Academic literature on the topic 'Tensor modes'
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Journal articles on the topic "Tensor modes"
Adawi, Tom, Martin Cederwall, Ulf Gran, Bengt E. W. Nilsson, and Behrooz Razaznejad. "Goldstone tensor modes." Journal of High Energy Physics 1999, no. 02 (February 1, 1999): 001. http://dx.doi.org/10.1088/1126-6708/1999/02/001.
Full textSASAKURA, NAOKI. "THE LOWEST MODES AROUND GAUSSIAN SOLUTIONS OF TENSOR MODELS AND THE GENERAL RELATIVITY." International Journal of Modern Physics A 23, no. 24 (September 30, 2008): 3863–90. http://dx.doi.org/10.1142/s0217751x0804130x.
Full textVan Eeghem, Frederik, Otto Debals, and Lieven De Lathauwer. "Tensor Similarity in Two Modes." IEEE Transactions on Signal Processing 66, no. 5 (March 1, 2018): 1273–85. http://dx.doi.org/10.1109/tsp.2017.2786208.
Full textSorbo, Lorenzo. "Odd tensor modes from inflation." Modern Physics Letters A 31, no. 21 (July 10, 2016): 1640010. http://dx.doi.org/10.1142/s0217732316400101.
Full textBaumann, Daniel, and Matias Zaldarriaga. "Causality and primordial tensor modes." Journal of Cosmology and Astroparticle Physics 2009, no. 06 (June 9, 2009): 013. http://dx.doi.org/10.1088/1475-7516/2009/06/013.
Full textWimalawarne, Kishan, Makoto Yamada, and Hiroshi Mamitsuka. "Scaled Coupled Norms and Coupled Higher-Order Tensor Completion." Neural Computation 32, no. 2 (February 2020): 447–84. http://dx.doi.org/10.1162/neco_a_01254.
Full textNomura, Yasunori, and Masahito Yamazaki. "Tensor modes in pure natural inflation." Physics Letters B 780 (May 2018): 106–10. http://dx.doi.org/10.1016/j.physletb.2018.02.071.
Full textPowell, Brian A. "Tensor tilt from primordial B modes." Monthly Notices of the Royal Astronomical Society 419, no. 1 (October 13, 2011): 566–72. http://dx.doi.org/10.1111/j.1365-2966.2011.19734.x.
Full textEfstathiou, George, and Sirichai Chongchitnan. "The Search for Primordial Tensor Modes." Progress of Theoretical Physics Supplement 163 (2006): 204–19. http://dx.doi.org/10.1143/ptps.163.204.
Full textFujita, Tomohiro, Ippei Obata, Takahiro Tanaka, and Shuichiro Yokoyama. "Statistically anisotropic tensor modes from inflation." Journal of Cosmology and Astroparticle Physics 2018, no. 07 (July 12, 2018): 023. http://dx.doi.org/10.1088/1475-7516/2018/07/023.
Full textDissertations / Theses on the topic "Tensor modes"
De, Martino Danilo. "String inflationary models with non-monotonic slow-roll and detectable tensor modes." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8391/.
Full textConigli, Alessandro. "Primordial tensor modes from inflation and their detectability with GW experiments." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18153/.
Full textRaghunathan, Srinivasan. "Experimental and theoretical challenges in the search for tensor B-modes." Tesis, Universidad de Chile, 2016. http://repositorio.uchile.cl/handle/2250/138002.
Full textThis thesis describes the work that I performed to analyse the data from the Atacama B-mode Search (ABS) experiment. The ABS experiment observed the Cosmic Microwave Background (CMB) radiation for three years using polarisation sensitive detectors. The telescope is located at the Atacama desert in the north of Chile at an altitude of 5190 metres. The goal of the experiment is to detect the primordial gravitational waves which were supposed to have been generated during the initial phase of exponential expansion of the universe. These gravitational waves leave unique signatures on the polarised CMB called the tensor B-modes. Several experiments have been built over the last decade to observe them but the primordial tensor B-modes still remain undetected. If found, they will be a direct evidence for a process called Cosmic inflation which is responsible for the initial period of exponential expansion. The detection will also provide hints about the physics of inflation as the characterisation of tensor B-modes via the parameter called tensor-to-scalar ratio r is directly related to the energy scale of inflation O(10^16) GeV, comparable to the grand-unification-theory (GUT) energy scales. The ABS experiment was designed and led by the Physics department at Princeton University. The ABS observed the CMB at 145 GHz using polarisation sensitive transition-edge-sensor (TES) bolometers. There are two mirrors, 60 cms each arranged in a compact crossed-Dragone configuration. The ABS was the first ground-based CMB experiment to successfully implement the rapid polarisation modulation using a continuously rotating (warm) half-wave-plate (HWP). In this article, I present the observation strategy, data acquisition, instrument calibration, and the data selection techniques used to produce the CMB maps and power spectrum estimation. For completeness, I also briefly describe the work done by other members of the ABS project but clearly mention my contribution at the start of every chapter. The final power spectrum is not shown as the data selection techniques and the modelling of the galactic foregrounds are still being finalised. However, the results from detailed statistical assessment of the data using an exhaustive suite of null tests indicate that we are not affected by any significant systematic effects. The assessment of the ABS null tests will be the major result of this work. ### en español: Esta tesis describe el trabajo que he realizado para analizar los datos del experimento Atacama B-mode Search (ABS). Utilizando el telescopio de ABS, cuyos detectores son sensible a la polarización, durante un periodo de tres años se observa la radiación en microondas del fonda cósmico (CMB). El telescopio esta instalado en el desierto de Atacama, en el norte de Chile, a una altura de 5190 metros. El objetivo del experimento es detectar las ondas gravitationales primordiales supuestamente generadas durante la fase inicial de expansión exponencial del universo. Estas ondas gravitacionales dejan registros únicas en polarizacion del CMB llamados tensor B-modes. Durante la ultima decada se han realizado varios instrumentos para observar tensor B-modes, pero no se han detectado aun. Si se les detecta, serian una evidencia directa de un proceso llamado inflación cósmica que sera el período inicial de la expansión exponencial. La detección también proporcionará pistas sobre la física de la inflación como la caracterización de tensor B-modes vía el cuociente tensor-a-escalar llamado r, está directamente relacionada con la escala de energía de la inflación O(10^16) GeV, comparable a la gran unificación teoría (GUT) escalas de energía. El experimento ABS fue diseñado y dirigido por el departamento de Física de la Universidad de Princeton. El ABS observo la CMB en la frecuencia de 145 GHz utilizando bolometros sensibles a la polarizacio del tipo transition-edge-sensor (TES). Posee dos espejos, de 60 cms cada uno y dispuestos en una configuracion del tipo compact crossed-Dragone. El ABS fue el primer experimento de medicion de la CMB, situado en la Tierra, en implementar exitosamente la modulacion de polarizacion rápida mediante una placa de media-onda half-wave-plate (HWP) mantenida a temperatura ambiente y girando continuamente. En este reporte, presento la estrategia de observación, adquisición de datos, la calibración del instrumento, y las técnicas de selección de datos utilizados para producir los mapas de la CMB y estimación del Espectro de potencia de la CMB. Por completitud, también describo brevemente el trabajo realizado por otros miembros del proyecto ABS, pero menciono claramente mi contribución al comienzo de cada capítulo. El espectro de potencia final no se ha incluido debido a que tanto las técnicas de selección de datos y el modelado de la absorpcion debida a nuestra galaxia no están aun finalizadas. Sin embargo, los resultados de la evaluación estadística detallada de los datos utilizando un conjunto exhaustivo de pruebas de sesgo nulo (null tests) indican que nuestras medidas no estan afectadas significativamente por efectos sistemáticos. La evaluación de las pruebas de sesgo nulo de las observaciones llevadas a cabo con el telescopio ABS nulos, es el principal resultado de este trabajo. Este resultado posibilita una determinacion robusta del Espectro de Potencia de la CMB.
Edwards, David Craig. "Theoretical considerations in the use of scalar-tensor theories of gravity in inflationary models." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31404.
Full textDelepouve, Thibault. "Quartic Tensor Models." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS085/document.
Full textTensor models are probability measures for random tensors. They generalise matrix models and were developed to study random geometry in arbitrary dimension. Moreover, they are strongly connected to quantum gravity theories as, additionally to the standard bare-bones models, they encompass the field theoretical approach to loop quantum gravity known as group field theory.In the present thesis, we focus on the restricted case of quartic tensor models, for which a far greater number of rigorous mathematical results have been proven. Quartic models can be re-written as multi-matrix models using the intermediate field representation, and their perturbative expansions can be written as series expansions over combinatorial maps. Using a variety of map expansions, we prove analyticity results and useful bounds for the cumulants of various tensor models : the most general standard quartic model at any rank and the simplest renormalisable tensor field theory at rank 3. Then, we introduce a new class of models, the enhanced models, which perturbative expansions display new behaviour, different to the so called melonic behaviour that characterise most known tensor models so far
Da, Silva Caroline Dos Santos. "Cosmic strings and scalar tensor gravity." Thesis, Durham University, 1999. http://etheses.dur.ac.uk/4577/.
Full textHou, Ming. "Tensor-based regression models and applications." Doctoral thesis, Université Laval, 2017. http://hdl.handle.net/20.500.11794/27787.
Full textAvec l’avancement des technologies modernes, les tenseurs d’ordre élevé sont assez répandus et abondent dans un large éventail d’applications telles que la neuroscience informatique, la vision par ordinateur, le traitement du signal et ainsi de suite. La principale raison pour laquelle les méthodes de régression classiques ne parviennent pas à traiter de façon appropriée des tenseurs d’ordre élevé est due au fait que ces données contiennent des informations structurelles multi-voies qui ne peuvent pas être capturées directement par les modèles conventionnels de régression vectorielle ou matricielle. En outre, la très grande dimensionnalité de l’entrée tensorielle produit une énorme quantité de paramètres, ce qui rompt les garanties théoriques des approches de régression classique. De plus, les modèles classiques de régression se sont avérés limités en termes de difficulté d’interprétation, de sensibilité au bruit et d’absence d’unicité. Pour faire face à ces défis, nous étudions une nouvelle classe de modèles de régression, appelés modèles de régression tensor-variable, où les prédicteurs indépendants et (ou) les réponses dépendantes prennent la forme de représentations tensorielles d’ordre élevé. Nous les appliquons également dans de nombreuses applications du monde réel pour vérifier leur efficacité et leur efficacité.
With the advancement of modern technologies, high-order tensors are quite widespread and abound in a broad range of applications such as computational neuroscience, computer vision, signal processing and so on. The primary reason that classical regression methods fail to appropriately handle high-order tensors is due to the fact that those data contain multiway structural information which cannot be directly captured by the conventional vector-based or matrix-based regression models, causing substantial information loss during the regression. Furthermore, the ultrahigh dimensionality of tensorial input produces huge amount of parameters, which breaks the theoretical guarantees of classical regression approaches. Additionally, the classical regression models have also been shown to be limited in terms of difficulty of interpretation, sensitivity to noise and absence of uniqueness. To deal with these challenges, we investigate a novel class of regression models, called tensorvariate regression models, where the independent predictors and (or) dependent responses take the form of high-order tensorial representations. We also apply them in numerous real-world applications to verify their efficiency and effectiveness. Concretely, we first introduce hierarchical Tucker tensor regression, a generalized linear tensor regression model that is able to handle potentially much higher order tensor input. Then, we work on online local Gaussian process for tensor-variate regression, an efficient nonlinear GPbased approach that can process large data sets at constant time in a sequential way. Next, we present a computationally efficient online tensor regression algorithm with general tensorial input and output, called incremental higher-order partial least squares, for the setting of infinite time-dependent tensor streams. Thereafter, we propose a super-fast sequential tensor regression framework for general tensor sequences, namely recursive higher-order partial least squares, which addresses issues of limited storage space and fast processing time allowed by dynamic environments. Finally, we introduce kernel-based multiblock tensor partial least squares, a new generalized nonlinear framework that is capable of predicting a set of tensor blocks by merging a set of tensor blocks from different sources with a boosted predictive power.
Ingalhalikar, Madhura Aditya Magnotta Vincent A. "Spatial normalization of diffusion models and tensor analysis." Iowa City : University of Iowa, 2009. http://ir.uiowa.edu/etd/299.
Full textOlness, James M. "The nucleon "tensor charges" and the Skyrme model." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35421.
Full textIngalhalikar, Madhura Aditya. "Spatial normalization of diffusion models and tensor analysis." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/299.
Full textBooks on the topic "Tensor modes"
Nestor, Cardozo, and Fisher Donald M, eds. Structural geology algorithms: Vectors and tensors. Cambridge: Cambridge University Press, 2011.
Find full textCheng, Dai-Zhan. Analysis and control of boolean networks: A semi-tensor product approach. London: Springer, 2011.
Find full textJoint Council for Landscape Industries. Grounds maintenance: Model forms of tender and contract documents. [Keighley]: BritishAssociation of Landscape Industries, 1987.
Find full textJoint Council for Landscape Industries. Grounds maintenance: Model form of tender and contract documents. [s.l.]: British Association of Landscape Industries, 1987.
Find full textZur Entwicklung der Kategorien Tempus und Modus im Indogermanischen. Innsbruck: Institut für Sprachwissenschaft der Universität Innsbruck, 1985.
Find full textBenthem, Johan van. The logic of time: A model-theoretic investigation into the varieties of temporal ontology and temporal discourse. 2nd ed. Dordrecht: Kluwer Academic Publishers, 1991.
Find full textJ. F. A. K. van Benthem. The logic of time: A model-theoretic investigation into the varieties of temporal ontology and temporal discourse. 2nd ed. Dordrecht: Kluwer Academic Publishers, 1991.
Find full textModes of modality: Modality, typology, and universal grammar. Amsterdam: John Benjamins Publishing Company, 2014.
Find full textMaslia, Morris L. Methods and computer program documentation for determining anisotropic transmissivity tensor components of two-dimensional ground-water flow. [Washington]: U.S. G.P.O., 1987.
Find full textKiyotaki, Nobuhiro. Search for a theory of money. Cambridge, MA: National Bureau of Economic Research, 1990.
Find full textBook chapters on the topic "Tensor modes"
Gleyzes, Jérôme. "Predictions for Primordial Tensor Modes." In Springer Theses, 71–83. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41210-8_4.
Full textKorondi, Péter, Csaba Budai, Hideki Hashimoto, and Fumio Harashima. "Tensor Product Model Transformation Based Sliding Mode Design for LPV Systems." In Recent Advances in Sliding Modes: From Control to Intelligent Mechatronics, 277–98. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18290-2_14.
Full textWiles, J., G. S. Halford, J. E. M. Stewart, M. S. Humphreys, W. H. Wilson, and J. D. Bain. "Tensor Models." In Artificial Intelligence and Creativity, 145–59. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-0793-0_10.
Full textŠílený, Jan. "Constrained Moment Tensors: Source Models and Case Studies." In Moment Tensor Solutions, 213–31. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77359-9_9.
Full textHashiguchi, Koichi. "Corotational Rate Tensor." In Foundations of Elastoplasticity: Subloading Surface Model, 471–87. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48821-9_16.
Full textRan, Shi-Ju, Emanuele Tirrito, Cheng Peng, Xi Chen, Luca Tagliacozzo, Gang Su, and Maciej Lewenstein. "Tensor Network Approaches for Higher-Dimensional Quantum Lattice Models." In Tensor Network Contractions, 87–97. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34489-4_4.
Full textPeláez, J. A., J. Henares, M. Hamdache, and C. Sanz de Galdeano. "A Seismogenic Zone Model for Seismic Hazard Studies in Northwestern Africa." In Moment Tensor Solutions, 643–80. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77359-9_29.
Full textHashiguchi, Koichi. "Vector and Tensor Analysis." In Foundations of Elastoplasticity: Subloading Surface Model, 1–63. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48821-9_1.
Full textBillio, Monica, Roberto Casarin, and Matteo Iacopini. "Bayesian Tensor Regression Models." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 149–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_28.
Full textTurhan, Fatih, Musavver Didem Cambaz, and Jiří Zahradník. "The Significance of Crustal Velocity Model in Moment Tensor Solutions: A Case Study of Yedisu Earthquakes." In Moment Tensor Solutions, 557–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77359-9_24.
Full textConference papers on the topic "Tensor modes"
Chen, Longxi, Yipeng Liu, and Ce Zhu. "Robust Tensor Principal Component Analysis in All Modes." In 2018 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2018. http://dx.doi.org/10.1109/icme.2018.8486550.
Full textRana, Santu, Wanquan Liu, Mihai Lazarescu, and Svetha Venkatesh. "Recognising faces in unseen modes: A tensor based approach." In 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2008. http://dx.doi.org/10.1109/cvpr.2008.4587813.
Full textHotta, Masashi, Mitsuo Hano, and Ikuo Awai. "Modes in Single-Negative Slab with Tensor Material Parameters." In 2006 European Microwave Conference. IEEE, 2006. http://dx.doi.org/10.1109/eumc.2006.281093.
Full textGuigot, Corentin, Dominique Leduc, Yann Lecieux, and Cyril Lupi. "Whispering gallery modes for in-situ measurement of strain tensor." In 2019 21st International Conference on Transparent Optical Networks (ICTON). IEEE, 2019. http://dx.doi.org/10.1109/icton.2019.8840236.
Full textDing, Xin, Wei Chen, and Ian Wassell. "Nonconvex compressive sensing reconstruction for tensor using structures in modes." In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2016. http://dx.doi.org/10.1109/icassp.2016.7472560.
Full textIchikawa, Kazuhide, Teruaki Suyama, Tomo Takahashi, Masahide Yamaguchi, Hideo Kodama, and Kunihito Ioka. "Non-Gaussianity, Spectral Index and Tensor Modes in Mixed Inflaton and Curvaton Models." In KEK COSMOPHYSICS GROUP INAUGURAL CONFERENCE “ACCELERATORS IN THE UNIVERSE”: Interplay between High Energy Physics and Cosmophysics. AIP, 2008. http://dx.doi.org/10.1063/1.2981533.
Full textNajafi, Mehrnaz, Lifang He, and Philip S. Yu. "Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/442.
Full textDONEVA, DANIELA D., STOYTCHO S. YAZADJIEV, KOSTAS D. KOKKOTAS, and IVAN ZH STEFANOV. "A CONNECTION BETWEEN QUASINORMAL MODES AND NONUNIQUENESS OF CHARGED SCALAR-TENSOR BLACK HOLES." In Proceedings of the MG13 Meeting on General Relativity. WORLD SCIENTIFIC, 2015. http://dx.doi.org/10.1142/9789814623995_0179.
Full textLi, Ping, Jiashi Feng, Xiaojie Jin, Luming Zhang, Xianghua Xu, and Shuicheng Yan. "Online Robust Low-Rank Tensor Learning." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/303.
Full textHotta, M., R. Ogawa, W. Murai, and M. Hano. "Modal analysis for TE volume modes in finite-thickness slab with partly negative permeability tensor component." In 2008 Asia Pacific Microwave Conference. IEEE, 2008. http://dx.doi.org/10.1109/apmc.2008.4958691.
Full textReports on the topic "Tensor modes"
Ulitsky, M. A Tensor Hyperviscosity Model in Kull. Office of Scientific and Technical Information (OSTI), June 2005. http://dx.doi.org/10.2172/919233.
Full textAnandkumar, Anima, Rong Ge, Daniel Hsu, Sham M. Kakade, and Matus Telgarsky. Tensor Decompositions for Learning Latent Variable Models. Fort Belvoir, VA: Defense Technical Information Center, December 2012. http://dx.doi.org/10.21236/ada604494.
Full textIbrahim, Khaled Z., Evgeny Epifanovsky, Samuel W. Williams, and Anna I. Krylov. Cross-scale Efficient Tensor Contractions for Coupled Cluster Computations Through Multiple Programming Model Backends. Office of Scientific and Technical Information (OSTI), July 2016. http://dx.doi.org/10.2172/1274416.
Full textBlaha, Georges. Resolution of a Rank-Deficient Adjustment Model Via an Isomorphic Geometrical Setup with Tensor Structure. Fort Belvoir, VA: Defense Technical Information Center, March 1987. http://dx.doi.org/10.21236/ada184198.
Full textKnotts, Lester W. Productive Tension in Joint Planning: A Constructivist Model. Fort Belvoir, VA: Defense Technical Information Center, November 2007. http://dx.doi.org/10.21236/ada476666.
Full textWheeler, A. A., and G. B. McFadden. On the notion of a *-vector and a stress tensor for a general class of anisotropic diffuse interface models. Gaithersburg, MD: National Institute of Standards and Technology, 1996. http://dx.doi.org/10.6028/nist.ir.5848.
Full textPoppeliers, Christian, Katherine Anderson Aur, and Leiph Preston. The use of atmospheric prediction models to invert infrasound for linear-equivalent time domain moment tensors: Source Physics Experiment Phase 1. Office of Scientific and Technical Information (OSTI), August 2018. http://dx.doi.org/10.2172/1468382.
Full textMoore, Keegan J., and Matthew Robert Brake. A Reduced Order Model of Force Displacement Curves for the Failure of Mechanical Bolts in Tension. Office of Scientific and Technical Information (OSTI), December 2015. http://dx.doi.org/10.2172/1234813.
Full textMatha, D., T. Fischer, M. Kuhn, and J. Jonkman. Model Development and Loads Analysis of a Wind Turbine on a Floating Offshore Tension Leg Platform. Office of Scientific and Technical Information (OSTI), February 2010. http://dx.doi.org/10.2172/972932.
Full textHuber, Marcia L. Models for viscosity, thermal conductivity, and surface tension of selected pure fluids as implemented in REFPROP v10.0. Gaithersburg, MD: National Institute of Standards and Technology, August 2018. http://dx.doi.org/10.6028/nist.ir.8209.
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