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Neural network enabled wide field-of-view imaging with hyperbolic metalenses
Authors:
Joel Yeo,
Deepak K. Sharma,
Saurabh Srivastava,
Aihong Huang,
Emmanuel Lassalle,
Egor Khaidarov,
Keng Heng Lai,
Yuan Hsing Fu,
N. Duane Loh,
Ramon Paniagua-Dominguez,
Arseniy I. Kuznetsov
Abstract:
The ultrathin form factor of metalenses makes them highly appealing for novel sensing and imaging applications. Amongst the various phase profiles, the hyperbolic metalens stands out for being free from spherical aberrations and having one of the highest focusing efficiencies to date. For imaging, however, hyperbolic metalenses present significant off-axis aberrations, severely restricting the ach…
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The ultrathin form factor of metalenses makes them highly appealing for novel sensing and imaging applications. Amongst the various phase profiles, the hyperbolic metalens stands out for being free from spherical aberrations and having one of the highest focusing efficiencies to date. For imaging, however, hyperbolic metalenses present significant off-axis aberrations, severely restricting the achievable field-of-view (FOV). Extending the FOV of hyperbolic metalenses is thus feasible only if these aberrations can be corrected. Here, we demonstrate that a Restormer neural network can be used to correct these severe off-axis aberrations, enabling wide FOV imaging with a hyperbolic metalens camera. Importantly, we demonstrate the feasibility of training the Restormer network purely on simulated datasets of spatially-varying blurred images generated by the eigen-point-spread function (eigenPSF) method, eliminating the need for time-intensive experimental data collection. This reference-free training ensures that Restormer learns solely to correct optical aberrations, resulting in reconstructions that are faithful to the original scene. Using this method, we show that a hyperbolic metalens camera can be used to obtain high-quality imaging over a wide FOV of 54° in experimentally captured scenes under diverse lighting conditions.
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Submitted 3 August, 2025; v1 submitted 29 July, 2025;
originally announced July 2025.
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On social simulation in 4D relativistic spacetime
Authors:
Kwun Hang Lai
Abstract:
Agent-based modeling and simulation allow us to study social phenomena in hypothetical scenarios. If we stretch our imagination, one of the interesting scenarios would be our interstellar future. To model an interstellar society, we need to consider relativistic physics, which is not straightforward to implement in existing agent-based simulation frameworks. In this paper, we present the mathemati…
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Agent-based modeling and simulation allow us to study social phenomena in hypothetical scenarios. If we stretch our imagination, one of the interesting scenarios would be our interstellar future. To model an interstellar society, we need to consider relativistic physics, which is not straightforward to implement in existing agent-based simulation frameworks. In this paper, we present the mathematics and algorithmic details needed for simulating agent-based models in 4D relativistic spacetime. These algorithms form the basis of our open-source computational framework, "Relativitization".
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Submitted 10 January, 2023; v1 submitted 8 February, 2022;
originally announced June 2022.
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Large-scale Huygens metasurfaces for holographic 3D near-eye displays
Authors:
Weitao Song,
Xinan Liang,
Shiqiang Li,
Dongdong Li,
Ramon Paniagua-Dominguez,
Keng Heng Lai,
Qunying Lin,
Yuanjin Zheng,
Arseniy I. Kuznetsov
Abstract:
Novel display technologies aim at providing the users with increasingly immersive experiences. In this regard, it is a long-sought dream to generate three-dimensional (3D) scenes with high resolution and continuous depth, which can be overlaid with the real world. Current attempts to do so, however, fail in providing either truly 3D information, or a large viewing area and angle, strongly limiting…
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Novel display technologies aim at providing the users with increasingly immersive experiences. In this regard, it is a long-sought dream to generate three-dimensional (3D) scenes with high resolution and continuous depth, which can be overlaid with the real world. Current attempts to do so, however, fail in providing either truly 3D information, or a large viewing area and angle, strongly limiting the user immersion. Here, we report a proof-of-concept solution for this problem, and realize a compact holographic 3D near-eye display with a large exit pupil of 10mm x 8.66mm. The 3D image is generated from a highly transparent Huygens metasurface hologram with large (>10^8) pixel count and subwavelength pixels, fabricated via deep-ultraviolet immersion photolithography on 300 mm glass wafers. We experimentally demonstrate high quality virtual 3D scenes with ~50k active data points and continuous depth ranging from 0.5m to 2m, overlaid with the real world and easily viewed by naked eye. To do so, we introduce a new design method for holographic near-eye displays that, inherently, is able to provide both parallax and accommodation cues, fundamentally solving the vergence-accommodation conflict that exists in current commercial 3D displays.
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Submitted 9 October, 2020;
originally announced October 2020.
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Demonstration of a-Si metalenses on a 12-inch glass wafer by CMOS-compatible technology
Authors:
Ting Hu,
Qize Zhong,
Nanxi Li,
Yuan Dong,
Yuan Hsing Fu,
Zhengji Xu,
Dongdong Li,
Vladimir Bliznetsov,
Keng Heng Lai,
Shiyang Zhu,
Qunying Lin,
Yuandong Gu,
Navab Singh,
Dim-Lee Kwong
Abstract:
Metalenses built up by artificial sub-wavelength nanostructures have shown the capability of realizing light focusing with miniature lens size. To date, most of the reported metalenses were patterned using electron beam lithography (EBL), which requires long processing time and is not suitable for mass production. Here, we demonstrate an amorphous silicon (a-Si) metalens on a 12-inch glass wafer v…
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Metalenses built up by artificial sub-wavelength nanostructures have shown the capability of realizing light focusing with miniature lens size. To date, most of the reported metalenses were patterned using electron beam lithography (EBL), which requires long processing time and is not suitable for mass production. Here, we demonstrate an amorphous silicon (a-Si) metalens on a 12-inch glass wafer via the 193 nm ArF deep UV immersion lithography, with critical dimension (CD) as small as 100 nm. The layer transfer technology is developed to solve the glass wafer handling issue in complementary metal-oxide-semiconductor (CMOS) fabrication line. The measured numerical aperture (NA) is 0.494 with a beam spot size of 1.26 μm, which agrees well with the simulation results. The focusing efficiency of 29.2% is observed at the designed wavelength of 940 nm. In addition, the metalens is applied in an imaging system, which further verifies its focusing functionality.
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Submitted 11 June, 2019;
originally announced June 2019.
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Network Topology of an Experimental Futures Exchange
Authors:
S. C. Wang,
J. J. Tseng,
C. C. Tai,
K. H. Lai,
W. S. Wu,
S. H. Chen,
S. P. Li
Abstract:
Many systems of different nature exhibit scale free behaviors. Economic systems with power law distribution in the wealth is one of the examples. To better understand the working behind the complexity, we undertook an empirical study measuring the interactions between market participants. A Web server was setup to administer the exchange of futures contracts whose liquidation prices were coupled…
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Many systems of different nature exhibit scale free behaviors. Economic systems with power law distribution in the wealth is one of the examples. To better understand the working behind the complexity, we undertook an empirical study measuring the interactions between market participants. A Web server was setup to administer the exchange of futures contracts whose liquidation prices were coupled to event outcomes. After free registration, participants started trading to compete for the money prizes upon maturity of the futures contracts at the end of the experiment. The evolving `cash' flow network was reconstructed from the transactions between players. We show that the network topology is hierarchical, disassortative and scale-free with a power law exponent of 1.02+-0.09 in the degree distribution. The small-world property emerged early in the experiment while the number of participants was still small. We also show power law distributions of the net incomes and inter-transaction time intervals. Big winners and losers are associated with high degree, high betweenness centrality, low clustering coefficient and low degree-correlation. We identify communities in the network as groups of the like-minded. The distribution of the community sizes is shown to be power-law distributed with an exponent of 1.19+-0.16.
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Submitted 17 May, 2007;
originally announced May 2007.