arXiv subjects

Quan Li

Publications and source records attributed to Quan Li.

89 records · Page 5Linked to original sources

arXiv2019

Metallic liquid H3O in a thin-shell zone inside Uranus and Neptune

The Solar System harbors deep unresolved mysteries despite centuries-long study. A highly intriguing case concerns anomalous non-dipolar and non-axisymmetric magnetic fields of Uranus and Neptune that have long eluded explanation by the prevailing theory. A thin-shell dynamo conjecture captures observed phenomena but leaves unexplained fundamental material basis and underlying mechanism. Here, we report the discovery of trihydrogen oxide (H3O) in metallic liquid state stabilized at extreme pressure and temperature conditions inside these icy planets. Calculated stability pressure field compared to known pressure-radius relation for Uranus and Neptune places metallic liquid H3O in a thin-shell zone near planetary cores. These findings from accurate quantum mechanical calculations rationalize the empirically conjectured thin-shell dynamo model and establish key physical benchmarks that are essential to elucidating the enigmatic magnetic-field anomaly of Uranus and Neptune, resolving a major mystery in planetary science.

physics.comp-ph↗

arXiv2019

Nanometer-precision non-local deformation reconstruction using nanodiamond orientation sensing

Information of material deformation upon loading is critical to evaluate mechanical properties of materials in general, and key to understand fundamental mechano-stimuli induced response of live systems in particular. Conventionally, such information is obtained at macroscopic scale about averaged properties, which misses the important details of deformation at individual structures; or at nanoscale with localized properties accessed, which misses the information of deformation at locations away from the force-loading positions. Here we demonstrate that an integration of nanodiamond orientation sensing and AFM nanoindentation offers a complementary approach to the nonlocal reconstruction of material deformation. This approach features a 5 nm precision in the loading direction and a sub-hundred nanometer lateral resolution. Using this tool, we mapped out the deformation of a PDMS thin film in air and that of the gelatin microgel particles in water, with precision high enough to disclose the significance of the surface/interface effects in the material deformation. The non-local nanometer-precision sensing of deformation upon a local impact brings in new opportunities in studying mechanical response of complex material systems.

cond-mat.mes-hall↗

arXiv2018

Quantum coherence control at near 1000 K

Quantum coherence control usually requires extremely low temperature environments. Even for spins in diamond, a remarkable exception, the coherence signal is lost as temperature approaches 700 K. Here we demonstrate quantum coherence control of the electron spins of nitrogen-vacancy centers in nanodiamonds at temperatures near 1000 K. The scheme is based on initialization and readout of the spins at room temperature and control at high temperature, which is enabled by pulse laser heating and rapid diffusion cooling of nanodiamonds on amorphous carbon films. Using high-temperature spin control, we observe the magnetic phase transition of a single nickel nanoparticle at about 615 K. This work enables nano-thermometry and nano-magnetometry in the high-temperature regime.

quant-ph↗

arXiv2018

Light Reconfigurable Geometric Phase Optical Element with Multi-stable States

We present the design methodology of a light reconfigurable geometric phase optical element with multi-stable diffraction efficiency states, enabled by a photoresponsive self-organized chiral liquid crystal. Experimental demonstration shows the device exhibits a broad diffraction efficiency tunable range that can be smoothly modulated under alternate stimulation of ultraviolet and green lights. Distinctive to previous designs, the regulation of diffraction efficiency fundamentally stems from the modulation of geometric phase together with dynamical phase retardation, and any intermediate diffractive state is memorized. Such multi-stability facilitates applications including energy-saving all-optical signal processing in classical and quantum level, and phase hologram for anti-counterfeit.

physics.optics↗

arXiv2018

WeSeer: Visual Analysis for Better Information Cascade Prediction of WeChat Articles

Social media, such as Facebook and WeChat, empowers millions of users to create, consume, and disseminate online information on an unprecedented scale. The abundant information on social media intensifies the competition of WeChat Public Official Articles (i.e., posts) for gaining user attention due to the zero-sum nature of attention. Therefore, only a small portion of information tends to become extremely popular while the rest remains unnoticed or quickly disappears. Such a typical `long-tail' phenomenon is very common in social media. Thus, recent years have witnessed a growing interest in predicting the future trend in the popularity of social media posts and understanding the factors that influence the popularity of the posts. Nevertheless, existing predictive models either rely on cumbersome feature engineering or sophisticated parameter tuning, which are difficult to understand and improve. In this paper, we study and enhance a point process-based model by incorporating visual reasoning to support communication between the users and the predictive model for a better prediction result. The proposed system supports users to uncover the working mechanism behind the model and improve the prediction accuracy accordingly based on the insights gained. We use realistic WeChat articles to demonstrate the effectiveness of the system and verify the improved model on a large scale of WeChat articles. We also elicit and summarize the feedback from WeChat domain experts.

cs.HC↗

arXiv2018

EmbeddingVis: A Visual Analytics Approach to Comparative Network Embedding Inspection

Constructing latent vector representation for nodes in a network through embedding models has shown its practicality in many graph analysis applications, such as node classification, clustering, and link prediction. However, despite the high efficiency and accuracy of learning an embedding model, people have little clue of what information about the original network is preserved in the embedding vectors. The abstractness of low-dimensional vector representation, stochastic nature of the construction process, and non-transparent hyper-parameters all obscure understanding of network embedding results. Visualization techniques have been introduced to facilitate embedding vector inspection, usually by projecting the embedding space to a two-dimensional display. Although the existing visualization methods allow simple examination of the structure of embedding space, they cannot support in-depth exploration of the embedding vectors. In this paper, we design an exploratory visual analytics system that supports the comparative visual interpretation of embedding vectors at the cluster, instance, and structural levels. To be more specific, it facilitates comparison of what and how node metrics are preserved across different embedding models and investigation of relationships between node metrics and selected embedding vectors. Several case studies confirm the efficacy of our system. Experts' feedback suggests that our approach indeed helps them better embrace the understanding of network embedding models.

cs.HC↗

arXiv2018

Enhanced nanosecond electro-optic effect in isotropic and nematic phases of dielectrically negative nematics doped by strongly polar additive

An electric field can induce or modify optical birefringence in both the isotropic and nematic phases of liquid crystals (LCs). In the isotropic phase, the electric field induces birefringence with an optical axis along the field. The phenomenon is known as the Kerr effect. In the nematic, the analog of the Kerr effect is the change of existing birefringence through nanosecond electric modification of order parameters (NEMOP) that does not require realignment of the optic axis. The utility of both effects for practical applications is challenged by a relatively weak birefringence induced by the field. We address the issue by adding a non-mesogenic additive 2, 3-dicyano-4-pentyloxyphenyl 4'-pentyloxybenzoate (DPP) with a large transverse dipole moment to mesogenic materials in order to enhance their negative dielectric anisotropy. The DPP doping substantially increases the field-induced birefringence in both NEMOP and Kerr effects, up to 0.02. The doping also slows down the switching processes, but this effect can be compensated by rising working temperatures, if necessary. The enhancement of field induced birefringence by the non-mesogenic dopant paves the way for practical applications of nanosecond electro-optic effects.

cond-mat.soft↗

arXiv2017

Matrix Completion from $O(n)$ Samples in Linear Time

We consider the problem of reconstructing a rank-$k$ $n \times n$ matrix $M$ from a sampling of its entries. Under a certain incoherence assumption on $M$ and for the case when both the rank and the condition number of $M$ are bounded, it was shown in \cite{CandesRecht2009, CandesTao2010, keshavan2010, Recht2011, Jain2012, Hardt2014} that $M$ can be recovered exactly or approximately (depending on some trade-off between accuracy and computational complexity) using $O(n \, \text{poly}(\log n))$ samples in super-linear time $O(n^{a} \, \text{poly}(\log n))$ for some constant $a \geq 1$. In this paper, we propose a new matrix completion algorithm using a novel sampling scheme based on a union of independent sparse random regular bipartite graphs. We show that under the same conditions w.h.p. our algorithm recovers an $ε$-approximation of $M$ in terms of the Frobenius norm using $O(n \log^2(1/ε))$ samples and in linear time $O(n \log^2(1/ε))$. This provides the best known bounds both on the sample complexity and computational complexity for reconstructing (approximately) an unknown low-rank matrix. The novelty of our algorithm is two new steps of thresholding singular values and rescaling singular vectors in the application of the "vanilla" alternating minimization algorithm. The structure of sparse random regular graphs is used heavily for controlling the impact of these regularization steps.

stat.ML↗

arXiv2017

Magnetic criticality-enhanced hybrid nanodiamond-thermometer under ambient conditions

Nitrogen vacancy (NV) centres in diamond are attractive as quantum sensors owing to their superb coherence under ambient conditions. However, the NV centre spin resonances are relatively insensitive to some important parameters such as temperature. Here we design and experimentally demonstrate a hybrid nano-thermometer composed of NV centres and a magnetic nanoparticle (MNP), in which the temperature sensitivity is enhanced by the critical magnetization of the MNP near the ferromagnetic-paramagnetic transition temperature. The temperature susceptibility of the NV center spin resonance reached 14 MHz/K, enhanced from the value without the MNP by two orders of magnitude. The sensitivity of a hybrid nano-thermometer composed of a Cu_{1-x}Ni_{x} MNP and a nanodiamond was measured to be 11 mK/Hz^{1/2} under ambient conditions. With such high-sensitivity, we monitored nanometer-scale temperature variation of 0.3 degree with a time resolution of 60 msec. This hybrid nano-thermometer provides a novel approach to studying a broad range of thermal processes at nanoscales such as nano-plasmonics, sub-cellular heat-stimulated processes, thermodynamics of nanostructures, and thermal remanent magnetization of nanoparticles.

quant-ph↗

arXiv2017

Stochastic Subspace Identification: Valid Model, Asymptotics and Model Error Bounds

This paper investigates the ability of the stochastic subspace identification technique to return a valid model from finite measurement data, its asymptotic properties as the data set becomes large, and asymptotic error bounds of the identified model (in terms of $\mathcal{H}_2$ and $\mathcal{H}_{\infty}$ norms). First, a new and straightforward LMI-based approach is proposed, which returns a valid identified model even in cases where the system poles are very close to unit circle and there is insufficient data to accurately estimate the covariance matrices. The approach, which is demonstrated by numerical examples, provides an altenative to other techniques which often fail under these circumstances. Then, an explicit expression for the variance of the asymptotically normally distributed sample output covariance matrices and block-Hankel matrix are derived. From this result, together with perturbation techniques, error bounds for the state-space matrices in the innovations model are derived, for a given confidence level. This result is in turn used to derive several error bounds for the identified transfer functions, for a given confidence level. One is an explicit $\mathcal{H}_2$ bound. Additionally, two $\mathcal{H}_{\infty}$ error bounds are derived, one via perturbation analysis, and the other via an LMI-based technique.

eess.SY↗

arXiv2017

On the Max-Cut of Sparse Random Graphs

We consider the problem of estimating the size of a maximum cut (Max-Cut problem) in a random Erdős-Rényi graph on $n$ nodes and $\lfloor cn \rfloor$ edges. It is shown in Coppersmith et al. ~\cite{Coppersmith2004} that the size of the maximum cut in this graph normalized by the number of nodes belongs to the asymptotic region $[c/2+0.37613\sqrt{c},c/2+0.58870\sqrt{c}]$ with high probability (w.h.p.) as $n$ increases, for all sufficiently large $c$. In this paper we improve both upper and lower bounds by introducing a novel bounding technique. Specifically, we establish that the size of the maximum cut normalized by the number of nodes belongs to the interval $[c/2+0.47523\sqrt{c},c/2+0.55909\sqrt{c}]$ w.h.p. as $n$ increases, for all sufficiently large $c$. Instead of considering the expected number of cuts achieving a particular value as is done in the application of the first moment method, we observe that every maximum size cut satisfies a certain local optimality property, and we compute the expected number of cuts with a given value satisfying this local optimality property. Estimating this expectation amounts to solving a rather involved two dimensional large deviations problem. We solve this underlying large deviation problem asymptotically as $c$ increases and use it to obtain an improved upper bound on the Max-Cut value. The lower bound is obtained by application of the second moment method, coupled with the same local optimality constraint, and is shown to work up to the stated lower bound value $c/2+0.47523\sqrt{c}$. It is worth noting that both bounds are stronger than the ones obtained by standard first and second moment methods. Finally, we also obtain an improved lower bound of $1.36000n$ on the Max-Cut for the random cubic graph or any cubic graph with large girth, improving the previous best bound of $1.33773n$.

math.PR↗

arXiv2017

Construction of crystal structure prototype database: methods and applications

Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the Crystal Structure Prototype Database (CSPD) by filtering the known crystallographic structures in a database. With similar method, a program Structure Prototype Analysis Package (SPAP) was developed to remove similar structures in CALYPSO prediction results and extract predicted low energy structures for a separate theoretical structure database. A series of statistics describing the distribution of crystal structure prototypes in the CSPD was compiled to provide an important insight for structure prediction and high-throughput calculations. Illustrative examples of the application of the proposed database are given, including the generation of initial structures for structure prediction and determination of the prototype structure in databases. These examples demonstrate the CSPD to be a generally applicable and useful tool for materials discovery.

cond-mat.mtrl-sci↗

arXiv2016

Finding a Large Submatrix of a Gaussian Random Matrix

We consider the problem of finding a $k\times k$ submatrix of an $n\times n$ matrix with i.i.d. standard Gaussian entries, which has a large average entry. It was shown earlier by Bhamidi et al. that the largest average value of such a matrix is $2\sqrt{\log n/k}$ with high probability. In the same paper an evidence was provided that a natural greedy algorithm called Largest Average Submatrix ($\LAS$) should produce a matrix with average entry approximately $\sqrt{2}$ smaller. In this paper we show that the matrix produced by the $\LAS$ algorithm is indeed $\sqrt{2\log n/k}$ w.h.p. Then by drawing an analogy with the problem of finding cliques in random graphs, we propose a simple greedy algorithm which produces a $k\times k$ matrix with asymptotically the same average value. Since the greedy algorithm is the best known algorithm for finding cliques in random graphs, it is tempting to believe that beating the factor $\sqrt{2}$ performance gap suffered by both algorithms might be very challenging. Surprisingly, we show the existence of a very simple algorithm which produces a matrix with average value $(4/3)\sqrt{2\log n/k}$. To get an insight into the algorithmic hardness of this problem, and motivated by methods originating in the theory of spin glasses, we conduct the so-called expected overlap analysis of matrices with average value asymptotically $α\sqrt{2\log n/k}$. The overlap corresponds to the number of common rows and common columns for pairs of matrices achieving this value. We discover numerically an intriguing phase transition at $α^*\approx 1.3608..$: when $α<α^*$ the space of overlaps is a continuous subset of $[0,1]^2$, whereas $α=α^*$ marks the onset of discontinuity, and the model exhibits the Overlap Gap Property when $α>α^*$. We conjecture that $α>α^*$ marks the onset of the algorithmic hardness.

math.PR↗

arXiv2015

ATLAS: A Real-Space Finite-Difference Implementation of Orbital-Free Density Functional Theory

Orbital-free density functional theory (OF-DFT) is a promising method for large-scale quantum mechanics simulation as it provides a good balance of accuracy and computational cost. Its applicability to large-scale simulations has been aided by progress in constructing kinetic energy functionals and local pseudopotentials. However, the widespread adoption of OF-DFT requires further improvement in its efficiency and robustly implemented software. Here we develop a real-space finite-difference method for the numerical solution of OF-DFT in periodic systems. Instead of the traditional self-consistent method, a powerful scheme for energy minimization is introduced to solve the Euler--Lagrange equation. Our approach engages both the real-space finite-difference method and a direct energy-minimization scheme for the OF-DFT calculations. The method is coded into the ATLAS software package and benchmarked using periodic systems of solid Mg, Al, and Al$_{3}$Mg. The test results show that our implementation can achieve high accuracy, efficiency, and numerical stability for large-scale simulations.

physics.comp-ph↗

arXiv2015

Realization of GHZ-like and W-like Third-order Spatial Correlation with Classical Light

The spatial correlation with classical lights, which has some similar aspects as that with entangled lights, is an interesting and fundamentally important topic. But the features of high-order spatial correlation with classical lights are not well known, and the types of high-order correlations produced are of limit. Here, we propose a scheme to produce third-order spatial correlated states by modulating the phases of three laser beams. With the scheme we can produce Greenberger-Horne-Zeilinger-type (GHZ-type) and W-type spatial correlations with different phase modulations. Our scheme can be easily generalized to produce $N$-order spatial correlation states and to probe the aspects of different multi-partite spatial correlations.

quant-ph↗

arXiv2015

Electrically tunable selective reflection of light from ultraviolet to visible and infrared by heliconical cholesterics

Cholesteric liquid crystals with helicoidal molecular architecture are known for their ability to selectively reflect light with the wavelength that is determined by the periodicity of molecular orientations. Here we demonstrate that by using a cholesteric with oblique helicoidal(heliconical) structure, as opposed to the classic right-angle helicoid, one can vary the wavelength of selectively reflected light in a broad spectral range, from ultraviolet to visible and infrared (360-1520 nm for the same chemical composition) by simply adjusting the electric field applied parallel to the helicoidal axis. The effect exists in a wide temperature range (including the room temperatures) and thus can enable many applications that require dynamically controlled transmission and reflection of electromagnetic waves, from energy-saving smart windows to tunable organic lasers, reflective color display, and transparent see-through displays.

cond-mat.soft↗

arXiv2005

Effects of Al Addition on the Native Defects in Hafnia

Two occupied native defect bands are detected in pure HfO2, with one located in the middle of the band gap and the other slightly above the valence band maximum. The investigation on the electronic structures of hafnium aluminate thin films as a function of Al concentration discloses the evolution of such bands while the density of states of the former one reduces drastically with the Al addition, that of the later one remains rather unaffected. Our first principles studies of the system attribute the two bands to the charged oxygen vacancy, and the oxygen interstitial related defect states of the HfO2, respectively. We further demonstrate that the observed evolution of the defect bands originates from the interaction in-between the added Al and the native defects of pure HfO2, which effectively passivates the VO+ induced mid-gap states but has little effect on other aspects of the electronic structure of the material.

cond-mat.mtrl-sci↗