Steady and dynamic magnetic phase transitions in interacting quantum dots arrays coupled with leads

We apply the Hubbard model, non-equilibrium Green's function (NEGF) theory, exact diagonalization (ED) and the hierarchical equations of motion (HEOM) method to investigate abundant magnetic phase transitions in the 1D interacting quantum dots arrays (QDA) sandwiched by non-interaction leads. The spin polarization phase transitions are firstly studied with a mean-field approximation. The many-body calculation of the ED method is then used to verify such transitions. We find with the weak device-leading couplings, the anti-ferromagnetic (AF) state only exists in the uniform odd-numbered QDA or the staggered-hopping QDA systems. With increasing the coupling strength or the bias potentials, there exists the magnetism-to non-magnetism phase transition. With the spin-resolved HEOM method we also investigate the detailed dynamic phase transition process of these lead-QDA-lead systems.Comment: 17 pages, 6 figure

AdaLomo: Low-memory Optimization with Adaptive Learning Rate

Large language models have achieved remarkable success, but their extensive parameter size necessitates substantial memory for training, thereby setting a high threshold. While the recently proposed low-memory optimization (LOMO) reduces memory footprint, its optimization technique, akin to stochastic gradient descent, is sensitive to hyper-parameters and exhibits suboptimal convergence, failing to match the performance of the prevailing optimizer for large language models, AdamW. Through empirical analysis of the Adam optimizer, we found that, compared to momentum, the adaptive learning rate is more critical for bridging the gap. Building on this insight, we introduce the low-memory optimization with adaptive learning rate (AdaLomo), which offers an adaptive learning rate for each parameter. To maintain memory efficiency, we employ non-negative matrix factorization for the second-order moment estimation in the optimizer state. Additionally, we suggest the use of a grouped update normalization to stabilize convergence. Our experiments with instruction-tuning and further pre-training demonstrate that AdaLomo achieves results on par with AdamW, while significantly reducing memory requirements, thereby lowering the hardware barrier to training large language models.Comment: Fix some typ

A system dynamics model for urban taxi price simulation

Urban taxi services have been developing year on year, playing an increasingly important role in the economy and the transportation markets of each city. This increases interest in measuring their performance. This paper analysed the relationship among the four stakeholders (including administrative department, operational companies, taxi drivers and customers) for urban taxi passenger transport system in China, and applied System Dynamics (SD) model to explore the dynamic characteristics of urban taxi price system. The main achievements of this paper are as follows, firstly, this paper adopted stakeholder mapping to describe the relationships among the four stakeholders. Then analysed the causal flow diagrams and the different variables of urban taxi passenger transport system operation, and presented the SD model, which considers factors that affect the taxi operation. With the combination of taxi operation data of Harbin city, we simulated eleven urban taxi operation scenarios and proposed kinds of suggestions to improve urban taxi passenger transport system operation, which can provide a good basis for recommending policy decisions for urban taxi market

Fiscal Incentives and Local Tax Competition: Evidence from China

This paper explores how fiscal incentives affect capital tax decisions by local governments in the Chinese context. We develop a model in which local governments, facing different fiscal incentives, compete for mobile capital over corporate taxes. The key prediction of the model, borne out in data from Chinese cities over the years 2004-2013, is that an increase in the local corporate income tax-sharing ratio, proxying local fiscal incentives, makes city governments’ horizontal tax reactions stronger. Our results contribute to the fiscal federalism literature by providing evidence in support of the argument that fiscal incentives faced by local governments significantly shape their policy choices. Additionally, we provide explicit evidence on local tax competition within provinces in China, which has long been regarded as one of the driving forces of China’s rapid economic growth

Numerical Investigation on the Impact of Exergy Analysis and Structural Improvement in Power Plant Boiler through Co-Simulation

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)In current power station boilers, fuel burns at a low temperature, which results in low exergy efficiency. This research combined the second law of t with the boiler structure to maximize the efficiency of a 350 MW power plant boiler. A three-dimensional simulation of the combustion process at the power plant boiler is performed. A one-dimensional simulation model of the boiler is then constructed to calculate the combustion exergy loss, heat transfer exergy loss, and boiler exergy efficiency. Under the principle of high-temperature air combustion technologies, this paper also proposes a new structure and improved operating parameters to improve the exergy efficiency of boilers by reducing the heat exchange area of the economizer and increasing the heat exchange area of the air preheater. Simulation results show that the exergy efficiency of the boiler increased from 47.29% to 48.35% through the modified model. The simulation outcomes can instruct future optimal boiler design and controls.Peer reviewe