Numerical Investigation of Vortex Formation in Bose-Einstein Condensates
Explore numerical modeling of vortex patterns in Bose-Einstein condensates using finite elements, focusing on mesh size requirements for accurate approximations of superfluid behavior.
Numerical Solutions of Schrödinger's Equation Applied to Atomic Physics - Class 3
Explore numerical solutions of Schrödinger's equation in atomic physics, focusing on advanced techniques and applications in the field.
Numerical Solutions of Schrödinger's Equation Applied to Atomic Physics - Class 1
Explore numerical solutions of Schrödinger's equation in atomic physics, focusing on fundamental concepts and computational techniques.
Coupled-Cluster Theory for Ground and Excited Eigenstates
Explore advanced quantum computing concepts through coupled-cluster theory, examining ground and excited eigenstates and their applications in quantum systems.
Particle-Laden Flows: Simulations and Data-Driven Modeling
Explore particle-laden flows through simulations and data-driven modeling techniques, gaining insights into complex fluid dynamics and engineering applications.
Applications of Computational Electromagnetics: Hybrid Methods - Motivation
Explore hybrid methods in computational electromagnetics, focusing on their motivations and applications in solving complex electromagnetic problems.
Regularized Reduced Order Models for Control of Navier-Stokes Equations
Explore regularized reduced order models for controlling Navier-Stokes equations in convection-dominated flows, focusing on evolve-filter-relax and approximate deconvolution techniques for numerical stabilization.
Physics Problem: Spacecraft Deflection due to an Asteroid
Explore spacecraft deflection by an asteroid using physics principles and Python code to calculate momentum changes.
Lagrangian - Bead on a Driven Hoop vs. Bead on a Free Hoop
Explore the motion dynamics of beads on rotating hoops through Lagrangian mechanics, comparing driven and free rotation scenarios.
Lagrangian Mechanics - Block on a Movable Wedge
Solve a complex physics problem using Lagrangian mechanics to analyze the motion of a frictionless mass on a movable wedge.
Симуляція флуктуацій чисельної густини біля критичної точки у системі скінченного розміру із фазовим переходом І роду
Дослідіть симуляцію флуктуацій густини та критичні явища у фізичних системах скінченного розміру з фазовим переходом першого роду.
A Deep Learning Scheme for Solving Fully Nonlinear Partial Differential Equations
Discover how deep learning algorithms converge to solve complex nonlinear PDEs, with applications in optimal investment problems and transaction cost analysis in financial mathematics.
Cyclic Projective t-Designs and How to Find Them
Explore complex projective t-designs in quantum states and their applications in optimal quantum tomography, focusing on cyclic designs generated through unitary operations.
Graph Convolutional Networks - GNN Paper Explained
Comprehensive exploration of Graph Convolutional Networks, covering theory, implementation, and applications. Delves into spectral methods, Weisfeiler-Lehman perspective, and GNN depth, offering insights for both beginners and experts.
Optimization: Interior Point Methods - Part 2
Explore advanced interior point methods for optimization, focusing on data structures and algorithms to enhance computational efficiency in solving complex problems.
Optimization: Interior Point Methods - Part 1
Explore interior point methods for optimization with Stanford's Yinyu Ye, covering fundamental concepts and applications in data structures and fast algorithms.
Aaron Sidford: Introduction to Interior Point Methods for Discrete Optimization, Lecture II
Explore interior point methods for discrete optimization, covering theory, advances, and applications in flow, matching, and linear programming problems.
Lectures on Standard and Less Standard Asymptotic Methods - Lecture 1
Explore advanced asymptotic methods for evaluating infinite sums and recognizing sequence patterns. Learn techniques from standard to unconventional, with practical examples and high-precision computations.
Approximation with Deep Networks - Remi Gribonval, Inria
Explore deep network approximation, focusing on expressivity, universal properties, sparse networks, and the impact of network architecture and activation functions on performance.
Neural Networks as Interacting Particle Systems
Explore neural networks as interacting particle systems, examining their mathematical foundations and applications in complex systems modeling across various scientific disciplines.
A Function Space View of Overparameterized Neural Networks - Rebecca Willet, University of Chicago
Explore function spaces of overparameterized neural networks, focusing on weight-bounded networks and their approximation capabilities. Insights from Radon transform analysis reveal novel perspectives on learning with ReLU networks.