Deep learning enhanced Rydberg multifrequency microwave recognition
arXiv:2202.13617 · doi:10.1038/s41467-022-29686-7
Abstract
Recognition of multifrequency microwave (MW) electric fields is challenging because of the complex interference of multifrequency fields in practical applications. Rydberg atom-based measurements for multifrequency MW electric fields is promising in MW radar and MW communications. However, Rydberg atoms are sensitive not only to the MW signal but also to noise from atomic collisions and the environment, meaning that solution of the governing Lindblad master equation of light-atom interactions is complicated by the inclusion of noise and high-order terms. Here, we solve these problems by combining Rydberg atoms with deep learning model, demonstrating that this model uses the sensitivity of the Rydberg atoms while also reducing the impact of noise without solving the master equation. As a proof-of-principle demonstration, the deep learning enhanced Rydberg receiver allows direct decoding of the frequency-division multiplexed (FDM) signal. This type of sensing technology is expected to benefit Rydberg-based MW fields sensing and communication.
References in corpus (24)
- Quantum superhet based on microwave-dressed Rydberg atoms
- ARC: An open-source library for calculating properties of alkali Rydberg atoms
- Broadband Rydberg Atom-Based Electric-Field Probe: From Self-Calibrated Measurements to Sub-Wavelength Imaging
- Digital Communication with Rydberg Atoms & Amplitude-Modulated Microwave Fields
- Waveguide-coupled Rydberg spectrum analyzer from 0 to 20 GHz
- Fast machine-learning online optimization of ultra-cold-atom experiments
- Assessment of Rydberg Atoms for Wideband Electric Field Sensing
- Quantum-Limited Atomic Receiver in the Electrically Small Regime
- Determining the Angle-of-Arrival of an Radio-Frequency Source with a Rydberg Atom-Based Sensor
- The credibility of Rydberg atom based digital communication over a continuously tunable radio-frequency carrier
- Rydberg-atom based radio-frequency electrometry using frequency modulation spectroscopy in room temperature vapor cells
- Machine learning-based classification of vector vortex beams
- Detecting and Receiving Phase Modulated Signals with a Rydberg Atom-Based Mixer
- Microwave electrometry via electromagnetically induced absorption in cold Rydberg atoms
- Deep learning enhanced Rydberg multifrequency microwave recognition
- Multiparameter optimisation of a magneto-optical trap using deep learning
- Enhanced electric field sensitivity of rf-dressed Rydberg dark states
- Atom-based quantum receiver for amplitude- and frequency-modulated baseband signals in high-frequency radio communication
- Quantum Physics Meets Music: A "Real-Time" Guitar Recording Using Rydberg-Atoms and Electromagnetically Induced Transparency
- Deep Reinforcement Learning Control of Quantum Cartpoles
- Machine learning recognition of light orbital-angular-momentum superpositions
- Bayesian optimal control of GHZ states in Rydberg lattices
- Controlled Online Optimization Learning (COOL): Finding the ground state of spin Hamiltonians with reinforcement learning
- Time-dependent atomic magnetometry with a recurrent neural network
Cited by in corpus (16)
- Enhanced metrology at the critical point of a many-body Rydberg atomic system
- Deep learning enhanced Rydberg multifrequency microwave recognition
- Highly sensitive measurement of a megahertz rf electric field with a Rydberg-atom sensor
- Quantum sensing of microwave electric fields based on Rydberg atoms
- Rydberg Atomic Quantum Receivers for Classical Wireless Communication and Sensing
- Improvement of response bandwidth and sensitivity of Rydberg Receiver using multi-channel excitations
- Sensitivity of Rydberg-atom receiver to frequency and amplitude modulation of microwaves
- Noise analysis of the atomic superheterodyne receiver based on flat-top laser beams
- Continuous field tracking with machine learning and steady state spin squeezing
- Detection of HF and VHF Fields through Floquet Sideband Gaps by `Rabi Matching' Dressed Rydberg Atoms
- Quantum scaling atomic superheterodyne receiver
- A Rydberg atom based system for benchmarking mmWave automotive radar chips
- Research progress of artificial intelligence empowered quantum communication and quantum sensing systems
- Fingerprint Recognition of Partial Discharge Signals in Deep Learning Enhanced Rydberg Atomic Sensors
- Non-Linearities In Atomic Quantum Receivers: Harmonic And Intermodulation Distortion
- Doppler-enhanced superheterodyne Rydberg microwave receiver