15,847 research outputs found
Probing triple-Higgs productions via decay channel at a 100 TeV hadron collider
The quartic self-coupling of the Standard Model Higgs boson can only be
measured by observing the triple-Higgs production process, but it is
challenging for the Large Hadron Collider (LHC) Run 2 or International Linear
Collider (ILC) at a few TeV because of its extremely small production rate. In
this paper, we present a detailed Monte Carlo simulation study of the
triple-Higgs production through gluon fusion at a 100 TeV hadron collider and
explore the feasibility of observing this production mode. We focus on the
decay channel , investigating
detector effects and optimizing the kinematic cuts to discriminate the signal
from the backgrounds. Our study shows that, in order to observe the Standard
Model triple-Higgs signal, the integrated luminosity of a 100 TeV hadron
collider should be greater than ab. We also explore the
dependence of the cross section upon the trilinear () and quartic
() self-couplings of the Higgs. We find that, through a search in
the triple-Higgs production, the parameters and can be
restricted to the ranges and , respectively. We also
examine how new physics can change the production rate of triple-Higgs events.
For example, in the singlet extension of the Standard Model, we find that the
triple-Higgs production rate can be increased by a factor of .Comment: 33 pages, 11 figures, added references, corrected typos, improved
text, affiliation is changed. This is the publication versio
Convergence Theory of Learning Over-parameterized ResNet: A Full Characterization
ResNet structure has achieved great empirical success since its debut. Recent
work established the convergence of learning over-parameterized ResNet with a
scaling factor on the residual branch where is the network
depth. However, it is not clear how learning ResNet behaves for other values of
. In this paper, we fully characterize the convergence theory of gradient
descent for learning over-parameterized ResNet with different values of .
Specifically, with hiding logarithmic factor and constant coefficients, we show
that for gradient descent is guaranteed to converge to the
global minma, and especially when the convergence is irrelevant
of the network depth. Conversely, we show that for ,
the forward output grows at least with rate in expectation and then the
learning fails because of gradient explosion for large . This means the
bound is sharp for learning ResNet with arbitrary depth.
To the best of our knowledge, this is the first work that studies learning
ResNet with full range of .Comment: 31 page
Determination of Lysophosphatidic Acids by Capillary Electrophoresis with Indirect Ultraviolet Detection
Lysophosphatidic acid (LPA) is the simplest form of lysophospholipid. Molecular species of LPA have been identified as the potent components in the ovarian cancer activation factor. The elevated plasma LPAs may be used as potential biomarkers for the early detection of ovarian cancer. This paper is the first report on the quantitative analysis of molecular species of LPA using capillary electrophoresis. In this work, the separation of LPAs was achieved within 14 min in an adenosine monophosphate-borate–methanol–water solution, and the measurement was accomplished by indirect UV detection. With LPA (D) as internal standard, the method had linear calibration ranges for LPAs from 2.8 to 75 μM. The detection limits for various molecular species of LPA were from 1.2 to 2.3 μM by the pressure injection at 3.45 kPa for 5 s. The method had been applied to serum fortified with LPA (S), LPA (O), LPA (P), and LPA (M) and the recoveries ranged from 83 to 112%
Performance of desiccant enhanced evaporative cooling system based on high-low control
Desiccant enhanced evaporative cooling system is a sustainable air-conditioning (A/C) system which deals the latent load and sensible load separately by a dehumidifier and an evaporative cooler. A LDD-RIEC system consists of a liquid desiccant dehumidifier (LDD) and a regenerative indirect evaporative cooler (RIEC) were investigated. The LDD-RIEC system is characterized by low energy consumption compared with conventional mechanical cooling system, but the main shortcoming is the high dependency on ambient air conditions. To maintain stable indoor temperature, a control scheme is essential. However, very limited research work regarding control strategy can be found in open literatures. In this paper, a novel controller named high-low (H-L) control is proposed. Multi-speed technology is utilized for primary air fan and secondary air fan operating either at high speed or at low speed. The annual performance of a LDD-RIEC system is simulated in Hong Kong, a typical hot and humid region. The results indicate that H-L control is effective in maintaining stable indoor thermal comfort with temperature fluctuation from 24 °C to 27 °C for 99% of time
Towards Successful Cloud Ordering Service
Background: The rise of cloud services has led to a drastic growth of e-commerce and a greater investment in development of new cloud services systems by related industries. For SaaS developers, it is important to understand customer needs and make use of available resources at as early as the system design and development stage. Objectives: This study integrates E-commerce Systems (ECS) Success model and Importance-Performance Analysis (IPA) into empirical research of the critical factors for cloud ordering system success. Methods/Approach: A survey research is conducted to collect data on customer perceptions of the importance and performance of each attribute of the particular cloud ordering service. The sample is further divided according to the degree of use of online shopping into high-usage users and low-usage users in order to explore their views regarding the system and generate adequate coping strategies. Results: Developers of online ordering systems can refer to the important factors obtained in this study when planning strategies of product/service improvement. Conclusions: The approach proposed in this study can also be applied to evaluation of other kinds of cloud services systems
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