4,993 research outputs found
Bosonization and Cluster Updating of Lattice Fermions
A lattice fermion model is formulated in Fock space using the Jordan-Wigner
representation for the fermion creation and annihilation operators. The
resulting path integral is a sum over configurations of lattice site occupation
numbers which may be viewed as bosonic Ising-like variables.
However, as a remnant of Fermi statistics a nonlocal sign factor arises for
each configuration. When this factor is included in measured observables the
bosonic occupation numbers interact locally, and one can use efficient cluster
algorithms to update the bosonized variables.Comment: 7 pages Latex, no figure
Thermal leptogenesis in extended supersymmetric seesaw
We consider an extended supersymmetric SO(10) seesaw model with only doublet
Higgs scalars, in which neutrino masses are suppressed by the scale of D-parity
violation. Leptogenesis can occur at the TeV scale through the decay of a
singlet Sigma, thereby avoiding the gravitino crisis. Washout of the asymmetry
can be effectively suppressed by the absence of direct couplings of Sigma to
leptons.Comment: 4 pages, 5 figure
Blockspin Cluster Algorithms for Quantum Spin Systems
Cluster algorithms are developed for simulating quantum spin systems like the
one- and two-dimensional Heisenberg ferro- and anti-ferromagnets. The
corresponding two- and three-dimensional classical spin models with four-spin
couplings are maped to blockspin models with two-blockspin interactions.
Clusters of blockspins are updated collectively. The efficiency of the method
is investigated in detail for one-dimensional spin chains. Then in most cases
the new algorithms solve the problems of slowing down from which standard
algorithms are suffering.Comment: 11 page
Ground and excited states Gamow-Teller strength distributions of iron isotopes and associated capture rates for core-collapse simulations
This paper reports on the microscopic calculation of ground and excited
states Gamow-Teller (GT) strength distributions, both in the electron capture
and electron decay direction, for Fe. The associated electron and
positron capture rates for these isotopes of iron are also calculated in
stellar matter. These calculations were recently introduced and this paper is a
follow-up which discusses in detail the GT strength distributions and stellar
capture rates of key iron isotopes. The calculations are performed within the
framework of the proton-neutron quasiparticle random phase approximation
(pn-QRPA) theory. The pn-QRPA theory allows a microscopic
\textit{state-by-state} calculation of GT strength functions and stellar
capture rates which greatly increases the reliability of the results. For the
first time experimental deformation of nuclei are taken into account. In the
core of massive stars isotopes of iron, Fe, are considered to be
key players in decreasing the electron-to-baryon ratio () mainly via
electron capture on these nuclide. The structure of the presupernova star is
altered both by the changes in and the entropy of the core material.
Results are encouraging and are compared against measurements (where possible)
and other calculations. The calculated electron capture rates are in overall
good agreement with the shell model results. During the presupernova evolution
of massive stars, from oxygen shell burning stages till around end of
convective core silicon burning, the calculated electron capture rates on
Fe are around three times bigger than the corresponding shell model
rates. The calculated positron capture rates, however, are suppressed by two to
five orders of magnitude.Comment: 18 pages, 12 figures, 10 table
Loop algorithms for quantum simulations of fermion models on lattices
Two cluster algorithms, based on constructing and flipping loops, are
presented for worldline quantum Monte Carlo simulations of fermions and are
tested on the one-dimensional repulsive Hubbard model. We call these algorithms
the loop-flip and loop-exchange algorithms. For these two algorithms and the
standard worldline algorithm, we calculated the autocorrelation times for
various physical quantities and found that the ordinary worldline algorithm,
which uses only local moves, suffers from very long correlation times that
makes not only the estimate of the error difficult but also the estimate of the
average values themselves difficult. These difficulties are especially severe
in the low-temperature, large- regime. In contrast, we find that new
algorithms, when used alone or in combinations with themselves and the standard
algorithm, can have significantly smaller autocorrelation times, in some cases
being smaller by three orders of magnitude. The new algorithms, which use
non-local moves, are discussed from the point of view of a general prescription
for developing cluster algorithms. The loop-flip algorithm is also shown to be
ergodic and to belong to the grand canonical ensemble. Extensions to other
models and higher dimensions is briefly discussed.Comment: 36 pages, RevTex ver.
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