Dissipation effect in the double-well Bose-Einstein Condensate

Dynamics of the double-well Bose-Einstein condensate subject to energy dissipation is studied by solving a reduced one-dimensional time-dependent Gross-Pitaevskii equation numerically. We first reproduce the phase space diagram of the system without dissipation systematically, and then calculate evolutionary trajectories of dissipated systems. It is clearly shown that the dissipation can drive the system to evolve gradually from the $\pi$-mode quantum macroscopic self-trapping state, a state with relatively higher energy, to the lowest energy stationary state in which particles distribute equally in the two wells. The average phase and phase distribution in each well are discussed as well. We show that the phase distribution varies slowly in each well but may exhibit abrupt changes near the barrier. This sudden change occurs at the minimum position in particle density profile. We also note that the average phase in each well varies much faster with time than the phase difference between two wells.Comment: 7 pages, 7 figures, to be published in Euro. Phys. J.

The Lifecycle and Cascade of WeChat Social Messaging Groups

Social instant messaging services are emerging as a transformative form with which people connect, communicate with friends in their daily life - they catalyze the formation of social groups, and they bring people stronger sense of community and connection. However, research community still knows little about the formation and evolution of groups in the context of social messaging - their lifecycles, the change in their underlying structures over time, and the diffusion processes by which they develop new members. In this paper, we analyze the daily usage logs from WeChat group messaging platform - the largest standalone messaging communication service in China - with the goal of understanding the processes by which social messaging groups come together, grow new members, and evolve over time. Specifically, we discover a strong dichotomy among groups in terms of their lifecycle, and develop a separability model by taking into account a broad range of group-level features, showing that long-term and short-term groups are inherently distinct. We also found that the lifecycle of messaging groups is largely dependent on their social roles and functions in users' daily social experiences and specific purposes. Given the strong separability between the long-term and short-term groups, we further address the problem concerning the early prediction of successful communities. In addition to modeling the growth and evolution from group-level perspective, we investigate the individual-level attributes of group members and study the diffusion process by which groups gain new members. By considering members' historical engagement behavior as well as the local social network structure that they embedded in, we develop a membership cascade model and demonstrate the effectiveness by achieving AUC of 95.31% in predicting inviter, and an AUC of 98.66% in predicting invitee.Comment: 10 pages, 8 figures, to appear in proceedings of the 25th International World Wide Web Conference (WWW 2016

DPF: Learning Dense Prediction Fields with Weak Supervision

Nowadays, many visual scene understanding problems are addressed by dense prediction networks. But pixel-wise dense annotations are very expensive (e.g., for scene parsing) or impossible (e.g., for intrinsic image decomposition), motivating us to leverage cheap point-level weak supervision. However, existing pointly-supervised methods still use the same architecture designed for full supervision. In stark contrast to them, we propose a new paradigm that makes predictions for point coordinate queries, as inspired by the recent success of implicit representations, like distance or radiance fields. As such, the method is named as dense prediction fields (DPFs). DPFs generate expressive intermediate features for continuous sub-pixel locations, thus allowing outputs of an arbitrary resolution. DPFs are naturally compatible with point-level supervision. We showcase the effectiveness of DPFs using two substantially different tasks: high-level semantic parsing and low-level intrinsic image decomposition. In these two cases, supervision comes in the form of single-point semantic category and two-point relative reflectance, respectively. As benchmarked by three large-scale public datasets PASCALContext, ADE20K and IIW, DPFs set new state-of-the-art performance on all of them with significant margins. Code can be accessed at https://github.com/cxx226/DPF

Effects Of Simultaneous CO2 Addition To The Fuel And Oxidizer Streams On Soot Formation In Co-flow Diffusion Ethylene Flame

Soot formation in a co-flow diffusion ethylene flame with the addition of CO2 to the fuel (the CO2-F), oxidizer (the CO2-O), and fuel/oxidizer (the CO2-F/O) streams was numerically and experimentally investigated in this study. The effects of different CO2 addition ways on soot inception, soot condensation, H-abstraction-C2H2-addition (HACA) and oxidation by O2/OH processes, were quantitatively analyzed by introducing the integrated reaction rates over the whole computational domain. The simulated and experimental results showed that the CO2-F/O was the most effective in inhibiting soot formation and flame temperature, followed by the CO2-O, and the CO2-F. Compared with the CO2-F, the suppression effect of the CO2-O on soot inception was weaker due to the higher concentration of benzo(ghi) fluoranthene (BGHIF). Since the rate of C4H2 formation via C2H4 → C2H3 → C2H2 → C4H2 was inhibited by the CO2-O, lowering the consumption rate of acenaphthalene (A2R5) via C4H2 + A2R5=\u3eA4, more A2R5 converted to BGHIF via A2R5 → A2- → A2 → BGHIF. The suppression effects of different ways of CO2 addition on HACA surface growth and soot condensation were identical: CO2-F \u3c CO2-O \u3c CO2-F/O. The decrease of benzo(a)pyrene (BAPYR) mole fraction accounted for the decline of soot condensation rate, and the decreases of H and OH mole fractions were responsible for the drop of HACA surface growth rate. Compared with the CO2-F, the CO2-O and the CO2-F/O had stronger suppression effects on the soot oxidation by O2 process due to the lower concentration of O2 in the oxidizer stream. Whichever CO2 addition ways were adopted, the soot oxidation by O2 process was more sensitive than the soot oxidation by OH process with the CO2 addition

Non-Abelian Chiral Spin Liquid on the Kagome Lattice

We study $S=1$ spin liquid states on the kagome lattice constructed by Gutzwiller-projected $p_x+ip_y$ superconductors. We show that the obtained spin liquids are either non-Abelian or Abelian topological phases, depending on the topology of the fermionic mean-field state. By calculating the modular matrices $S$ and $T$, we confirm that projected topological superconductors are non-Abelian chiral spin liquid (NACSL). The chiral central charge and the spin Hall conductance we obtained agree very well with the $SO(3)_1$ (or, equivalently, $SU(2)_2$) field theory predictions. We propose a local Hamiltonian which may stabilize the NACSL. From a variational study we observe a topological phase transition from the NACSL to the $Z_2$ Abelian spin liquid.Comment: 12 pages, 7 figures, 1 tabl

Control of astrocyte progenitor specification, migration and maturation by Nkx6.1 homeodomain transcription factor.

Although astrocytes are the most abundant cell type in the central nervous system (CNS), little is known about their molecular specification and differentiation. It has previously been reported that transcription factor Nkx6.1 is expressed in neuroepithelial cells that give rise to astrocyte precursors in the ventral spinal cord. In the present study, we systematically investigated the function of Nkx6.1 in astrocyte development using both conventional and conditional Nkx6.1 mutant mice. At early postnatal stages, Nkx6.1 was expressed in a subpopulation of astrocytes in the ventral spinal cord. In the conventional Nkx6.1KO spinal cord, the initial specification of astrocyte progenitors was affected by the mutation, and subsequent migration and differentiation were disrupted in newborn mice. In addition, the development of VA2 subtype astrocytes was also inhibited in the white matter. Further studies with Nkx6.1 conditional mutants revealed significantly delayed differentiation and disorganized arrangement of fibrous astrocytes in the ventral white matter. Together, our studies indicate that Nkx6.1 plays a vital role in astrocyte specification and differentiation in the ventral spinal cord

Triangle Counting Rule: An Approach to Forecast the Magnetic Properties of Benzenoid Polycyclic Hydrocarbons

Open-shell benzenoid polycyclic hydrocarbons (BPHs) are promising materials for future quantum applications. However, the search and realization of open-shell BPHs with desired properties is a challenging task due to the gigantic chemical space of BPHs, requiring new strategies for both theoretical understanding and experimental advancement. In this work, by building a structure database of BPHs through graphical enumeration, performing data-driven analysis, and combining tight-binding and mean-field Hubbard calculations, we discovered that the number of the internal vertices of the BPH graphs is closely correlated to their open-shell characters. We further established a series of simple rules, the triangle counting rule (TCR), to predict the magnetic ground state of BPHs. These findings not only provide a database of open-shell BPHs, but also extend the well-known Lieb's theorem and Ovchinnikov's rule and provide a straightforward method for designing open-shell carbon nanostructures. These insights may aid in the exploration of emerging quantum phases and the development of magnetic carbon materials for technology applications.Comment: 6 pages, 4 figure