3D object retrieval benchmarks, ModelNet40 and ShapeNetCore 55, demonstrate the effectiveness of our proposed loss, and our method has achieved state-of-the-art results on various 3D shape datasets. Copyright © 2018, The Authors. All rights reserved.

关键词： Embeddings

Expanding the horizon of automated metamaterials discovery via quantum annealing

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arXiv 2019年

作者： Kitai, Koki Guo, Jiang Ju, Shenghong Tanaka, Shu Tsuda, Koji Shiomi, Junichiro Tamura, Ryo Graduate School of Frontier Sciences University of Tokyo Chiba277-8568 Japan Department of Mechanical Engineering University of Tokyo Tokyo113-8654 Japan Research and Services Division of Materials Data and Integrated System National Institute for Materials Science Ibaraki305-0047 Japan Green Computing Systems Research Organization Waseda University Tokyo162-0042 Japan JST PRESTO Saitama332-0012 Japan RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science Ibaraki305-0044 Japan

Complexity of materials designed by machine learning is currently limited by the inefficiency of classical computers. We show how quantum annealing can be incorporated into automated materials discovery and conduct a proof-of-principle study on designing complex thermofunctional metamaterials consisting of SiO2, SiC, and Poly(methyl methacrylate). Empirical computing time of our quantum-classical hybrid algorithm involving a factorization machine, a rigorous coupled wave analysis, and a D-Wave 2000Q quantum annealer was insensitive to the problem size, while a classical counterpart experienced rapid increase. Our method was used to design complex structures of wavelength selective radiators showing much better concordance with the thermal atmospheric transparency window in comparison to existing human-designed alternatives. Our result shows that quantum annealing provides scientists gigantic computational power that may change how materials are designed. Copyright © 2019, The Authors. All rights reserved.

关键词： Metamaterials

Euclid preparation. Simulations and nonlinearities beyond ΛCDM. 2. Results from non-standard simulations

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arXiv 2024年

作者： Rácz, G. Breton, M.-A. Fiorini, B. Le Brun, A.M.C. Winther, H.-A. Sakr, Z. Pizzuti, L. Ragagnin, A. Gayoux, T. Altamura, E. Carella, E. Pardede, K. Verza, G. Koyama, K. Baldi, M. Pourtsidou, A. Vernizzi, F. Adame, A.G. Adamek, J. Avila, S. Carbone, C. Despali, G. Giocoli, C. Hernández-Aguayo, C. Hassani, F. Kunz, M. Li, B. Rasera, Y. Yepes, G. Gonzalez-Perez, V. Corasaniti, P.-S. García-Bellido, J. Hamaus, N. Kiessling, A. Marinucci, M. Moretti, C. Mota, D.F. Piga, L. Pisani, A. Szapudi, I. Tallada-Crespí, P. Aghanim, N. Andreon, S. Baccigalupi, C. Bardelli, S. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Camera, S. Capobianco, V. Cardone, V.F. Carretero, J. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Courbin, F. Courtois, H.M. Da Silva, A. Degaudenzi, H. De Lucia, G. Douspis, M. Dubath, F. Duncan, C.A.J. Dupac, X. Dusini, S. Ealet, A. Farina, M. Farrens, S. Ferriol, S. Fosalba, P. Frailis, M. Franceschi, E. Fumana, M. Galeotta, S. Gillis, B. Gómez-Alvarez, P. Grazian, A. Grupp, F. Haugan, S.V.H. Holmes, W. Hormuth, F. Hornstrup, A. Ilić, S. Jahnke, K. Jhabvala, M. Joachimi, B. Keihänen, E. Kermiche, S. Kilbinger, M. Kitching, T. Kubik, B. Kurki-Suonio, H. Lilje, P.B. Lindholm, V. Lloro, I. Mainetti, G. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Medinaceli, E. Mei, S. Mellier, Y. Meneghetti, M. Meylan, G. Moresco, M. Moscardini, L. Niemi, S.-M. Padilla, C. Paltani, S. Pasian, F. Pedersen, K. Percival, W.J. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Raison, F. Rebolo, R. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Saglia, R. Salvignol, J.-C. Sánchez, A.G. Sapone, D. Sartoris, B. Schirmer, M. Schrabback, T. Secroun, A. Seidel, G. Serrano, S. Sirignano, C. Sirri, G. Stanco, L. Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Department of Physics University of Helsinki P.O. Box 64 00014 Finland Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Campus UAB Carrer de Can Magrans s/n Cerdanyola del Vallés Barcelona08193 Spain Laboratoire Univers et Théorie Observatoire de Paris Université PSL Université Paris Cité CNRS Meudon92190 France Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom School of Physics and Astronomy Queen Mary University of London Mile End Road LondonE1 4NS United Kingdom Institut d’Astrophysique de Paris UMR 7095 CNRS Sorbonne Université 98 bis boulevard Arago Paris75014 France Institute of Theoretical Astrophysics University of Oslo P.O. Box 1029 Blindern Oslo0315 Norway Institut für Theoretische Physik University of Heidelberg Philosophenweg 16 Heidelberg69120 Germany Université de Toulouse CNRS UPS CNES 14 Av. Edouard Belin Toulouse31400 France Université St Joseph Faculty of Sciences Beirut Lebanon Dipartimento di Fisica "G. Occhialini" Università degli Studi di Milano Bicocca Piazza della Scienza 3 Milano20126 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Dipartimento di Fisica e Astronomia "Augusto Righi" Alma Mater Studiorum Università di Bologna via Piero Gobetti 93/2 Bologna40129 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy University of Manchester Oxford Road ManchesterM13 9PL United Kingdom INAF-IASF Milano Via Alfonso Corti 12 Milano20133 Italy Dipartimento di Fisica "Aldo Pontremoli" Università degli Studi di Milano Via Celoria 16

The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard Λ-cold-dark-matter (ΛCDM) paradigm and in many non-standard models beyond ΛCDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard ΛCDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid. © 2024, CC BY.

关键词： Dark energy