arXiv subjects

Xiaoxuan Ma

Publications and source records attributed to Xiaoxuan Ma.

49 records · Page 3Linked to original sources

arXiv2022

Magnetically Tuned Continuous Transition from Weak to Strong Coupling in Terahertz Magnon Polaritons

Depending on the relative rates of coupling and dissipation, a light-matter coupled system is either in the weak- or strong-coupling regime. Here, we present a unique system where the coupling rate continuously increases with an externally applied magnetic field while the dissipation rate remains constant, allowing us to monitor a weak-to-strong coupling transition as a function of magnetic field. We observed a Rabi splitting of a terahertz magnon mode in yttrium orthoferrite above a threshold magnetic field of ~14 T. Based on a microscopic theoretical model, we show that with increasing magnetic field the magnons transition into magnon polaritons through an exceptional point, which will open up new opportunities for in situ control of non-Hermitian systems.

cond-mat.mes-hall↗

arXiv2022

Reconfigurable Application-Specific Photonic Integrated Circuit for solving Partial Differential Equations

Solving mathematical equations faster and more efficiently has been a Holy Grail for centuries for scientists and engineers across all disciplines. While electronic digital circuits have revolutionized equation solving in recent decades, it has become apparent that performance gains from brute-force approaches of compute-solvers are quickly saturating over time. Instead, paradigms that leverage the universes natural tendency to minimize a systems free energy, such as annealers or Ising Machines, are being sought after due to favorable complexity scaling. Here we introduce a programmable analog solver leveraging the mathematical formal equivalence between Maxwells equations and photonic circuitry. It features a mesh network of nanophotonic beams to find solutions to partial differential equations. As an example, we designed, fabricated, and demonstrated a novel application-specific photonic integrated circuit comprised of electro-optically reconfigurable nodes, and experimentally validated 90% accuracy with respect to a commercial solver. Finally, we tested this photonic integrated chip performance by simulating thermal diffusion on a spacecrafts heat shield during re-entry to a planets atmosphere. The programmable light-circuitry presented herein offers a facile route for solving complex problems and thus will have profound potential applications across many scientific and engineering fields.

physics.optics↗

arXiv2022

VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual Data

While monocular 3D pose estimation seems to have achieved very accurate results on the public datasets, their generalization ability is largely overlooked. In this work, we perform a systematic evaluation of the existing methods and find that they get notably larger errors when tested on different cameras, human poses and appearance. To address the problem, we introduce VirtualPose, a two-stage learning framework to exploit the hidden "free lunch" specific to this task, i.e. generating infinite number of poses and cameras for training models at no cost. To that end, the first stage transforms images to abstract geometry representations (AGR), and then the second maps them to 3D poses. It addresses the generalization issue from two aspects: (1) the first stage can be trained on diverse 2D datasets to reduce the risk of over-fitting to limited appearance; (2) the second stage can be trained on diverse AGR synthesized from a large number of virtual cameras and poses. It outperforms the SOTA methods without using any paired images and 3D poses from the benchmarks, which paves the way for practical applications. Code is available at https://github.com/wkom/VirtualPose.

cs.CV↗

arXiv2022

Electrical Programmable Multi-Level Non-volatile Photonic Random-Access Memory

Photonic Random-Access Memories (P-RAM) are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data links. Emerging Phase Change Materials (PCMs) have been showed multilevel memory capability, but demonstrations still yield relatively high optical loss and require cumbersome WRITE-ERASE approaches increasing power consumption and system package challenges. Here we demonstrate a multi-state electrically-programmed low-loss non-volatile photonic memory based on a broadband transparent phase change material (Ge2Sb2Se5, GSSe) with ultra-low absorption in the amorphous state. A zero-static-power and electrically-programmed multi-bit P-RAM is demonstrated on a silicon-on-insulator platform, featuring efficient amplitude modulation up to 0.2 dB/μm and an ultra-low insertion loss of total 0.12 dB for a 4-bit memory showing a 100x improved signal to loss ratio compared to other phase-change-materials based photonic memories. We further optimize the positioning of dual micro-heaters validating performance tradeoffs. Experimentally we demonstrate a half-a million cyclability test showcasing the robust approach of this material and device. Low-loss photonic retention-of-state adds a key feature for photonic functional and programmable circuits impacting many applications including neural networks, LiDAR, and sensors for example.

physics.optics↗

arXiv2021

Giant shifts of crystal-field excitations with temperature as consequence of internal magnetic exchange fields

Crystal-field excitations, for example in transition-metal oxides where a rare-earth element is used as a spacer between the transition-metal-oxide tetrahedra and octahedra, are assumed to be extremely robust with respect to external perturbations such as temperature. Using inelastic neutron scattering experiments, a giant shift of the energy of the lowest crystal-field excitation of Er3+ (4I15/2) in ErFeO3 from 0.30(2) meV to 0.75(2) meV was measured below the magnetic-ordering temperature of erbium at 4.1 K. Quantum-mechanical point-charge calculations of the crystal-field levels indicate that the shift is caused by the internal magnetic field created by the erbium spins themselves, which causes a Zeeman splitting of the erbium 4f electronic levels, and therefore a change in the energies of crystal-field transitions. To verify this explanation, the effect of an external magnetic field on the crystal-field excitations was measured by inelastic neutron scattering and compared to the field-dependent point-charge calculations. The existence of an internal magnetic exchange interaction will have implications for a deeper understanding of a broader group of phenomena such as multiferroic properties or spin frustration, which are a consequence of various competing electronic and magnetic exchange interactions.

cond-mat.str-el↗

arXiv2021

Context Modeling in 3D Human Pose Estimation: A Unified Perspective

Estimating 3D human pose from a single image suffers from severe ambiguity since multiple 3D joint configurations may have the same 2D projection. The state-of-the-art methods often rely on context modeling methods such as pictorial structure model (PSM) or graph neural network (GNN) to reduce ambiguity. However, there is no study that rigorously compares them side by side. So we first present a general formula for context modeling in which both PSM and GNN are its special cases. By comparing the two methods, we found that the end-to-end training scheme in GNN and the limb length constraints in PSM are two complementary factors to improve results. To combine their advantages, we propose ContextPose based on attention mechanism that allows enforcing soft limb length constraints in a deep network. The approach effectively reduces the chance of getting absurd 3D pose estimates with incorrect limb lengths and achieves state-of-the-art results on two benchmark datasets. More importantly, the introduction of limb length constraints into deep networks enables the approach to achieve much better generalization performance.

cs.CV↗

arXiv2021

All-Chalcogenide Programmable All-Optical Deep Neural Networks

Deeplearning algorithms are revolutionising many aspects of modern life. Typically, they are implemented in CMOS-based hardware with severely limited memory access times and inefficient data-routing. All-optical neural networks without any electro-optic conversions could alleviate these shortcomings. However, an all-optical nonlinear activation function, which is a vital building block for optical neural networks, needs to be developed efficiently on-chip. Here, we introduce and demonstrate both optical synapse weighting and all-optical nonlinear thresholding using two different effects in a chalcogenide material photonic platform. We show how the structural phase transitions in a wide-bandgap phase-change material enables storing the neural network weights via non-volatile photonic memory, whilst resonant bond destabilisation is used as a nonlinear activation threshold without changing the material. These two different transitions within chalcogenides enable programmable neural networks with near-zero static power consumption once trained, in addition to picosecond delays performing inference tasks not limited by wire charging that limit electrical circuits; for instance, we show that nanosecond-order weight programming and near-instantaneous weight updates enable accurate inference tasks within 20 picoseconds in a 3-layer all-optical neural network. Optical neural networks that bypass electro-optic conversion altogether hold promise for network-edge machine learning applications where decision-making in real-time are critical, such as for autonomous vehicles or navigation systems such as signal pre-processing of LIDAR systems.

physics.optics↗

arXiv2021

Ultrastrong Magnon-Magnon Coupling Dominated by Antiresonant Interactions

Exotic quantum vacuum phenomena are predicted in cavity quantum electrodynamics (QED) systems with ultrastrong light-matter interactions. Their ground states are predicted to be vacuum squeezed states with suppressed quantum fluctuations. The source of such phenomena are antiresonant terms in the Hamiltonian, yet antiresonant interactions are typically negligible compared to resonant interactions in light-matter systems. We report an unusual coupled matter-matter system of magnons that can simulate a unique cavity QED Hamiltonian with coupling strengths that are easily tunable into the ultrastrong coupling regime and with dominant antiresonant terms. We found a novel regime where vacuum Bloch-Siegert shifts, the hallmark of antiresonant interactions, greatly exceed analogous frequency shifts from resonant interactions. Further, we theoretically explored the system's ground state and calculated up to 5.9 dB of quantum fluctuation suppression. These observations demonstrate that magnonic systems provide an ideal platform for simulating exotic quantum vacuum phenomena predicted in ultrastrongly coupled light-matter systems.

quant-ph↗

arXiv2020

Analog Computing with Metatronic Circuits

Analog photonic solutions offer unique opportunities to address complex computational tasks with unprecedented performance in terms of energy dissipation and speeds, overcoming current limitations of modern computing architectures based on electron flows and digital approaches. The lack of modularization and lumped element reconfigurability in photonics has prevented the transition to an all-optical analog computing platform. Here, we explore a nanophotonic platform based on epsilon-near-zero materials capable of solving in the analog domain partial differential equations (PDE). Wavelength stretching in zero-index media enables highly nonlocal interactions within the board based on the conduction of electric displacement, which can be monitored to extract the solution of a broad class of PDE problems. By exploiting control of deposition technique through process parameters, we demonstrate the possibility of implementing the proposed nano-optic processor using CMOS-compatible indium-tin-oxide, whose optical properties can be tuned by carrier injection to obtain programmability at high speeds and low energy requirements. Our nano-optical analog processor can be integrated at chip-scale, processing arbitrary inputs at the speed of light.

physics.optics↗

arXiv2020

Induced Homomorphism Kirchhoffs Law in Photonics

When solving, modelling or reasoning about complex problems, it is usually convenient to use the knowledge of a parallel physical system for representing it. This is the case of lumped-circuit abstraction, which can be used for representing mechanical and acoustic systems, thermal and heat-diffusion problems and in general partial differential equations. Integrated photonic platforms hold the prospect to perform signal processing and analog computing inherently, by mapping into hardware specific operations which relies on the wave-nature of their signals, without trusting on logic gates and digital states like electronics. Although, the distributed nature of photonic platforms leads to the absence of an equivalent approximation to Kirchhoffs law, the main principle used for representing physical systems using circuits. Here we argue that in absence of a straightforward parallelism and homomorphism can be induced. We introduce a photonic platform capable of mimicking Kirchhoffs law in photonics and used as node of a finite difference mesh for solving partial differential equation using monochromatic light in the telecommunication wavelength. We experimentally demonstrate generating in one-shot discrete solutions of a Laplace partial differential equation, with an accuracy above 95% relative to commercial solvers, for an arbitrary set of boundary conditions. Our photonic engine can provide a route to achieve chip-scale, fast (10s of ps), and integrable reprogrammable accelerators for the next generation hybrid high performance computing.

physics.optics↗

arXiv2019

A Lateral MOS-Capacitor Enabled ITO Mach-Zehnder Modulator for Beam Steering

Here, we experimentally demonstrate an Indium Tin Oxide (ITO) Mach-Zehnder interferometer heterogeneously integrated in silicon photonics. The phase shifter section is realized in a novel lateral MOS configuration, which, due to favorable electrostatic overlap, leads to efficient modulation (VπL = 63 Vum). This is achieved by (i) selecting a strong index changing material (ITO) and (ii) improving the field overlap as verified by the electrostatic field lines. Furthermore, we show that this platform serves as a building block in an endfire silicon photonics optical phased array (OPA) with a half-wavelength pitch within the waveguides with anticipated performance, including narrow main beam lobe (<3°) and >10 dB suppression of the side lobes, while electrostatically steering the emission profile up to plus/minus 80°, and if further engineered, can lead not only towards nanosecond-fast beam steering capabilities in LiDAR systems but also in holographic display, free-space optical communications, and optical switches.

physics.app-ph↗

arXiv2018

Large Perpendicular Magnetocrystalline Anisotropy at Fe/Pb(001) interface

Search for ultrathin magnetic film with large perpendicular magnetocrystalline anisotropy (PMA) has been inspired for years by the continuous miniaturization of magnetic units in spintronics devices. The common magnetic materials used in research and applications are based on Fe because the pure Fe metal is the best yet simple magnetic material from nature. Through systematic first-principles calculations, we explored the possibility to produce large PMA with ultrathin Fe on non-noble and non-magnetic Pb(001) substrate. Interestingly, huge magnetocrystalline anisotropy energy (MAE) of 7.6 meV was found in Pb/Fe/Pb(001) sandwich structure with only half monolayer Fe. Analysis of electronic structures reveals that the magnetic proximity effect at the interface is responsible for this significant enhancement of MAE. The MAE further increases to 13.6 meV with triply repeated capping Pb and intermediate Fe layers. Furthermore, the MAE can be tuned conveniently by charge injection.

cond-mat.mtrl-sci↗

arXiv2018

Invariant Wide Bandgaps in Honeycomb Monolayer and Single-Walled Nanotubes of IIB-VI Semiconductors

Search for low-dimensional materials with unique electronic properties is important for the development of electronic devices in nano scale. Through systematic first-principles calculations, we found that the band gaps of the two-dimensional honeycomb monolayers and one-dimensional single-walled nanotubes of IIB-VI semiconductors (ZnO, CdO, ZnS and CdS) are nearly chirality-independent and weakly diameter-dependent. Based on analysis of the electronic structures, it was found that the conduction band minimum is contributed by the spherically symmetric $s$ orbitals of cations and the valence band maximum is dominated by the in-plane $(d_{xy}-p_y)$ and $(d_{x^2-y^2}-p_x)$ hybridizations. These electronic states are robust against radius curvature, resulting in the invariant feature of the band gaps for the structures changing from honeycomb monolayer to single-walled nanotubes. The band gaps of these materials range from 2.3 eV to 4.7 eV, which is of potential applications in electronic devices and optoelectronic devices. Our studies show that searching for and designing specific electronic structures can facilitate the process of exploring novel nanomaterials for future applications.

cond-mat.mtrl-sci↗