13,249 research outputs found
Effective Sublattice Magnetization and Neel Temperature in Quantum Antiferromagnets
We present an analytic expression for the finite temperature effective
sublattice magnetization which would be detected by inelastic neutron
scattering experiments performed on a two-dimensional square-lattice quantum
Heisenberg antiferromagnets with short range N\'eel order. Our expression,
which has no adjustable parameters, is able to reproduce both the qualitative
behaviour of the phase diagram and the experimental values of the
N\'eel temperature for either doped YBaCuO and
stoichiometric LaCuO compounds. Finally, we remark that by
incorporating frustration and 3D effects as perturbations is sufficient to
explain the deviation of the experimental data from our theoretical curves.Comment: 4 pages, RevTex, 3 figure
Vanishing conductivity of quantum solitons in polyacetylene
Quantum solitons or polarons are supposed to play a crucial role in the
electric conductivity of polyacetylene, in the intermediate doping regime. We
present an exact fully quantized calculation of the quantum soliton
conductivity in polyacetylene and show that it vanishes exactly. This is
obtained by applying a general method of soliton quantization, based on
order-disorder duality, to a Z(2)-symmetric complex extension of the TLM
dimerization effective field theory. We show that, in this theory,
polyacetylene solitons are sine-Gordon solitons in the phase of the complex
field.Comment: To appear in J. Phys. A: Math. Theor., 15 page
Fermionic Operators from Bosonic Fields in 3+1 Dimensions
We present a construction of fermionic operators in 3+1 dimensions in terms
of bosonic fields in the framework of . The basic bosonic variables are
the electric fields and their conjugate momenta . Our construction
generalizes the analogous constuction of fermionic operators in 2+1 dimensions.
Loosely speaking, a fermionic operator is represented as a product of an
operator that creates a pointlike charge and an operator that creates an
infinitesimal t'Hooft loop of half integer strength. We also show how the axial
transformations are realized in this construction.Comment: 8 pages, two figures available on request, LA-UR-94-286
Inverter-converter automatic paralleling and protection
Electric control and protection circuits for parallel operation of inverter-converte
Dataset of ideological polarization in Western Europe
This dataset provides data on ideological polarization in Western Europe. It is based on parties’ left-right placement provided by several expert surveys. Then, it uses Dalton’s polarization index (2008) to calculate the polarization score in terms of votes and seats for each election. The dataset covers 20 Western European countries since 1945, for a total of 398 parliamentary elections and legislatures (Lower House). The dataset will be regularly updated to include the polarization scores of new elections and legislatures
Topological obstructions in the way of data-driven collective variables
Nonlinear dimensionality reduction (NLDR) techniques are increasingly used to visualize molecular trajectories and to create data-driven collective variables for enhanced sampling simulations. The success of these methods relies on their ability to identify the essential degrees of freedom characterizing conformational changes. Here, we show that NLDR methods face serious obstacles when the underlying collective variables present periodicities, e.g., arising from proper dihedral angles. As a result, NLDR methods collapse very distant configurations, thus leading to misinterpretations and inefficiencies in enhanced sampling. Here, we identify this largely overlooked problem and discuss possible approaches to overcome it. We also characterize the geometry and topology of conformational changes of alanine dipeptide, a benchmark system for testing new methods to identify collective variables. Nonlinear dimensionality reduction (NLDR) techniques are increasingly used to visualize molecular trajectories and to create data-driven collective variables for enhanced sampling simulations. The success of these methods relies on their ability to identify the essential degrees of freedom characterizing conformational changes. Here, we show that NLDR methods face serious obstacles when the underlying collective variables present periodicities, e.g., arising from proper dihedral angles. As a result, NLDR methods collapse very distant configurations, thus leading to misinterpretations and inefficiencies in enhanced sampling. Here, we identify this largely overlooked problem and discuss possible approaches to overcome it. We also characterize the geometry and topology of conformational changes of alanine dipeptide, a benchmark system for testing new methods to identify collective variables
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