Creep motion of a domain wall in the two-dimensional random-field Ising model with a driving field

With Monte Carlo simulations, we study the creep motion of a domain wall in the two-dimensional random-field Ising model with a driving field. We observe the nonlinear fieldvelocity relation, and determine the creep exponent {\mu}. To further investigate the universality class of the creep motion, we also measure the roughness exponent {\zeta} and energy barrier exponent {\psi} from the zero-field relaxation process. We find that all the exponents depend on the strength of disorder.Comment: 5 pages, 4 figure

Corrections to scaling in the dynamic approach to the phase transition with quenched disorder

With dynamic Monte Carlo simulations, we investigate the continuous phase transition in the three-dimensional three-state random-bond Potts model. We propose a useful technique to deal with the strong corrections to the dynamic scaling form. The critical point, static exponents $\beta$ and $\nu$, and dynamic exponent $z$ are accurately determined. Particularly, the results support that the exponent $\nu$ satisfies the lower bound $\nu \geqslant 2/d$.Comment: 10 pages, 6 figures, 2 table

Dynamic effect of overhangs and islands at the depinning transition in two-dimensional magnets

With the Monte Carlo methods, we systematically investigate the short-time dynamics of domain-wall motion in the two-dimensional random-field Ising model with a driving field ?DRFIM?. We accurately determine the depinning transition field and critical exponents. Through two different definitions of the domain interface, we examine the dynamics of overhangs and islands. At the depinning transition, the dynamic effect of overhangs and islands reaches maximum. We argue that this should be an important mechanism leading the DRFIM model to a different universality class from the Edwards-Wilkinson equation with quenched disorderComment: 9 pages, 6 figure

Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050

As China’s rapid urbanization continues and urban dwellers become more affluent, energy use in buildings is expected to grow. To understand how this growth can be slowed, we explore four scenarios for Chinese buildings, ranging from a high-energy-demand scenario with no new energy policies to lowest energy demand under a techno-economic-potential scenario that assumes full deployment of cost-effective efficient and renewable technologies by 2050. We show that, in the high energy demand scenario, building energy demand has an average annual growth rate of about 2.8%, with slower growth rates in the other three scenarios. In all scenarios, CO2 emissions grow slower than energy, with building CO2 peaking around 2045 in the high energy demand scenario, and as early as 2030 in the techno-economic-potential scenario. We show that although various technological solutions, systems and practices can be very effective in minimizing building energy use, rigorous policies are needed to overcome multiple implementation barriers

Energy and CO2 implications of decarbonization strategies for China beyond efficiency: Modeling 2050 maximum renewable resources and accelerated electrification impacts

Energy efficiency has played an important role in helping China achieve its domestic and international energy and climate change mitigation targets, but more significant near-term actions to decarbonize are needed to help China and the world meet the Paris Agreement goals. Accelerating electrification and maximizing supply-side and demand-side renewable adoption are two recent strategies being considered in China, but few bottom-up modeling studies have evaluated the potential near-term impacts of these strategies across multiple sectors. To fill this research gap, we use a bottom-up national end-use model that integrates energy supply and demand systems and conduct scenario analysis to evaluate even lower CO2 emissions strategies and subsequent pathways for China to go beyond cost-effective efficiency and fuel switching. We find that maximizing non-conventional electric and renewable technologies can help China peak its national CO2 emissions as early as 2025, with significant additional CO2 emission reductions on the order of 7 Gt CO2 annually by 2050. Beyond potential CO2 reductions from power sector decarbonization, significant potential lies in fossil fuel displaced by renewable heat in industry. These results suggest accelerating the utilization of non-conventional electric and renewable technologies present additional CO2 reduction opportunities for China, but new policies and strategies are needed to change technology choices in the demand sectors. Managing the pace of electrification in tandem with the pace of decarbonization of the power sector will also be crucial to achieving CO2 reductions from the power sector in a scenario of increased electrification

Impact of edge-removal on the centrality betweenness of the best spreaders

The control of epidemic spreading is essential to avoid potential fatal consequences and also, to lessen unforeseen socio-economic impact. The need for effective control is exemplified during the severe acute respiratory syndrome (SARS) in 2003, which has inflicted near to a thousand deaths as well as bankruptcies of airlines and related businesses. In this article, we examine the efficacy of control strategies on the propagation of infectious diseases based on removing connections within real world airline network with the associated economic and social costs taken into account through defining appropriate quantitative measures. We uncover the surprising results that removing less busy connections can be far more effective in hindering the spread of the disease than removing the more popular connections. Since disconnecting the less popular routes tend to incur less socio-economic cost, our finding suggests the possibility of trading minimal reduction in connectivity of an important hub with efficiencies in epidemic control. In particular, we demonstrate the performance of various local epidemic control strategies, and show how our approach can predict their cost effectiveness through the spreading control characteristics.Comment: 11 pages, 4 figure

Understanding and Improving the Wang-Landau Algorithm

We present a mathematical analysis of the Wang-Landau algorithm, prove its convergence, identify sources of errors and strategies for optimization. In particular, we found the histogram increases uniformly with small fluctuation after a stage of initial accumulation, and the statistical error is found to scale as $\sqrt{\ln f}$ with the modification factor $f$. This has implications for strategies for obtaining fast convergence.Comment: 4 pages, 2 figures, to appear in Phys. Rev.

Critical domain-wall dynamics of model B

With Monte Carlo methods, we simulate the critical domain-wall dynamics of model B, taking the two-dimensional Ising model as an example. In the macroscopic short-time regime, a dynamic scaling form is revealed. Due to the existence of the quasi-random walkers, the magnetization shows intrinsic dependence on the lattice size $L$. A new exponent which governs the $L$-dependence of the magnetization is measured to be $\sigma=0.243(8)$.Comment: 10pages, 4 figure