arXiv subjects

Sen Li

Publications and source records attributed to Sen Li.

86 records · Page 5Linked to original sources

arXiv2019

Phenomenological Single-Particle Green's Function for the Pseudogap and Superconducting Phases of High-T$_c$ Cuprates

We present a phenomenological Green's function to characterize the superconducting and pseudogap phases of the cuprates based on a microscopic theory of doped Mott insulators. In this framework, the "Fermi arc" and "kink" phenomena observed by angle-resolved photoemission spectroscopy (ARPES) experiments in the pseudogap phase can be systematically explained as a function of doping, which is further connected to the two-gap feature in the superconducting phase with dichotomy between the nodal and antinodal physics. We demonstrate that a phase-string-induced fractionalization plays the key role in giving rise to such a peculiar Green's function with a unique two-component structure.

cond-mat.str-el↗

arXiv2019

Transactive Energy System: Market-Based Coordination of Distributed Energy Resources

Distributed energy resources (DER) provide significant value for renewable energy integration in modern power grids. However, unlocking this value requires complex design and coordination. This paper focuses on the emerging {\em transactive energy systems}, which draw tools and principles from economics to design the coordination strategies for DERs. The concept of transactive energy system broadly captures a huge body of literature, and many of them are closely related but fundamentally different. This gives rise to the following questions: how to formally compare different transactive energy systems and their proposed approaches? How to choose the right transactive energy system to formulate a given problem? What tools are available in the literature for each class of transactive energy systems? In this paper, we answer these questions by synthesizing a unifying framework for a large class of problems studied in the literature. The framework consists of preferences, control decision, information structure and solution concept. These elements are important in identifying and distinguishing various transactive energy systems in the literature. We employ the proposed framework to analyze a few important class of transactive energy systems. Their connections and differences are discussed, and available tools for each class of problems are surveyed.

math.OC↗

arXiv2019

Anomalous doping evolution of nodal dispersion revealed by in-situ ARPES on continuously doped cuprates

We study the systematic doping evolution of nodal dispersions by in-situ angle-resolved photoemission spectroscopy on the continuously doped surface of a high-temperature superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$. We reveal that the nodal dispersion has three segments separated by two kinks, located at ~10 meV and roughly 70 meV, respectively. The three segments have different band velocities and different doping dependence. In particular, the velocity of the high-energy segment increases monotonically as the doping level decreases and can even surpass the bare band velocity. We propose that electron fractionalization is a possible cause for this anomalous nodal dispersion and may even play a key role in the understanding of exotic properties of cuprates.

cond-mat.supr-con↗

arXiv2019

Regulating TNCs: Should Uber and Lyft Set Their Own Rules?

We evaluate the impact of three proposed regulations of transportation network companies (TNCs) like Uber, Lyft and Didi: (1) a minimum wage for drivers, (2) a cap on the number of drivers or vehicles, and (3) a per-trip congestion tax. The impact is assessed using a queuing theoretic equilibrium model which incorporates the stochastic dynamics of the app-based ride-hailing matching platform, the ride prices and driver wages established by the platform, and the incentives of passengers and drivers. We show that a floor placed under driver earnings pushes the ride-hailing platform to hire more drivers and offer more rides, at the same time that passengers enjoy faster rides and lower total cost, while platform rents are reduced. Contrary to standard economic theory, enforcing a minimum wage for drivers benefits both drivers and passengers, and promotes the efficiency of the entire system. This surprising outcome holds for almost all model parameters, and it occurs because the wage floors curbs TNC labor market power. In contrast to a wage floor, imposing a cap on the number of vehicles hurts drivers, because the platform reaps all the benefits of limiting supply. The congestion tax has the expected impact: fares increase, wages and platform revenue decrease. We also construct variants of the model to briefly discuss platform subsidy, platform competition, and autonomous vehicles.

math.OC↗

arXiv2019

Optimal Resource Procurement and the Price of Causality

This paper studies the problem of procuring diverse resources in a forward market to cover a set $\bf{E}$ of uncertain demand signals $\bf{e}$. We consider two scenarios: (a) $\bf{e}$ is revealed all at once by an oracle (b) $\bf{e}$ reveals itself causally. Each scenario induces an optimal procurement cost. The ratio between these two costs is defined as the {\em price of causality}. It captures the additional cost of not knowing the future values of the uncertain demand signal. We consider two application contexts: procuring energy reserves from a forward capacity market, and purchasing virtual machine instances from a cloud service. An upper bound on the price of causality is obtained, and the exact price of causality is computed for some special cases. The algorithmic basis for all these computations is set containment linear programming. A mechanism is proposed to allocate the procurement cost to consumers who in aggregate produce the demand signal. We show that the proposed cost allocation is fair, budget-balanced, and respects the cost-causation principle. The results are validated through numerical simulations.

math.OC↗

arXiv2019

DADA-2000: Can Driving Accident be Predicted by Driver Attention? Analyzed by A Benchmark

Driver attention prediction is currently becoming the focus in safe driving research community, such as the DR(eye)VE project and newly emerged Berkeley DeepDrive Attention (BDD-A) database in critical situations. In safe driving, an essential task is to predict the incoming accidents as early as possible. BDD-A was aware of this problem and collected the driver attention in laboratory because of the rarity of such scenes. Nevertheless, BDD-A focuses the critical situations which do not encounter actual accidents, and just faces the driver attention prediction task, without a close step for accident prediction. In contrast to this, we explore the view of drivers' eyes for capturing multiple kinds of accidents, and construct a more diverse and larger video benchmark than ever before with the driver attention and the driving accident annotation simultaneously (named as DADA-2000), which has 2000 video clips owning about 658,476 frames on 54 kinds of accidents. These clips are crowd-sourced and captured in various occasions (highway, urban, rural, and tunnel), weather (sunny, rainy and snowy) and light conditions (daytime and nighttime). For the driver attention representation, we collect the maps of fixations, saccade scan path and focusing time. The accidents are annotated by their categories, the accident window in clips and spatial locations of the crash-objects. Based on the analysis, we obtain a quantitative and positive answer for the question in this paper.

cs.CV↗

arXiv2018

Difference in charge and spin dynamics in a quantum dot-lead coupled system

We analyze time evolution of charge and spin states in a quantum dot coupled to an electric reservoir. Utilizing high-speed single-electron detection, we focus on dynamics induced by the first-order tunneling. We find that there is a difference between the spin and the charge relaxation: the former appears slower than the latter. The difference depends on the Fermi occupation factor and the spin relaxation becomes slower when the energy level of the quantum dot is lowered. We explain this behavior by a theory which includes the first-order tunneling processes. We conduct detailed comparison of the experiment and the theory with changing the energy of the quantum dot levels, and the theory can reproduce the experimental results.

cond-mat.mes-hall↗

arXiv2018

Connections between Mean-Field Game and Social Welfare Optimization

This paper studies the connection between a class of mean-field games and a social welfare optimization problem. We consider a mean-field game in function spaces with a large population of agents, and each agent seeks to minimize an individual cost function. The cost functions of different agents are coupled through a mean-field term that depends on the mean of the population states. We show that although the mean-field game is not a potential game, under some mild condition the $ε$-Nash equilibrium of the mean-field game coincides with the optimal solution to a social welfare optimization problem, and this is true even when the individual cost functions are non-convex. The connection enables us to evaluate and promote the efficiency of the mean-field equilibrium. In addition, it also leads to several important implications on the existence, uniqueness, and computation of the mean-field equilibrium. Numerical results are presented to validate the solution, and examples are provided to show the applicability of the proposed approach.

math.OC↗

arXiv2016

On Social Optima of Non-Cooperative Mean Field Games

This paper studies the connections between mean-field games and the social welfare optimization problems. We consider a mean field game in functional spaces with a large population of agents, each of which seeks to minimize an individual cost function. The cost functions of different agents are coupled through a mean field term that depends on the mean of the population states. We show that under some mild conditions any $ε$-Nash equilibrium of the mean field game coincides with the optimal solution to a convex social welfare optimization problem. The results are proved based on a general formulation in the functional spaces and can be applied to a variety of mean field games studied in the literature. Our result also implies that the computation of the mean field equilibrium can be cast as a convex optimization problem, which can be efficiently solved by a decentralized primal dual algorithm. Numerical simulations are presented to demonstrate the effectiveness of the proposed approach.

math.OC↗

arXiv2016

Multi-Stage Pricing for Coordination of Thermostatically Controlled Loads: A Dynamic Stackelberg Game Approach

This paper focuses on multi-stage coordination for a population of thermostatically controlled loads (TCL). Each load maximizes the individual utility in response to an energy price, while the coordinator determines the price to maximize the social welfare subject to a peak energy constraint. The coordination problem is formulated as a dynamic Stackelberg game. The Stackelberg solution is derived using an indirect approach: we first obtain an upper bound of the Stackelberg game, then we prove that this upper bound is attainable. Sufficient conditions for the optimal solution are characterized. Based on these conditions, a pricing algorithm with guaranteed convergence is developed to compute the Stackelberg solution employing the monotonicity of the user responses. Our control strategy is validated using real market data and weather information, and realistic simulation results are presented to demonstrate the effectiveness of the proposed control framework.

math.OC↗

arXiv2016

Constrained Linear Quadratic Stackelberg Games with Applications in Demand Response

This paper studies a class of dynamic Stackelberg games under open-loop information structure with constrained linear agent dynamics and quadratic utility functions. We show two important properties for this class of dynamic Stackelberg games. First, we prove that under mild conditions, the optimal control of individual agents at the solution of the Stackelberg game coincides with the solution to the team problem, where all agents cooperatively achieve the coordinator's objective. Second, we show that the the agent's control at each time step is non-increasing with respect to the coordinator's control at the same step, and non-decreasing with respect the coordinator's control at other steps. These properties enable us to develop an algorithm that converges to the globally optimal solution to the dynamic Stackelberg game. The proposed algorithm is illustrated by two demand response applications: the coordination of electric vehicle charging and the coordination of thermostatically controlled loads. Numerical examples are shown to demonstrate the effectiveness of the proposed approach.

math.OC↗

arXiv2015

Uniform-Price Mechanism Design for a Large Population of Dynamic Agents

This paper focuses on the coordination of a large population of dynamic agents with private information over multiple periods. Each agent maximizes the individual utility, while the coordinator determines the market rule to achieve group objectives. The coordination problem is formulated as a dynamic mechanism design problem. A mechanism is proposed based on the competitive equilibrium of the large population game. We derive the conditions for the general nonlinear dynamic systems under which the proposed mechanism is incentive compatible and can implement the social choice function in $ε$-Nash equilibrium. In addition, we show that for linear quadratic problems with bounded parameters, the proposed mechanism can maximize the social welfare subject to a total resource constraint in $ε$-dominant strategy equilibrium.

eess.SY↗

arXiv2015

Formation of Long Single Quantum Dots in High Quality InSb Nanowires Grown by Molecular Beam Epitaxy

We report on realization and transport spectroscopy study of single quantum dots (QDs) made from InSb nanowires grown by molecular beam epitaxy (MBE). The nanowires employed are 50-80 nm in diameter and the QDs are defined in the nanowires between the source and drain contacts on a Si/SiO$_2$ substrate. We show that highly tunable QD devices can be realized with the MBE-grown InSb nanowires and the gate-to-dot capacitance extracted in the many-electron regimes is scaled linearly with the longitudinal dot size, demonstrating that the devices are of single InSb nanowire QDs even with a longitudinal size of ~700 nm. In the few-electron regime, the quantum levels in the QDs are resolved and the Landé g-factors extracted for the quantum levels from the magnetotransport measurements are found to be strongly level-dependent and fluctuated in a range of 18-48. A spin-orbit coupling strength is extracted from the magnetic field evolutions of a ground state and its neighboring excited state in an InSb nanowire QD and is on the order of ~300 $μ$eV. Our results establish that the MBE-grown InSb nanowires are of high crystal quality and are promising for the use in constructing novel quantum devices, such as entangled spin qubits, one-dimensional Wigner crystals and topological quantum computing devices.

cond-mat.mes-hall↗

arXiv2015

A Mechanism Design Approach for Coordination of Thermostatically Controlled Loads

This paper focuses on the coordination of a population of thermostatically controlled loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the device bidding and market clearing strategies to motivate self-interested users to realize efficient energy allocation subject to a peak energy constraint. This coordination problem is formulated as a mechanism design problem, and we propose a mechanism to implement the social choice function in dominant strategy equilibrium. The proposed mechanism consists of a novel bidding and clearing strategy that incorporates the internal dynamics of TCLs in the market mechanism design, and we show it can realize the team optimal solution. A learning scheme is proposed to address the unknown load model parameters. Numerical simulations are performed to validate the effectiveness of the proposed coordination framework.

math.OC↗