Renormalization group improved predictions for ttˉW±t\bar{t}W^\pm production at hadron colliders

We study the factorization and resummation of the $t\bar{t}W^\pm$ production at hadron colliders. The cross section in the threshold limit can be factorized into a convolution of hard and soft functions and parton distribution functions with the soft-collinear effective theory. We calculate the next-to-leading order soft function for the associated production of the heavy quark pair and colorless particle, and we perform the resummation calculation with the next-to-next-to-leading logarithms accuracy. Our results show that the resummation effects reduce the dependence of the cross section on the scales significantly and increase the total cross section by $7-13\%$ compared with NLO QCD results.Comment: 23 pages, 7 figures and 2 tables; final version in PR

Threshold resummation for the production of a color sextet (antitriplet) scalar at the LHC

We investigate threshold resummation effects in the production of a color sextet (antitriplet) scalar at next-to-next-to-leading logarithmic (NNLL) order at the LHC in the frame of soft-collinear effective theory. We show the total cross section and the rapidity distribution with NLO+NNLL accuracy, and we compare them with the NLO results. Besides, we use recent dijet data at the LHC to give the constraints on the couplings between the colored scalars and quarks.Comment: 21 pages,9 figures,3 tables; Version published in EPJ

Signature of the γ\gamma+jet and dijet production mediated by an excited quark with QCD next-to-leading order accuracy at the LHC

We present a detailed study of the production and decay of the excited quark at the QCD next-to-leading order (NLO) level at the Large Hadron Collider, using the narrow width approximation and helicity amplitudes method. We find that the QCD NLO corrections can tighten the constraints on the model parameters and reduce the scale dependencies of the total cross sections. We discuss the signals of the excited quark production with decay mode $q^{\ast}\rightarrow q\gamma$ and $q^{\ast}\rightarrow qg$, and present several important kinematic distributions. Moreover, we give the upper limits of the excited quark excluded mass range and the allowed parameter space for the coupling constants and the excited quark mass.Comment: 20 pages, 13 figures; version published in PR

Janus monolayers of transition metal dichalcogenides.

Structural symmetry-breaking plays a crucial role in determining the electronic band structures of two-dimensional materials. Tremendous efforts have been devoted to breaking the in-plane symmetry of graphene with electric fields on AB-stacked bilayers or stacked van der Waals heterostructures. In contrast, transition metal dichalcogenide monolayers are semiconductors with intrinsic in-plane asymmetry, leading to direct electronic bandgaps, distinctive optical properties and great potential in optoelectronics. Apart from their in-plane inversion asymmetry, an additional degree of freedom allowing spin manipulation can be induced by breaking the out-of-plane mirror symmetry with external electric fields or, as theoretically proposed, with an asymmetric out-of-plane structural configuration. Here, we report a synthetic strategy to grow Janus monolayers of transition metal dichalcogenides breaking the out-of-plane structural symmetry. In particular, based on a MoS2 monolayer, we fully replace the top-layer S with Se atoms. We confirm the Janus structure of MoSSe directly by means of scanning transmission electron microscopy and energy-dependent X-ray photoelectron spectroscopy, and prove the existence of vertical dipoles by second harmonic generation and piezoresponse force microscopy measurements

Effects of Thyroxine Exposure on Osteogenesis in Mouse Calvarial Pre-Osteoblasts

The incidence of craniosynostosis is one in every 1,800-2500 births. The gene-environment model proposes that if a genetic predisposition is coupled with environmental exposures, the effects can be multiplicative resulting in severely abnormal phenotypes. At present, very little is known about the role of gene-environment interactions in modulating craniosynostosis phenotypes, but prior evidence suggests a role for endocrine factors. Here we provide a report of the effects of thyroid hormone exposure on murine calvaria cells. Murine derived calvaria cells were exposed to critical doses of pharmaceutical thyroxine and analyzed after 3 and 7 days of treatment. Endpoint assays were designed to determine the effects of the hormone exposure on markers of osteogenesis and included, proliferation assay, quantitative ALP activity assay, targeted qPCR for mRNA expression of Runx2, Alp, Ocn, and Twist1, genechip array for 28,853 targets, and targeted osteogenic microarray with qPCR confirmations. Exposure to thyroxine stimulated the cells to express ALP in a dose dependent manner. There were no patterns of difference observed for proliferation. Targeted RNA expression data confirmed expression increases for Alp and Ocn at 7 days in culture. The genechip array suggests substantive expression differences for 46 gene targets and the targeted osteogenesis microarray indicated 23 targets with substantive differences. 11 gene targets were chosen for qPCR confirmation because of their known association with bone or craniosynostosis (Col2a1, Dmp1, Fgf1, 2, Igf1, Mmp9, Phex, Tnf, Htra1, Por, and Dcn). We confirmed substantive increases in mRNA for Phex, FGF1, 2, Tnf, Dmp1, Htra1, Por, Igf1 and Mmp9, and substantive decreases for Dcn. It appears thyroid hormone may exert its effects through increasing osteogenesis. Targets isolated suggest a possible interaction for those gene products associated with calvarial suture growth and homeostasis as well as craniosynostosis. © 2013 Cray et al

ROAM: memory-efficient large DNN training via optimized operator ordering and memory layout

As deep learning models continue to increase in size, the memory requirements for training have surged. While high-level techniques like offloading, recomputation, and compression can alleviate memory pressure, they also introduce overheads. However, a memory-efficient execution plan that includes a reasonable operator execution order and tensor memory layout can significantly increase the models' memory efficiency and reduce overheads from high-level techniques. In this paper, we propose ROAM which operates on computation graph level to derive memory-efficient execution plan with optimized operator order and tensor memory layout for models. We first propose sophisticated theories that carefully consider model structure and training memory load to support optimization for large complex graphs that have not been well supported in the past. An efficient tree-based algorithm is further proposed to search task divisions automatically, along with delivering high performance and effectiveness to solve the problem. Experiments show that ROAM achieves a substantial memory reduction of 35.7%, 13.3%, and 27.2% compared to Pytorch and two state-of-the-art methods and offers a remarkable 53.7x speedup. The evaluation conducted on the expansive GPT2-XL further validates ROAM's scalability