Noise assisted quantum coherence protection in hierarchical environment

In this paper, we investigate coherence protection of a quantum system coupled to a hierarchical environment by utilizing noise. As an example, we solve the Jaynes-Cummings (J-C) model in presence of both a classical and a quantized noise. The master equation is derived beyond the Markov approximation, where the influence of memory effects from both noises is taken into account. More importantly, we find that the performance of the coherence protection sensitively depends on the non-Markovian properties of both noises. By analyzing the mathematical mechanism of the coherence protection, we show the decoherence caused by a non-Markovian noise with longer memory time can be suppressed by another Markovian noise with shorter memory time. Last but not least, as an outlook, we try to analyze the connection between the atom-cavity entanglement and the atomic coherence, then discuss the possible clue to search for the required noise. The results presented in this paper show the possibility of protecting coherence by utilizing noise and may open a new path to design noise-assisted coherence protection schemes.Comment: 17 pages, 9 figure

Two Case Reports of Familial Chylomicronemia Syndrome

Familial chylomicronemia is a rare autosomal recessive disorder which is also called Hyperlipoproteinemia type I. Here we report two cases with this rare disorder that were admitted to our hospital in recent years

Poly[[tetra­aqua­bis­(μ3-5-carboxybenzene-1,2,4-tri­carboxyl­ato)tricadmium] tetra­hydrate]

There are three independent CdII ions in the title complex, {[Cd3(C10H3O8)2(H2O)4]·4H2O}n, one of which is coordinated by four O atoms from three 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands and by two water mol­ecules in a distorted octa­hedral geometry. The second CdII ion is coordinated by five O atoms from four 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands and by one water mol­ecule also in a distorted octa­hedral geometry while the third CdII ion is coordinated by five O atoms from three 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands and by one water mol­ecule in a highly distorted octa­hedral geometry. The 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands bridge the CdII ions, resulting in the formation of a three-dimensional structure. Intra- and inter­molecular O—H⋯O hydrogen bonds are present throughout the three-dimensional structure

Methyl 2-hydr­oxy-3-nitro­benzoate

The title compound, C8H7NO5, assumes an approximately planar mol­ecular structure with an intra­molecular O—H⋯O hydrogen bond between the hydr­oxy and carboxyl­ate groups. Weak inter­molecular C—H⋯O hydrogen bonding is present in the crystal structure

Nonlinear Analysis of Auscultation Signals in TCM Using the Combination of Wavelet Packet Transform and Sample Entropy

Auscultation signals are nonstationary in nature. Wavelet packet transform (WPT) has currently become a very useful tool in analyzing nonstationary signals. Sample entropy (SampEn) has recently been proposed to act as a measurement for quantifying regularity and complexity of time series data. WPT and SampEn were combined in this paper to analyze auscultation signals in traditional Chinese medicine (TCM). SampEns for WPT coefficients were computed to quantify the signals from qi- and yin-deficient, as well as healthy, subjects. The complexity of the signal can be evaluated with this scheme in different time-frequency resolutions. First, the voice signals were decomposed into approximated and detailed WPT coefficients. Then, SampEn values for approximated and detailed coefficients were calculated. Finally, SampEn values with significant differences in the three kinds of samples were chosen as the feature parameters for the support vector machine to identify the three types of auscultation signals. The recognition accuracy rates were higher than 90%

Comparison and analysis of bare soil evaporation models combined with ASTER data in Heihe River Basin

AbstractBased on ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) remote sensing data, bare soil evaporation was estimated with the Penman-Monteith model, the Priestley-Taylor model, and the aerodynamics model. Evaporation estimated by each of the three models was compared with actual evaporation, and error sources of the three models were analyzed. The mean absolute relative error was 9% for the Penman-Monteith model, 14% for the Priestley-Taylor model, and 32% for the aerodynamics model; the Penman-Monteith model was the best of these three models for estimating bare soil evaporation. The error source of the Penman-Monteith model is the neglect of the advection estimation. The error source of the Priestley-Taylor model is the simplification of the component of aerodynamics as 0.72 times the net radiation. The error source of the aerodynamics model is the difference of vapor pressure and neglect of the radiometric component. The spatial distribution of bare soil evaporation is evident, and its main factors are soil water content and elevation