Real-time Holography Research Articles

Complex-valued generative adversarial network for real-time and high-quality computer-generated holography

Complex-valued generative adversarial network for real-time and high-quality computer-generated holography

UV-enhanced photorefractive response rate in a thin-film lithium niobate microdisk.

The photorefractive (PR) effect plays a critical role in emerging photonic technologies, including dynamic volume holography and on-chip all-optical functionalities. Nevertheless, its slow response rate has posed a significant obstacle to its practical application. Here, we experimentally demonstrate the enhancement of the PR response rate in a high-Q thin-film lithium niobate (TFLN) microdisk under UV light irradiation. At an irradiation intensity of 30 mW/cm2, the PR effect achieves a high response bandwidth of approximately 256 kHz. By employing this UV-assisted PR effect, we have achieved rapid laser-cavity locking and self-stabilization, where perturbations are automatically compensated. This technique paves the way toward real-time dynamic holography, editable photonic devices on a lithium niobate platform, and high-speed all-optical information processing.

Real-time nearfield acoustic holography using particle velocity.

In this paper, a series of impulse response functions between acoustic quantities on the source plane and particle velocity on the hologram plane are derived. In virtue of these functions, real-time nearfield acoustic holography (RT-NAH) is extended from pressure-based to particle velocity. Pressure, normal velocity, acceleration, and displacement radiated from planar sources can be reconstructed by measuring time-dependent particle velocity signals on the hologram plane. A simulation of an excited aluminum plate is performed to evaluate the difference in accuracy between RT-NAHs based on pressure and based on particle velocity. This study also examines the impact of impulse response functions on the reconstruction results, allowing for detailed analysis of the reconstruction accuracy based on these functions. The simulation results demonstrate that using RT-NAH based on particle velocity obtains significantly higher-accuracy reconstruction results when reconstructing normal velocity and displacement and slightly more accurate reconstructed pressure and normal acceleration.

What do spore particles look like - use of real-time measurements and holography imaging to view spore particles from four bioaerosol generators

What do spore particles look like - use of real-time measurements and holography imaging to view spore particles from four bioaerosol generators

Real time holography for higher spin theories

Real time holography is studied in the context of the embedding space formalism. In the first part of this paper, we present matching conditions for on-shell integer spin fields when going from Euclidean to Lorentzian signature on AdS background. Using the BTZ black hole as an example, we discuss various ways of lifting the physical solution from the AdS surface to the whole embedding space. The BTZ propagator for higher spin field is expressed elegantly in terms of the embedding coordinates. In the second part of the paper, we develop the proposed duality between higher spin theory and vector models. We obtain a specific map between the field configurations of these two theories in real time, so called Lorentzian AdS/CFT map. We conclude by exploring the matching conditions for higher spin fields satisfying the proposed bulk quadratic action. The physical and ghost modes can be treated independently during the Wick rotation; only physical modes are considered to be external modes.

Real-time millimeter wave holography with an arrayed detector.

Millimeter and terahertz wave imaging has emerged as a powerful tool for applications such as security screening, biomedical imaging, and material analysis. However, intensity images alone are often insufficient for detecting variations in the dielectric constant of a sample, and extraction of material properties without additional phase information requires extensive prior knowledge of the sample. Digital holography provides a means for intensity-only detectors to reconstruct both amplitude and phase images. Here we utilize a commercially available source and detector array, both operating at room temperature, to perform digital holography in real-time for the first time in the mm-wave band (at 290 GHz). We compare the off-axis and phase-shifting approaches to digital holography and discuss their trade-offs and practical challenges in this regime. Owing to the low pixel count, we find phase-shifting holography to be the most practical and high fidelity approach for such commercial mm-wave cameras even under real-time operational requirements.

Real-time acoustic holography with physics-reinforced contrastive learning for acoustic field reconstruction

Acoustic holography (AH) provides a promising technique for arbitrary acoustic field reconstruction, supporting many applications like robotic micro-nano manipulation, neuromodulation, volumetric imaging, and virtual reality. In AH, three-dimensional (3D) acoustic fields quantified with complex-valued acoustic pressures are reconstructed by virtue of two-dimensional (2D) acoustic holograms. Phase-only hologram (POH) is recently regarded as an energy-efficient way for AH, which is typically implemented by a dynamically programmable phased array of transducers (PATs). As a result, spatiotemporal precise acoustic field reconstruction is enabled by precise, dynamic, and individual actuation of PAT. Thus, 2D POH is required per arbitrary acoustic fields, which can be viewed as a physical inverse problem. However, solving the aforementioned physical inverse problem in numerical manners poses challenges due to its non-linear, high-dimensional, and complex coupling natures. The existing iterative algorithms like the iterative angular spectrum approach (IASA) and iterative backpropagation (IB) still suffer from speed-accuracy trade-offs. Hence, this paper explores a novel physics-iterative-reinforced deep learning method, in which frequency-argument contrastive learning is proposed facilitated by the inherent physical nature of AH, and the energy conservation law is under consideration. The experimental results demonstrate the effectiveness of the proposed method for acoustic field reconstruction, highlighting its significant potential in the domain of acoustics, and pushing forward the combination of physics into deep learning.

Real-Time Acoustic Holography With Physics-Based Deep Learning for Robotic Manipulation

Real-Time Acoustic Holography With Physics-Based Deep Learning for Robotic Manipulation

Asymmetrical neural network for real-time and high-quality computer-generated holography.

Computer-generated holography based on neural network holds great promise as a real-time hologram generation method. However, existing neural network-based approaches prioritize lightweight networks to achieve real-time display, which limits their capacity for network fitting. Here, we propose an asymmetrical neural network with a non-end-to-end structure that enhances fitting capacity and delivers superior real-time display quality. The non-end-to-end structure decomposes the overall task into two sub-tasks: phase prediction and hologram encoding. The asymmetrical design tailors each sub-network to its specific sub-task using distinct basic net-layers rather than relying on similar net-layers. This method allows for a sub-network with strong feature extraction and inference capabilities to match the phase predictor, while another sub-network with efficient coding capability matches the hologram encoder. By matching network functions to tasks, our method enhances the overall network's fitting capacity while maintaining a lightweight architecture. Both numerical reconstructions and optical experiments validate the reliability and effectiveness of our proposed method.

Reconstruction of transient acoustic field using sparse real-time near-field acoustic holography

A sparse real-time near-field acoustic holography method is proposed to precisely and stably reconstruct a transient sound field. By a time-domain impulse response function, a time domain convolution equation between the pressure time-wavenumber spectra on the hologram and reconstruction planes is first established. Then, a smoothed ℓ0-norm optimization algorithm is applied to solve the serious ill-conditioned problem of the inverse process to get the pressure time-wavenumber spectrum of the reconstruction plane. The key part of solving this problem is to approximate replace the discontinuous ℓ0-norm by using a suitable continuous Gaussian function family, and a steepest ascent algorithm is introduced to minimize the continuous function for obtaining the optimal solution. Finally, the pressure time-wavenumber spectra of the reconstruction plane for all wavenumbers at all times are solved, and the corresponding time-dependent pressures are gained by the two-dimensional space inverse Fourier transform. A numerical simulation is conducted to observe the reconstruction capacity of the proposed method. The simulation effect prove that the proposed method can accurately reconstruct the transient sound field, and its reconstruction results are compared to those of the real-time near-field acoustic holography (RTNAH) with Tikhonov regularization and YALL1 modal for verifying the superiority of the proposed method. The YALL1 module utilizes an alternating direction algorithm for solving the ℓ1 minimization problems. Several parameters including the noise, position of the holograph plane and two initialization values are discussed in the simulation. The comparison and discussion results show that the reconstruction effect of the proposed method is much better than those of RTNAH with Tikhonov regularization and YALL1 modal under different parameter configurations. An experiment with a percussive steel plate is implemented for further validating the effectivity of the proposed method.

Diffraction model-driven neural network trained using hybrid domain loss for real-time and high-quality computer-generated holography.

Learning-based computer-generated holography (CGH) has demonstrated great potential in enabling real-time, high-quality holographic displays. However, most existing learning-based algorithms still struggle to produce high-quality holograms, due to the difficulty of convolutional neural networks (CNNs) in learning cross-domain tasks. Here, we present a diffraction model-driven neural network (Res-Holo) using hybrid domain loss for phase-only hologram (POH) generation. Res-Holo utilizes the weights of the pretrained ResNet34 as the initialization during the encoder stage of the initial phase prediction network to extract more generic features and also to help prevent overfitting. Also, frequency domain loss is added to further constrain the information that the spatial domain loss is insensitive. The peak signal-to-noise ratio (PSNR) of the reconstructed image is improved by 6.05 dB using hybrid domain loss compared to using spatial domain loss alone. Simulation results show that the proposed Res-Holo can generate high-fidelity 2 K resolution POHs with an average PSNR of 32.88 dB at 0.014 seconds/frame on the DIV2K validation set. Both monochrome and full-color optical experiments show that the proposed method can effectively improve the quality of reproduced images and suppress image artifacts.

Real-time noise-free inline self-interference incoherent digital holography with temporal geometric phase multiplexing

In this paper, we propose a real-time incoherent digital holographic (IDH) recording system free from bias and twin-image noises. A motionless three-step polarization-encoded phase-shifter operating at 99 Hz is realized with two electrically controllable birefringence-mode liquid crystal cells operating in tandem with a geometric phase lens and polarizers. Based on the proposed optical configuration, a coaxial straight-line self-interference IDH recording system is devised. Notably, the elimination of bias and twin-image noise from three phase-shifted images is demonstrated as a proof of concept. Moreover, complex-valued holographic video acquisitions with a resolution greater than 20 megapixels are demonstrated, with an effective acquisition frequency of 33 Hz.

Thermal three-point functions from holographic Schwinger-Keldysh contours

We compute fully retarded scalar three-point functions of holographic CFTs at finite temperature using real-time holography. They describe the nonlinear response of a holographic medium under scalar forcing, and display single and higher-order poles associated to resonant QNM excitations. This involves computing the bulk-to-bulk propagator on a piecewise mixed-signature spacetime, the dual of the Schwinger-Keldysh contour. We show this construction is equivalent to imposing ingoing boundary conditions on a single copy of a black hole spacetime, similar to the case of the two-point function. We also compute retarded scalar correlators with stress-tensor insertions in general CFTs by solving Ward identities on the Schwinger-Keldysh contour.

Wormholes, geons, and the illusion of the tensor product

In this paper I argue that the Hilbert space of states of a holographic, traversable wormhole does not factorize into the tensor product of the boundary Hilbert spaces. After presenting the general argument I analyze two examples: the scalar sectors of the BTZ geon and the AdS2 eternal wormhole. Utilizing real-time holography I derive the Hilbert spaces, identify the dual states and evaluate correlation functions. I show that the number of peculiarities associated with the wormhole and black hole physics emerges once the factorization is a priori assumed. This includes null states and null operators, highly entangled vacuum states and the cross-boundary interactions all emerging as avatars of non-factorization.

From picture to 3D hologram: end-to-end learning of real-time 3D photorealistic hologram generation from 2D image input.

In this Letter, we demonstrate a deep-learning-based method capable of synthesizing a photorealistic 3D hologram in real-time directly from the input of a single 2D image. We design a fully automatic pipeline to create large-scale datasets by converting any collection of real-life images into pairs of 2D images and corresponding 3D holograms and train our convolutional neural network (CNN) end-to-end in a supervised way. Our method is extremely computation-efficient and memory-efficient for 3D hologram generation merely from the knowledge of on-hand 2D image content. We experimentally demonstrate speckle-free and photorealistic holographic 3D displays from a variety of scene images, opening up a way of creating real-time 3D holography from everyday pictures.

Fourier-inspired neural module for real-time and high-fidelity computer-generated holography.

Learning-based computer-generated holography (CGH) algorithms appear as novel alternatives to generate phase-only holograms. However, most existing learning-based approaches underperform their iterative peers regarding display quality. Here, we recognize that current convolutional neural networks have difficulty learning cross-domain tasks due to the limited receptive field. In order to overcome this limitation, we propose a Fourier-inspired neural module, which can be easily integrated into various CGH frameworks and significantly enhance the quality of reconstructed images. By explicitly leveraging Fourier transforms within the neural network architecture, the mesoscopic information within the phase-only hologram can be more handily extracted. Both simulation and experiment were performed to showcase its capability. By incorporating it into U-Net and HoloNet, the peak signal-to-noise ratio of reconstructed images is measured at 29.16 dB and 33.50 dB during the simulation, which is 4.97 dB and 1.52 dB higher than those by the baseline U-Net and HoloNet, respectively. Similar trends are observed in the experimental results. We also experimentally demonstrated that U-Net and HoloNet with the proposed module can generate a monochromatic 1080p hologram in 0.015 s and 0.020 s, respectively.

Spectroscopic properties and effect of chromium in (PVA + ZnO) polymer films

The Various Chromium Ion Concentrations doped (PVA + ZnO) polymer films prepared by the slow evaporation method at room temperature. This paper reviews, in addition to the preparation and optimization of films of (PVA + ZnO) doped with different chromium ion concentrations, the role of dopant involved in electronic mechanism, with the Real-time holography, nanophotonics, optical sensors, and microlasers are a few examples of applications. Spectroscopic techniques such as EPR, optical, FT-IR, XRD, and SEM were used to examine the electrical and structural properties of polymer films. The EPR spectra exhibits lande g-factor at g≈4.53 and 4.38 resonance signals in the low field and at g≈2.02 to 2.08 in the high magnetic field region for PVAZn:Cr3+(0.2 and 0.8 mol %) polymer films. The optical absorption spectra of PVAZn:Cr3+ polymer films shows characteristic bands of Cr3+ions in octahedral sites. For 0.2 mol % concentration of Cr3+, the absorption edges were observed at 420 nm and 686 nm respectively. These bands are correspond to 4A2g(F)→4T1g(F) and 4A2g(F)→4T2g(F) transitions of Cr3+ions. The X-ray diffraction pattern revealed the semi-crystalline nature of the polymer films and SEM data indicates the structural variations the polymer films. The FT-IR analysis shows the incorporation of chromium ions in the PVAZn polymer matrix. The FTIR spectra show different modes of functional groups in the polymer matrix.[copyright information to be updated in production process]

Reconstruction and analysis of a non-stationary sound field in a uniformly flow medium

A multistep time domain plane wave superposition method (M-TPWM) is expanded into a new environment that the medium is fluid, and an M-TPWM with flow medium (FM-TPWM) is proposed to reconstruct the non-stationary sound field in a uniformly flow medium. In the FM-TPWM, two situations that the flow directions of the medium are parallel to and perpendicular to the hologram plane are researched. The time-varying pressures on the hologram plane in these two situations are expressed as a superposition of time convolutions between the pressure time-wavenumber spectra of a virtual source plane and the corresponding new time domain propagation kernel derived in the flow medium. Subsequently, the discrete solving equations in the parallel and perpendicular situations at one time are established. The pressure time-wavenumber spectra at only this time can be solved by once solving inverse calculation. Then, these discrete solving equations in the flow medium at several times are combined for forming the larger solving matrix equations in the parallel and perpendicular situations, and by once multistep calculation, the pressure spectra at these times are acquired concurrently. Consequently, the time-varying pressures on the reconstruction plane in the flow medium are calculated by the corresponding acquired pressure time-wavenumber spectra. Numerical simulations with parallel and perpendicular situations are applied to examine the performance of the proposed FM-TPWM, in which two monopole sources in the flow medium are used to engender the non-stationary sound field. The simulation results prove that the proposed FM-TPWM can reconstruct the non-stationary sound field very well when the flow directions of the medium are parallel to and perpendicular to the hologram plane, respectively. Besides, several meaningful parameters are discussed in detail to prove the adaptability and robustness of the proposed FM-TPWM in the flow medium, and its reconstruction advantages are protruded in comparison to the real-time nearfield acoustic holography with the flow medium.

Real-time holography and hybrid WKB for BTZ wormholes

We study probe scalar correlation functions in a Solodukhin wormhole corresponding to the non-rotating BTZ black hole, as a toy model for microstate geometries thereof. Using real-time holography, we obtain the retarded scalar correlator in the wormhole geometry and quantitatively compare it to the result of the hybrid WKB method for the same correlator. We also calculate an off-diagonal correlator ∼ 〈HLLH′〉 involving two different (heavy) wormhole states.

Metal Doped PVA Films for Opto-Electronics-Optical and Electronic Properties, an Overview.

Polyvinyl alcohol is unique among polymers. Apart from its preparation, it is not built up in polymerization reactions from monomers, unlike most vinyl-polymers, and it is biodegradable in the presence of suitably acclimated microorganisms. It is an environmentally friendly material for a wide range of applications, from medical ones, based on its biocompatibility, to integrated optics. This paper reviews, in addition to the preparation and optimization of films of polyvinyl alcohol doped with different metal species, the role of dopants and doping technologies in the involved electronic mechanism. The optical properties were studied by UV-VIS-IR, Mössbauer spectroscopy, and other measurement techniques, with applications such as real-time holography, microlasers, optical sensors or nanophotonics in mind.