
- Chinese Optics Letters
- Vol. 23, Issue 7, 071104 (2025)
Abstract
1. Introduction
THz radiation (0.1–10 THz) is widely used in industrial applications like medical imaging, security screening, and communication[1] due to its non-ionizing, low-energy properties. Additionally, it serves as a unique tool in scientific research, enabling the study of fundamental modes, such as electron motion, molecular rotations, lattice vibrations, and superconducting oscillations[2].
Recent advancements in THz imaging technologies have demonstrated significant progress. Frequency-domain THz imaging now operates through three primary sensor types[3]: thermal sensors[4,5], field sensors[6,7], and photon sensors[8,9]. Thermal sensors typically achieve millimeter-scale spatial resolution but suffer from sub-Hz frame rates and limited sensitivity at room temperature[10]. Photon sensors, though offering high sensitivity and faster imaging speeds as tens of frames per second (fps), require cryogenic cooling and complicated practical deployment[11]. Field sensors bring sub-millimeter spatial resolution and frame rates of 10–100 fps, yet their sensitivity remains insufficient for high-precision applications[12]. Notably, none of these conventional approaches simultaneously deliver high speed, high sensitivity, and room temperature operation[13]. Building on the breakthrough performance in microwave detection[14–16], Rydberg atom-based sensors now demonstrate revolutionary capabilities in THz regimes[17–20]. Resulting from the large electric dipole moment, the Rydberg atom has nearly single-photon sensitivity to THz radiation, which surpasses thermal sensors and field sensors by orders of magnitude and is similar to photon sensors. In addition, it potentially enables imaging with a speed on the order of the megahertz.
A method for real-time full-field imaging[21] has recently been developed, leveraging cesium Rydberg atoms to up-convert THz frequencies into the optical range. This innovation allows conventional optical cameras to rapidly capture full-field images, enabling real-time imaging in the THz spectrum. Furthermore, an improved THz imaging system has been introduced[22], achieving remarkable sensitivity and an impressive imaging speed of 6000 fps.
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Rydberg atom-based THz imaging, while promising, encounters significant challenges such as diffraction, interference fringes, and background noise, which degrade spatial resolution. Although studies[21,22] have shown that Rydberg-based detection systems can theoretically achieve diffraction-limited spatial resolution, these findings are largely based on experimental evaluations conducted under single pinhole imaging. The actual performance of these detectors in large-area imaging scenarios remains unverified. This study tackles these issues by reducing THz wave interference within the atomic vapor cell physically and employing image preprocessing techniques. Additionally, an untrained neural network is utilized to process images captured by the camera, effectively minimizing noise and diffraction effects, thereby improving the quality of fluorescence imaging.
2. Experimental Setup
The system depicted in Fig. 1 utilizes cesium atoms in a Rydberg state to convert THz waves into detectable visible fluorescence, which is subsequently captured by a charge-coupled device (CCD). The cesium atoms within the atomic vapor cell are excited into the Rydberg state through a three-step excitation process[23] involving three infrared laser beams, as outlined in prior research[21]. These infrared beams form an elliptical spot measuring 100 µm in width and 20 mm in height and are shaped by a cylindrical lens. A dove prism is also employed to correct for angular misalignment, ensuring proper beam overlap.
Figure 1.Layout of the terahertz imaging experiment. SAS, saturated absorption spectroscopy; EIT, electromagnetically induced transparency; HR mirror, high reflective mirror.
The detection laser (wavelength: 852 nm, power: 35 mW) is initially stabilized to the
The detection and coupling beams travel in the same direction along the
The emitted fluorescence is focused on an optical camera, generating a single-shot image of the incident THz field. To enhance the conversion efficiency from THz to optical, the cesium vapor is heated by encasing two-thirds of the vapor cell in a Teflon shell, with ceramic heaters (HT24S) maintaining the temperature at 65°C to maximize fluorescence output. By scanning the frequency of the THz source from 548.58 to 548.64 GHz, we observe that the fluorescence intensity peaks at a frequency of 548.613 GHz[22], confirming that this imaging system operates as a single-frequency THz imaging setup at this precise frequency.
3. Principle and Method
3.1. Interference fringe suppression
The Rydberg atom-based sensor employs cesium atoms in a Rydberg state within a quartz-encased atomic vapor cell to detect THz waves at 548.613 GHz, which carry object information. However, THz waves reflecting off the inner surface of the vapor cell generate standing waves, resulting in interference fringes on the detection plane. In the experiment, as shown in Fig. 2(a), 29 bright fringes are observed on a vapor cell measuring
Figure 2.Fluorescence images acquired pre- and post-installation of a terahertz polarizer. (a) The fluorescence image before positioning a terahertz polarizer. (b) The fluorescence image after positioning a terahertz polarizer.
3.2. Diffraction pattern suppression
The object modulates the transmitted THz waves, encoding information within the complex function of the wavefront, as shown in Eq. (1), where
In coherent imaging, directly determining
The neural network architecture used in this study, depicted in Fig. 3(a), is the U-Net convolutional neural network[28], widely applied in computational imaging. It comprises four main components: a
Figure 3.Schematic illustration of the pipeline of the untrained neural network. (a) Details for the U-shaped network structure. (b) Schematic diagram of the physics-enhanced deep neural network.
3.3. Background noise suppression
Raw fluorescence images are typically unsuitable for direct enhancement due to their high noise levels, requiring preprocessing for effective recovery. The fluorescence resulting from incident THz waves contains emissions around 535 nm, which correspond to the de-excitation of the
Initially, cesium atoms in the vapor cell are in the ground state, and a grayscale image
4. Simulation and Experimental Results
As indicated by Eq. (4), in an aberration-free imaging system or in regions where aberrations can be neglected, the amplitude and phase of the system’s impulse response can be experimentally measured, yielding the complex point spread function. This enables high-resolution reconstruction of diffraction patterns, as shown by the iterative process in Eq. (10),
However, in THz imaging, the development of aberration-correcting lens systems is prohibitively expensive due to the limited range of suitable materials and the high fabrication cost. Fortunately, free space inherently functions as an aberration-free imaging system[30], with its system transfer function
To validate this approach, we simulated THz imaging using a resolution test card (Type 18D). The incident THz wavefront’s amplitude was modulated by the card, as shown in Fig. 4(a), while the phase remained constant. After propagating 9 mm in free space, the pattern in Fig. 4(b1) appeared on the detection plane, and after 13 mm, the pattern in Fig. 4(b2) emerged. Applying a neural network to these patterns allowed for reconstruction. With
Figure 4.Simulation for the resolution test card imaging. (a) Binarization diagram of the resolution test card. (b1) Intensity image of the resolution test card at 9 mm distance. (b2) Intensity image of the resolution test card at 13 mm distance.
Figure 5.Simulation for fluorescence image processing using untrained neural networks. (a1), (b1) represent the amplitude image and the phase image predicted by the neural network with n = 1, respectively. (a2), (b2) represent the amplitude image and the phase image predicted by the neural network with n = 2, respectively.
We conducted experiments with the setup depicted in Fig. 1, replacing the imaging light path assembly with free space filled with air, as illustrated in Fig. 6. In practice, the lasers used for the Rydberg atom excitation are sensitive to environmental factors, such as vibration, temperature, and humidity, leading to up to 20% fluctuations in fluorescence intensity. Nevertheless, the method requires capturing at least two images at different distances along the optical axis, which may experience fluorescence intensity variations between captures. To address the issue, we employed a solution outlined in Eq. (11), which normalizes the fluorescence signal based on the optimization of Eq. (8),
Figure 6.Schematic diagram of the imaging experiment.
In our imaging experiment, we acquired fluorescence images of the resolution test card at varying distances from the light sheet ranging from 2.5 to 12.5 mm in 2 mm increments, as illustrated in Fig. 7. Due to diffraction effects, the line-pair patterns on the detection plane appeared blurred and indistinct.
Figure 7.Resolution test card fluorescence imaging experiment. (a)–(f) denote the imaging distances of 2.5, 4.5, 6.5, 8.5, 10.5, and 12.5 mm, respectively.
Applying our methods, we reconstruct the amplitude image shown in Fig. 8(a) with
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Figure 8.Resolution test card fluorescence image processing results. (a)–(c) represent the amplitude images reconstructed from n = 2, n = 4, and n = 6 pictures by our algorithm, respectively.
In this experiment, the atomic vapor cell is made of quartz, a material that reflects THz radiation. This reflection results in multiple internal interactions with cesium atoms, generating scattering noise that compromises signal quality. As shown in Fig. 9, a circular metallic disc is positioned adjacent to the cell wall to block THz waves from entering the atomic vapor. Despite this measure, fluorescence signals remain affected by speckle patterns and additional interference caused by quartz reflections, which degrade imaging resolution and prevent the system from reaching the diffraction limit. To address this, replacing quartz with a material that exhibits better THz transmission properties could reduce reflection-based noise. Furthermore, the excitation laser’s light sheet suffers from non-uniform energy distribution, operating effectively over a
Figure 9.Phenomenon of THz waves reflecting within the atom vapor cell. (a) Fluorescence image of the metallic disc. (b) Fluorescence image without THz irradiation.
The neural network was developed utilizing the PyTorch framework and Python version 3.10.0. We employed the Adam optimizer with a learning rate set at 0.001 to optimize the weights and biases. To improve convergence, uniformly distributed noise within the range of 0 to 0.01 is introduced to the fixed input
5. Conclusion
This study tackles the issue of high noise levels in single-frequency THz imaging systems leveraging Rydberg atoms, presenting an innovative method for processing raw images and optimizing the illumination system. By employing an untrained deep neural network, the approach effectively reduces diffraction noise in preprocessed fluorescence images, eliminating the need for specialized THz datasets. Experimental outcomes demonstrate notable enhancements in imaging quality, achieving a resolution exceeding 1.25 lp/mm at an imaging distance of 2.5 mm, all without relying on lens-based systems. Furthermore, with anticipated advancements in the materials used for atomic vapor cells and the stability of excitation lasers, the resolution is projected to approach the diffraction limit of 3.55 lp/mm. These breakthroughs pave the way for high-resolution high-speed THz imaging, representing a significant leap forward in the field.
References
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