Differentiable Numerical Simulations of Physical Systems, Differentiable Physics
Introduction to Differentiable Physics The central goal of these methods is to use existing numerical solvers, and equip them with…
Physics
kevin-tofu Note : Navier-Stokes Equation
Navier-Stokes There are many ways to represent this equation. Polite Form to represent(Looks redundant) p is the pressure, ρ is…
Integrating Differential Physics into NN Training
About This article is almost copy and paste of below link. https://physicsbaseddeeplearning.org/diffphys-examples.html Comparing with straight forward Differential Physics, It seemes…
Burgers Equation with Differential Physics, PhiFlow
Burgers Equation The one-dimensional Burgers’ equation is expressed in the following formula Here, u represents the velocity field, t is…
Maxwells Equations
Maxwell’s Equations Maxwell’s Equation is described by 4 queations as following(not only Integral form but also differential form), this article…
Modulus
Overview Nvidia is developing Neural Networks training tool for Physics. Here shows what functions it has https://docs.nvidia.com/deeplearning/modulus/modulus-v2209/user_guide/basics/modulus_overview.html Neural Netork Models…
Neural Operator for Training Partial Differential Equations
What this field is going to do The previously introduced Physics Informed Neural Network (PINN) directly estimates the solution (field)…
The Jordan Normal Form
Diagonalization of matrices plays a crucial role in numerical computations. However, when diagonalization of a matrix is not possible, how…
Bloch Sphere
|\psi\rangle = e^{i\Phi} \left( \cos\frac{\theta}{2} |0\rangle + \sin\frac{\theta}{2} e^{i\phi} |1\rangle \right)
The difference between Hamiltonian and Unitary transform in Quantum Computing
In summary, the Hamiltonian provides the “cause” for the temporal evolution of a quantum system, while the resulting time evolution…