arXiv subjects

Qiang Song

Publications and source records attributed to Qiang Song.

13 recordsLinked to original sources

arXiv2026

Differentiable eigendecomposition-free RCWA for full-tensor anisotropic photonics

Full-tensor anisotropy transforms rigorous coupled-wave analysis (RCWA) into a large, fully coupled non-Hermitian eigenproblem, making eigendecomposition expensive and difficult to differentiate. We introduce a differentiable, eigendecomposition-free RCWA framework for spatially patterned media with fully coupled permittivity tensors, using boundary fields rather than internal eigenmodes as the layer representation. A boundary-value cascade constructs scattering operators directly from these fields, enabling automatic differentiation and efficient GPU execution. Benchmarks against finite-element and transfer-matrix solutions show close agreement in scattering responses, while automatic-differentiation gradients agree with finite differences and enable topology optimization. At 529 Fourier harmonics, layer construction is 22.8 times faster than conventional eigendecomposition on the same GPU. Our framework offers a general computational route toward scalable forward modeling and inverse design in anisotropic photonic systems.

physics.optics↗

arXiv2026

Volumetric Optical Scattering Neural Networks

Optical neural networks offer a route to low-latency and energy-efficient inference by encoding computation in light propagation. However, most existing implementations rely on planar photonic circuits or discretely spaced diffractive layers, restricting volumetric integration and imposing stringent alignment requirements. Here we demonstrate a volumetric optical scattering neural network (OSNN) in which densely packed weak scatterers form a three-dimensional, locally connected optical computing medium. In contrast to fully connected diffractive architectures, the OSNN uses near-field scattering interactions, described under the first-Born approximation, to compress optical interconnections into a monolithic volume. We implement this concept using resilient inverse design and two-photon nanolithography, yielding OSNN devices with a volume of ~$3.8*10^{-4}mm^{3}$ and a record-breaking neuron density of $1.0*10^{9}/mm^{3}$. Experimentally, the fabricated classifier achieves $94.8\%$ blind-test accuracy on MNIST, while the imager performs optical compressed imaging with a $1-{\mu}m$ effective resolution and average FSIM values of $0.93$ on Fashion-MNIST and $0.91$ on VesselMNIST3D. OSNN paves the way for ultra-dense, ultra-compact, and efficient optical computing, creating a universal platform for embedded optical intelligence and promising widespread application in AI fields ranging from autonomous driving to medical diagnosis.

physics.optics↗

arXiv2025

Ultracompact Wide-FOV Near-infrared Camera with Wafer-level Manufactured Meta-Aspheric Lens

Overcoming the trade-off between wide field of view (FOV) and compactness remains a central challenge for integrating near-infrared (NIR) imaging into smartphones and AR glasses. Existing refractive NIR optics cannot simultaneously achieve ultra-wide angles above 100{\deg} and ultrathin total track length (TTL) below 5 mm, limiting their use in portable devices. Here, we present a wafer-level-manufactured meta-aspheric lens (MAL) that achieves a 101.5{\deg} FOV, 3.39 mm TTL, and F/1.64 aperture within a compact volume of 0.02 cubic centimeters. Unlike previous hybrid lenses with separate refractive and diffractive components, our MAL features a fully integrated structure, which enables a compact form factor. This integration also simplifies fabrication, allowing high-throughput production via micrometer-level precision alignment and bonding on a single wafer, with only one dicing step and no need for additional mechanical fixtures. Furthermore, the design process explicitly considers manufacturability and accurately models metalens dispersion, ensuring that experimental performance matches simulated results. We validate our MAL through both direct and computational imaging experiments. Despite its small form factor, our scalable MAL demonstrates strong NIR imaging performance in blood vessel imaging, eye tracking, and computational pixel super-resolution tasks. This scalable MAL technology establishes a new benchmark for high-performance, miniaturized NIR imaging and opens the door to next-generation smartphone and AR optical systems.

physics.optics↗

arXiv2025

Unfolding Framework with Complex-Valued Deformable Attention for High-Quality Computer-Generated Hologram Generation

Computer-generated holography (CGH) has gained wide attention with deep learning-based algorithms. However, due to its nonlinear and ill-posed nature, challenges remain in achieving accurate and stable reconstruction. Specifically, ($i$) the widely used end-to-end networks treat the reconstruction model as a black box, ignoring underlying physical relationships, which reduces interpretability and flexibility. ($ii$) CNN-based CGH algorithms have limited receptive fields, hindering their ability to capture long-range dependencies and global context. ($iii$) Angular spectrum method (ASM)-based models are constrained to finite near-fields.In this paper, we propose a Deep Unfolding Network (DUN) that decomposes gradient descent into two modules: an adaptive bandwidth-preserving model (ABPM) and a phase-domain complex-valued denoiser (PCD), providing more flexibility. ABPM allows for wider working distances compared to ASM-based methods. At the same time, PCD leverages its complex-valued deformable self-attention module to capture global features and enhance performance, achieving a PSNR over 35 dB. Experiments on simulated and real data show state-of-the-art results.

cs.CV↗

arXiv2024

Achromatic single-layer hologram

Phase retrieval is a fundamental technique of advanced optical technologies, enabling precise control over wavefront properties. A persistent challenge in diffractive optical element (DOE) design is that a single hologram typically operates within a single wavelength or color channel, limiting it to monochromatic image generation. This limitation in channel capacity significantly restricts the applicability of DOE in optical applications. In this study, we propose a design strategy for full-color, single-layer hologram based on a variable-scale diffraction model. By imposing strict constraints in Fourier domain and reducing depth of focus (DOF), we achieve the simultaneous encryption and storage of red, green, and blue channel information within a single achromatic hologram. This strategy facilitates color separation in large-depth 3D holography and enables achromatic full-color image displays. We demonstrated full-color holographic video playback at a full refresh rate of 60 Hz, achieving a temporal resolution three times greater than that of existing methods. Furthermore, we successfully fabricated achromatic, twin-image-free, full-color binary pure-phase DOEs at low cost. This achromatic strategy addresses the demands across various fields in optics, including high-refresh-rate full-color displays, high-density optical information storage, advanced optical security, high-reusability holographic metasurface optical element, and high-performance achromatic metalenses.

physics.optics↗

arXiv2024

Phase space framework enables a variable-scale diffraction model for coherent imaging and display

The fast algorithms in Fourier optics have invigorated multifunctional device design and advanced imaging technologies. However, the necessity for fast computations has led to limitations in the widely used conventional Fourier methods, manifesting as fixed size image plane at a certain diffraction distance. These limitations pose challenges in intricate scaling transformations, 3D reconstructions and full-color displays. Currently, there is a lack of effective solutions, often resorting to pre-processing that compromise fidelity. In this paper, leveraging a higher-dimensional phase space method, we present a universal framework allowing for customized diffraction calculation methods. Within this framework, we establish a variable-scale diffraction computation model which allows the adjustment of the size of the image plane and can be operated by fast algorithms. We validate the model's robust variable-scale capabilities and its aberration automatic correction capability for full-color holography, achieving high fidelity. The large-magnification tomography experiment demonstrates that this model provides a superior solution for holographic 3D reconstruction. In addition, this model is applied to achieve full-color metasurface holography with near-zero crosstalk, showcasing its versatile applicability at nanoscale. Our model presents significant prospects for applications in the optics community, such as beam shaping, computer-generated holograms (CGHs), augmented reality (AR), metasurface optical elements (MOEs) and advanced holographic head-up display (HUD) systems.

physics.app-ph↗

arXiv2023

B-Spine: Learning B-Spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

Spinal curvature estimation is important to the diagnosis and treatment of the scoliosis. Existing methods face several issues such as the need of expensive annotations on the vertebral landmarks and being sensitive to the image quality. It is challenging to achieve robust estimation and obtain interpretable results, especially for low-quality images which are blurry and hazy. In this paper, we propose B-Spine, a novel deep learning pipeline to learn B-spline curve representation of the spine and estimate the Cobb angles for spinal curvature estimation from low-quality X-ray images. Given a low-quality input, a novel SegRefine network which employs the unpaired image-to-image translation is proposed to generate a high quality spine mask from the initial segmentation result. Next, a novel mask-based B-spline prediction model is proposed to predict the B-spline curve for the spine centerline. Finally, the Cobb angles are estimated by a hybrid approach which combines the curve slope analysis and a curve-based regression model. We conduct quantitative and qualitative comparisons with the representative and SOTA learning-based methods on the public AASCE2019 dataset and our new proposed CJUH-JLU dataset which contains more challenging low-quality images. The superior performance on both datasets shows our method can achieve both robustness and interpretability for spinal curvature estimation.

eess.IV↗

arXiv2021

Establishment of the fundamental phase-to-polarization link in classical optics

Vector polarization induced by a change in scalar phase has been far beyond our understanding of the relationship between polarization and phase in classical optics due to the entanglement of inherent polarized modes of light beams. To overcome this limitation, we establish this miraculous relationship by the principle of phase vectorization, which can transform three particular phases into linear, circular and elliptical polarizations. A polarized-spatial light modulator based on the principle of phase vectorization can be achieved using a phase-only spatial light modulator, which not only enables pixel-level polarization manipulation of light beams in a real-time dynamic way but also simultaneously retains complete phase control. This work demonstrates the phase-to-polarization link and reports the creation of polarized-spatial light modulator, which will transform our view of the natural properties of light beam and pave the way for the era of vector optics.

physics.optics↗

arXiv2019

LED illumination faceted Fresnel DOEs generating perceived virtual 3D vision

An approach for the optimization and synthesis of a phase-only faceted Fresnel type diffractive optical element (FDOE) generating 3D virtual images is proposed. The FDOE is a transmissive Fresnel type DOE array, which produces the perception of a customized floating 3D virtual image behind the FDOE when illuminated with a divergent monochromatic Light Emitter Diode (LED) source. Each DOE unit of the FDOE is optimized with a modified iterative Fourier transform algorithm (M-IFTA). Each unit of the FDOE locally deflects the incident light to the same position to form a designated view of the target plane. The FDOE is fabricated using our home-built parallel write photo-lithography machine. Numerical simulations and optical experiments are performed to verify the proposed design method. Photos of the generated image are also presented. This work can find applications in optical security, anti-counterfeiting, and holographic display.

physics.optics↗

arXiv2018

Free-space creation of ultralong anti-diffracting light beam with multiple energy oscillations adjusted using optical pen

A light beam propagating with an infinite anti-diffracting distance requires infinite power to preserve its shape. However, the fundamental barrier of finite power in free space has made the problem of diffraction insurmountable over the past few decades. Here, to overcome this limitation, we report an approach that employs the multiple energy oscillation mechanism, thereby permitting the creation of a light beam with an ultralong anti-diffracting distance in free space. The anti-diffracting distance is no longer restricted by finite power in free space but instead depends on the number of energy oscillations. This unprecedented propagation behavior is attributed to a new understanding of non-diffractive light beam: when an anti-diffracting light beam completely discharges its energy, it cannot recharge again. A versatile optical pen is therefore developed to manipulate the number, amplitude, position and phase of energy oscillations for an arbitrary numerical aperture of a focusing lens so that energy recharge can occur in free space and multiple energy oscillations can be realized. A light beam with a tunable number of energy oscillations is eventually generated in free space and propagates along a wavy trajectory. This work will enable extending non-diffractive light beams to an expanded realm and facilitate extensive developments in optics and other research fields, such as electronics and acoustics.

physics.optics↗

arXiv2017

Joint Domain Based Massive Access for Small Packets Traffic of Uplink Wireless Channel

The fifth generation (5G) communication scenarios such as the cellular network and the emerging machine type communications will produce massive small packets. To support massive connectivity and avoid signaling overhead caused by the transmission of those small packets, this paper proposes a novel method to improve the transmission efficiency for massive connections of wireless uplink channel. The proposed method combines compressive sensing (CS) with power domain NOMA jointly, especially neither the scheduling nor the centralized power allocation is necessary in the method. Both the analysis and simulation show that the method can support up to two or three times overloading.

cs.IT↗

arXiv2014

DNA methylation variation in Arabidopsis has a genetic basis and shows evidence of local adaptation

Epigenome modulation in response to the environment potentially provides a mechanism for organisms to adapt, both within and between generations. However, neither the extent to which this occurs, nor the molecular mechanisms involved are known. Here we investigate DNA methylation variation in Swedish Arabidopsis thaliana accessions grown at two different temperatures. Environmental effects on DNA methylation were limited to transposons, where CHH methylation was found to increase with temperature. Genome-wide association mapping revealed that the extensive CHH methylation variation was strongly associated with genetic variants in both cis and trans, including a major trans-association close to the DNA methyltransferase CMT2. Unlike CHH methylation, CpG gene body methylation (GBM) on the coding region of genes was not affected by growth temperature, but was instead strongly correlated with the latitude of origin. Accessions from colder regions had higher levels of GBM for a significant fraction of the genome, and this was correlated with elevated transcription levels for the genes affected. Genome-wide association mapping revealed that this effect was largely due to trans-acting loci, a significant fraction of which showed evidence of local adaptation. These findings constitute the first direct link between DNA methylation and adaptation to the environment, and provide a basis for further dissecting how environmentally driven and genetically determined epigenetic variation interact and influence organismal fitness.

q-bio.GN↗

arXiv2010

Transconductance and Coulomb blockade properties of in-plane grown carbon nanotube field effect transistors

Single electron transistors (SETs) made from single wall carbon nanotubes (SWCNTs) are promising for quantum electronic devices operating with ultra-low power consumption and allow fundamental studies of electron transport. We report on SETs made by registered in-plane growth utilizing tailored nanoscale catalyst patterns and chemical vapor deposition. Metallic SWCNTs have been removed by an electrical burn-in technique and the common gate hysteresis was removed using PMMA and baking, leading to field effect transistors with large on/off ratios up to 10^5. Further segmentation into 200 nm short semiconducting SWCNT devices created quantum dots which display conductance oscillations in the Coulomb blockade regime. The demonstrated utilization of registered in-plane growth opens possibilities to create novel SET device geometries which are more complex, i.e. laterally ordered and scalable, as required for advanced quantum electronic devices.

cond-mat.mes-hall↗