An ab initio and force field study on the conformation and chain flexibility of the dichlorophosphazene trimer

Ab initio molecular orbital calculations have been used to study the conformation, valence electron charge density, and chain flexibility of a dichlorophosphazene trimer (CH3[NP(Cl2)]3CH3). The calculations were carried out at the restricted Hartree-Fock level with the 6-31 G* basis set. The dichlorophosphazene trimer adopts a planar transcis conformation. The valence electron charge distribution indicates strong charge separations along the backbone of the molecule, and is in agreement with Dewar's island delocalization model for bonding in linear and cyclic phosphazenes. In order to determine the height of the torsional barrier (2,5 kcal/mol), the torsional potential of a central P-N bond of the trimer was studied with a rigid rotor scan and geometry optimizations of selected rotamers. The flexibility of the P-N-P bond angle contributes significantly to the chain flexibility. Based on the results of the ab initio calculations, an empirical force field for the dichlorophosphazene trimer was developed. The energy expression includes bond stretch, angle bend, electrostatic, van der Waals, and torsional potential terms. A relaxed scan with the force field achieves good agreement with the ab initio results for the torsional potential in the vicinity of the stable conformation, and an excellent agreement with the ab initio results on changes in the P2N2P3 bond angle and the N1P2 - N2P3 dihedral angle during a full rotation around the N2 - P3 bond

Disentanglement and decoherence in two-spin and three-spin systems under dephasing

We compare disentanglement and decoherence rates within two-spin and three-spin entangled systems subjected to all possible combinations of local and collective pure dephasing noise combinations. In all cases, the bipartite entanglement decay rate is found to be greater than or equal to the dephasing-decoherence rates and often significantly greater. This sharpens previous results for two-spin systems [T. Yu and J. H. Eberly Phys. Rev. B 68, 165322 (2003)] and extends them to the three-spin context.Comment: 17 page

UHE neutrino searches using a Lunar target: First Results from the RESUN search

During the past decade there have been several attempts to detect cosmogenic ultra high energy (UHE) neutrinos by searching for radio Cerenkov bursts resulting from charged impact showers in terrestrial ice or the lunar regolith. So far these radio searches have yielded no detections, but the inferred flux upper limits have started to constrain physical models for UHE neutrino generation. For searches which use the Moon as a target, we summarize the physics of the interaction, properties of the resulting Cerenkov radio pulse, detection statistics, effective aperture scaling laws, and derivation of upper limits for isotropic and point source models. We report on initial results from the RESUN search, which uses the Expanded Very Large Array configured in multiple sub-arrays of four antennas at 1.45 GHz pointing along the lunar limb. We detected no pulses of lunar origin during 45 observing hours. This implies upper limits to the differential neutrino flux E^2 dN/dE < 0.003 EeV km^{-2} s^{-1} sr^{-1} and < 0.0003 EeV km$^{-2} s^{-1} at 90% confidence level for isotropic and sampled point sources respectively, in the neutrino energy range 10^{21.6} < E(eV) < 10^{22.6}. The isotropic flux limit is comparable to the lowest published upper limits for lunar searches. The full RESUN search, with an additional 200 hours observing time and an improved data acquisition scheme, will be be an order of magnitude more sensitive in the energy range 10^{21} < E(eV) < 10^{22} than previous lunar-target searches, and will test Z burst models of neutrino generation.Comment: 26 pages, 14 figure

Proton NMR relaxometry as a useful tool to evaluate swelling processes in peat soils

Dramatic physical and physico-chemical changes in soil properties may arise due to temperature and moisture variations as well as swelling of soil organic matter (SOM) under constant conditions. Soil property variations may influence sorption/desorption and transport processes of environmental contaminants and nutrients in natural-organic-matterrich soils. Notwithstanding the studies reported in literature, a mechanistic model for SOM swelling is unavailable yet. The objective of the present study was the evaluation of the swelling of peat soils, considered as SOM models, by 1H NMR relaxometry and differential scanning calorimetry (DSC). Namely, information on the processes governing physical and physicochemical changes of peat during re-hydration were collected. The basic hypothesis of the present study was that the changes are slow and may affect water state as well as amounts of different water types into the peats. For this reason, such changes can be evidenced through the variations of mobility and thermal behaviour of the involved H2O molecules by using 1H NMR relaxometry and DSC. According to the experimental results, a mechanistic model, describing the fundamental processes of peat swelling, was obtained. Two different peats re-wetted at three temperatures were used. The swelling process was monitored by measuring spin-spin relaxation time (T2) over a hydration time of several months. Moreover, DSC, T1 – T2 and T2 – D correlation measurements were done at the beginning and at the end of the hydration. Supplementary investigations were also done in order to discriminate between the swelling effects and the contributions from soil solution, internal magnetic field gradients and/or soil microorganisms to proton relaxation. All the results revealed peat swelling. It was evidenced by pore size distribution changes, volumetric expansion and redistribution of water, increasing amounts of nonfreezable and loosely bound water, as well as formation of gel phases and reduction of the translational and rotational mobility of H2O molecules. All the findings implied that changes of the physical and physicochemical properties of peats were obtained. In particular, three different processes having activation energies comprised in the interval 5 – 50 kJ mol-1 were revealed. The mechanistic model which was, then, developed included water reorientation in bound water phases, water diffusion into the peat matrix and reorientation of SOM chains as fundamental processes governing SOM swelling. This study is of environmental significance in terms of re-naturation and re-watering of commercially applied peatlands and of sorption/desorption and transport processes of pollutants and nutrients in natural organic matter rich soil

Towards violation of Born's rule: description of a simple experiment

Recently a new model with hidden variables of the wave type was elaborated, so called prequantum classical statistical field theory (PCSFT). Roughly speaking PCSFT is a classical signal theory applied to a special class of signals -- "quantum systems". PCSFT reproduces successfully all probabilistic predictions of QM, including correlations for entangled systems. This model peacefully coexists with all known no-go theorems, including Bell's theorem. In our approach QM is an approximate model. All probabilistic predictions of QM are only (quite good) approximations of "real physical averages". The latter are averages with respect to fluctuations of prequantum fields. In particular, Born's rule is only an approximate rule. More precise experiments should demonstrate its violation. We present a simple experiment which has to produce statistical data violating Born's rule. Since the PCSFT-presentation of this experiment may be difficult for experimenters, we reformulate consequences of PCSFT in terms of the conventional wave function. In general, deviation from Born's rule is rather small. We found an experiment amplifying this deviation. We start with a toy example in section 2. Then we present a more realistic example based on Gaussian states with very small dispersion, see section 3.Comment: The paper was completed with the description of an experiment with Gaussian states with very small dispersion. This experiment should induce violation of Born's rule, the fundamental law of Q

Optimal Dynamical Decoherence Control of a Qubit

A theory of dynamical control by modulation for optimal decoherence reduction is developed. It is based on the non-Markovian Euler-Lagrange equation for the energy-constrained field that minimizes the average dephasing rate of a qubit for any given dephasing spectrum.Comment: 6 pages, including 2 figures and an appendi

Hierarchical Temporal Representation in Linear Reservoir Computing

Recently, studies on deep Reservoir Computing (RC) highlighted the role of layering in deep recurrent neural networks (RNNs). In this paper, the use of linear recurrent units allows us to bring more evidence on the intrinsic hierarchical temporal representation in deep RNNs through frequency analysis applied to the state signals. The potentiality of our approach is assessed on the class of Multiple Superimposed Oscillator tasks. Furthermore, our investigation provides useful insights to open a discussion on the main aspects that characterize the deep learning framework in the temporal domain.Comment: This is a pre-print of the paper submitted to the 27th Italian Workshop on Neural Networks, WIRN 201

Learning Markov Decision Processes for Model Checking

Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system. The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation is performed by analyzing the probabilistic linear temporal logic properties of the system as well as by analyzing the schedulers, in particular the optimal schedulers, induced by the learned models.Comment: In Proceedings QFM 2012, arXiv:1212.345