This lecture delves into the principles and applications of symmetry in magnetism, covering topics such as the symmetry of response tensors, transformations of tensors, time-reversal symmetry, and beyond point groups. It explores the symmetry of local effects, equivalent magnetic configurations, exp

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Python is a powerful language for machine learning, but it can be slow for numerical computations. NumPy and SciPy are essential packages for working with matrices efficiently in Python. NumPy supports features crucial for machine learning, such as fast numerical computations and high-level math fun

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This project focuses on calculating modifications to the Newtonian gravitational force through experimental short-range tests of gravity. Utilizing the Standard-Model Extension (SME) test framework to search for potential violations of General Relativity and Newtonian Gravity. Key objectives include

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Precision in cosmological models based on teleparallel gravity is explored, including fundamental theories, modifications, and applications in the context of General Relativity. The construction principles of GR modifications, characteristic tensors, relation between different metric-affine geometri

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The Hall Effect in conductors is described in detail, showcasing how a magnetic field affects the conductivity tensor, breaking symmetry and leading to unique properties. The discussion covers the separation of the conductivity tensor, the impact of magnetic fields on conductivity components, and th

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TensorFlow, a popular open-source machine learning framework, offers various execution modes including graph and eager execution. It provides benefits such as distributed training and performance optimizations. The architecture involves assembling computational graphs and executing operations using

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This research delves into multimodal semantic indexing methods for image retrieval, focusing on extending Latent Semantic Indexing (LSI) and probabilistic LSI to a multi-modal setting. Contributions include the refinement of graph models and partitioning algorithms to enhance image retrieval from tr

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Researchers like C. J. Horowitz and Kwing-Lam Leung are exploring the effects of dark matter, scalar fields, and ultra-light dark matter on compact stars like neutron stars. Methods involve calculating tidal love numbers, using energy-momentum tensors, and studying equilibrium solutions. The study a

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This research paper presented an evaluation of communication costs for distributed sparse tensor factorization on multi-GPU systems. It discussed the background of tensors, tensor factorization methods like CP-ALS, and communication requirements in RefacTo. The motivation highlighted the dominance o

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This article discusses non-negative tensor factorization with RESCAL, covering topics such as Non-Negative Matrix Factorization, Multiplicative Updates, RESCAL for Relational Learning, and Non-Negative Constraint for RESCAL. It explores how factorizing matrices/tensors into non-negative factors can

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Explore the fundamentals of vectors, matrices, rotations, and coordinate transformations in Euclidean space. Learn about points, tensors, and the significance of vectors in representing physical quantities. Discover the Parallelogram Law and Coordinate Frames for effective visualization and computat

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