Excitonic Instabilities and Insulating States in Bilayer Graphene

The competing ground states of bilayer graphene are studied by applying renormalization group techniques to a bilayer honeycomb lattice with nearest neighbor hopping. In the absence of interactions, the Fermi surface of this model at half-filling consists of two nodal points with momenta $\mathbf{K}$, $\mathbf{K}'$, where the conduction band and valence band touch each other, yielding a semi-metal. Since near these two points the energy dispersion is quadratic with perfect particle-hole symmetry, excitonic instabilities are inevitable if inter-band interactions are present. Using a perturbative renormalization group analysis up to the one-loop level, we find different competing ordered ground states, including ferromagnetism, superconductivity, spin and charge density wave states with ordering vector $\mathbf{Q}=\mathbf{K}-\mathbf{K}'$, and excitonic insulator states. In addition, two states with valley symmetry breaking are found in the excitonic insulating and ferromagnetic phases. This analysis strongly suggests that the ground state of bilayer graphene should be gapped, and with the exception of superconductivity, all other possible ground states are insulating.Comment: 17 pages, 6 figures, 2 Tables, Added reference

Simulation and detection of Dirac fermions with cold atoms in an optical lattice

We propose an experimental scheme to simulate and observe relativistic Dirac fermions with cold atoms in a hexagonal optical lattice. By controlling the lattice anisotropy, one can realize both massive and massless Dirac fermions and observe the phase transition between them. Through explicit calculations, we show that both the Bragg spectroscopy and the atomic density profile in a trap can be used to demonstrate the Dirac fermions and the associated phase transition.Comment: 4 pages; Published versio

Experimental study of flashing LNG jet fires following horizontal releases

A horizontally oriented jet fire could occur if the leaking liquefied natural gas (LNG) from the side surface of a pipe or storage tank was ignited. Previous work with LNG mostly focused on pool fires. In the present study, horizontally oriented LNG jet fires were studied through 10 open field full scale tests. The flames were visualized by both infrared and video cameras. The recorded flame shapes are compared and analysed. Peak temperatures and heat fluxes at various flow rates were measured and recorded. For relatively low reservoir pressure, a small amount of LNG was found to spray through the fire and rainout onto the ground, forming an LNG pool. A correlation was established to calculate the flame length from the mass flow rate

Scaling of geometric phases close to quantum phase transition in the XY chain

We show that geometric phase of the ground state in the XY model obeys scaling behavior in the vicinity of a quantum phase transition. In particular we find that geometric phase is non-analytical and its derivative with respect to the field strength diverges at the critical magnetic field. Furthermore, universality in the critical properties of the geometric phase in a family of models is verified. In addition, since quantum phase transition occurs at a level crossing or avoided level crossing and these level structures can be captured by Berry curvature, the established relation between geometric phase and quantum phase transitions is not a specific property of the XY model, but a very general result of many-body systems.Comment: 4 page

Implementing topological quantum manipulation with superconducting circuits

A two-component fermion model with conventional two-body interactions was recently shown to have anyonic excitations. We here propose a scheme to physically implement this model by transforming each chain of two two-component fermions to the two capacitively coupled chains of superconducting devices. In particular, we elaborate how to achieve the wanted operations to create and manipulate the topological quantum states, providing an experimentally feasible scenario to access the topological memory and to build the anyonic interferometry.Comment: 4 pages with 3 figures; V2: published version with minor updation

A new class of (2+1)(2+1)-d topological superconductor with Z8\mathbb{Z}_8 topological classification

The classification of topological states of matter depends on spatial dimension and symmetry class. For non-interacting topological insulators and superconductors the topological classification is obtained systematically and nontrivial topological insulators are classified by either integer or $Z_2$. The classification of interacting topological states of matter is much more complicated and only special cases are understood. In this paper we study a new class of topological superconductors in $(2+1)$ dimensions which has time-reversal symmetry and a $\mathbb{Z}_2$ spin conservation symmetry. We demonstrate that the superconductors in this class is classified by $\mathbb{Z}_8$ when electron interaction is considered, while the classification is $\mathbb{Z}$ without interaction.Comment: 5 pages main text and 3 pages appendix. 1 figur

Fluctuation-Driven Vortex Fractionalization in Topologically Ordered Superfluids of Cold Atoms

We have studied spin structures of fluctuation-driven fractionalized vortices and topological spin order in 2D nematic superfluids of cold sodium atoms. Our Monte Carlo simulations suggest a softened pi-spin disclination structure in a half-quantum vortex when spin correlations are short ranged; in addition, calculations indicate that a unique non-local topological spin order emerges simultaneously as cold atoms become a superfluid below a critical temperature. We have also estimated fluctuation-dependent critical frequencies for half-quantum vortex nucleation in rotating optical traps and discussed probing these excitations in experiments.Comment: 5 pages, 2 figures; revised version accepted by Europhysics Letter

Dissipationless Phonon Hall Viscosity

We study the acoustic phonon response of crystals hosting a gapped time-reversal symmetry breaking electronic state. The phonon effective action can in general acquire a dissipationless "Hall" viscosity, which is determined by the adiabatic Berry curvature of the electron wave function. This Hall viscosity endows the system with a characteristic frequency, \omega_v; for acoustic phonons of frequency \omega, it shifts the phonon spectrum by an amount of order (\omega/\omega_v)^2 and it mixes the longitudinal and transverse acoustic phonons with a relative amplitude ratio of \omega/\omega_v and with a phase shift of +/- \pi/2, to lowest order in \omega/\omega_v. We study several examples, including the integer quantum Hall states, the quantum anomalous Hall state in Hg_{1-y}Mn_{y}Te quantum wells, and a mean-field model for p_x + i p_y superconductors. We discuss situations in which the acoustic phonon response is directly related to the gravitational response, for which striking predictions have been made. When the electron-phonon system is viewed as a whole, this provides an example where measurements of Goldstone modes may serve as a probe of adiabatic curvature of the wave function of the gapped sector of a system.Comment: 14 page

Prompt-Matched Semantic Segmentation

The objective of this work is to explore how to effectively and efficiently adapt pre-trained visual foundation models to various downstream tasks of semantic segmentation. Previous methods usually fine-tuned the entire networks for each specific dataset, which will be burdensome to store massive parameters of these networks. A few recent works attempted to insert some extra trainable parameters into the frozen networks to learn visual prompts for parameter-efficient tuning. However, these works showed poor generality as they were designed specifically for Transformers. Moreover, using limited information in these schemes, they exhibited a poor capacity to learn beneficial prompts. To alleviate these issues, we propose a novel Stage-wise Prompt-Matched Framework for generic and effective visual prompt tuning. Specifically, to ensure generality, we divide the pre-trained backbone with frozen parameters into multiple stages and perform prompt learning between different stages, which makes the proposed scheme applicable to various architectures of CNN and Transformer. For effective tuning, a lightweight Semantic-aware Prompt Matcher (SPM) is designed to progressively learn reasonable prompts with a recurrent mechanism, guided by the rich information of interim semantic maps. Working as deep matched filter of representation learning, the proposed SPM can well transform the output of the previous stage into a desirable input for the next stage, thus achieving the better matching/stimulating for the pre-trained knowledge. Extensive experiments on four benchmarks demonstrate that the proposed scheme can achieve a promising trade-off between parameter efficiency and performance effectiveness. Our code and models will be released

Utility based cooperative resource sharing in symbiotic radio aided Internet of Things networks

Symbiotic radio (SR) is a key technique to solve the energy shortage and spectrum limitation of the future Internet of Things (IoT). In the SR-aided IoT networks supporting energy harvesting (EH), we study the cooperation schemes and offloading strategy between the primary users (PUs), IoT devices and the base station (BS) for reasonably allocating the spectrum, power and time resources. Considering the monetary transactions between the PUs and IoT devices, two cooperation schemes, namely the “Preferential Scenario" and the “No-Preferential Scenario", are proposed. In the “Preferential Scenario", based on the final strategy, the IoT devices use the purchased spectrum and power to offload their own tasks to the BS after assisting the cooperative PUs to offload during a certain time slot. Due to the assistance of IoT devices for the PUs, IoT devices enjoy a discount when paying for the purchased spectrum and power. In the “No-Preferential Scenario", the IoT devices and the cooperative PUs offload tasks to the BS together in a certain time slot according to the offloading strategy. The spectrum and power used by the IoT devices are purchased at the original price without a discount. For each scenario, we study the utility maximization problem of the PUs, where the utility of PUs includes the transmission rates and income. The utility based resource sharing algorithm is proposed to obtain an approximately optimal resource allocation scheme. Our simulation results indicate that the proposed algorithm provides good performances for both scenarios, while each scenario applying the proposed algorithm has its own advantages