Insights into Symmetry and Magnetism in Summer School Curriculum
Delve into the principles and applications of symmetry in magnetism through topics like tensor transformations, Edelstein effect, and breaking inversion symmetry in magnetic materials. Explore the role of crystal structures and interfaces in breaking symmetry, especially in antiferromagnets, providi
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Understanding Diffusion Weighted Imaging (DWI) in Neuroimaging Research
This content delves into the significance of Diffusion Weighted Imaging (DWI) in studying the motion of water molecules in brain tissue. It explains how water diffusion varies in different brain matter types and explores techniques like Diffusion Tensor Imaging (DTI). The impact factors on diffusion
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Classical Mechanics at Neotech Institute of Applied Science and Research, Virod
Delve into the world of Classical Mechanics in B.Sc Semester-V at Neotech Institute of Applied Science and Research, located in Virod, Vadodara. Explore topics such as motion of rigid bodies, angular momentum, Euler's theorem, inertia tensor, and Euler's equations of motion through a comprehensive s
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Understanding Seismic Source Parameters in Earthquake Dynamics
The seismic source parameters in earthquake dynamics involve describing a fault as a discontinuity causing displacements, requiring a complex treatment of forces. The Earth's equilibrium necessitates a specific system of forces to explain displacements along faults. The seismic moment tensor, consis
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Understanding the Energy-Momentum Tensor of the Electromagnetic Field
Exploring the intricacies of the energy-momentum tensor of the electromagnetic field, including its components, symmetries, and implications on field interactions and invariants. Delve into the mathematical derivations and transformations involved in studying this fundamental concept in electromagne
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Understanding Nucleon Structure: Insights from EIC Workshop
Exploring the mechanics of nucleons and the physics goals of the Electron-Ion Collider (EIC), this content delves into the origin of nucleon mass and spin, emergent properties of dense gluon systems, and energy-momentum tensor in QCD. It discusses the role of gluons in understanding nucleon structur
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Understanding Flowing Gluon Fields and Color Glass Phenomena in QCD
Explore the collective phenomena of gluon fields in classical QCD, focusing on the Standard Model of URHICs, Color Glass, and Gluon Fields in the Forward Lightcone. The research delves into topics like local thermal equilibrium, viscous hydrodynamics, and the interaction of probes with quarks and gl
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Exploring TensorFlow for Social Good: Session Insights and Tips
Delve into Session 3 of TensorFlow for Social Good with Zhixun Jason He, covering topics such as TensorFlow model training loops, regularization techniques, tensor concepts, learning rate scheduling, and custom loss functions. Discover practical tips and valuable resources to enhance your understand
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Robust Parity Test for Extracting Parallel Vectors in 3D
Fundamental primitives for visualizing 3D data include line features like ridges and valleys of a scalar field, stream lines of a vector field, vortices of a velocity field, and extremal curves of a tensor field. Parallel Vectors (PV) provide a unified representation of 3D line features, forming con
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Overcoming Memory Constraints in Deep Neural Network Design
Limited availability of high bandwidth on-device memory presents a challenge in exploring new architectures for deep neural networks. Memory constraints have been identified as a bottleneck in state-of-the-art models. Various strategies such as Tensor Rematerialization, Bottleneck Activations, and G
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Insights into Dark Energy Detection and Gravity Tests
This collaboration delves into direct detection of dark energy, evidencing acceleration in expansion and delving into the evolution of background cosmology. Gravity tests, including solar system trials, are discussed, along with models like f(R) gravity and chameleon screening in the context of scal
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Understanding the Acceleration of the Universe and the Equivalence Principle Violation in the Horndeski Vector-Tensor Theory
Exploring the implications of the Equivalence Principle Violation after reheating in the context of the accelerated expansion of the universe. The study delves into the Horndeski vector-tensor theory, gravitational waves, and the impact of modified gravity and dark energy. Insights are provided on t
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Understanding the Hall Effect in Conductors
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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Improved Rectangular Matrix Multiplication Using Coppersmith-Winograd Tensor
In this research, the complexity of rectangular matrix multiplication is enhanced by analyzing the fourth power of the Coppersmith-Winograd tensor. By extending the understanding of the tensor's power, significant advancements have been made in the efficiency of non-square matrix multiplication, sur
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Understanding Nucleon Spin Decomposition and Proton Spin Problem
Explore the complex realm of nucleon spin decomposition and the enigmatic proton spin problem, delving into concepts like orbital angular momentum, quarks and gluons' helicity, and longitudinal double spin asymmetry in polarized deep inelastic scattering. Learn about the spin crisis, gluon polarizat
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Dynamic Load Balancing in Block-Sparse Tensor Contractions
This paper discusses load balancing algorithms for block-sparse tensor contractions, focusing on dynamic load balancing challenges and implementation strategies. It explores the use of Global Arrays (GA), performance experiments, Inspector/Executor design, and dynamic buckets implementation to optim
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Communication Costs in Distributed Sparse Tensor Factorization on Multi-GPU Systems
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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Understanding Spontaneous Scalarization in Gravitational Theories
Spontaneous scalarization presents a unique phenomenon where compact objects experience field growth triggered by tachyonic instability, leading to stable field configurations. Explored in various theories, such as Horndeski gravity and scalar Gauss-Bonnet gravity, spontaneous scalarization is studi
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Non-Negative Tensor Factorization with RESCAL
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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Nonstationary Configurations of a Spherically Symmetric Scalar Field
Action and stress-energy tensor, Einstein-Klein-Gordon equations, and method for constructing nonstationary configurations of a spherically symmetric scalar field are discussed in this study. The behavior of the characteristic function allows interpretations such as black holes, wormholes, or naked
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Exploring Google's Tensor Processing Unit (TPU) and Deep Neural Networks in Parallel Computing
Delve into the world of Google's TPU and deep neural networks as key solutions for speech recognition, search ranking, and more. Learn about domain-specific architectures, the structure of neural networks, and the essence of matrix multiplication in parallel computing.
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Instant Travel Time Estimation with Sparse Trajectories
This research by Dr. Yu Zheng aims to estimate travel time on road networks instantly using historical and current trajectories generated by vehicles. The methodology involves a context-aware tensor decomposition approach, optimal concatenation, and frequent trajectory pattern mining to address chal
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Cutting-Edge Training Architecture Overview
Delve into the latest training innovations featuring NVIDIA Volta, Intel NNP-T/I, ScaleDeep, and vDNN. Learn about the impressive capabilities of the NVIDIA Volta GPU, Intel NNP-T with Tensor Processing Clusters, and Intel NNP-I for inference tasks. Explore the intricacies of creating mini-batches,
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