Determining Hadron-Quark Phase Transition Chemical Potential via Astronomical Observations

We propose a scheme to determine the chemical potential and baryon number density of the hadron-quark phase transition in cold dense strong interaction matter (compact star matter). The hadron matter is described with the relativistic mean field theory, and the quark matter is described with the Dyson-Schwinger equation approach of QCD. To study the first-order phase transition, we take the sound speed as the interpolation objective to construct the equation of state in the middle density region. With the maximum mass, the tidal deformability and the radius of neutron stars being taken as calibration quantities, the phase transition chemical potential is constrained to a quite small range. And the most probable value of the phase transition chemical potential is found.Comment: 5 pages, 3 figures, 1 tabl

Constraining the Hadron-Quark Phase Transition Chemical Potential via Astronomical Observation

We investigate the chemical potential and baryon number density of the hadron-quark phase transition in neutron star matter. The hadron matter is described with relativistic mean field theory, and the quark matter is described with the Dyson-Schwinger equation approach of QCD. In order to study the first-order phase transition, we develop the sound speed interpolation scheme to construct the equation of state in the middle density region where the hadron phase and quark phase coexist. The phase transition chemical potential is constrained with the maximum mass, the tidal deformability and the radius of neutrons stars. And the most probable value of the phase transition chemical potential is found.Comment: 20 pages, 11 figures, 2 tables. Extension of arXiv:1903.12336. Contribution to the Proceedings of the CUSTIPEN Workshop on the EOS of Dense Neutron-Rich Matter in the Era of Gravitational-Wave Astronomy. One Figure, some discussions and References adde

On Exploring Undetermined Relationships for Visual Relationship Detection

In visual relationship detection, human-notated relationships can be regarded as determinate relationships. However, there are still large amount of unlabeled data, such as object pairs with less significant relationships or even with no relationships. We refer to these unlabeled but potentially useful data as undetermined relationships. Although a vast body of literature exists, few methods exploit these undetermined relationships for visual relationship detection. In this paper, we explore the beneficial effect of undetermined relationships on visual relationship detection. We propose a novel multi-modal feature based undetermined relationship learning network (MF-URLN) and achieve great improvements in relationship detection. In detail, our MF-URLN automatically generates undetermined relationships by comparing object pairs with human-notated data according to a designed criterion. Then, the MF-URLN extracts and fuses features of object pairs from three complementary modals: visual, spatial, and linguistic modals. Further, the MF-URLN proposes two correlated subnetworks: one subnetwork decides the determinate confidence, and the other predicts the relationships. We evaluate the MF-URLN on two datasets: the Visual Relationship Detection (VRD) and the Visual Genome (VG) datasets. The experimental results compared with state-of-the-art methods verify the significant improvements made by the undetermined relationships, e.g., the top-50 relation detection recall improves from 19.5% to 23.9% on the VRD dataset

Incentivizing Users of Data Centers Participate in The Demand Response Programs via Time-Varying Monetary Rewards

Demand response is widely employed by today's data centers to reduce energy consumption in response to the increasing of electricity cost. To incentivize users of data centers participate in the demand response programs, i.e., breaking the "split incentive" hurdle, some prior researches propose market-based mechanisms such as dynamic pricing and static monetary rewards. However, these mechanisms are either intrusive or unfair. In this paper, we use time-varying rewards to incentivize users, who have flexible deadlines and are willing to trading performance degradation for monetary rewards, grant time-shifting of their requests. With a game-theoretic framework, we model the game between a single data center and its users. Further, we extend our design via integrating it with two other emerging practical demand response strategies: server shutdown and local renewable energy generation. With real-world data traces, we show that a DC with our design can effectively shed its peak electricity load and overall electricity cost without reducing its profit, when comparing it with the current practice where no incentive mechanism is established

Instance Search via Instance Level Segmentation and Feature Representation

Instance search is an interesting task as well as a challenging issue due to the lack of effective feature representation. In this paper, an instance level feature representation built upon fully convolutional instance-aware segmentation is proposed. The feature is ROI-pooled from the segmented instance region. So that instances in various sizes and layouts are represented by deep features in uniform length. This representation is further enhanced by the use of deformable ResNeXt blocks. Superior performance is observed in terms of its distinctiveness and scalability on a challenging evaluation dataset built by ourselves. In addition, the proposed enhancement on the network structure also shows superior performance on the instance segmentation task

Preparing remotely two instances of quantum state

In this short note, we propose a scheme, in which two instances of an equatorial state (or a polar state) can be remotely prepared in one-shot operation to different receivers with prior entanglement and 1 bit of broadcasting. The trade-off curve between the amount of entanglement and the achievable fidelity is derived.Comment: 7 pages, 1 figur

Cyclic Quantum Dilogarithm and Shift Operator

{}From the cyclic quantum dilogarithm the shift operator is constructed with $q$ is a root of unit and the representation is given for the current algebra introduced by Faddeev $et ~al$. It is shown that the theta-function is factorizable also in this case by using the star-square equation of the Baxter-Bazhanov model.Comment: 9 pages, latex, no figure

Remarks on the Star-Triangle Relation in the Baxter-Bazhanov Model

In this letter we show that the restricted star-triangle relation introduced by Bazhanov and Baxter can be obtained either from the star-triangle relation of chiral Potts model or from the star-square relation which is proposed by Kashaev $et ~al$ and give a response of the guess which is suggested by Bazhanov and Baxter in Ref. \cite{b2}.Comment: 6 pages, latex file, AS-ITP-94-3

Collective Shape-Phases of Interacting Fermion Systems

A microscopic theory is presented for identifying shape-phase structures and transitions in interacting fermion systems. The method provides a microscopic description for collective shape-phases, and reveals detailed dependence of such shape-phases on microscopic interaction strengths. The theory is generally applicable to fermion systems such as nuclei, quarks, and in particular trapped cold atoms, where shape-phases may be observed and investigated in a controlled manner.Comment: 4 pages, 6 figure

Revisiting the Equation of State of Hybrid Stars in the Dyson-Schwinger Equation Approach to QCD

We investigate the equation of state(EoS) and the effect of the hadron-quark phase transition of strong interaction matter in compact stars. The hadron matter is described with the relativistic mean field theory,and the quark matter is described with the Dyson-Schwinger equation approach of QCD. The complete EoS of the hybrid star matter is constructed with not only the Gibbs construction but also the 3-window interpolation. The mass-radius relation of hybrid stars is also investigated. We find that, although the EoSs of both the hadron matter with hyperon and $\Delta$-baryon and the quark matter are generally softer than that of the nucleon matter, the 3-window interpolation construction may provide an EoS stiff enough for a hybrid star with mass exceeding 2$M_{\odot}^{}$ and, in turn, solve the so called "hyperon puzzle".Comment: 19 pages, 27 figures, Completely a new appearance comparing the last version (with great extension