Soft gluon resummation in the signal-background interference process of gg(→h∗)→ZZgg(\to h^*) \to ZZ

We present a precise theoretical prediction for the signal-background interference process of $gg(\to h^*) \to ZZ$, which is useful to constrain the Higgs boson decay width and to measure Higgs couplings to the SM particles. The approximate NNLO $K$-factor is in the range of $2.05-2.45$ ($1.85-2.25$), depending on $M_{ZZ}$, at the 8 (13) TeV LHC. And the soft gluon resummation can increase the approximate NNLO result by about $10\%$ at both the 8 TeV and 13 TeV LHC. The theoretical uncertainties including the scale, uncalculated multi-loop amplitudes of the background and PDF$+\alpha_s$ are roughly $\mathcal{O}(10\%)$ at ${\rm NNLL'}$. We also confirm that the approximate $K$-factors in the interference and the pure signal processes are the same.Comment: 18 pages, 9 figures; v2 published in JHE

Renormalization-group improved predictions for Higgs boson production at large pTp_T

We study the next-to-next-to-leading logarithmic order resummation for the large $p_T$ Higgs boson production at the LHC in the framework of soft-collinear effective theory. We find that the resummation effects reduce the scale uncertainty significantly and decrease the QCD NLO results by about $11\%$ in the large $p_T$ region. The finite top quark mass effects and the effects of the NNLO singular terms are also discussed.Comment: 31 pages, 17 figures, version published in Phys.Rev.

Projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks

We study projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks. We relax some limitations of previous work, where projective-anticipating and projective-lag synchronization can be achieved only on two coupled chaotic systems. In this paper, we can realize projective-anticipating and projective-lag synchronization on complex dynamical networks composed by a large number of interconnected components. At the same time, although previous work studied projective synchronization on complex dynamical networks, the dynamics of the nodes are coupled partially linear chaotic systems. In this paper, the dynamics of the nodes of the complex networks are time-delayed chaotic systems without the limitation of the partial-linearity. Based on the Lyapunov stability theory, we suggest a generic method to achieve the projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random dynamical networks and find both the existence and sufficient stability conditions. The validity of the proposed method is demonstrated and verified by examining specific examples using Ikeda and Mackey-Glass systems on Erdos-Renyi networks.Comment: 14 pages, 6 figure

Functional renormalization group and variational Monte Carlo studies of the electronic instabilities in graphene near 1/4 doping

We study the electronic instabilities of near 1/4 electron doped graphene using the functional renormalization group (FRG) and variational Monte-Carlo method. A modified FRG implementation is utilized to improve the treatment of the von Hove singularity. At 1/4 doping the system is a chiral spin density wave state exhibiting the anomalous quantized Hall effect, or equivalently a Chern insulator. When the doping deviates from 1/4, the $d_{x^2-y^2}+i d_{xy}$ Cooper pairing becomes the leading instability. Our results suggest near 1/4 electron or hole doped graphene is a fertile playground for the search of Chern insulators and superconductors.Comment: 7 pages, 8 figures, with technical details, published versio

Transverse momentum resummation for color sextet and antitriplet scalar production at the LHC

We study the factorization and resummation of the transverse momentum spectrum of the color sextet and antitriplet scalars produced at the LHC based on soft-collinear effective theory. Compared to Z boson and Higgs production, a soft function is required to account for the soft gluon emission from the final-state colored scalar. The soft function is calculated at the next-to-leading order, and the resummation is performed at the approximate next-to-next-to-leading logarithmic accuracy. The non-perturbative effects and PDF uncertainties are also discussed.Comment: 20 pages, 7 figure

Transverse-Momentum Resummation for Gauge Boson Pair Production at the Hadron Collider

We perform the transverse-momentum resummation for $W^{+}W^{-}$, $ZZ$, and $W^{\pm}Z$ pair productions at the next-to-next-to-leading logarithmic accuracy using soft-collinear effective theory for $\sqrt{S}=8 \text{TeV}$ and $\sqrt{S}=14 \text{TeV}$ at the LHC, respectively. Especially, this is the first calculation of $W^{\pm}Z$ transverse-momentum resummation. We also include the non-perturbative effects and discussions on the PDF uncertainties. Comparing with the next-to-leading logarithmic results, the next-to-next-to-leading logarithmic resummation can reduce the dependence of the transverse-momentum distribution on the factorization scales significantly. Finally, we find that our numerical results are consistent with data measured by CMS collaboration for the $ZZ$ production, which have been only reported by the LHC experiments for the unfolded transverse-momentum distribution of the gauge boson pair production so far, within theoretical and experimental uncertainties.Comment: 22 pages, 6 figures, re-versio

Effects of degree distribution in mutual synchronization of neural networks

We study the effects of the degree distribution in mutual synchronization of two-layer neural networks. We carry out three coupling strategies: large-large coupling, random coupling, and small-small coupling. By computer simulations and analytical methods, we find that couplings between nodes with large degree play an important role in the synchronization. For large-large coupling, less couplings are needed for inducing synchronization for both random and scale-free networks. For random coupling, cutting couplings between nodes with large degree is very efficient for preventing neural systems from synchronization, especially when subnetworks are scale-free.Comment: 5 pages, 4 figure