Impact of top-Higgs couplings on di-Higgs production at future colliders

Measuring the Higgs-self coupling is one of the most crucial goals of the future colliders, such as the LHC Run-II and the ILC-based photon collider. Since the new physics can affects the di-Higgs production not only from the Higgs self-coupling but also from the top-Higgs coupling, we investigate the di-Higgs production in the presence of the non-standard top-Higgs coupling at the LHC and ILC-based photon collider given the recent Higgs data. Due to the changed interference behaviors of the top quark loops with itself or $W$ boson loops, we find that the cross section of di-Higgs production at the LHC-14 TeV and ILC-500 GeV can be respectively enhanced up to nearly 3 and 2 times the SM predictions within 2$\sigma$ Higgs data allowed parameter region.Comment: 16 pages, references and discussions added, accepted by JHE

Higgs boson production and decay at e+e−e^{+}e^{-} colliders as a probe of the Left-Right twin Higgs model

In the framework of the Left-Right twin Higgs (LRTH) model, we consider the constrains from the latest search for high-mass dilepton resonances at the LHC and find that the heavy neutral boson $Z_H$ is excluded with mass below 2.76 TeV. Under these constrains, we study the Higgs-Gauge coupling production processes $e^{+}e^{-}\rightarrow ZH$, $e^{+}e^{-}\rightarrow \nu_{e}\bar{\nu_{e}}H$ and $e^{+}e^{-}\rightarrow e^{+}e^{-}H$, top quark Yukawa coupling production process $e^{+}e^{-}\rightarrow t\bar{t}H$, Higgs self-couplings production processes $e^{+}e^{-}\rightarrow ZHH$ and $e^{+}e^{-}\rightarrow \nu_{e}\bar{\nu_{e}}HH$ at $e^{+}e^{-}$ colliders. Besides, we study the major decay modes of the Higgs boson, namely $h\rightarrow f\bar{f}$($f=b,c,\tau$), $VV^{*}(V=W, Z)$, $gg$, $\gamma\gamma$. We find that the LRTH effects are sizable so that the Higgs boson processes at $e^{+}e^{-}$ collider can be a sensitive probe for the LRTH model.Comment: Final version to appear in Nucl.Phys.

Context-Aware Zero-Shot Recognition

We present a novel problem setting in zero-shot learning, zero-shot object recognition and detection in the context. Contrary to the traditional zero-shot learning methods, which simply infers unseen categories by transferring knowledge from the objects belonging to semantically similar seen categories, we aim to understand the identity of the novel objects in an image surrounded by the known objects using the inter-object relation prior. Specifically, we leverage the visual context and the geometric relationships between all pairs of objects in a single image, and capture the information useful to infer unseen categories. We integrate our context-aware zero-shot learning framework into the traditional zero-shot learning techniques seamlessly using a Conditional Random Field (CRF). The proposed algorithm is evaluated on both zero-shot region classification and zero-shot detection tasks. The results on Visual Genome (VG) dataset show that our model significantly boosts performance with the additional visual context compared to traditional methods