arXiv subjects

Zhihao Jiang

Publications and source records attributed to Zhihao Jiang.

At least 37 records · Page 2Linked to original sources

arXiv2023

Zero-field magnetic structure and metamagnetic phase transitions of the cobalt chain compound Li$_2$CoCl$_4$

Exploring the uncharacterized magnetic phases of Co$^{2+}$ chain compounds is critical for finding new low-dimensional magnets hosting quantized excitations. We map the unexplored magnetic phases of the Co$^{2+}$ chain compound Li$_2$CoCl$_4$. Magnetometry reveals magnetic ordering below 7 K with a metamagnetic transition near 16.5 kOe and a gradual transition to a field-aligned paramagnetic state above 31 kOe. Curie-Weiss fits to the high temperature susceptibility reveal a high-spin (spin-$\frac{3}{2}$) state for cobalt. Heat capacity data, though, give a magnetic entropy change of 5.46 J/mol, consistent with cobalt effective spin-$\frac{1}{2}$ systems. To characterize the zero-field antiferromagnetic ordering, we separately calculated the energy of proposed magnetic structures with density functional theory and collected 3.5 K neutron diffraction data, finding that Li$_2$CoCl$_4$ has ferromagnetic chains with antiferromagnetic interactions between them. Increasing field rotates these spin chains, producing the antiferromagnetic to intermediate to paramagnetic transition sequence.

cond-mat.str-el↗

arXiv2023

Integrating Magnons for Quantum Information

Magnons, the quanta of collective spin excitations in magnetically ordered materials, have distinct properties that make them uniquely appealing for quantum information applications. They can have ultra-small wavelengths down to the nanometer scale even at microwave frequencies. They can provide coupling to a diverse set of other quantum excitations, and their inherently gyrotropic dynamics forms the basis for pronounced non-reciprocities. In this article we discuss what the current research challenges are for integrating magnetic materials into quantum information systems and provide a perspective on how to address them.

cond-mat.mtrl-sci↗

arXiv2022

On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood

We provide an efficient unified plug-in approach for estimating symmetric properties of distributions given $n$ independent samples. Our estimator is based on profile-maximum-likelihood (PML) and is sample optimal for estimating various symmetric properties when the estimation error $ε\gg n^{-1/3}$. This result improves upon the previous best accuracy threshold of $ε\gg n^{-1/4}$ achievable by polynomial time computable PML-based universal estimators [ACSS21, ACSS20]. Our estimator reaches a theoretical limit for universal symmetric property estimation as [Han21] shows that a broad class of universal estimators (containing many well known approaches including ours) cannot be sample optimal for every $1$-Lipschitz property when $ε\ll n^{-1/3}$.

stat.ML↗

arXiv2022

Programming moiré patterns in 2D materials by bending

Moiré superlattices in twisted two-dimensional materials have generated tremendous excitement as a platform for achieving quantum properties on demand. However, the moiré pattern is highly sensitive to the interlayer atomic registry, and current assembly techniques suffer from imprecise control of the average twist angle, spatial inhomogeneity in the local twist angle, and distortions due to random strain. Here, we demonstrate a new way to manipulate the moiré patterns in hetero- and homo-bilayers through in-plane bending of monolayer ribbons, using the tip of an atomic force microscope. This technique achieves continuous variation of twist angles with improved twist-angle homogeneity and reduced random strain, resulting in moiré patterns with highly tunable wavelength and ultra-low disorder. Our results pave the way for detailed studies of ultra-low disorder moiré systems and the realization of precise strain-engineered devices.

cond-mat.mes-hall↗

arXiv2022

Plasmons in Z2 Topological Insulators

We study plasmonic excitations in the Kane-Mele model, a two-dimensional Z2 topological insulator on the honeycomb lattice, using the random phase approximation (RPA). In the topologically non-trivial phase, the model has conducting edge states that traverse the bulk energy gap and display spin-momentum-locking. Such a state of matter is called the quantum spin hall (QSH) phase, which is robust against time-reversal (TR) invariant perturbations. We find that in the QSH phase, gapless spin-polarized plasmons can be excited on the edges of the system. The propagation of these plasmons is chiral for each individual spin component and shows spin-momentum-locking for both spin components on the same edge. Moreover, we study the effect of external magnetic fields on the gapless edge plasmons. Specifically, out-of-plane magnetic fields delocalize edge plasmons propagating in one direction without affecting the other one, while an in-plane magnetic field can be applied to selectively excite a specific spin-plasmon branch with proper doping or gating to the system. Our findings may have potential applications in novel plasmonic and spintronic devices. We also investigate plasmons in the Kane-Mele model on a finite-sized diamond-shaped nanoflake and observe low-energy plasmons circulating the boundary of the material.

cond-mat.mes-hall↗

arXiv2021

Control of Plasmons in Topological Insulators via Local Perturbations

We use a fully quantum mechanical approach to demonstrate control of plasmonic excitations in prototype models of topological insulators by molecule-scale perturbations. Strongly localized surface plasmons are present in the host systems, arising from the topologically non-trivial single-particle edge states. A numerical evaluation of the RPA equations for the perturbed systems reveals how the positions and the internal electronic structure of the added molecules affect the degeneracy of the locally confined collective excitations, i.e., shifting the plasmonic energies of the host system and changing their spatial charge density profile. In particular, we identify conditions under which significant charge transfer from the host system to the added molecules occurs. Furthermore, the induced field energy density in the perturbed topological systems due to external electric fields is determined.

cond-mat.mes-hall↗

arXiv2021

Model-based Pre-clinical Trials for Medical Devices Using Statistical Model Checking

Clinical trials are considered as the golden standard for medical device validation. However, many sacrifices have to be made during the design and conduction of the trials due to cost considerations and partial information, which may compromise the significance of the trial results. In this paper, we proposed a model-based pre-clinical trial framework using statistical model checking. Physiological models represent disease mechanism, which enable automated adjudication of simulation results. Sampling of the patient parameters and hypothesis testing are performed by statistical model checker. The framework enables a broader range of hypothesis to be tested with guaranteed statistical significance, which are useful complements to the clinical trials. We demonstrated our framework with a pre-clinical trial on implantable cardioverter defibrillators.

stat.AP↗

arXiv2021

Environment Modeling During Model Checking of Cyber-Physical Systems

Ensuring the safety and efficacy of Cyber-Physical Systems (CPSs) is challenging due to the large variability of their operating environment. Model checking has been proposed for validation of CPSs, but the models of the environment are either too specific to capture the variability of the environment, or too abstract to provide counter-examples interpretable by experts in the application domain. Domain-specific solutions to this problem require expertise in both formal methods and the application domain, which prevents effective application of model checking in CPSs validation. A domain-independent framework based on timed-automata is proposed for abstraction and refinement of environment models during model checking. The framework maintains an abstraction tree of environment models, which provides interpretable counter-examples while ensuring coverage of environment behaviors. With the framework, experts in the application domain can effectively use model checking without expertise in formal methods.

cs.FL↗

arXiv2021

Fair for All: Best-effort Fairness Guarantees for Classification

Standard approaches to group-based notions of fairness, such as \emph{parity} and \emph{equalized odds}, try to equalize absolute measures of performance across known groups (based on race, gender, etc.). Consequently, a group that is inherently harder to classify may hold back the performance on other groups; and no guarantees can be provided for unforeseen groups. Instead, we propose a fairness notion whose guarantee, on each group $g$ in a class $\mathcal{G}$, is relative to the performance of the best classifier on $g$. We apply this notion to broad classes of groups, in particular, where (a) $\mathcal{G}$ consists of all possible groups (subsets) in the data, and (b) $\mathcal{G}$ is more streamlined. For the first setting, which is akin to groups being completely unknown, we devise the {\sc PF} (Proportional Fairness) classifier, which guarantees, on any possible group $g$, an accuracy that is proportional to that of the optimal classifier for $g$, scaled by the relative size of $g$ in the data set. Due to including all possible groups, some of which could be too complex to be relevant, the worst-case theoretical guarantees here have to be proportionally weaker for smaller subsets. For the second setting, we devise the {\sc BeFair} (Best-effort Fair) framework which seeks an accuracy, on every $g \in \mathcal{G}$, which approximates that of the optimal classifier on $g$, independent of the size of $g$. Aiming for such a guarantee results in a non-convex problem, and we design novel techniques to get around this difficulty when $\mathcal{G}$ is the set of linear hypotheses. We test our algorithms on real-world data sets, and present interesting comparative insights on their performance.

cs.LG↗

arXiv2021

Plasmonic Waveguides from Coulomb-Engineered Two-Dimensional Metals

Coulomb interactions play an essential role in atomically-thin materials. On one hand, they are strong and long-ranged in layered systems due to the lack of environmental screening. On the other hand, they can be efficiently tuned by means of surrounding dielectric materials. Thus all physical properties which decisively depend on the exact structure of the electronic interactions can be in principle efficiently controlled and manipulated from the outside via Coulomb engineering. Here, we show how this concept can be used to create fundamentally new plasmonic waveguides in metallic layered materials. We discuss in detail how dielectrically structured environments can be utilized to non-invasively confine plasmonic excitations in an otherwise homogeneous metallic 2D system by modification of its many-body interactions. We define optimal energy ranges for this mechanism and demonstrate plasmonic confinement within several nanometers. In contrast to conventional functionalization mechanisms, this scheme relies on a purely many-body concept and does not involve any direct modifications to the active material itself.

cond-mat.mes-hall↗

arXiv2021

Plasmons in Two-Dimensional Topological Insulators

We analyze collective excitations in models of two-dimensional topological insulators using the random phase approximation. In a two-dimensional extension of the Su-Schrieffer-Heeger model, edge plasmonic excitations with induced charge-density distributions localized at the boundaries of the system are found in the topologically non-trivial phase, dispersing similarly as one-dimensional bulk plasmons in the conventional Su-Schrieffer-Heeger chain. For two-dimensional bulk collective modes, we reveal regimes of enhanced inter-band wave function correlations, leading to characteristic hardening and softening of inter- and intra-band bulk plasmonic branches, respectively. In the two-dimensional Haldane Chern insulator model, chiral, uni-directional edge plasmons in nano-ribbon architectures are observed, which can be characterized by an effective Coulomb interaction cross section. Bulk collective excitations in the two-dimensional Haldane model are shown to be originated by single-particle band structure details in different topological phases.

cond-mat.mes-hall↗

arXiv2021

Control of Plasmons in Doped Topological Insulators via Basis Atoms

Collective excitations in topologically non-trivial systems have attracted considerable attention in recent years. Here we study plasmons in the Su-Schrieffer-Heeger model whose low-energy electronic band is only partially filled, such that the system is metallic. Using the random phase approximation, we calculate the intra- and inter-band polarization functions and determine the bulk plasmonic dispersion from the dielectric function within the random phase approximation. We find that the sub-lattice basis states strongly affect the polarization functions and therefore control the system's plasmonic excitations. By varying the real-space separation of these local orbitals, one can thus selectively enhance or suppress the plasmonic energies via a tunable trade-off between intra-band and inter-band screening processes. Specifically, this mechanism can be used to stabilize undamped high energy plasmons that have already been reported in related models. We propose scenarios on how to control and observe these effects in experiments.

cond-mat.mtrl-sci↗

arXiv2020

Online Algorithms for Weighted Paging with Predictions

In this paper, we initiate the study of the weighted paging problem with predictions. This continues the recent line of work in online algorithms with predictions, particularly that of Lykouris and Vassilvitski (ICML 2018) and Rohatgi (SODA 2020) on unweighted paging with predictions. We show that unlike unweighted paging, neither a fixed lookahead nor knowledge of the next request for every page is sufficient information for an algorithm to overcome existing lower bounds in weighted paging. However, a combination of the two, which we call the strong per request prediction (SPRP) model, suffices to give a 2-competitive algorithm. We also explore the question of gracefully degrading algorithms with increasing prediction error, and give both upper and lower bounds for a set of natural measures of prediction error.

cs.DS↗

arXiv2020

Approximately Stable Committee Selection

In the committee selection problem, we are given $m$ candidates, and $n$ voters. Candidates can have different weights. A committee is a subset of candidates, and its weight is the sum of weights of its candidates. Each voter expresses an ordinal ranking over all possible committees. The only assumption we make on preferences is monotonicity: If $S \subseteq S'$ are two committees, then any voter weakly prefers $S'$ to $S$. We study a general notion of group fairness via stability: A committee of given total weight $K$ is stable if no coalition of voters can deviate and choose a committee of proportional weight, so that all these voters strictly prefer the new committee to the existing one. Extending this notion to approximation, for parameter $c \ge 1$, a committee $S$ of weight $K$ is said to be $c$-approximately stable if for any other committee $S'$ of weight $K'$, the fraction of voters that strictly prefer $S'$ to $S$ is strictly less than $\frac{c K'}{K}$. When $c = 1$, this condition is equivalent to classical core stability. The question we ask is: Does a $c$-approximately stable committee of weight at most any given value $K$ always exist for constant $c$? It is relatively easy to show that there exist monotone preferences for which $c \ge 2$. However, even for simple and widely studied preference structures, a non-trivial upper bound on $c$ has been elusive. In this paper, we show that $c = O(1)$ for all monotone preference structures. Our proof proceeds via showing an existence result for a randomized notion of stability, and iteratively rounding the resulting fractional solution.

cs.GT↗

arXiv2019

Localized Plasmons in Topological Insulators

We investigate in a fully quantum-mechanical manner how the many-body excitation spectrum of topological insulators is affected by the presence of long-range Coulomb interactions. In the one-dimensional Su-Schrieffer-Heeger model and its mirror-symmetric variant strongly localized plasmonic excitations are observed which originate from topologically non-trivial single-particle states. These \textit{"topological plasmons"} inherit some of the characteristics of their constituent topological single-particle states, but they are not equally well protected against disorder due to the admixture of non-topological bulk single-particle states in the polarization function. The strength of the effective Coulomb interactions is also shown to have strong effects on the plasmonic modes. Furthermore, we show how external modifications via dielectric screening and applied electric fields with distinct symmetries can be used to study topological plasmons, thus allowing for experimental verification of our atomistic predictions.

cond-mat.mtrl-sci↗

arXiv2019

Group Fairness in Committee Selection

In this paper, we study fairness in committee selection problems. We consider a general notion of fairness via stability: A committee is stable if no coalition of voters can deviate and choose a committee of proportional size, so that all these voters strictly prefer the new committee to the existing one. Our main contribution is to extend this definition to stability of a distribution (or lottery) over committees. We consider two canonical voter preference models: the Approval Set setting where each voter approves a set of candidates and prefers committees with larger intersection with this set; and the Ranking setting where each voter ranks committees based on how much she likes her favorite candidate in a committee. Our main result is to show that stable lotteries always exist for these canonical preference models. Interestingly, given preferences of voters over committees, the procedure for computing an approximately stable lottery is the same for both models and therefore extends to the setting where some voters have the former preference structure and others have the latter. Our existence proof uses the probabilistic method and a new large deviation inequality that may be of independent interest.

cs.GT↗

arXiv2019

Line Outage Detection and Localization via Synchrophasor Measurement

Since transmission lines are crucial links in the power system, one line outage event may bring about interruption or even cascading failure of the power system. If a quick and accurate line outage detection and localization can be achieved, the system operator can take necessary actions in time to mitigate the negative impact. Therefore, the objective of this paper is to study a method for line outage detection and localization via synchrophasor measurements. The density of deployed phasor measurement units (PMUs) is increasing recently, which greatly improves the visibility of the power grid. Taking advantage of the high-resolution synchrophasor data, the proposed method utilizes frequency measurement for line outage detection and power change for localization. The procedure of the proposed method is given. Compared with conventional methods, it does not require the pre-knowledge on the system. Simulation study validates the effectiveness of the proposed method.

eess.SP↗

arXiv2019

An FPTAS for Stochastic Unbounded Min-Knapsack Problem

In this paper, we study the stochastic unbounded min-knapsack problem ($\textbf{Min-SUKP}$). The ordinary unbounded min-knapsack problem states that: There are $n$ types of items, and there is an infinite number of items of each type. The items of the same type have the same cost and weight. We want to choose a set of items such that the total weight is at least $W$ and the total cost is minimized. The \prob~generalizes the ordinary unbounded min-knapsack problem to the stochastic setting, where the weight of each item is a random variable following a known distribution and the items of the same type follow the same weight distribution. In \prob, different types of items may have different cost and weight distributions. In this paper, we provide an FPTAS for $\textbf{Min-SUKP}$, i.e., the approximate value our algorithm computes is at most $(1+ε)$ times the optimum, and our algorithm runs in $poly(1/ε,n,\log W)$ time.

cs.DS↗