On the quantization of SU(3)-skyrmions

The quantization condition derived previously for SU(2) solitons quantized with SU(3)-collective coordinates is generalized for SU(3) skyrmions with strangeness content different from zero. Quantization of the dipole-type configuration with large strangeness content found recently is considered as an example.Comment: 7 pages, 2 figures (available by request

Precision spectroscopy of the 3s-3p fine structure doublet in Mg+

We apply a recently demonstrated method for precision spectroscopy on strong transitions in trapped ions to measure both fine structure components of the 3s-3p transition in 24-Mg+ and 26-Mg+. We deduce absolute frequency reference data for transition frequencies, isotope shifts and fine structure splittings that are in particular useful for comparison with quasar absorption spectra, which test possible space-time variations of the fine structure constant. The measurement accuracy improves previous literature values, when existing, by more than two orders of magnitude

Semiclassical quantization of SU(3) skyrmions

Semiclassical quantization of the SU(3)-skyrmions is performed by means of the collective coordinate method. The quantization condition known for the SU(2)-solitons quantized with SU(3) collective coordinates is generalized for the SU(3) skyrmions with strangeness content different from zero. Quantization of the dipole-type configuration with large strangeness content found recently is considered as an example, the spectrum and the mass splitting of the quantized states are estimated. The energy and baryon number density of SU(3) skyrmions are presented in the form emphasizing their symmetry in different SU(2) subgroups of SU(3), and the lower boundary for the static energy of SU(3) skyrmions is derived.Comment: 16 pages, 2 figures (available upon request). Submitted to JETP on May 6, 1997; in print. A preliminary short version of this paper is hep-th/960916

Self-Consistent Pushing and Cranking Corrections to the Meson Fields of the Chiral Quark-Loop Soliton

We study translational and spin-isospin symmetry restoration for the two-flavor chiral quark-loop soliton. Instead of a static soliton at rest we consider a boosted and rotating hedgehog soliton. Corrected classical meson fields are obtained by minimizing a corrected energy functional which has been derived by semi-classical methods ('variation after projection'). We evaluate corrected meson fields in the region 300 MeV \le M \le 600 MeV of constituent quark masses M and compare them with the uncorrected fields. We study the effect of the corrections on various expectation values of nuclear observables such as the root-mean square radius, the axial-vector coupling constant, magnetic moments and the delta-nucleon mass splitting.Comment: 19 pages, LaTeX, 7 postscript figures included using 'psfig.sty', to appear in Int.J.Mod.Phys.

Electro-Magnetic Nucleon Form Factors and their Spectral Functions in Soliton Models

It is demonstrated that in simple soliton models essential features of the electro-magnetic nucleon form factors observed over three orders of magnitude in momentum transfer $t$ are naturally reproduced. The analysis shows that three basic ingredients are required: an extended object, partial coupling to vector mesons, and relativistic recoil corrections. We use for the extended object the standard skyrmion, one vector meson propagator for both isospin channels, and the relativistic boost to the Breit frame. Continuation to timelike $t$ leads to quite stable results for the spectral functions in the regime from the 2- or 3-pion threshold to about two rho masses. Especially the onset of the continuous part of the spectral functions at threshold can be reliably determined and there are strong analogies to the results imposed on dispersion theoretic approaches by the unitarity constraint.Comment: 24 pages, (RevTeX), 5 PS-figures; Data points in fig.2 and corresponding references added. Final version, to be published in Z.Physik

Loosely bound hyperons in the SU(3) Skyrme model

Hyperon pairs bound in deuteron like states are obtained within the SU(3) Skyrme model in agreement with general expectations from boson exchange models. The central binding from the flavor symmetry breaking terms increases with the strangeness contents of the interacting baryons whereas the kinetic non-linear $\sigma$-model term fixes the spin and isospin of the bound pair. We give a complete account of the interactions of octet baryons within the product approximation to baryon number $B=2$ configurations.Comment: 35 pages REVTEX including 2 figs, with 3 further figs available on request from [email protected] or from [email protected] SI-94-TP3S2; STPHY-Th/94-

Measurement noise floor for a long-distance optical carrier transmission via fiber

We investigated the measurement floor and link stability for the transfer of an ultra-stable optical frequency via an optical fiber link. We achieved a near-delay-limited instability of 3x10^(-15)/(tau x Hz) for 147 km deployed fiber, and 10^(-20) (integrations time tau = 4000 s) for the noise floor.Comment: 5 pages, 3 figures, 7th Symposium on Frequency Standards and Metrology (Pacific Grove,USA, Oct 2008

Machine learning approach for computing optical properties of a photonic crystal fiber

Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers. In this paper, machine learning techniques are used to compute various optical properties including effective index, effective mode area, dispersion and confinement loss for a solid-core PCF. These machine learning algorithms based on artificial neural networks are able to make accurate predictions of above-mentioned optical properties for usual parameter space of wavelength ranging from 0.5-1.8 µm, pitch from 0.8-2.0 µm, diameter by pitch from 0.6-0.9 and number of rings as 4 or 5 in a silica solid-core PCF. We demonstrate the use of simple and fast-training feed-forward artificial neural networks that predicts the output for unknown device parameters faster than conventional numerical simulation techniques. Computation runtimes required with neural networks (for training and testing) and Lumerical MODE solutions are also compared