Phase diagram of a Bose gas near a wide Feshbach resonance

In this paper, we study the phase diagram of a homogeneous Bose gas with a repulsive interaction near a wide Feshbach resonance at zero temperature. The Bose-Einstein-condensation (BEC) state of atoms is a metastable state. When the scattering length $a$ exceeds a critical value depending on the atom density $n$, $na^3>0.035$, the molecular excitation energy is imaginary and the atomic BEC state is dynamically unstable against molecule formation. The BEC state of diatomic molecules has lower energy, where the atomic excitation is gapped and the molecular excitation is gapless. However when the scattering length is above another critical value, $na^3>0.0164$, the molecular BEC state becomes a unstable coherent mixture of atoms and molecules. In both BEC states, the binding energy of diatomic molecules is reduced due to the many-body effect.Comment: 5 pages, 4 figure

Entanglement and purity of single- and two-photon states

Whereas single- and two-photon wave packets are usually treated as pure states, in practice they will be mixed. We study how entanglement created with mixed photon wave packets is degraded. We find in particular that the entanglement of a delocalized single-photon state of the electro-magnetic field is determined simply by its purity. We also discuss entanglement for two-photon mixed states, as well as the influence of a vacuum component.Comment: 11 pages, 10 figures, 1 debuting autho

Sequence Classification Restricted Boltzmann Machines With Gated Units

For the classification of sequential data, dynamic Bayesian networks and recurrent neural networks (RNNs) are the preferred models. While the former can explicitly model the temporal dependences between the variables, and the latter have the capability of learning representations. The recurrent temporal restricted Boltzmann machine (RTRBM) is a model that combines these two features. However, learning and inference in RTRBMs can be difficult because of the exponential nature of its gradient computations when maximizing log likelihoods. In this article, first, we address this intractability by optimizing a conditional rather than a joint probability distribution when performing sequence classification. This results in the ``sequence classification restricted Boltzmann machine'' (SCRBM). Second, we introduce gated SCRBMs (gSCRBMs), which use an information processing gate, as an integration of SCRBMs with long short-term memory (LSTM) models. In the experiments reported in this article, we evaluate the proposed models on optical character recognition, chunking, and multiresident activity recognition in smart homes. The experimental results show that gSCRBMs achieve the performance comparable to that of the state of the art in all three tasks. gSCRBMs require far fewer parameters in comparison with other recurrent networks with memory gates, in particular, LSTMs and gated recurrent units (GRUs)

Plasmonic Brownian ratchet

Here we present a Brownian ratchet based on plasmonic interactions. By periodically turning on and off a laser beam that illuminates a periodic array of plasmonic nanostructures with broken spatial symmetry, the random thermal motion of a subwavelength dielectric bead is rectified into one direction. By means of the Molecular Dynamics technique we show a statistical directed drift in particle flow

Detecting non-Markovian plasmonic band gaps in quantum dots using electron transport

Placing a quantum dot close to a metal nanowire leads to drastic changes in its radiative decay behavior because of evanescent couplings to surface plasmons. We show how two non-Markovian effects, band-edge and retardation, could be observed in such a system. Combined with a quantum dot p-i-n junction, these effects could be readout via current-noise measurements. We also discuss how these effects can occur in similar systems with restricted geometries, like phononic cavities and photonic crystal waveguides. This work links two previously separate topics: surface-plasmons and current-noise measurements.Comment: 8 page

Classifying Crises-Information Relevancy with Semantics

Social media platforms have become key portals for sharing and consuming information during crisis situations. However, humanitarian organisations and affected communities often struggle to sieve through the large volumes of data that are typically shared on such platforms during crises to determine which posts are truly relevant to the crisis, and which are not. Previous work on automatically classifying crisis information was mostly focused on using statistical features. However, such approaches tend to be inappropriate when processing data on a type of crisis that the model was not trained on, such as processing information about a train crash, whereas the classifier was trained on floods, earthquakes, and typhoons. In such cases, the model will need to be retrained, which is costly and time-consuming. In this paper, we explore the impact of semantics in classifying Twitter posts across same, and different, types of crises. We experiment with 26 crisis events, using a hybrid system that combines statistical features with various semantic features extracted from external knowledge bases. We show that adding semantic features has no noticeable benefit over statistical features when classifying same-type crises, whereas it enhances the classifier performance by up to 7.2% when classifying information about a new type of crisis

Tunneling Qubit Operation on a Protected Josephson Junction Array

We discuss a protected quantum computation process based on a hexagon Josephson junction array. Qubits are encoded in the punctured array, which is topologically protected. The degeneracy is related to the number of holes. The topological degeneracy is lightly shifted by tuning the flux through specific hexagons. We also show how to perform single qubit operation and basic quantum gate operations in this system.Comment: 8 pages, 4 figures. The published version in Phys. Rev., A81(2010)01232

Probing the mechanism of electron capture and electron transfer dissociation using tags with variable electron affinity

Electron capture dissociation (ECD) and electron transfer dissociation (ETD) of doubly protonated electron affinity (EA)-tuned peptides were studied to further illuminate the mechanism of these processes. The model peptide FQpSEEQQQTEDELQDK, containing a phosphoserine residue, was converted to EA-tuned peptides via β-elimination and Michael addition of various thiol compounds. These include propanyl, benzyl, 4-cyanobenzyl, perfluorobenzyl, 3,5-dicyanobenzyl, 3-nitrobenzyl, and 3,5-dinitrobenzyl structural moieties, having a range of EA from −1.15 to +1.65 eV, excluding the propanyl group. Typical ECD or ETD backbone fragmentations are completely inhibited in peptides with substituent tags having EA over 1.00 eV, which are referred to as electron predators in this work. Nearly identical rates of electron capture by the dications substituted by the benzyl (EA = −1.15 eV) and 3-nitrobenzyl (EA = 1.00 eV) moieties are observed, which indicates the similarity of electron capture cross sections for the two derivatized peptides. This observation leads to the inference that electron capture kinetics are governed by the long-range electron−dication interaction and are not affected by side chain derivatives with positive EA. Once an electron is captured to high-n Rydberg states, however, through-space or through-bond electron transfer to the EA-tuning tags or low-n Rydberg states via potential curve crossing occurs in competition with transfer to the amide π* orbital. The energetics of these processes are evaluated using time-dependent density functional theory with a series of reduced model systems. The intramolecular electron transfer process is modulated by structure-dependent hydrogen bonds and is heavily affected by the presence and type of electron-withdrawing groups in the EA-tuning tag. The anion radicals formed by electron predators have high proton affinities (approximately 1400 kJ/mol for the 3-nitrobenzyl anion radical) in comparison to other basic sites in the model peptide dication, facilitating exothermic proton transfer from one of the two sites of protonation. This interrupts the normal sequence of events in ECD or ETD, leading to backbone fragmentation by forming a stable radical intermediate. The implications which these results have for previously proposed ECD and ETD mechanisms are discussed