Abstract
We use a self-guided random walk to solve the ground-state problem of Hamiltonian U(1) pure gauge theory in 2+1 dimensions in the string sector. By making use of the electric-field representation, we argue that the spatial distribution of the electric field can be more easily measured than in ordinary Monte Carlo simulations. ((orig.)).
Citation Formats
Best, C, and Schaefer, A.
U(1) flux tube profiles from Hamiltonian lattice gauge theory using a random walk ground-state projector.
Netherlands: N. p.,
1995.
Web.
doi:10.1016/0920-5632(95)00205-N.
Best, C, & Schaefer, A.
U(1) flux tube profiles from Hamiltonian lattice gauge theory using a random walk ground-state projector.
Netherlands.
https://doi.org/10.1016/0920-5632(95)00205-N
Best, C, and Schaefer, A.
1995.
"U(1) flux tube profiles from Hamiltonian lattice gauge theory using a random walk ground-state projector."
Netherlands.
https://doi.org/10.1016/0920-5632(95)00205-N.
@misc{etde_101195,
title = {U(1) flux tube profiles from Hamiltonian lattice gauge theory using a random walk ground-state projector}
author = {Best, C, and Schaefer, A}
abstractNote = {We use a self-guided random walk to solve the ground-state problem of Hamiltonian U(1) pure gauge theory in 2+1 dimensions in the string sector. By making use of the electric-field representation, we argue that the spatial distribution of the electric field can be more easily measured than in ordinary Monte Carlo simulations. ((orig.)).}
doi = {10.1016/0920-5632(95)00205-N}
journal = []
volume = {42}
journal type = {AC}
place = {Netherlands}
year = {1995}
month = {Apr}
}
title = {U(1) flux tube profiles from Hamiltonian lattice gauge theory using a random walk ground-state projector}
author = {Best, C, and Schaefer, A}
abstractNote = {We use a self-guided random walk to solve the ground-state problem of Hamiltonian U(1) pure gauge theory in 2+1 dimensions in the string sector. By making use of the electric-field representation, we argue that the spatial distribution of the electric field can be more easily measured than in ordinary Monte Carlo simulations. ((orig.)).}
doi = {10.1016/0920-5632(95)00205-N}
journal = []
volume = {42}
journal type = {AC}
place = {Netherlands}
year = {1995}
month = {Apr}
}