Silicon photonics (SiPh) are considered a promising technology for increasing interconnect speed and capacity while decreasing power consumption. Mode division multiplexing (MDM) enables signals to be transmitted in different orthogonal modes in a single waveguide core. Wideband MDM components simultaneously supporting wavelength division multiplexing (WDM) and orthogonal frequency-division multiplexing (OFDM) can significantly increase the transmission capacity for optical interconnects. In this work, we propose, fabricate and demonstrate a wideband and channel switchable MDM optical power divider on an SOI platform, supporting single, dual and triple modes. The switchable MDM power divider consists of two parts. The first part is a cascaded Mach-Zehnder interferometer (MZI) for switching the data from their original TE, TE and TE modes to different modes among themselves. After the target modes are identified, mode up-conversion and Y-branch are utilized in the second part for the MDM power division. Here, 48 WDM wavelength channels carrying OFDM data are successfully switched and power divided. An aggregated capacity of 7.682 Tbit/s is achieved, satisfying the pre-forward error correction (pre-FEC) threshold (bit-error-rate, BER = 3.8 × 10). Although up to three MDM modes are presented in the proof-of-concept demonstration here, the proposed scheme can be scaled to higher order modes operation.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866329PMC
http://dx.doi.org/10.3390/s23020711DOI Listing

Publication Analysis

Top Keywords

division multiplexing
12
power divider
12
wideband channel
8
channel switchable
8
mode division
8
multiplexing mdm
8
mdm optical
8
optical power
8
7682 tbit/s
8
optical interconnects
8

Similar Publications

Background: Delirium after cardiac surgery is common, morbid, and costly, but may be prevented with risk stratification and targeted intervention. In this study, we aimed to identify protein biomarkers and develop a predictive model for postoperative delirium in older patients undergoing cardiac surgery.

Methods: SomaScan analysis of 1305 proteins in the plasma from 57 older adults undergoing cardiac surgery requiring cardiopulmonary bypass was conducted to define delirium-specific protein signatures at baseline (preoperative baseline timepoint [PREOP]) and postoperative day 2 (POD2).

View Article and Find Full Text PDF

As the demand for computational performance in artificial intelligence (AI) continues to increase, diffractive deep neural networks (DNNs), which can perform AI computing at the speed of light by repeated optical modulation with diffractive optical elements (DOEs), are attracting attention. DOEs are varied in terms of fabrication methods and materials, and among them, volume holographic optical elements (vHOEs) have unique features such as high selectivity and multiplex recordability for wavelength and angle. However, when those are used for DNNs, they suffer from unknown wavefront aberrations compounded by multiple fabrication errors.

View Article and Find Full Text PDF

Self-supervised parametric map estimation for multiplexed PET with a deep image prior.

Phys Med Biol

January 2025

The Division of Imaging Sciences and Biomedical Engineering, King's College London, 5th Floor Becket House, London, SE1 7EH, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

Multiplexed positron emission tomography (mPET) imaging allows simultaneous observation of physiological and pathological information from multiple tracers in a single PET scan. Although supervised deep learning has demonstrated superior performance in mPET image separation compared to purely model-based methods, acquiring large amounts of paired single-tracer data and multi-tracer data for training poses a practical challenge and needs extended scan durations for patients. In addition, the generalisation ability of the supervised learning framework is a concern, as the patient being scanned and their tracer kinetics may potentially fall outside the training distribution.

View Article and Find Full Text PDF

Unlabelled: Due to its natural influenza susceptibility, clinical signs, transmission, and similar sialic acid residue distribution, the ferret is the primary animal model for human influenza research. Antibodies generated following infection of ferrets with human influenza viruses are used in surveillance to detect antigenic drift and cross-reactivity with vaccine viruses and circulating strains. Inoculation of ferrets, with over 1,500 human clinical influenza isolates (1998-2019) resulted in lower antibody responses (HI <1:160) to 86% (387 out of 448) influenza B viruses (IBVs) compared to 2.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!