Fermionic wave functions from neural-network constrained hidden states
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In this paper we propose and analyze a stochastic collocation method for solving the second order wave equation with a random wave speed and subjected to deterministic boundary and initial conditions. The speed is piecewise smooth in the physical space and ...
The problem of improving image quality in ultrafast ultrasound (US) imaging by means of regularized iterative algorithms has raised a vast interest in the US community. These approaches usually rely on standard image processing priors, such as wavelet spar ...
The fast and reliable determination of wave functions and electron densities of macromolecules has been one of the goals of theoretical chemistry for a long time, and in this context, several linear scaling techniques have been successfully devised over th ...
In this paper we propose and analyze a stochastic collocation method for solving the second order wave equation with a random wave speed and subjected to deterministic boundary and initial conditions. The speed is piecewise smooth in the physical space and ...
The phase of a quantum state may not return to its original value after the system's parameters cycle around a closed path; instead, the wave function may acquire a measurable phase difference called the Berry phase. Berry phases typically have been access ...
American Association for the Advancement of Science2017
Using a density-functional scheme, we study the migration of a single O atom in a (110) plane between two adjacent bond-center sites in bulk Si. The minimum energy migration path is found through the nudged elastic band method within a generalized gradient ...
We investigate the feasibility of the use of convolutional neural networks to estimate the amount of groundwater stored in the aquifer and delineate water-table level from active-source seismic data. The seismic data to train and test the neural networks a ...
This thesis explores various approaches of studying the long-range colour order of antiferromagnetic SU(N) Heisenberg models with the linear flavour-wave theory (LFWT). The LFWT is an extension of the well-known SU(2) spin-wave theory to SU(N), and this se ...
We report spin wave excitations in a nanopatterned antidot lattice fabricated from a 30-nm thick Ni80Fe20 film. The 250-nm-wide circular holes are arranged in a rhombic unit cell with a lattice constant of 400 nm. By Brillouin light scattering, we find tha ...
Deep learning presents notorious computational challenges. These challenges in- clude, but are not limited to, the non-convexity of learning objectives and estimat- ing the quantities needed for optimization algorithms, such as gradients. While we do not a ...
