Deep Modulation Research Articles

Fourier single-pixel imaging in the terahertz regime

We demonstrate Fourier single-pixel imaging in the terahertz regime. The experimental system is implemented using a photoinduced coded aperture setup, where monolayer graphene on a high-resistance silicon substrate illuminated by a coded laser beam works as a terahertz modulator. The results show that high-quality terahertz images can be reconstructed using a greatly reduced number of measurements. We further find that deep photoinduced terahertz modulation, by adding a monolayer graphene on the silicon substrate and by using high laser power, can significantly improve the image quality. Compared to Hadamard single-pixel imaging with a reordered Hadamard matrix, the Fourier approach has higher image quality. We expect that this work will speed up the efficiency of single-pixel terahertz imaging and advance terahertz imaging applications.

Saturable Absorption in 2D Nanomaterials and Related Photonic Devices

AbstractWide‐spectral saturable absorption (SA) has been experimentally demonstrated in two‐dimensional (2D) nanomaterials with outstanding performance, such as low saturation intensity, deep modulation depth, and fast recovery time of excited carriers. Hence, 2D nanomaterials can be utilized as saturable absorbers for mode‐locking or Q‐switching to generate laser pulses with short duration and high repetition rate. Here, the SA properties of graphene, layered transition metal dichalcogenides, Group‐V elements, and other 2D nanomaterials are reviewed by summarizing their slow‐ or fast‐ saturable absorption behavior using the modified Frantz–Nodvik model or the steady‐state solution of Hercher's rate equations. The dependence of SA in 2D nanomaterials on excitation wavelength, linear absorption coefficient, and pulse duration is also explained. Finally, the applications of these 2D nanomaterials in a range of pulsed lasers are summarized.

Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks

We consider a cognitive heterogeneous network (HetNet), in which multiple pairs of secondary users adopt sensing-based approaches to coexist with a pair of primary users on a certain spectrum band. Due to imperfect spectrum sensing, secondary transmitters (STs) may cause interference to the primary receiver (PR) and make it difficult for the PR to select a proper modulation and/or coding scheme (MCS). To deal with this issue, we exploit deep reinforcement learning (DRL) and propose an intelligent MCS selection algorithm for the primary transmission. To reduce the system overhead caused by MCS switchings, we further introduce a switching cost factor in the proposed algorithm. Simulation results show that the primary transmission rate of the proposed algorithm without the switching cost factor is 90 percent to 100 percent of the optimal MCS selection scheme, which assumes that the interference from the STs is perfectly known at the PR as prior information, and is 30 percent to 100 percent higher than those of the benchmark algorithms. Meanwhile, the proposed algorithm with the switching cost factor can achieve a better balance between the primary transmission rate and system overheads than both the optimal algorithm and benchmark algorithms.

Bifurcations and oscillations in divertor plasma

A qualitative picture of development of a bifurcated plasma state in a single-null and double-null divertor configurations is discussed. The simple analytical considerations are verified with SOLPS code modeling in quasi-1D setup. In a more realistic, 2D model, these bifurcations cause self-sustained oscillations of the plasma parameters, leading to deep modulation of the power loading on the divertor targets. In the symmetric double-null case, the bifurcations prompt a spontaneous loss of the up-down symmetry, which results in a sharp, counter-intuitive increase of the power loading on one of the targets along with an increase of the particle content in the divertor plasma.

Grating-like nanostructures formed by the focused fs laser pulse in the volume of transparent dielectric.

The evolution of optical discharge induced in the volume of transparent dielectric by a focused fs laser pulse is studied under condition of ionization instability that results in deep small-scale periodic modulation of breakdown plasma parameters in the direction of laser polarization. Laser pulse intensity range is found where the instability evolving from very small seed perturbations leads to formation of the contrast subwavelength periodic structure containing narrow zones with overcritical plasma density and enhanced energy deposition. The latter allows considering this structure as underlying the nanograting formation observed experimentally in the fused silica irradiated by series of repeated fs pulses.

Theoretical research on TEM mode feedback for compact design of an X-band triaxial klystron amplifier

A relativistic triaxial klystron amplifier (TKA) is considered to be one of the most promising high power microwave (HPM) sources for coherent power combination in high frequency bands. In general investigations, the TEM mode leakage and asymmetric modes' competition are considered to play unfavorable roles in the normal operation of TKA. Therefore, mode reflectors with high reflection efficiency in both the TEM mode and the asymmetric modes are employed and expected to significantly suppress the transmissions of the microwaves between the cavities. So the cavities can be separated from each other, while the long drift length is necessary to achieve the deep modulation. Therefore, the size of TKA is noticeably larger compared to other HPM oscillators, which requires large magnetic coil and huge energy consumption. In our present research, it is found that the TEM mode leakage can be utilized to form positive feedback between the cavities, which is significant for electron beam modulation and furthermore to make the devices more compact. In this paper, the mechanism of TEM mode feedback between the cavities is discussed and the conditions of positive and negative feedback are achieved. Besides, an especially designed reflector with high reflection coefficients in asymmetric modes and low reflection coefficients in the TEM mode is designed to utilize the TEM mode and suppress the asymmetric modes. Based on the above research, a TKA adopting positive TEM mode feedback, whose total length is decreased by 23.6% compared to the previous design, is presented. A high power microwave with a power of 2.25 GW and a frequency of 8.4 GHz is generated with a 690 kV, 9.3 kA electron beam excitation and a 40 kW radio-frequency signal injection. Meanwhile, there is insignificant self-excitation of the parasitic mode in the proposed structure in three-dimensional particle-in-cell simulation, and the relative phase shifts between the injected signals and the output microwaves are kept locked after the amplifier becomes saturated.

Reconfigurable Terahertz Quarter-Wave Plate for Helicity Switching Based on Babinet Inversion of an Anisotropic Checkerboard Metasurface

Dynamic helicity switching by utilizing metasurfaces is challenging because it requires deep modulation of polarization states. To realize such helicity switching, this paper proposes a dynamic metasurface functioning as a switchable quarter-wave plate, the fast axis of which can be dynamically rotated by $90^\circ$. The device is based on the critical transition of an anisotropic metallic checkerboard, which realizes the deep modulation and simultaneous design of the switchable states. After verifying the functionality of the ideally designed device in a simulation, we tune its structural parameters to realize practical experiments in the terahertz frequency range. By evaluating the fabricated sample with vanadium dioxide, the conductivity of which can be controlled by temperature, its dynamic helicity switching function is demonstrated.

Effect of rate altered perception of deep band modulated phrase in noise from normal hearing younger and older adult groups

Purpose: To evaluate the effect of speaking rate on speech perception with unprocessed (UP) and envelope enhancement in noise on normal hearing younger adults (YAG) and older adults (OAG).Method: A purposive sampling with repeated measures research design was adopted to evaluate envelope enhancement on speech perception in adverse listening condition. Study samples: Thirty normal hearing participants were grouped into two based on age: YAG (N = 15) within age range of 18–25 years and OAG (N = 15) within the age range of 65–83 years. Phrases prepared in three speech rates (normal, 35% and 40%) at three different signal-to-noise ratios (SNRs) (quiet, –1 dB SNR and –5 dB SNR) were presented at participant’s comfortable level.Results: In each of the rate of speech at each SNR, the perception score was significantly better in deep band modulation (DBM) than UP. Further, perception score of UP from YAG was almost equal to scores of DBM from OAG, in each experimental condition.Conclusion: Older adults can take advantage of envelope enhancement when speech rate is altered and embedded in noise.

Ultrahighly Saturated Structural Colors Enhanced by Multipolar-Modulated Metasurfaces.

Colors with high saturation are of prime significance for display and imaging devices. So far, structural colors arising from all-dielectric metasurfaces, particularly amorphous silicon and titanium oxide, have exceeded the gamut of standard RGB (sRGB) space. However, the excitation of higher-order modes for dielectric materials hinders the further increase of saturation. Here, to address the challenge, we propose a new design strategy of multipolar-modulated metasurfaces with multi-dielectric stacked layers to realize the deep modulation of multipolar modes. Index matching between layers can suppress the multipolar modes at nonresonant wavelength, resulting in the dramatic enhancement in the monochromaticity of reflection spectra. Ultrahigh-saturation colors ranging from 70% to 90% with full hue have been theoretically and experimentally obtained. The huge gamut space can be realized in an unprecedented way, taking up 171% sRGB space, 127% Adobe RGB space, and 57% CIE space. More interestingly, the coverage forRecommendation 2020 (Rec. 2020) space, which almost has not been successfully realized so far, can reach 90%. We anticipate that the proposed multipolar-modulated metasurfaces are promising for the enlargement of the color range for high-end and advanced display applications.

Intelligent closed-loop deep brain stimulation modulation platform with multi-sensor information feedback

This paper describes an intelligent closed-loop deep brain stimulation modulation platform with multi-sensor information input feedback, adaptive, interactive, and high integration. This platform has 16 channels of data acquisition channels and 4 channels of stimulation channels. Four channels of the acquisition channel are used for intracranial LFPs acquisition, and 12 channels are used for acquisition of extracranial signals (EEG, ECG and EMG). The output waveform of stimulation channels is a configurable and arbitrary waveform. The stimulation voltage is in constant voltage mode, the stimulation voltage range is -5 V ∼ +5 V, and the impedance range of the stimulation load is 500 Ω ∼ 5 KΩ. This study achieved simultaneously the stimulation at the recording, which effectively reduces the influence of the stimulation artifacts on the recorded signal. The platform constructs multi-information closed-loop deep brain stimulation for Parkinson's disease from three aspects: motor behavior signal feedback, extracranial electrical signal feedback, and deep brain field potential signal feedback. A modular portable and universal closed-loop neuromodulation research platform has been formed. This study completed the acquisition and recording and adaptive closed-loop algorithm and stimulation function, effectively eliminating the stimulus artifacts, adapting to wide dynamic range brain impedance, and enhancing the stability of stimulus output. It has the characteristics of compact structure, small size, low power consumption and stable operation.

Deep Learning-Based Signal Modulation Identification in OFDM Systems

Signal modulation identification (SMI) plays a very important role in orthogonal frequency-division multiplexing (OFDM) systems. Currently, SMI methods are often implemented via feature extraction based on machine learning. However, the traditional methods encounter a bottleneck where the probability of correct classification (PCC) is very limited and hence it is hard to implement in practical OFDM systems due to the fact that traditional methods are difficult to extract feature of the OFDM signals. In order solve these problems, we propose a deep learning (DL) based SMI method for identifying OFDM signals. Specifically, convolutional neural network (CNN) is adopted to train in-phase and quadrature (IQ) samples for OFDM signals. Then we choose dropout layer to prevent overfitting and improve its identification accuracy. In addition, datasets with different modulation modes are adopted to verify our trained CNN. Experiments are conducted to show that our proposed method achieves higher accuracy and better consistency than traditional methods. Moreover, extensive results confirm that the proposed method performs robustly in different datasets.

Modulating phase by metasurfaces with gated ultra-thin TiN films.

Active control over the flow of light is highly desirable because of its applicability to information processing, telecommunication, and spectroscopic imaging. In this paper, by employing the tunability of carrier density in a 1 nm titanium nitride (TiN) film, we numerically demonstrate deep phase modulation (PM) in an electrically tunable gold strip/TiN film hybrid metasurface. A 337° PM is achieved at 1.550 μm with a 3% carrier density change in the TiN film. We also demonstrate that a continuous 180° PM can be realized at 1.537 μm by applying a realistic experiment-based gate voltage bias and continuously changing the carrier density in the TiN film. The proposed design of active metasurfaces capable of deep PM near the wavelength of 1.550 μm has considerable potential in active beam steering, dynamic hologram generation, and flat photonic devices with reconfigurable functionalities.

Graphene-loaded metal wire grating for deep and broadband THz modulation in total internal reflection geometry

We employed a metallic wire grating loaded with graphene and operating in total internal reflection (TIR) geometry to realize deep and broadband THz modulation. The non-resonant field enhancement effect of the evanescent wave in TIR geometry and in the subwavelength wire grating was combined to demonstrate a ∼77% modulation depth (MD) in the frequency range of 0.2–1.4 THz. This MD, achieved electrically with a SiO2/Si gated graphene device, was 4.5 times higher than that of the device without a metal grating in transmission geometry. By optimizing the parameters of the metallic wire grating, the required sheet conductivity of graphene for deep modulation was lowered to 0.87 mS. This work has potential applications in THz communication and real-time THz imaging.

Graphene controlled Brewster angle device for ultra broadband terahertz modulation

Terahertz modulators with high tunability of both intensity and phase are essential for effective control of electromagnetic properties. Due to the underlying physics behind existing approaches there is still a lack of broadband devices able to achieve deep modulation. Here, we demonstrate the effect of tunable Brewster angle controlled by graphene, and develop a highly-tunable solid-state graphene/quartz modulator based on this mechanism. The Brewster angle of the device can be tuned by varying the conductivity of the graphene through an electrical gate. In this way, we achieve near perfect intensity modulation with spectrally flat modulation depth of 99.3 to 99.9 percent and phase tunability of up to 140 degree in the frequency range from 0.5 to 1.6 THz. Different from using electromagnetic resonance effects (for example, metamaterials), this principle ensures that our device can operate in ultra-broadband. Thus it is an effective principle for terahertz modulation.

Implementation of Deep Learning-Based Automatic Modulation Classifier on FPGA SDR Platform

Intelligent radios collect information by sensing signals within the radio spectrum, and the automatic modulation recognition (AMR) of signals is one of their most challenging tasks. Although the result of a modulation classification based on a deep neural network is better, the training of the neural network requires complicated calculations and expensive hardware. Therefore, in this paper, we propose a master–slave AMR architecture using the reconfigurability of field-programmable gate arrays (FPGAs). First, we discuss the method of building AMR, by using a stack convolution autoencoder (CAE), and analyze the principles of training and classification. Then, on the basis of the radiofrequency network-on-chip architecture, the constraint conditions of AMR in FPGA are proposed from the aspects of computing optimization and memory access optimization. The experimental results not only demonstrated that AMR-based CAEs worked correctly, but also showed that AMR based on neural networks could be implemented on FPGAs, with the potential for dynamic spectrum allocation and cognitive radio systems.

Deep and fast free-space electro-absorption modulation in a mobility-independent graphene-loaded Bragg resonator

Deep and fast electro-optic modulation is critical for high-speed near infrared signal processing. We combine the electro-absorption tunability of graphene with the high-Q resonance of a Bragg-based Fabry-Perot resonator at λ = 1550 nm and show that ∼100% free-space signal modulation at small insertion loss and GHz speed can always be achieved independently of graphene quality (mobility), provided that the device operates in the reflection mode and is tuned in critical coupling with graphene. Remarkably, the critical coupling mechanism produces a higher extinction ratio for lower graphene mobility. We use practical considerations to optimize the device architecture and operation as a function of graphene mobility. With a small modification, this scheme can be turned into a very sensitive acousto-absorption modulator with an extinction ratio of ∼30 dB/Å or an index sensor with a sensitivity of 107%/RIU. These designs can be extended throughout the IR spectrum by appropriate material selection and scaling of layer dimensions.

Numerical investigation of narrowband infrared absorber and sensor based on dielectric-metal metasurface.

Metasurfaces are investigated intensively for biophotonics applications due to their resonant wavelength flexibly tuned in the near infrared region specially matching biological tissues. Here, we present numerically a metasurface structure combining dielectric resonance with surface plasmon mode of a metal plane, which is a perfect absorber with a narrow linewidth 10 nm wide and quality factor 120 in the near infrared regime. As a sensor, its bulk sensitivity and bulk figure of merit reach respectively 840 nm/RIU and 84/RIU, while its surface sensitivity and surface figure of merit are respectively 1 and 0.1/nm. For different types of adsorbate layers with the same thickness of 8 nm, its surface sensitivity and figure of merit are respectively 32.3 and 3.2/RIU. The enhanced electric field is concentrated on top of dielectric patch ends and in the patch ends simultaneously. Results show that the presented structure has high surface (and bulk) sensing capability in sensing applications due to its narrow linewidth and deep modulation depth. This could pave a new route toward dielectric-metal metasurface in biosensing applications, such as early disease detections and designs of neural stem cell sensing platforms.

Dynamically tunable band stop filter enabled by the metal-graphene metamaterials

Dynamically tunable band stop filter based on metal-graphene metamaterials is proposed and numerically investigated at mid-infrared frequencies. The proposed filter is constructed by unit cells with simple gold strips on the stack of monolayer graphene and the substrate of BaF2. A stable modulation depth up to −23.26 dB can be achieved. Due to the cooperative effect of the “bright-bright” elements, the amount of the gold strips in each unit cell determines the number of the stop-bands, providing a simple and flexible approach to develop multispectral devices. Further investigations illustrate that the location of the stop bands not only can be adjusted by varying the length of gold strips, but also can be dynamically controlled by tuning the Fermi energy level of graphene, and deep modulation is acquired through designing the carrier mobility. With the sensitivity as high as 2393 nm/RIU of the resonances to the varieties of surrounding medium, the structure is also enabled to be an index based sensor. The results will benefit the on plane or integrated micro-structure research with simple structure and flexible tunability, and can be applied in multi-band stop filters, sensors and other graphene-based multispectral devices.

Beam steering of the acoustic metasurface under a subwavelength periodic modulation

In this study, we introduce a subwavelength periodic thin plate array into an acoustic metasurface and investigate the modulation effect on acoustic surface waves. Both anomalous sound refraction and reflection are observed in the metasurface, and an analytic expression is derived to clarify the underlying mechanism. We theoretically prove that flexible beam steering can be realized by phase gradient acoustic metasurfaces with deep subwavelength periodic modulation. This study potentially adds another degree of freedom to controlling sound transmission by using an acoustic metasurface.

Low-Cost Highly Sensitive Refractive Index Measurement Based on Deep Frequency Modulation Interferometry

A novel low-cost technique for refractive index (RI) measurement is proposed and experimentally demonstrated based on the concept of deep frequency modulation (DFM). By omitting electro-optic modulator from conventional DFM, the frequency modulation is realized by direct current modulation of a laser diode which leads to cost reduction. The flicker noise effect on the DFM performance, which is considered as a major obstacle of homodyne detection, has been considered in our numerical analysis; hence, a realistic analysis of the results is presented. Hereby, a modification in the DFM signal processing has been suggested to mitigate the flicker noise effect. Through proper selection of higher harmonics of the wideband detected DFM signal, the normalized error can be reduced more than 10 dB. We have implemented this method for a Michelson interferometer to measure RI of an aqueous solution. An interference signal is formed on the photodetector, which is then processed to measure RI by estimating the optical path length difference between the two interferometer arms. It is shown that this setup provides a resolution of better than $2.1 \times {10^{-5}}$ in RI unit. The proposed cost-effective measurement technique can be readily integrated in applications, where high precision real-time measurements over a wide measurement range are required.