arXiv subjects

Hui Cao

Publications and source records attributed to Hui Cao.

At least 73 records · Page 4Linked to original sources

arXiv2021

Depth-Targeted Energy Deposition Deep Inside Scattering Media

A grand challenge in fundamental physics and practical applications is overcoming wave diffusion to deposit energy into a target region deep inside a diffusive system. While it is known that coherently controlling the incident wavefront allows diffraction-limited focusing inside a diffusive system, in many applications targets are significantly larger than such a focus and the maximum deliverable energy remains unknown. Here, we introduce the "deposition matrix", which maps an input wavefront to its internal field distribution, and theoretically predict the ultimate limitations on energy deposition at any depth. For example, the maximum obtainable energy enhancement occurs at 3/4 a diffusive system's thickness: regardless of its scattering strength. Experimentally we measure the deposition matrix and excite its eigenstates to enhance/suppress the energy within an extended target region. Our theoretical analysis reveals that such enhancement/suppression results from both selective transmission eigenchannel excitation and constructive/destructive interference among these channels.

physics.optics↗

arXiv2021

Customizing the angular memory effect for scattering media

The memory effect in disordered systems is a key physical phenomenon that has been employed for optical imaging, metrology, and communication through opaque media. Under the conventional memory effect, when the incident beam is tilted slightly, the transmitted pattern tilts in the same direction. However, the "memory" is limited in its angular range and tilt direction. Here, we present a general approach to customize the memory effect by introducing an angular memory operator. Its eigenstates possess perfect correlation for tilt angles and directions that can be arbitrarily chosen separately for the incident and transmitted waves, and can be readily realized with wavefront shaping. This work reveals the power of wavefront shaping in creating any desired memory for applications of classical and quantum waves in complex systems.

physics.optics↗

arXiv2021

An Object Detection based Solver for Google's Image reCAPTCHA v2

Previous work showed that reCAPTCHA v2's image challenges could be solved by automated programs armed with Deep Neural Network (DNN) image classifiers and vision APIs provided by off-the-shelf image recognition services. In response to emerging threats, Google has made significant updates to its image reCAPTCHA v2 challenges that can render the prior approaches ineffective to a great extent. In this paper, we investigate the robustness of the latest version of reCAPTCHA v2 against advanced object detection based solvers. We propose a fully automated object detection based system that breaks the most advanced challenges of reCAPTCHA v2 with an online success rate of 83.25%, the highest success rate to date, and it takes only 19.93 seconds (including network delays) on average to crack a challenge. We also study the updated security features of reCAPTCHA v2, such as anti-recognition mechanisms, improved anti-bot detection techniques, and adjustable security preferences. Our extensive experiments show that while these security features can provide some resistance against automated attacks, adversaries can still bypass most of them. Our experimental findings indicate that the recent advances in object detection technologies pose a severe threat to the security of image captcha designs relying on simple object detection as their underlying AI problem.

cs.CR↗

arXiv2021

Manipulate the Electronic State of Mott Iridate Superlattice through Protonation Induced Electron-Filling

Spin-orbit-coupled Mott iridates show great similarity with parent compounds of superconducting cuprates, attracting extensive research interests especially for their electron-doped states. However, previous experiments are largely limited within a small doping range due to the absence of effective dopants, and therefore the electron-doped phase diagram remains elusive. Here we utilize an ionic-liquid-gating induced protonation method to achieve electron-doping into a 5d Mott-insulator built with SrIrO3/SrTiO3 superlattice, and achieve a systematic mapping of its electron-doped phase diagram with the evolution of the iridium valence state from 4+ to 3+, equivalent to doping of one electron per iridium ion. Along increasing doping level, the parent Mott-insulator is first turned into a localized metallic state with gradually suppressed magnetic ordering, and then further evolved into a nonmagnetic band insulating state. This work forms an important step forward for the study of electron-doped Mott iridate systems, and the strategy of manipulating the band filling in an artificially designed superlattice structure can be readily extended into other systems with more exotic states to explore.

cond-mat.str-el↗

arXiv2021

Massively parallel ultrafast random bit generation with a chip-scale laser

Random numbers are widely used for information security, cryptography, stochastic modeling, and quantum simulations. Key technical challenges for physical random number generation are speed and scalability. We demonstrate a method for ultrafast generation of hundreds of random bit streams in parallel with a single laser diode. Spatio-temporal interference of many lasing modes in a specially designed cavity is introduced as a scheme for greatly accelerated random bit generation. Spontaneous emission, caused by quantum fluctuations, produces stochastic noise that makes the bit streams unpredictable. We achieve a total bit rate of 250 terabits per second with off-line post-processing, which is more than two orders of magnitude higher than the current post-processing record. Our approach is robust, compact, and energy efficient with potential applications in secure communication and high-performance computation.

physics.optics↗

arXiv2021

Circumventing the optical diffraction limit with customized speckles

Speckle patterns have been widely used in imaging techniques such as ghost imaging, dynamic speckle illumination microscopy, structured illumination microscopy, and photoacoustic fluctuation imaging. Recent advances in the ability to control the statistical properties of speckles has enabled the customization of speckle patterns for specific imaging applications. In this work, we design and create special speckle patterns for parallelized nonlinear pattern-illumination microscopy based on fluorescence photoswitching. We present a proof-of-principle experimental demonstration where we obtain a spatial resolution three times higher than the diffraction limit of the illumination optics in our setup. Furthermore, we show that tailored speckles vastly outperform standard speckles. Our work establishes that customized speckles are a potent tool in parallelized super-resolution microscopy.

physics.optics↗

arXiv2021

Realization of electron antidoping by modulating the breathing distortion in BaBiO$_3$

The recent proposal of antidoping scheme breaks new ground in conceiving conversely functional materials and devices, yet the few available examples belong to the correlated electron systems. Here we demonstrate both theoretically and experimentally that the main group oxide BaBiO$_3$ is a model system for antidoping using oxygen vacancies. The first principles calculations show that the band gap systematically increases due to the strongly enhanced BiO breathing distortions away from the vacancies and the annihilation of Bi 6s and O 2p hybridized conduction bands near the vacancies. The spectroscopic experiments confirm the band gap increasing systematically with electron doping, with a maximal gap enhancement of 75% when the film's stoichiometry is reduced to BaBiO$_{2.75}$. The Raman and diffraction experiments show the suppression of the overall breathing distortion. The study unambiguously demonstrates the remarkable antidoping effect in a material without strong electron correlations and underscores the importance of bond disproportionation in realizing such an effect.

cond-mat.mtrl-sci↗

arXiv2020

Electrically pumped semiconductor laser with low spatial coherence and directional emission

We design and fabricate an on-chip laser source that produces a directional beam with low spatial coherence. The lasing modes are based on the axial orbit in a stable cavity and have good directionality. To reduce the spatial coherence of emission, the number of transverse lasing modes is maximized by fine-tuning the cavity geometry. Decoherence is reached in a few nanoseconds. Such rapid decoherence will facilitate applications in ultrafast speckle-free full-field imaging.

physics.optics↗

arXiv2020

Suppressing meta-holographic artifacts by laser coherence tuning

A metasurface hologram combines fine spatial resolution and large viewing angles with a planar form factor and compact size. However, it suffers coherent artifacts originating from electromagnetic cross-talk between closely packed meta-atoms and fabrication defects of nanoscale features. Here, we introduce an efficient method to remove all artifacts by fine-tuning the spatial coherence of illumination. Our method is implemented with a degenerate cavity laser, which allows precise, continuous tuning of spatial coherence over a wide range with little variation in emission spectrum and total power. We find the optimal degree of spatial coherence to remove the coherent artifacts of a meta-hologram while maintaining the image sharpness. This work paves the way to compact and dynamical holographic display free of coherent defects.

physics.optics↗

arXiv2020

Fluctuations and correlations of transmission eigenchannels in diffusive media

Selective excitation of a diffusive system's transmission eigenchannels enables manipulation of its internal energy distribution. The fluctuations and correlations of the eigenchannels' spatial profiles, however, remain unexplored so far. Here we show that the depth profiles of high-transmission eigenchannels exhibit low realization-to-realization fluctuations. Furthermore, our experimental and numerical studies reveal the existence of inter-channel correlations, which are significant for low-transmission eigenchannels. Because high-transmission eigenchannels are robust and independent from other eigenchannels, they can reliably deliver energy deep inside turbid media.

cond-mat.dis-nn↗

arXiv2020

Spatial structure of lasing modes in wave-chaotic semiconductor microcavities

We present experimental and numerical studies of broad-area semiconductor lasers with chaotic ray dynamics. The emission intensity distributions at the cavity boundaries are measured and compared to ray tracing simulations and numerical calculations of the passive cavity modes. We study two different cavity geometries, a D-cavity and a stadium, both of which feature fully chaotic ray dynamics. While the far-field distributions exhibit fairly homogeneous emission in all directions, the emission intensity distributions at the cavity boundary are highly inhomogeneous, reflecting the non-uniform intensity distributions inside the cavities. The excellent agreement between experiments and simulations demonstrates that the intensity distributions of wave-chaotic semiconductor lasers are primarily determined by the cavity geometry. This is in contrast to conventional Fabry-Perot broad-area lasers for which the intensity distributions are to a large degree determined by the nonlinear interaction of the lasing modes with the semiconductor gain medium.

physics.optics↗

arXiv2020

Accelerating speckle suppression by a degenerate cavity laser with an intracavity phase diffuser

Fast speckle suppression is crucial for time-resolved full-field imaging with laser illumination. Here, we introduce a method to accelerate the spatial decoherence of laser emission, achieving speckle suppression in the nanosecond integration time scale. The method relies on the insertion of an intracavity phase diffuser into a degenerate cavity laser to break the frequency degeneracy of transverse modes and broaden the lasing spectrum. The ultrafast decoherence of laser emission results in the reduction of speckle contrast to $3\%$ in less than 1 nanosecond.

physics.optics↗

arXiv2020

Multi-level scalar structure in complex system analyses

The geometrical structure is among the most fundamental ingredients in understanding complex systems. Is there any systematic approach in defining structures quantitatively, rather than illustratively? If yes, what are the basic principles to follow? By introducing the concept of extremal points at different scale levels, a multi-level dissipation element approach has been developed to define structures at different scale levels, in accordance with the concept of structure hierarchy. Each dissipation element can be characterized by the length scale and the scalar variance inside. Using the two-dimensional fractal Brownian motion as a benchmark case, the conditional mean of the scalar difference with respect to the length scale shows clearly a power law and the scaling exponent is in agreement with the Hurst number. For the 3D turbulence velocity component, the 1/3 scaling law can be represented. These results indicate the important linkage between the turbulence physics and ow structure, if well posed and defined. In principle, the multi-level dissipation element idea is generally applicable in analyzing other multiscale complex systems as well.

physics.flu-dyn↗

arXiv2020

Correlation-driven eightfold magnetic anisotropy in a two-dimensional oxide monolayer

Engineering magnetic anisotropy in two-dimensional systems has enormous scientific and technological implications. The uniaxial anisotropy universally exhibited by two-dimensional magnets has only two stable spin directions, demanding 180 degrees spin switching between states. We demonstrate a novel eightfold anisotropy in magnetic SrRuO3 monolayers by inducing a spin reorientation in (SrRuO3)1/(SrTiO3)N superlattices, in which the magnetic easy axis of Ru spins is transformed from uniaxial <001> direction (N = 1 and 2) to eightfold <111> directions (N = 3, 4 and 5). This eightfold anisotropy enables 71 and 109 degrees spin switching in SrRuO3 monolayers, analogous to 71 and 109 degrees polarization switching in ferroelectric BiFeO3. First-principle calculations reveal that increasing the SrTiO3 layer thickness induces an emergent correlation-driven orbital ordering, tuning spin-orbit interactions and reorienting the SrRuO3 monolayer easy axis. Our work demonstrates that correlation effects can be exploited to substantially change spin-orbit interactions, stabilizing unprecedented properties in two-dimensional magnets and opening rich opportunities for low-power, multi-state device applications.

cond-mat.mtrl-sci↗

arXiv2020

Accurate DOA Estimation Based on Real-Valued Singular Value Decomposition

In this paper, an accurate direction-of-arrival (DOA) estimator is developed based on the real-valued singular value decomposition (SVD) of covariance matrix. Unitary transform on the complex-valued covariance matrix is first applied, and then SVD performs on the resulting real-valued data matrix. The singular vector is then utilized with a weighted least squares (WLS) method to achieve DOA estimation. The performance of the proposed algorithm is compared with several state-of-the-art methods as well as the CRB. The results indicate the accuracy and effectiveness of the proposed method.

eess.SP↗

arXiv2020

InSphereNet: a Concise Representation and Classification Method for 3D Object

In this paper, we present an InSphereNet method for the problem of 3D object classification. Unlike previous methods that use points, voxels, or multi-view images as inputs of deep neural network (DNN), the proposed method constructs a class of more representative features named infilling spheres from signed distance field (SDF). Because of the admirable spatial representation of infilling spheres, we can not only utilize very fewer number of spheres to accomplish classification task, but also design a lightweight InSphereNet with less layers and parameters than previous methods. Experiments on ModelNet40 show that the proposed method leads to superior performance than PointNet and PointNet++ in accuracy. In particular, if there are only a few dozen sphere inputs or about 100000 DNN parameters, the accuracy of our method remains at a very high level (over 88%). This further validates the conciseness and effectiveness of the proposed InSphere 3D representation. Keywords: 3D object classification , signed distance field , deep learning , infilling sphere

cs.CV↗

arXiv2019

Creating and Controlling Complex Light

Random light fields -- commonly known as speckles -- demonstrate Rayleigh intensity statistics and only possess local correlations: which occur within the individual speckle grains. In this work, we develop an experimental method for customizing the intensity probability density function (PDF) of speckle patterns while simultaneously introducing non-local spatial correlations among the speckle grains. The various families of tailored speckle patterns -- created by our method -- can exhibit radically different topologies, statistics, and variable degrees of spatial order. Irrespective of their distinct statistical properties, however, all of these speckles are created by appropriately encoding high-order correlations into the phase front of a monochromatic laser beam with a spatial light modulator. In addition to our experimental demonstration, we explore both the theoretical and practical limitations on the extent to which the intensity PDF and the spatial intensity correlations can be manipulated concurrently in a speckle pattern. This work provides a versatile methodology for creating complex light fields and controlling their statistical properties with varied applications in microscopy, imaging, and optical manipulation.

physics.optics↗

arXiv2019

Deep learning of ultrafast pulses with a multimode fiber

Characterizing ultrashort optical pulses has always been a critical but difficult task, which has a broad range of applications. We propose and demonstrate a self-referenced method of characterizing ultrafast pulses with a multimode fiber. The linear and nonlinear speckle patterns formed at the distal end of a multimode fiber are used to recover the spectral amplitude and phase of an unknown pulse. We deploy a deep learning algorithm for phase recovery. The diversity of spatial and spectral modes in a multimode fiber removes any ambiguity in the sign of the recovered spectral phase. Our technique allows for single-shot pulse characterization in a simple experimental setup. This work reveals the potential of multimode fibers as a versatile and multi-functional platform for optical sensing.

physics.optics↗