Phase Shift Research Articles

Changes in the SST Seasonal Cycle in a Warmer North Pacific without Ocean Dynamical Feedbacks

Abstract Climate models project a significant intensification of the sea surface temperature (SST) seasonal cycle over the subpolar North Pacific due to global warming, with the shallower mixed layer widely recognized as the dominant factor. However, employing slab ocean experiments with only ocean–atmosphere thermal coupling, we find a substantial contribution from changes in surface heat flux to this seasonal cycle intensification. In particular, the stronger Newtonian cooling effect in winter acts as a more potent damping than in summer. This differential damping inhibits the warming in colder seasons, significantly contributing to the intensified SST seasonal cycle in the subpolar North Pacific. In addition, consistent phase shifts in the North Pacific are identified across CMIP6 models. In the northwest North Pacific, a phase advance is associated with anomalous heating in early spring, driven by enhanced warm atmospheric advection from lower latitudes and sea ice melting in marginal seas. In contrast, the southeast North Pacific exhibits a phase delay attributed to the anomalous cooling in spring relative to autumn. This cooling is due to weakened trade winds and increased presence of high clouds. The former leads to stronger evaporative cooling in spring, while the latter impedes shortwave radiation from reaching the ocean.

Adaptive tunicate swarm optimization with partial transmit sequence for phase optimization in MIMO-OFDM

<span>Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are widely utilized in wireless systems and maximum data rate communications. The MIMO-OFDM technology increases the efficiency of spectrum utilization. The peak-to-average-power ratio (PAPR) minimization in MIMO-OFDM is a complex task in wireless communications systems. In this research, an adaptive tunicate swarm optimization with partial transmit sequence (ATSO-PTS) algorithm is proposed for a reduction of PAPR in MIMO-OFDM. The nonsquare-matrix-based differential space time coding (N-DSTC) scheme is used for the encoding and decoding process of MIMO-OFDM. The N-DSTC encoding and decoding are linear error-correcting codes that are utilized for message transmission over noisy channels. The pre-specified quadrate phase shift keying (QPSK) symbol is deployed for the modulation and demodulation scheme. On the receiver side, the serial to parallel (S/P) conversion, and fast Fourier transform (FFT) are accomplished, alongside the received data bits being demodulated to obtain the output bits. The proposed ATSO-PTS method achieves better results according to performance metrices PAPR, bit error rate (BER) and signal-to-noise-ratio (SNR), with values of about 2.9, 0.01 and 0.025, respectively. This ensures superior results when compared to the existing methods of twin symbol hybrid optimization applied to partial transmit sequence (TSHO-PTS), selective level mapping and PTS (SLM-PTS), and particle swarm and grey wolf (PS-GW) with PTS, respectively.</span>

Cognitive learning enabled agile optical network

Nonlinear equalization (NLE) is essential for guaranteeing the performance of an optical network (ON). Effective NLE implementation relies on key parameters of the transmission link, including the modulation format (MF) and the launch power. As ONs become more agile, the parameters of fiber optical transmission need to be adaptive and relevant to the routing condition. Therefore, successful NLE implementation relies on the realization of transmission awareness (TA). Although machine learning-enabled optical performance monitoring (OPM) has been extensively investigated in the past few years, current NLE algorithms cannot autonomously perceive transmission parameters. Furthermore, current TA implementation still needs human intervention to guide the NLE. In addition, existing ML-based OPM and NLE cannot be trained autonomously, leading to the incapability of environmental change and mislabeling. Here, we propose cognitive learning (CL) for TA-guided NLE in agile ONs. We perform an experiment involving 32 Gbaud polarization-division-multiplexed (PDM)-quadrature phase shift keying (QPSK)/16-quadrature amplitude modulation (QAM) transmission over 1500 km of standard single-mode fiber (SSMF) with a variable launch power from 0 to 3 dBm. When a deep neural network (DNN) with amplitude histograms (AHs) as inputs and one step per span-learned digital back-propagation (1stps-LDBP) are developed, the CL simultaneously enables both TA and NLE, with the capability of self-learning, mislabeling resistance, and dynamic adaptation. The proof-of-concept experimental results indicate that both the accuracy of TA and the Q-factor of PDM-16QAM can be improved by 34.8% and 0.84 dB, respectively, when the launch power is 3 dBm. Moreover, the accuracy of TA is enhanced by 35.3%, even when the used data has 30% mislabeling. Therefore, the CL framework can be customized to satisfy various NLE implementations, thereby supporting the adaptive transmission of agile ONs.

Phase-Shifted Fiber Bragg Grating by Selective Pitch Slicing

This paper presents a new type of phase-shifted Fiber Bragg Grating (FBG): the sliced-FBG (SFBG). The fabrication process involves cutting a standard FBG inside its grating region. As a result, the last grating pitch is shorter than the others. The optical output signal consists of the overlap between the FBG reflection and the reflection at the fiber-cleaved tip. This new fiber optic device has been studied as a vibration sensor, allowing for the characterization of this sensor in the frequency range of 150 Hz to 70 kHz. How the phase shift in the FBG can be controlled by changing the length of the last pitch is also shown. This device can be used as a filter and a sensing element. As a sensing element, we will demonstrate its application as a vibration sensor that can be utilized in various applications, particularly in monitoring mechanical structures.

Circadian rhythm disruption modulates enteric neural precursor cells differentiation leading to gastrointestinal motility dysfunction via the NR1D1/NF-κB axis

ObjectivesCircadian rhythm disruption (CRD) is implicated with numerous gastrointestinal motility diseases, with the enteric nervous system (ENS) taking main responsibility for the coordination of gastrointestinal motility. The purpose of this study is to explore the role of circadian rhythms in ENS remodeling and to further elucidate the underlying mechanisms.MethodsFirst, we established a jet-lagged mice model by advancing the light/dark phase shift by six hours every three days for eight weeks. Subsequent changes in gastrointestinal motility and the ENS were then assessed. Additionally, a triple-transgenic mouse strain (Nestin-creERT2 × Ngfr-DreERT2: DTRGFP) was utilized to track the effects of CRD on the differentiation of enteric neural precursor cells (ENPCs). RNA sequencing was also performed to elucidate the underlying mechanism.ResultsCompared to the control group, CRD significantly accelerated gastrointestinal motility, evidenced by faster intestinal peristalsis (P < 0.01), increased fecal output (P < 0.01), and elevated fecal water content (P < 0.05), as well as enhanced electrical field stimulation induced contractions (P < 0.05). These effects were associated with an increase in the number of glial cells and nitrergic neurons in the colonic myenteric plexus. Additionally, ENPCs in the colon showed a heightened differentiation into glial cells and nitrergic neurons. Notably, the NR1D1/nuclear factor-kappaB (NF-κB) axis played a crucial role in the CRD-mediated changes in ENPCs differentiation. Supplementation with NR1D1 agonist or NF-κB antagonist was able to restore gastrointestinal motility and normalize the ENS in jet-lagged mice.ConclusionsCRD regulates the differentiation of ENPCs through the NR1D1/NF-κB axis, resulting in dysfunction of the ENS and impaired gastrointestinal motility in mice.

Optimal Configuration Model for Large Capacity Synchronous Condenser Considering Transient Voltage Stability in Multiple UHV DC Receiving End Grids

In a multi-fed DC environment, the UHV DC recipient grid faces significant challenges related to DC phase shift failure and voltage instability due to the high AC/DC coupling strength and low system inertia level. While the new large-capacity synchronous condensers (SCs) can provide effective transient reactive power support, the associated investment and operation costs are high. Therefore, it is valuable to investigate the optimization of SC configuration at key nodes in the recipient grid in a scientific and rational manner. This study begins by qualitatively and quantitatively analyzing the dynamic characteristics of DC reactive power and induction motors under AC faults. The sub-transient and transient reactive power output model is established to describe the SC output characteristics, elucidating the coupling relationship between the SC’s reactive power output and the DC reactive power demand at different time scales. Subsequently, a critical stabilized voltage index for dynamic loads is defined, and the SC’s reactive power compensation target is quantitatively calculated across different time scales, revealing the impact of transient changes in DC reactive power on the transient voltage stability of the multi-fed DC environment with dynamic load integration. Finally, an optimal configuration model for the large-capacity SC is proposed under the critical stability constraint of dynamic loads to maximize the SC’s reactive power support capability at the lowest economic cost. The proposed model is validated in a multi-fed DC area, demonstrating that the optimal configuration scheme effectively addresses issues related to DC phase shift failures and voltage instability resulting from AC bus voltage drops.

Unveiling non-monochromatic modes and nonlinearity in Piet Hein quantum semiconductor waveguides

We investigate the propagation characteristics of transverse electric (TE) and transverse magnetic (TM) modes in a semiconductor quantum plasma-filled coaxial waveguide with a Piet Hein cross-section. The unique geometry of the Piet Hein cross-section offers intriguing possibilities for tailoring modal properties and exploiting novel nonlinear phenomena. Using analytical and numerical methods, we unveil the non-monochromatic behaviour of TE and TM modes, characterized by distinct peaks and troughs in their field components. The Ez\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_{z}$$\\end{document} component of the TM mode exhibits a suppressed field within the central core and higher concentration in the cladding region, potentially minimizing energy loss within the waveguide. The Eρ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_{\\rho }$$\\end{document} component exhibits pronounced oscillations near the waveguide boundaries, suggesting constructive and destructive interference patterns. The Eξ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_{\\xi }$$\\end{document} component displays a non-monotonic behaviour with multiple pits and bumps, highlighting the interplay between the TE mode, the Piet Hein geometry, and the semiconductor quantum plasma properties. The Bρ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_{\\rho }$$\\end{document} component of the TM mode exhibits a non-monochromatic behaviour with multiple maxima and minima, attributed to the complex interactions between propagating waves with different phase shifts. The Bξ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_{\\xi }$$\\end{document} component exhibits a non-uniform distribution with distinct pits and bumps, with a resurgence towards the waveguide edges potentially due to higher-order mode contributions and local field enhancement effects. Our findings pave the way for the development of novel photonic devices with enhanced functionalities based on Piet Hein semiconductor quantum plasma waveguides.

Flat double-layer metal-only metasurface with polarization-dependent operation in a C/X dual band

In this communication, a dual-band, orthogonal polarization transmission metasurface antenna operating at 6.5 GHz and 9.5 GHz is proposed. The element of this transmitarray is composed of only two identical layers of metal plates, with air medium filling the space between the upper and lower layers. Each layer has four sets of staggered I-slots, thus ensuring dual-frequency orthogonal polarization operation. Moreover the proposed element overcomes the challenge of achieving full 360-degree phase shift in dual-layer metal-only structures without any additional connecting elements. By altering the length of the slots, it can achieve a continuous full 360-degree phase shift while maintaining a transmission amplitude above −2 dB and exhibits co-polarized transmission in both bands. Then a prototype containing 16 × 16 elements is designed and fabricated to verify the feasibility of the design scheme. The measurement results, which are consistent with the simulation, demonstrate that the maximum gains of 24.85 and 27.64 dBi are obtained at 6.4 GHz and 9.4 GHz, with corresponding aperture efficiencies of 23.18% and 20.4% and a 3-dB gain bandwidth of 15.6% and 22.34%. The good transmission coefficients of the element and the dual-band capability make the design a competitive candidate for satellite and high-power applications.

Non-orthogonal unicast and multicast transmission with IRS-assisted Rate-Splitting Multiple Access in multiuser MISO systems

Abstract. In MISO systems, novel communication technologies such as NOMA and multicast transmission have attracted widespread attention to meet the diverse needs of users. However, traditional NOMA and multicast transmission schemes have certain limitations in dynamic interference management and resource allocation. To resolve this issue, this paper proposes a RSMA scheme assisted by phase quantized Intelligent Reflecting Surface (IRS) for downlink MISO systems with nonorthogonal transmission of unicast and multicast signals. In this scheme, through reconfiguring unicast and multicast signals and combining them into a super-common stream and partial unicast messages, RSMA achieves dynamic interference management of multi-user while effectively separating unicast and multicast streams. To maximize the weighted sum rate(WSR), we put forward an alternating optimization(AO) algorithm that utilizes Weighted Minimum Mean Square Error (WMMSE) estimation and convex set intersection representation, which jointly optimizes the equivalent beamforming matrix,rate allocation and phase shift matrix. Simulation results illustrate that the proposed single-layer RSMA exhibits performance closer to that of DPC encoding compared to traditional NOMA and MULP schemes. Furthermore, we extensively investigate the relationship between the WSR of RSMA and system parameters, providing important guidance for practical engineering applications.

High-speed 3D measurement using the kinoform array and light source shift

A new, to the best of our knowledge, fringe projector using the kinoform is proposed in this Letter. The kinoform array makes the hologram easy to manufacture, and the phase shift is realized by light source shift. The fringes can be shifted at a high speed due to the high-speed switch of the light source. An active binocular 3D measurement system using the proposed projector is demonstrated, and a binocular matching algorithm from coarse to fine using a laser speckle and fringe phase is proposed. Three laser diodes are adopted as light sources, and the three-step phase-shifting is achieved. The dimension of the projector is 30 mm × 26 mm × 12 mm and the switching speed is up to 1.5 kHz. The 3D measurement speed reaches 70 fps in the experiment.

Motion-induced phase shift for dynamic structured light measurement

Motion-induced phase shift for dynamic structured light measurement

Sub-∘C-precision temperature imaging using phase-shift luminescence thermometry

Abstract This work explores the potential of luminescence thermometry to provide temperature imaging with high temperature resolution using the phase-shift method. Phosphor thermometry has been widely used for temperature imaging, especially with the decay-time method. However, the phase-shift method was rarely used. In this approach, excitation is modulated in time, and due to the temperature-dependent luminescence dynamics of the painted luminescent probe, the emission waveform is phase-shifted with respect to the excitation waveform. Initially, a parametric study was performed on the effect of excitation waveform frequency and shape, based on a millisecond-decay time phosphor. The study found that the best precision is achieved with a square waveform at a frequency such that the phase shift is π 4 at the target temperature. Then, this method was compared with the well-established decay-time method. Phase-shift method offered a three-fold improvement in temperature precision under identical peak excitation power. Finally, two-dimensional measurements were demonstrated on a temperature-controlled plate using a high speed CMOS camera, and an LED illumination. A temperature precision of 0.13 ∘C was obtained at a temporal resolution of 0.25 s and a spatial resolution of around 1 mm, due to a pre-processing binning of 7 by 7 pixels. This technique can be used as a robust alternative to infrared thermometry to probe the thermal processes with small temperature differences.

Impact of the frequency error of direct digital synthesizers on the evaluation of two-photon light shift in atom gravimeters

One major systematic error for free-fall atom gravimeters is the effect of two-photon light shift (LS2). In the process of evaluating LS2, the results can be affected by the residual frequency error of direct digital synthesizers due to necessary experimental parameter changes. In this paper, the impact of the coupling effect between the frequency error and LS2 has been investigated and analyzed, along with the related physical mechanisms. The parameters of the frequency error sequence, such as the time step of δt and the time delay of Δt, significantly affect the bias and uncertainty of LS2. Notably, when these parameters are significantly altered or misaligned, the impact can reach several tens of µGal. Conversely, when they remain within the optimal ranges, the impact can be minimal. Specifically, when δt is less than or equal to 10 µs, the impact on the LS2 bias is less than 0.3 µGal, with the contribution to the total uncertainty of the gravity value being approximately 0.1 µGal. Furthermore, after correcting the phase shift introduced by the frequency error, the evaluation results have a similar improvement effect on the whole. Compared to the LS2 theoretical value, the residual is generally on the order of µGal. Through the comprehensive analysis and optimization, as well as related experiments, this cross-effect is managed and decoupled, leading to accurate LS2 evaluation results. This improvement ensures a better accuracy in the obtained absolute gravity values. The analysis methods discussed can provide an effective strategy for enhancing the performance of atom gravimeters.

Integrated non-reciprocal magneto-optics with ultra-high endurance for photonic in-memory computing

AbstractProcessing information in the optical domain promises advantages in both speed and energy efficiency over existing digital hardware for a variety of emerging applications in artificial intelligence and machine learning. A typical approach to photonic processing is to multiply a rapidly changing optical input vector with a matrix of fixed optical weights. However, encoding these weights on-chip using an array of photonic memory cells is currently limited by a wide range of material- and device-level issues, such as the programming speed, extinction ratio and endurance, among others. Here we propose a new approach to encoding optical weights for in-memory photonic computing using magneto-optic memory cells comprising heterogeneously integrated cerium-substituted yttrium iron garnet (Ce:YIG) on silicon micro-ring resonators. We show that leveraging the non-reciprocal phase shift in such magneto-optic materials offers several key advantages over existing architectures, providing a fast (1 ns), efficient (143 fJ per bit) and robust (2.4 billion programming cycles) platform for on-chip optical processing.

Real-time four-dimensional scanning transmission electron microscopy through sparse sampling

Abstract Four-dimensional scanning transmission electron microscopy (4-D STEM) is a state-of-theart image acquisition mode used to reveal high and low mass elements at atomic resolution. The acquisition of the electron momenta at each real space probe location allows for various analyses to be performed from a single dataset, including virtual imaging, electric field analysis, as well as analytical or iterative extraction of the object induced phase shift. However, the limiting factor in 4-D STEM is the speed of acquisition which is bottlenecked by the read-out speed of the camera, which must capture a convergent beam electron diffraction (CBED) pattern at each probe position in the scan. Recent developments in sparse sampling and image inpainting (a branch of compressive sensing) for STEM have allowed for real-time recovery of sparsely acquired data from fixed monolithic detectors, Further developments in compressive sensing for 4-D STEM have also demonstrated that acquisition speeds can be increased i.e. live video rate 4D imaging is now possible. In this work, we demonstrate the first practical implementations of compressive 4-D STEM for real-time inference on two different scanning transmission electron microscopes.

Magnetic Induction Tomography for Brain Tissue Imaging Based on Conductivity Distribution for Parkinson’s Disease Diagnosis

Parkinson's disease is a prevalent neurodegenerative complication defined by the accumulation of alpha synuclein lewy bodies in the brain. Misdiagnosis results widespread of Parkinson’s disease because clinical diagnosis is challenging, underlining a need of a better detection technique, such as non-invasive magnetic induction tomography (MIT) technique. Non-invasive techniques for biological tissues imaging are becoming popular in biomedical engineering field. Therefore, MIT technology as a non-invasive technique has been encouraged in a medical field due to its advancement of technology in diagnosing diseases. The measurement parameters in MIT are passive electromagnetic properties (conductivity, permittivity, permeability) for biological tissue and the most dominant parameter in MIT is conductivity properties. It is uses a phase shift between a primary magnetic field and an induced field caused by a target object's conductivity. As a function of conductivity, the phase shift between the applied and secondary fields is expressed. Thus, the phase shift can be used to characterize the conductivity of a target object. The phase shift between the excitation and induced magnetic fields (EMF and IMF) reflects the change in conductivity in biological tissues. This paper focuses on the virtual simulation by using COMSOL Multi-physics for the design and development of MIT system that emphasizes on single channel magnetic induction tomography for biological tissue (bran tissue) imaging based on conductivity distribution for Parkinson’s disease diagnosis. The develop system employs the use of excitation coils to induce an electromagnetic field (e.m.f) in the brain tissue, which is then measured at the receiving side by sensors. The proposed system is capable of indicating Parkinson’s disease based on conductivity distribution. This method provides the valuable information of the brain abnormality based on differences of conductivities of normal brain and Parkinson’s disease brain tissues.

Silicon photonics foundry fabricated, slow-light enhanced, low power thermal phase shifter

In this research, we developed a low-power silicon photonics foundry-fabricated slow-light thermal phase shifter (SLTPS) where the slow-light (SL) effect is achieved using an integrated Bragg grating (BG) waveguide. Heating the grating induces a red shift in the transmission spectrum, leading to an increased group index ng during operation, which facilitates a further reduction in the voltage needed for a π phase shift, i.e., Vπ. Additionally, we investigated a compact Mach–Zehnder Interferometer (MZI) that incorporates the SLTPS in both arms with a phase shifter length of 50 μm. A detailed theoretical analysis was conducted to address the non-idealities of the SL-MZI due to uneven optical power splitting and unbalanced loss in the two MZI arms. Vπ and power consumption for a π phase shift (Pπ) of the SL-MZI were quantified for operation in the slow-light regime, demonstrating a Vπ of 1.1 V and a Pπ of 3.63 mW at an operational wavelength near the photonic band edge. The figure of merit Pπ×τ is commonly used to assess the performance of thermal optical switches. The SL-MZI in this work has achieved a low Pπ×τ of 5.1 mW μs with an insertion loss of 4.4 dB, indicating a trade-off with the Vπ reduction.

Semi-active vibration control via a magnetorheological damper and active disturbance rejection control

This work provides an alternative for the semi-active vibration control problem via state feedback plus an active disturbance rejection control (K-ADRC) for a multistory building structure equipped with one magnetorheological damper (MRD) located between the ground and the first story. This control law introduces a disturbance observer (DOB) to estimate the total disturbance in real time, produced by the earthquake perturbation, unmodeled dynamics, and parametric uncertainties, and then cancel their effect using a part of the control signal. Moreover, using a diffeomorphism, the K-ADRC provides a proportional derivative (PD) controller designed to improve internal stability. A prominent feature of the active disturbance rejection control (ADRC) algorithm is that the value of the DOB gain is selected according to the system bandwidth. The stability of the system is verified via Lyapunov analysis. Moreover, the building structure model and the MRD are accomplished by incorporating a nonlinearity state that represents the hysteresis effect to perform real behavior in addition to assuming that acceleration is the only available measurement of building structures. Thus, integral filters are provided based on the appropriate cut-off frequency to estimate displacement and velocity, avoiding bias, offset, and phase shifts. Experimental results from a reduced-scale two-story building prototype demonstrate that the proposed K-ADRC is promising for real applications, and it has better performance than the state feedback (K) and the linear quadratic regulator (LQR) control techniques.

Cybernic robot hand-arm that realizes cooperative work as a new hand-arm for people with a single upper-limb dysfunction

A robot hand-arm that can perform various tasks with the unaffected arm could ease the daily lives of patients with a single upper-limb dysfunction. A smooth interaction between robot and patient is desirable since their other arm functions normally. If the robot can move in response to the user’s intentions and cooperate with the unaffected arm, even without detailed operation, it can effectively assist with daily tasks. This study aims to propose and develop a cybernic robot hand-arm with the following features: 1) input of user intention via bioelectrical signals from the paralyzed arm, the unaffected arm’s motion, and voice; 2) autonomous control of support movements; 3) a control system that integrates voluntary and autonomous control by combining 1) and 2) to thus allow smooth work support in cooperation with the unaffected arm, reflecting intention as a part of the body; and 4) a learning function to provide work support across various tasks in daily use. We confirmed the feasibility and usefulness of the proposed system through a pilot study involving three patients. The system learned to support new tasks by working with the user through an operating function that does not require the involvement of the unaffected arm. The system divides the support actions into movement phases and learns the phase-shift conditions from the sensor information about the user’s intention. After learning, the system autonomously performs learned support actions through voluntary phase shifts based on input about the user’s intention via bioelectrical signals, the unaffected arm’s motion, and by voice, enabling smooth collaborative movement with the unaffected arm. Experiments with patients demonstrated that the system could learn and provide smooth work support in cooperation with the unaffected arm to successfully complete tasks they find difficult. Additionally, the questionnaire subjectively confirmed that cooperative work according to the user’s intention was achieved and that work time was within a feasible range for daily life. Furthermore, it was observed that participants who used bioelectrical signals from their paralyzed arm perceived the system as part of their body. We thus confirmed the feasibility and usefulness of various cooperative task supports using the proposed method.

Graphene Phase Modulators Operating in the Transparency Regime.

Next-generation data networks need to support Tb/s rates. In-phase and quadrature (IQ) modulation combine phase and intensity information to increase the density of encoded data, reduce overall power consumption by minimizing the number of channels, and increase noise tolerance. To reduce errors when decoding the received signal, intersymbol interference must be minimized. This is achieved with pure phase modulation, where the phase of the optical signal is controlled without changing its intensity. Phase modulators are characterized by the voltage required to achieve a π phase shift, Vπ, the device length, L, and their product, VπL. To reduce power consumption, IQ modulators are needed with <1 V drive voltages and compact (sub-cm) dimensions, which translate in VπL < 1Vcm. Si and LiNbO3 (LN) IQ modulators do not currently meet these requirements because VπL > 1Vcm. Here, we report a double single-layer graphene (SLG) Mach-Zehnder modulator (MZM) with pure phase modulation in the transparency regime, where optical losses are minimized and remain constant with increasing voltage. Our device has VπL ∼ 0.3Vcm, matching state-of-the-art SLG-based MZMs and plasmonic LN MZMs, but with pure phase modulation and low insertion loss (∼5 dB), essential for IQ modulation. Our VπL is ∼5 times lower than the lowest thin-film LN MZMs and ∼3 times lower than the lowest Si MZMs. This enables devices with complementary metal-oxide semiconductor compatible VπL (<1Vcm) and smaller footprint than LN or Si MZMs, improving circuit density and reducing power consumption by 1 order of magnitude.