arXiv subjects

Cong Chen

Publications and source records attributed to Cong Chen.

At least 109 records · Page 6Linked to original sources

arXiv2020

Pricing Multi-Interval Dispatch under Uncertainty Part II: Generalization and Performance

Pricing multi-interval economic dispatch of electric power under operational uncertainty is considered in this two-part paper. Part I investigates dispatch-following incentives for generators under the locational marginal pricing (LMP) and temporal locational marginal pricing (TLMP) policies. Extending the theoretical results developed in Part I, Part II evaluates a broader set of performance measures under a general network model. For networks with power flow constraints, TLMP is shown to have an energy-congestion-ramping price decomposition. Under the one-shot dispatch and pricing model, this decomposition leads to a nonnegative merchandising surplus equal to the sum of congestion and ramping surpluses. It is also shown that, comparing with LMP, TLMP imposes a penalty on generators with limited ramping capabilities, thus giving incentives for generators to reveal their ramping limits truthfully and improve their ramping capacities. Several benchmark pricing mechanisms are evaluated under the rolling-window dispatch and pricing models. The performance measures considered are the level of out-of-the-market uplifts, the revenue adequacy of the system operator, consumer payment, generator profit, level of discriminative payment, and price volatility.

eess.SY↗

arXiv2020

Graphyne as a second-order and real Chern topological insulator in two dimensions

Higher-order topological phases and real topological phases are two emerging topics in topological states of matter, which have been attracting considerable research interest. However, it remains a challenge to find realistic materials that can realize these exotic phases. Here, based on first-principles calculations and theoretical analysis, we identify graphyne, the representative of the graphyne-family carbon allotropes, as a two-dimensional (2D) second-order topological insulator and a real Chern insulator. We show that graphyne has a direct bulk band gap at the three $M$ points, forming three valleys. The bulk bands feature a double band inversion, which is characterized by the nontrivial real Chern number enabled by the spacetime-inversion symmetry. The real Chern number is explicitly evaluated by both the Wilson-loop method and the parity approach, and we show that it dictates the existence of Dirac type edge bands and the topological corner states. Furthermore, we find that the topological phase transition in graphyne from the second-order topological insulator to a trivial insulator is mediated by a 2D Weyl semimetal phase. The robustness of the corner states against symmetry breaking and possible experimental detection methods are discussed.

cond-mat.mtrl-sci↗

arXiv2020

The curse of rationality in sequential scheduling games

Despite the emphases on computability issues in research of algorithmic game theory, the limited computational capacity of players have received far less attention. This work examines how different levels of players' computational ability (or "rationality") impact the outcomes of sequential scheduling games. Surprisingly, our results show that a lower level of rationality of players may lead to better equilibria. More specifically, we characterize the sequential price of anarchy (SPoA) under two different models of bounded rationality, namely, players with $k$-lookahead and simple-minded players. The model in which players have $k$-lookahead interpolates between the "perfect rationality" ($k=n-1$) and "online greedy" ($k=0$). Our results show that the inefficiency of equilibria (SPoA) increases in $k$ the degree of lookahead: $\mathrm{SPoA} = O (k^2)$ for two machines and $\mathrm{SPoA} = O\left(2^k \min \{mk,n\}\right)$ for $m$ machines, where $n$ is the number of players. Moreover, when players are simple-minded, the SPoA is exactly $m$, which coincides with the performance of "online greedy".

cs.GT↗

arXiv2020

Sequential Solutions in Machine Scheduling Games

We consider the classical machine scheduling, where $n$ jobs need to be scheduled on $m$ machines, and where job $j$ scheduled on machine $i$ contributes $p_{i,j}\in \mathbb{R}$ to the load of machine $i$, with the goal of minimizing the makespan, i.e., the maximum load of any machine in the schedule. We study inefficiency of schedules that are obtained when jobs arrive sequentially one by one, and the jobs choose themselves the machine on which they will be scheduled, aiming at being scheduled on a machine with small load. We measure the inefficiency of a schedule as the ratio of the makespan obtained in the worst-case equilibrium schedule, and of the optimum makespan. This ratio is known as the \emph{sequential price of anarchy}. We also introduce two alternative inefficiency measures, which allow for a favorable choice of the order in which the jobs make their decisions. As our first result, we disprove the conjecture of Hassin and Yovel claiming that the sequential price of anarchy for $m=2$ machines is at most 3. We show that the sequential price of anarchy grows at least linearly with the number $n$ of players, i.e., we show that $SPoA = Ω(n)$. Furthermore, we show that there exists an order of the jobs, resulting in makespan that is at most linearly larger than the optimum makespan. To the end, we show that if an authority can change the order of the jobs adaptively to the decisions made by the jobs so far (but cannot influence the decisions of the jobs), then there exists an adaptive ordering in which the jobs end up in an optimum schedule.

cs.GT↗

arXiv2020

Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection

This paper focuses on Semi-Supervised Object Detection (SSOD). Knowledge Distillation (KD) has been widely used for semi-supervised image classification. However, adapting these methods for SSOD has the following obstacles. (1) The teacher model serves a dual role as a teacher and a student, such that the teacher predictions on unlabeled images may be very close to those of student, which limits the upper-bound of the student. (2) The class imbalance issue in SSOD hinders an efficient knowledge transfer from teacher to student. To address these problems, we propose a novel method Temporal Self-Ensembling Teacher (TSE-T) for SSOD. Differently from previous KD based methods, we devise a temporally evolved teacher model. First, our teacher model ensembles its temporal predictions for unlabeled images under stochastic perturbations. Second, our teacher model ensembles its temporal model weights with the student model weights by an exponential moving average (EMA) which allows the teacher gradually learn from the student. These self-ensembling strategies increase data and model diversity, thus improving teacher predictions on unlabeled images. Finally, we use focal loss to formulate consistency regularization term to handle the data imbalance problem, which is a more efficient manner to utilize the useful information from unlabeled images than a simple hard-thresholding method which solely preserves confident predictions. Evaluated on the widely used VOC and COCO benchmarks, the mAP of our method has achieved 80.73% and 40.52% on the VOC2007 test set and the COCO2014 minval5k set respectively, which outperforms a strong fully-supervised detector by 2.37% and 1.49%. Furthermore, our method sets the new state-of-the-art in SSOD on VOC2007 test set which outperforms the baseline SSOD method by 1.44%. The source code of this work is publicly available at http://github.com/syangdong/tse-t.

cs.CV↗

arXiv2020

The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Study

Face recognition has become essential in our daily lives as a convenient and contactless method of accurate identity verification. Process such as identity verification at automatic border control gates or the secure login to electronic devices are increasingly dependant on such technologies. The recent COVID-19 pandemic have increased the value of hygienic and contactless identity verification. However, the pandemic led to the wide use of face masks, essential to keep the pandemic under control. The effect of wearing a mask on face recognition in a collaborative environment is currently sensitive yet understudied issue. We address that by presenting a specifically collected database containing three session, each with three different capture instructions, to simulate realistic use cases. We further study the effect of masked face probes on the behaviour of three top-performing face recognition systems, two academic solutions and one commercial off-the-shelf (COTS) system.

cs.CV↗

arXiv2020

Universal Approach to Magnetic Second-Order Topological Insulator

We propose a universal practical approach to realize magnetic second-order topological insulator (SOTI) materials, based on properly breaking the time reversal symmetry in conventional (first-order) topological insulators. The approach works for both three dimensions (3D) and two dimensions (2D), and is particularly suitable for 2D, where it can be achieved by coupling a quantum spin Hall insulator with a magnetic substrate. Using first-principles calculations, we predict bismuthene on EuO(111) surface as the first realistic system for a 2D magnetic SOTI. We explicitly demonstrate the existence of the protected corner states. Benefited from the large spin-orbit coupling and sizable magnetic proximity effect, these corner states are located in a boundary gap $\sim 83$ meV, hence can be readily probed in experiment. By controlling the magnetic phase transition, a topological phase transition between a first-order TI and a SOTI can be simultaneously achieved in the system. The effect of symmetry breaking, the connection with filling anomaly, and the experimental detection are discussed.

cond-mat.mtrl-sci↗

arXiv2020

Nonsymmorphic nodal-line metals in the two-dimensional rare earth monochalcogenides MX (M = Sc, Y; X = S, Se, Te)

We predict a new family of two-dimensional (2D) rare earth monochalcogenide materials MX (M = Sc, Y; X = S, Se, Te). Based on first-principles calculations, we confirm their stability and systematically investigate their mechanical properties. We find that these materials are metallic and interestingly, they possess nodal lines in the low-energy band structure surrounding the whole Brillouin zone, protected by nonsymmorphic crystal symmetries in the absence of spin-orbit coupling (SOC). SOC opens small energy gaps at the nodal line, except for two high-symmetry points, at which fourfold degenerate 2D spin-orbit Dirac points are obtained. We show that these topological band features are robust under uniaxial and biaxial strains, but can be lifted by the shear strain. We also investigate the optical conductivities of these materials, and show that the transformation of the band structure under strain can be inferred from the optical absorption spectrum. Our work reveals a new family of 2D topological metal materials with interesting mechanical and electronic properties, which will facilitate the study of nonsymmorphic symmetry enabled nodal features in 2D.

cond-mat.mtrl-sci↗

arXiv2020

Fermi liquid behavior and colossal magnetoresistance in layered MoOCl2

A characteristic of a Fermi liquid is the T^2 dependence of its resistivity, sometimes referred to as the Baber law. However, for most metals, this behavior is only restricted to very low temperatures, usually below 20 K. Here, we experimentally demonstrate that for the single-crystal van der Waals layered material MoOCl2, the Baber law holds in a wide temperature range up to ~120 K, indicating that the electron-electron scattering plays a dominant role in this material. Combining with the specific heat measurement, we find that the modified Kadowaki-Woods ratio of the material agrees well with many other strongly correlated metals. Furthermore, in the magneto-transport measurement, a colossal magneto-resistance is observed, which reaches ~350% at 9 T and displays no sign of saturation. With the help of first-principles calculations, we attribute this behavior to the presence of open orbits on the Fermi surface. We also suggest that the dominance of electron-electron scattering is related to an incipient charge density wave state of the material. Our results establish MoOCl2 as a strongly correlated metal and shed light on the underlying physical mechanism, which may open a new path for exploring the effects of electron-electron interaction in van der Waals layered structures.

cond-mat.mtrl-sci↗

arXiv2020

HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression

The emerging edge computing has promoted immense interests in compacting a neural network without sacrificing much accuracy. In this regard, low-rank tensor decomposition constitutes a powerful tool to compress convolutional neural networks (CNNs) by decomposing the 4-way kernel tensor into multi-stage smaller ones. Building on top of Tucker-2 decomposition, we propose a generalized Higher Order Tucker Articulated Kernels (HOTCAKE) scheme comprising four steps: input channel decomposition, guided Tucker rank selection, higher order Tucker decomposition and fine-tuning. By subjecting each CONV layer to HOTCAKE, a highly compressed CNN model with graceful accuracy trade-off is obtained. Experiments show HOTCAKE can compress even pre-compressed models and produce state-of-the-art lightweight networks.

cs.LG↗

arXiv2020

Two-dimensional second-order topological insulator in graphdiyne

A second-order topological insulator (SOTI) in $d$ spatial dimensions features topologically protected gapless states at its $(d-2)$-dimensional boundary at the intersection of two crystal faces, but is gapped otherwise. As a novel topological state, it has been attracting great interest, but it remains a challenge to identify a realistic SOTI material in two dimensions (2D). Here, based on combined first-principles calculations and theoretical analysis, we reveal the already experimentally synthesized 2D material graphdiyne as the first realistic example of a 2D SOTI, with topologically protected 0D corner states. The role of crystalline symmetry, the robustness against symmetry-breaking, and the possible experimental characterization are discussed. Our results uncover a hidden topological character of graphdiyne and promote it as a concrete material platform for exploring the intriguing physics of higher-order topological phases.

cond-mat.mes-hall↗

arXiv2020

Kernelized Support Tensor Train Machines

Tensor, a multi-dimensional data structure, has been exploited recently in the machine learning community. Traditional machine learning approaches are vector- or matrix-based, and cannot handle tensorial data directly. In this paper, we propose a tensor train (TT)-based kernel technique for the first time, and apply it to the conventional support vector machine (SVM) for image classification. Specifically, we propose a kernelized support tensor train machine that accepts tensorial input and preserves the intrinsic kernel property. The main contributions are threefold. First, we propose a TT-based feature mapping procedure that maintains the TT structure in the feature space. Second, we demonstrate two ways to construct the TT-based kernel function while considering consistency with the TT inner product and preservation of information. Third, we show that it is possible to apply different kernel functions on different data modes. In principle, our method tensorizes the standard SVM on its input structure and kernel mapping scheme. Extensive experiments are performed on real-world tensor data, which demonstrates the superiority of the proposed scheme under few-sample high-dimensional inputs.

cs.LG↗

arXiv2019

Nilpotent varieties of some finite dimensional restricted Lie algebras

In the late 1980s, A. Premet conjectured that the variety of nilpotent elements of any finite dimensional restricted Lie algebra over an algebraically closed field of characteristic $p>0$ is irreducible. This conjecture remains open, but it is known to hold for a large class of simple restricted Lie algebras, e.g. for Lie algebras of connected algebraic groups, and for Cartan series $W, S$ and $H$. In this thesis we start by proving that Premet's conjecture can be reduced to the semisimple case. The proof is straightforward. However, the reduction of the semisimple case to the simple case is very non-trivial in prime characteristic as semisimple Lie algebras are not always direct sums of simple ideals. Then we consider some semisimple restricted Lie algebras. Under the assumption that $p>2$, we prove that Premet's conjecture holds for the semisimple restricted Lie algebra whose socle involves the special linear Lie algebra $\mathfrak{sl}_2$ tensored by the truncated polynomial ring $k[X]/(X^{p})$. Then we extend this example to the semisimple restricted Lie algebra whose socle involves $S\otimes \mathcal{O}(m; \underline{1})$, where $S$ is any simple restricted Lie algebra such that $\text{ad} S=\text{Der} S$ and its nilpotent variety $\mathcal{N}(S)$ is irreducible, and $\mathcal{O}(m; \underline{1})=k[X_1, \dots, X_m]/(X_1^p, \dots, X_m^p)$ is the truncated polynomial ring in $m\geq 2$ variables. In the final chapter we assume that $p>3$. We confirm Premet's conjecture for the minimal $p$-envelope $W(1; n)_{p}$ of the Zassenhaus algebra $W(1; n)$ for all $n\geq 2$. This is the main result of the research paper [3] (see thesis) which was published in the Journal of Algebra and Its Applications.

math.RA↗

arXiv2019

Origin of Two Larmor Frequencies in the Coherent Spin Dynamics of Colloidal CdSe Quantum Dots Revealed by Controlled Charging

Coherent spin dynamics in colloidal CdSe quantum dots (QDs) typically show two spin components with different Larmor frequencies, whose origin is an open question. We exploit the photocharging approach to identify their origin and find that surface states play a key role in the appearance of the spin signals. By controlling the photocharging with electron or hole acceptors, we show that the specific spin component can be enhanced by the choice of acceptor type. In core/shell CdSe/ZnS QDs, the spin signals are significantly weaker. Our results exclude the neutral exciton as the spin origin and suggest that both Larmor frequencies are related to the coherent spin precession of electrons in photocharged QDs. The lower frequency is due to the electron confined in the middle of the QD, and the higher frequency to the electron additionally localized in the vicinity of the surface.

cond-mat.mes-hall↗

arXiv2019

Two-dimensional Weyl Half Semimetal and Tunable Quantum Anomalous Hall Effect in Monolayer PtCl$_{3}$

We propose a new topological quantum state of matter---the two-dimensional (2D) Weyl half semimetal (WHS), which features 2D Weyl points at Fermi level belonging to a single spin channel, such that the low-energy electrons are described by fully spin-polarized 2D Weyl fermions. We predict its realization in the ground state of monolayer PtCl$_3$. We show that the material is a half metal with an in-plane magnetization, and its Fermi surface consists of a pair of fully spin-polarized Weyl points protected by a mirror symmetry, which are robust against spin-orbit coupling. Remarkably, we show that the WHS state is a critical state at the topological phase transition between two quantum anomalous Hall insulator phases with opposite Chern numbers, such that a switching between quantum anomalous Hall states can be readily achieved by rotating the magnetization direction. Our findings demonstrate that WHS offers new opportunity to control the chiral edge channels, which will be useful for designing new topological electronic devices.

cond-mat.mtrl-sci↗

arXiv2019

A physical mechanism of heterogeneity in stem cell, cancer and cancer stem cell

Heterogeneity is ubiquitous in stem cells (SC), cancer cells (CS), and cancer stem cells (CSC). SC and CSC heterogeneity is manifested as diverse sub-populations with self-renewing and unique regeneration capacity. Moreover, the CSC progeny possesses multiple plasticity and cancerous characteristics. Many studies have demonstrated that cancer heterogeneity is one of the greatest obstacle for therapy. This leads to the incomplete anti-cancer therapies and transitory efficacy. Furthermore, numerous micro-metastasis leads to the wide spread of the tumor cells across the body which is the beginning of metastasis. The epigenetic processes (DNA methylation or histone remodification etc.) can provide a source for certain heterogeneity. In this study, we develop a mathematical model to quantify the heterogeneity of SC, CSC and cancer taking both genetic and epigenetic effects into consideration. We uncovered the roles and physical mechanisms of heterogeneity from the three aspects (SC, CSC and cancer). In the adiabatic regime (relatively fast regulatory binding and effective coupling among genes), seven native states (SC, CSC, Cancer, Premalignant, Normal, Lesion and Hyperplasia) emerge. In non-adiabatic regime (relatively slow regulatory binding and effective weak coupling among genes), multiple meta-stable SC, CS, CSC and differentiated states emerged which can explain the origin of heterogeneity. In other words, the slow regulatory binding mimicking the epigenetics can give rise to heterogeneity. Elucidating the origin of heterogeneity and dynamical interrelationship between intra-tumoral cells has clear clinical significance in helping to understand the cellular basis of treatment response, therapeutic resistance, and tumor relapse.

q-bio.MN↗

arXiv2018

Online scheduling of jobs with favorite machines

This work introduces a natural variant of the online machine scheduling problem on unrelated machines, which we refer to as the favorite machine model. In this model, each job has a minimum processing time on a certain set of machines, called favorite machines, and some longer processing times on other machines. This type of costs (processing times) arise quite naturally in many practical problems. In the online version, jobs arrive one by one and must be allocated irrevocably upon each arrival without knowing the future jobs. We consider online algorithms for allocating jobs in order to minimize the makespan. We obtain tight bounds on the competitive ratio of the greedy algorithm and characterize the optimal competitive ratio for the favorite machine model. Our bounds generalize the previous results of the greedy algorithm and the optimal algorithm for the unrelated machines and the identical machines. We also study a further restriction of the model, called the symmetric favorite machine model, where the machines are partitioned equally into two groups and each job has one of the groups as favorite machines. We obtain a 2.675-competitive algorithm for this case, and the best possible algorithm for the two machines case.

cs.DS↗

arXiv2018

Weyl-loop half metal in Li$_3$(FeO$_3$)$_2$

Nodal-line metals and semimetals, as interesting topological states of matter, have been mostly studied in nonmagnetic materials. Here, based on first-principles calculations and symmetry analysis, we predict that fully spin-polarized Weyl loops can be realized in the half metal state for the three-dimensional material Li$_3$(FeO$_3$)$_2$. We show that this material has a ferromagnetic ground state, and it is a half metal with only a single spin channel present near the Fermi level. The spin-up bands form two separate Weyl loops close to the Fermi level, which arise from band inversions and are protected by the glide mirror symmetry. One loop is of type-I, whereas the other loop is of hybrid type. Corresponding to these two loops in the bulk, on the (100) surface, there exist two fully spin-polarized drumheads of surface states within the surface projections of the loops. The effects of the electron correlation and the spin-orbit coupling, as well as the possible hourglass Weyl chains in the nonmagnetic state have been discussed. The realization of fully spin-polarized Weyl-loop fermions in the bulk and drumhead fermions on the surface for a half metal may generate promising applications in spintronics.

cond-mat.mtrl-sci↗