arXiv subjects

Jianwei Huang

Publications and source records attributed to Jianwei Huang.

At least 91 records · Page 5Linked to original sources

arXiv2021

Flatband-Induced Itinerant Ferromagnetism in RbCo$_2$Se$_2$

$A$Co$_2$Se$_2$ ($A$=K,Rb,Cs) is a homologue of the iron-based superconductor, $A$Fe$_2$Se$_2$. From a comprehensive study of RbCo$_2$Se$_2$ via measurements of magnetization, transport, neutron diffraction, angle-resolved photoemission spectroscopy, and first-principle calculations, we identify a ferromagnetic order accompanied by an orbital-dependent spin-splitting of the electronic dispersions. Furthermore, we identify the ordered moment to be dominated by a $d_{x^2-y^2}$ flatband near the Fermi level, which exhibits the largest spin splitting across the ferromagnetic transition, suggesting an itinerant origin of the ferromagnetism. In the broader context of the iron-based superconductors, we find this $d_{x^2-y^2}$ flatband to be a common feature in the band structures of both iron-chalcogenides and iron-pnictides, accessible via heavy electron doping.

cond-mat.supr-con↗

arXiv2021

Momentum-Resolved Visualization of Electronic Evolution in Doping a Mott Insulator

High temperature superconductivity in cuprates arises from doping a parent Mott insulator by electrons or holes. A central issue is how the Mott gap evolves and the low-energy states emerge with doping. Here we report angle-resolved photoemission spectroscopy measurements on a cuprate parent compound by sequential in situ electron doping. The chemical potential jumps to the bottom of the upper Hubbard band upon a slight electron doping, making it possible to directly visualize the charge transfer band and the full Mott gap region. With increasing doping, the Mott gap rapidly collapses due to the spectral weight transfer from the charge transfer band to the gapped region and the induced low-energy states emerge in a wide energy range inside the Mott gap. These results provide key information on the electronic evolution in doping a Mott insulator and establish a basis for developing microscopic theories for cuprate superconductivity.

cond-mat.str-el↗

arXiv2021

Non-Thermal Emergence of an Orbital-Selective Mott Phase in FeTe$_{1-x}$Se$_x$

Electronic correlation is of fundamental importance to high temperature superconductivity. Iron-based superconductors are believed to possess moderate correlation strength, which combined with their multi-orbital nature makes them a fascinating platform for the emergence of exotic phenomena. A particularly striking form is the emergence of an orbital selective Mott phase, where the localization of a subset of orbitals leads to a drastically reconstructed Fermi surface. Here, we report spectroscopic evidence of the reorganization of the Fermi surface from FeSe to FeTe as Se is substituted by Te. We uncover a particularly transparent way to visualize the localization of the $d_{xy}$ electron orbital through the suppression of its hybridization with the more coherent $d$ electron orbitals, which leads to a redistribution of the orbital-dependent spectral weight near the Fermi level. These noteworthy features of the Fermi surface are accompanied by a divergent behavior of a band renormalization in the $d_{xy}$ orbital. All of our observations are further supported by our theoretical calculations to be salient spectroscopic signatures of such a non-thermal evolution from a strongly correlated metallic phase towards an orbital-selective Mott phase in FeTe$_{1-x}$Se$_x$ as Se concentration is reduced.

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arXiv2021

Practical Speech Re-use Prevention in Voice-driven Services

Voice-driven services (VDS) are being used in a variety of applications ranging from smart home control to payments using digital assistants. The input to such services is often captured via an open voice channel, e.g., using a microphone, in an unsupervised setting. One of the key operational security requirements in such setting is the freshness of the input speech. We present AEOLUS, a security overlay that proactively embeds a dynamic acoustic nonce at the time of user interaction, and detects the presence of the embedded nonce in the recorded speech to ensure freshness. We demonstrate that acoustic nonce can (i) be reliably embedded and retrieved, and (ii) be non-disruptive (and even imperceptible) to a VDS user. Optimal parameters (acoustic nonce's operating frequency, amplitude, and bitrate) are determined for (i) and (ii) from a practical perspective. Experimental results show that AEOLUS yields 0.5% FRR at 0% FAR for speech re-use prevention upto a distance of 4 meters in three real-world environments with different background noise levels. We also conduct a user study with 120 participants, which shows that the acoustic nonce does not degrade overall user experience for 94.16% of speech samples, on average, in these environments. AEOLUS can therefore be used in practice to prevent speech re-use and ensure the freshness of speech input.

cs.SD↗

arXiv2020

Selfish Caching Games on Directed Graphs

Caching networks can reduce the routing costs of accessing contents by caching contents closer to users. However, cache nodes may belong to different entities and behave selfishly to maximize their own benefits, which often lead to performance degradation for the overall network. While there has been extensive literature on allocating contents to caches to maximize the social welfare, the analysis of selfish caching behaviors remains largely unexplored. In this paper, we model the selfish behaviors of cache nodes as selfish caching games on arbitrary directed graphs with heterogeneous content popularity. We study the existence of a pure strategy Nash equilibrium (PSNE) in selfish caching games, and analyze its efficiency in terms of social welfare. We show that a PSNE does not always exist in arbitrary-topology caching networks. However, if the network does not have a mixed request loop, i.e., a directed loop in which each edge is traversed by at least one content request, we show that a PSNE always exists and can be found in polynomial time. Furthermore, we can avoid mixed request loops by properly choosing request forwarding paths. We then show that the efficiency of Nash equilibria, captured by the price of anarchy (PoA), can be arbitrarily poor if we allow arbitrary content request patterns, and adding extra cache nodes can make the PoA worse, i.e., cache paradox happens. However, when cache nodes have homogeneous request patterns, we show that the PoA is bounded even allowing arbitrary topologies. We further analyze the selfish caching games for cache nodes with limited computational capabilities, and show that an approximate PSNE exists with bounded PoA in certain cases of interest. Simulation results show that increasing the cache capacity in the network improves the efficiency of Nash equilibria, while adding extra cache nodes can degrade the efficiency of Nash equilibria.

cs.GT↗

arXiv2020

Incentive Mechanism Design for Distributed Coded Machine Learning

A distributed machine learning platform needs to recruit many heterogeneous worker nodes to finish computation simultaneously. As a result, the overall performance may be degraded due to straggling workers. By introducing redundancy into computation, coded machine learning can effectively improve the runtime performance by recovering the final computation result through the first $k$ (out of the total $n$) workers who finish computation. While existing studies focus on designing efficient coding schemes, the issue of designing proper incentives to encourage worker participation is still under-explored. This paper studies the platform's optimal incentive mechanism for motivating proper workers' participation in coded machine learning, despite the incomplete information about heterogeneous workers' computation performances and costs. A key contribution of this work is to summarize workers' multi-dimensional heterogeneity as a one-dimensional metric, which guides the platform's efficient selection of workers under incomplete information with a linear computation complexity. Moreover, we prove that the optimal recovery threshold $k$ is linearly proportional to the participator number $n$ if we use the widely adopted MDS (Maximum Distance Separable) codes for data encoding. We also show that the platform's increased cost due to incomplete information disappears when worker number is sufficiently large, but it does not monotonically decrease in worker number.

cs.GT↗

arXiv2020

Origin of the Electronic Structure in Single-Layer FeSe/SrTiO3 Films

The accurate theoretical description of the underlying electronic structures is essential for understanding the superconducting mechanism of iron-based superconductors. Compared to bulk FeSe, the superconducting single-layer FeSe/SrTiO3 films exhibit a distinct electronic structure consisting of only electron Fermi pockets, due to the formation of a new band gap at the Brillouin zone (BZ) corners and an indirect band gap between the BZ center and corners. Although intensive studies have been carried out, the origin of such a distinct electronic structure and its connection to bulk FeSe remain unclear. Here we report a systematic study on the temperature evolution of the electronic structure in single-layer FeSe/SrTiO3 films by angle-resolved photoemission spectroscopy. A temperature-induced electronic phase transition was clearly observed at 200 K, above which the electronic structure of single-layer FeSe/SrTiO3 films restored to that of bulk FeSe, characterized by the closing of the new band gap and the vanishing of the indirect band gap. Moreover, the interfacial charge transfer effect induced band shift of ~ 60 meV was determined for the first time. These observations not only show the first direct evidence that the electronic structure of single-layer FeSe/SrTiO3 films originates from bulk FeSe through a combined effect of an electronic phase transition and an interfacial charge transfer, but also provide a quantitative basis for theoretical models in describing the electronic structure and understanding the superconducting mechanism in single-layer FeSe/SrTiO3 films.

cond-mat.supr-con↗

arXiv2020

Cost-Effective Federated Learning Design

Federated learning (FL) is a distributed learning paradigm that enables a large number of devices to collaboratively learn a model without sharing their raw data. Despite its practical efficiency and effectiveness, the iterative on-device learning process incurs a considerable cost in terms of learning time and energy consumption, which depends crucially on the number of selected clients and the number of local iterations in each training round. In this paper, we analyze how to design adaptive FL that optimally chooses these essential control variables to minimize the total cost while ensuring convergence. Theoretically, we analytically establish the relationship between the total cost and the control variables with the convergence upper bound. To efficiently solve the cost minimization problem, we develop a low-cost sampling-based algorithm to learn the convergence related unknown parameters. We derive important solution properties that effectively identify the design principles for different metric preferences. Practically, we evaluate our theoretical results both in a simulated environment and on a hardware prototype. Experimental evidence verifies our derived properties and demonstrates that our proposed solution achieves near-optimal performance for various datasets, different machine learning models, and heterogeneous system settings.

cs.LG↗

arXiv2020

On the Privacy and Integrity Risks of Contact-Tracing Applications

Smartphone-based contact-tracing applications are at the epicenter of the global fight against the Covid-19 pandemic. While governments and healthcare agencies are eager to mandate the deployment of such applications en-masse, they face increasing scrutiny from the popular press, security companies, and human rights watch agencies that fear the exploitation of these technologies as surveillance tools. Finding the optimal balance between community safety and privacy has been a challenge, and strategies to address these concerns have varied among countries. This paper describes two important attacks that affect a broad swath of contact-tracing applications. The first, referred to as contact-isolation attack, is a user-privacy attack that can be used to identify potentially infected patients in your neighborhood. The second is a contact-pollution attack that affects the integrity of contact tracing applications by causing them to produce a high volume of false-positive alerts. We developed prototype implementations and evaluated both attacks in the context of the DP-3T application framework, but these vulnerabilities affect a much broader class of applications. We found that both attacks are feasible and realizable with a minimal attacker work factor. We further conducted an impact assessment of these attacks by using a simulation study and measurements from the SafeGraph database. Our results indicate that attacks launched from a modest number (on the order of 10,000) of monitoring points can effectively decloak between 5-40\% of infected users in a major metropolis, such as Houston.

cs.CR↗

arXiv2020

Economics of Mobile Data Trading Market

To exploit users' heterogeneous data demands, several mobile network operators worldwide have launched the mobile data trading markets, where users can trade mobile data quota with each other. In this paper, we aim to understand the importance of data trading market (DTM) by studying the users' operator selection and trading decisions, and analyzing the operator's profit maximizing strategy. We model the interactions between the mobile operator and the users as a three-stage Stackelberg game. In Stage I, the operator chooses the operation fee imposed on sellers to maximize its profit. In Stage II, each user chooses his operator. In Stage III, each DTM user chooses his trading decisions. We derive the closed-form expression of the unique Nash equilibrium (NE) in Stages II and III, where every user proposes the same price such that the total demand matches with the total supply. We further show that the Stage I's problem is convex and compute the optimal operation fee. Our analysis and numerical results show that an operator with a small initial market share can increase its profit by proposing a DTM, which is in line with the real-world situation in Hong Kong.

cs.GT↗

arXiv2020

Spectroscopic Evidence of Superconductivity Pairing at 83 K in Single-Layer FeSe/SrTiO3 Films

Single-layer FeSe films grown on the SrTiO3 substrate (FeSe/STO) have attracted much attention because of their possible record-high superconducting critical temperature Tc and distinct electronic structures in iron-based superconductors. However, it has been under debate on how high its Tc can really reach due to the inconsistency of the results obtained from the transport, magnetic and spectroscopic measurements. Here we report spectroscopic evidence of superconductivity pairing at 83 K in single-layer FeSe/STO films. By preparing high-quality single-layer FeSe/STO films, we observe for the first time strong superconductivity-induced Bogoliubov back-bending bands that extend to rather high binding energy ~100 meV by high-resolution angle-resolved photoemission measurements. The Bogoliubov back-bending band provides a new definitive benchmark of superconductivity pairing that is directly observed up to 83 K in the single-layer FeSe/STO films. Moreover, we find that the superconductivity pairing state can be further divided into two temperature regions of 64-83 K and below 64 K. We propose the 64-83 K region may be attributed to superconductivity fluctuation while the region below 64 K corresponds to the realization of long-range superconducting phase coherence. These results indicate that either Tc as high as 83 K is achievable in iron-based superconductors, or there is a pseudogap formation from superconductivity fluctuation in single-layer FeSe/STO films.

cond-mat.supr-con↗

arXiv2020

Contract-based Time-of-use Pricing for Energy Storage Investment

Time-of-use (ToU) pricing is widely used by the electricity utility. A carefully designed ToU pricing can incentivize end-users' energy storage deployment, which helps shave the system peak load and reduce the system social cost. However, the optimization of ToU pricing is highly non-trivial, and an improperly designed ToU pricing may lead to storage investments that are far from the social optimum. In this paper, we aim at designing the optimal ToU pricing, jointly considering the social cost of the utility and the storage investment decisions of users. Since the storage investment costs are users' private information, we design low-complexity contracts to elicit the necessary information and induce the proper behavior of users' storage investment. The proposed contracts only specify three contract items, which guides users of arbitrarily many different storage-cost types to invest in full, partial, or no storage capacity with respect to their peak demands. Our contracts can achieve the social optimum when the utility knows the aggregate demand of each storage-cost type (but not the individual user's type). When the utility only knows the distribution of each storage-cost type's demand, our contracts can lead to a near-optimal solution. The gap with the social optimum is as small as 1.5% based on the simulations using realistic data. We also show that the proposed contracts can reduce the system social cost by over 30%, compared with no storage investment benchmark.

eess.SY↗

arXiv2020

Electronic Evolution from the Parent Mott Insulator to a Superconductor in Lightly Hole-Doped Bi2Sr2CaCu2O8+delta

High temperature superconductivity in cuprates is realized by doping the Mott insulator with charge carriers. A central issue is how such an insulating state can evolve into a conducting or superconducting state when charge carriers are introduced. Here, by in situ vacuum annealing and Rb deposition on the Bi2Sr2Ca0.6Dy0.4Cu2O8+delta (Bi2212) sample surface to push its doping level continuously from deeply underdoped (Tc=25 K, doping level p-0.066) to the near zero doping parent Mott insulator, angle-resolved photoemission spectroscopy measurements are carried out to observe the detailed electronic structure evolution in lightly hole-doped region for the first time. Our results indicate that the chemical potential lies at about 1 eV above the charge transfer band for the parent state at zero doping which is quite close to the upper Hubbard band. With increasing hole doping, the chemical potential moves continuously towards the charge transfer band and the band structure evolution exhibits a rigid band shift-like behavior. When the chemical potential approaches the charge transfer band at a doping level of -0.05, the nodal spectral weight near the Fermi level increases, followed by the emergence of the coherent quasiparticle peak and the insulator-superconductor transition. Our observations provide key insights in understanding the insulator-superconductor transition in doping the parent cuprate compound and for establishing related theories.

cond-mat.supr-con↗

arXiv2020

Spectroscopic Evidence of Bilayer Splitting and Interlayer Pairing in an Iron Based Superconductor

In high temperature cuprate superconductors, the interlayer coupling between the CuO$_2$ planes plays an important role in dictating superconductivity, as indicated by the sensitive dependence of the critical temperature (T$_C$) on the number of CuO$_2$ planes in one structural unit. In Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ superconductor with two CuO$_2$ planes in one structural unit, the interaction between the two CuO$_2$ planes gives rise to band splitting into two Fermi surface sheets (bilayer splitting) that have distinct superconducting gap. The iron based superconductors are composed of stacking of the FeAs/FeSe layers; whether the interlayer coupling can cause similar band splitting and its effect on superconductivity remain unclear. Here we report high resolution laser-based angle-resolved photoemission spectroscopy (ARPES) measurements on a newly discovered iron based superconductor, KCa$_2$Fe$_4$As$_4$F$_2$ (T$_C$=33.5\,K) which consists of stacking FeAs blocks with two FeAs layers separated by insulating Ca$_2$F$_2$ blocks. Bilayer splitting effect is observed for the first time that gives rise to totally five hole-like Fermi surface sheets around the Brilliouin zone center. Band structure calculations reproduce the observed bilayer splitting by identifying interlayer interorbital interaction between the two FeAs layers within one FeAs block. All the hole-like pockets around the zone center exhibit Fermi surface-dependent and nodeless superconducting gap. The gap functions with short-range antiferromagetic fluctuations are proposed and the gap symmetry can be well understood when the interlayer pairing is considered. The particularly strong interlayer pairing is observed for one of the bands. Our observations provide key information on the interlayer coupling and interlayer pairing in understanding superconductivity in iron based superconductors.

cond-mat.supr-con↗

arXiv2019

Evidence for an Additional Symmetry Breaking from Direct Observation of Band Splitting in the Nematic State of FeSe Superconductor

The iron-based superconductor FeSe has attracted much recent attention because of its simple crystal structure, distinct electronic structure and rich physics exhibited by itself and its derivatives. Determination of its intrinsic electronic structure is crucial to understand its physical properties and superconductivity mechanism. Both theoretical and experimental studies so far have provided a picture that FeSe consists of one hole-like Fermi surface around the Brillouin zone center in its nematic state. Here we report direct observation of two hole-like Fermi surface sheets around the Brillouin zone center, and the splitting of the associated bands, in the nematic state of FeSe by taking high resolution laser-based angle-resolved photoemission measurements. These results indicate that, in addition to nematic order and spin-orbit coupling, there is an additional order in FeSe that breaks either inversion or time reversal symmetries. The new Fermi surface topology asks for reexamination of the existing theoretical and experimental understanding of FeSe and stimulates further efforts to identify the origin of the hidden order in its nematic state.

cond-mat.supr-con↗

arXiv2019

Prospect Theoretic Analysis of Privacy-Preserving Mechanism

We study a problem of privacy-preserving mechanism design. A data collector wants to obtain data from individuals to perform some computations. To relieve the privacy threat to the contributors, the data collector adopts a privacy-preserving mechanism by adding random noise to the computation result, at the cost of reduced accuracy. Individuals decide whether to contribute data when faced with the privacy issue. Due to the intrinsic uncertainty in privacy protection, we model individuals' privacy-related decision using Prospect Theory. Such a theory more accurately models individuals' behavior under uncertainty than the traditional expected utility theory, whose prediction always deviates from practical human behavior. We show that the data collector's utility maximization problem involves a polynomial of high and fractional order, the root of which is difficult to compute analytically. We get around this issue by considering a large population approximation, and obtain a closed-form solution that well approximates the precise solution. We discover that the data collector who considers the more realistic Prospect Theory based individual decision modeling would adopt a more conservative privacy-preserving mechanism, compared with the case based on the expected utility theory modeling. We also study the impact of Prospect Theory parameters, and concludes that more loss-averse or risk-seeking individuals will trigger a more conservative mechanism. When individuals have different Prospect Theory parameters, simulations demonstrate that the privacy protection first becomes stronger and then becomes weaker as the heterogeneity increases from a low value to a high one.

cs.GT↗

arXiv2019

Selective Hybridization between Main Band and Superstructure Band in Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ Superconductor

High-resolution laser-based angle-resolved photoemission measurements have been carried out on Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ (Bi2212) and Bi$_2$Sr$_{2-x}$La$_x$CuO$_{6+δ}$ (Bi2201) superconductors. Unexpected hybridization between the main band and the superstructure band in Bi2212 is clearly revealed. In the momentum space where one main Fermi surface intersects with one superstructure Fermi surface, four bands are observed instead of two. The hybridization exists in both superconducting state and normal state, and in Bi2212 samples with different doping levels. Such a hybridization is not observed in Bi2201. This phenomenon can be understood by considering the bilayer splitting in Bi2212, the selective hybridization of two bands with peculiar combinations, and the altered matrix element effects of the hybridized bands. These observations provide strong evidence on the origin of the superstructure band which is intrinsic to the CuO$_2$ planes. Therefore, understanding physical properties and superconductivity mechanism in Bi2212 should consider the complete Fermi surface topology which involves the main bands, the superstructure bands and their interactions.

cond-mat.supr-con↗

arXiv2019

Storage or No Storage: Duopoly Competition Between Renewable Energy Suppliers in a Local Energy Market

This paper studies the duopoly competition between renewable energy suppliers with or without energy storage in a local energy market. The storage investment brings the benefits of stabilizing renewable energy suppliers' outputs, but it also leads to substantial investment costs as well as some surprising changes in the market outcome. To study the equilibrium decisions of storage investment in the renewable energy suppliers' competition, we model the interactions between suppliers and consumers using a three-stage game-theoretic model. In Stage I, at the beginning of the investment horizon, suppliers decide whether to invest in storage. Once such decisions have been made, in the day-ahead market of each day, suppliers decide on their bidding prices and quantities in Stage II, based on which consumers decide the electricity quantity purchased from each supplier in Stage III. In the real-time market, a supplier is penalized if his actual generation falls short of his commitment. We characterize a price-quantity competition equilibrium of Stage II, and we further characterize a storage-investment equilibrium in Stage I incorporating electricity-selling revenue and storage cost. Counter-intuitively, we show that the uncertainty of renewable energy without storage investment can lead to higher supplier profits compared with the stable generations with storage investment due to the reduced market competition under random energy generation. Simulations further illustrate results due to the market competition. For example, a higher penalty for not meeting the commitment, a higher storage cost, or a lower consumer demand can sometimes increase a supplier's profit. We also show that although storage investment can increase a supplier 's profit, the first-mover supplier who invests in storage may benefit less than the free-rider competitor who chooses not to invest.

eess.SY↗