Effects of transmitted noise on receiver signal-to-noise ratios
Effects of transmitted noise on receiver signal to noise ratios
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Effects of transmitted noise on receiver signal to noise ratios
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This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.
This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.
This invention relates to a system for use in a ground station radio communication receiver for improving the signal-to-noise ratio of weak signals received from distant spacecraft.
Signal information is processed with the help of algorithms, and then on the basis of such processing, a part of the information is subjected to further processing with the help of more precise algorithms. Such a system of algorithms is studied, a comparative evaluation of a series of lower level algorithms is given, and the corresponding algorithms of higher level are characterized.
The multi-pass Thomson scattering (TS) scheme enables obtaining many photons by accumulating multiple TS signals. The signal-to-noise ratio (SNR) depends on the accumulation number. In this study, we performed multi-pass TS measurements for ohmically heated plasmas, and the relationship between SNR and the accumulation number was investigated. As a result, improvement of SNR in this experiment indicated similar tendency to that calculated for the background noise dominant situation.
The signal-to-noise ratio received at Earth is typically larger than 10 dB-Hz for radio tracking of a spacecraft in deep space, allowing a phase-locked loop to execute reliable carrier tracking. Recently, missions have been proposed to utilize low-gain antennas for Doppler tracking where the signal-to-noise ratio may be at the single-digit (dB-Hz) level. In this work, we discuss spacecraft Doppler tracking at these low signal-to-noise ratios through an analysis of thermal noise on the radio link, results from ground testing with the Deep Space Network, and demonstrations with an active spacecraft. We show that by utilizing an open-loop receiver to capture the carrier signal and by applying post-processing techniques, radio data with the signal-to-noise ratio as low as 4 dB-Hz can be used to derive Doppler data with precision sufficient for tracking a spacecraft in deep space.
Influence of bandwidth restriction on signal to noise performance of modulated PCM/NRZ signal
Purpose: To evaluate implementation of AAPM TG-150’s draft recommendations via a parameter study for testing the performance of digital image receptors. Methods: Flat field images were acquired from 9 calibrated digital image receptors associated with 9 new portable digital radiography systems (Carestream Health, Inc.) based on the draft recommendations and manufacturer-specified calibration conditions (set of 4 images at input detector air kerma ranging from 1 to 25 µGy). Effects of exposure response function (linearized and logarithmic), ‘Presentation Intent Type’ (‘For Processing’ and ‘For Presentation’), detector orientation with respect to the anode-cathode axis (4 orientations; 900 rotations per iteration), different ROI sizes (5×5–40×40 mm{sup 2}) and elimination of varying dimensions of image border (0 mm i.e., without boundary elimination to 150 mm) on signal, noise, signal-to-noise ratio (SNR) and the associated nonuniformities were evaluated. Images were analyzed in Matlab and quantities were compared using ANOVA. Results: Signal, noise and SNR values averaged over 9 systems with default parameter values in draft recommendations were 4837.2±139.4, 19.7±0.9 and 246.4±10.1 (mean ± standard deviation), respectively (at input detector air kerma: 12.5 µGy). Signal, noise and SNR showed characteristic dependency on exposure response function and on ‘Presentation Intent Type’. These values were not affected by ROI size and detector orientation, but analysis showed that eliminating the edge pixels along the boundary was required for the noise parameter (coefficient of variation range for noise: 72%–106% and 3%–4% without and with boundary elimination; respectively). Local and global nonuniformities showed a similar dependence on the need for boundary elimination. Interestingly, computed non-uniformities showed agreement with manufacturer-reported values except for noise non-uniformities in two units; artifacts were seen in images from these two units highlighting the importance of independent evaluations. Conclusion: The effect of different parameters on performance characterization of digital image receptors was evaluated based on TG-150’s draft recommendations.
This research presents an innovative approach to improving the Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals, utilizing FPGA-based adaptive filtering on the control board. Our solution aims to bolster quantum computations' reliability by providing a more accurate and precise way to obtain our readout traces and achieve a higher discernability between excitation states in real-time.
Variance of signal-estimation error minimized. Mathematical technique extracts best estimates of signal component from periodic digital samples of signal plus noise. Technique combines Kalman- and smoothingfilter algorithms to minimize mean-square estimation error based on past, present, and predicted samples of signal plus noise. Technique useful in image analysis and other applications involving processing of noisy signals.
Signal-induced noise is generated when a photomultiplier tube (PMT) is subjected to an intense light pulse. The PMT signal does not return to the dark current level after the signal is removed, but decays slowly (i.e., signal-induced noise). This is of practical significance for DIAL (Differential Absorption lidar) measurements where signal-induced noise decays are superimposed on the on-line (absorption) and off-line signals. Errors in the ozone density calculation result for stratosphere measurements. Other researchers have implemented mechanical choppers that block the intense pulse which may be from near field return scattering or scattering from a cloud. This configuration cannot be implemented for the DIAL system employed for aircraft measurements since the on-line and off-line pulses are 300 microseconds apart. A scheme has been developed in this study to electronically attenuate the signal induced noise. A ring electrode, external to the PMT photocathode, is utilized to perturb the electron trajectories between the photocathode and the first dynode. This effect has been used for position sensitive PMTs and suggested for gating PMTS.
Horizon sensor - signal-to-noise ratio at three temperatures and two bandwidths
The Signal-to-Noise Ratio (SNR) of a radar echo signal will vary across a range swath, due to spherical wavefront spreading, atmospheric attenuation, and antenna beam illumination. The antenna beam illumination will depend on antenna pointing. Calculations of geometry are complicated by the curved earth, and atmospheric refraction. This report investigates optimizing antenna pointing to maximize the minimum SNR across the range swath.
A method includes receiving an output signal from a sensor, recovering a noise signal from the output signal, comparing the noise signal with a stored baseline noise signature, and reporting authentication of the sensor if the comparison is within a pre-determined error limit. A sensor authentication apparatus, comprises a processor and a memory operably coupled with the processor. Instructions, when executed, cause the processor to separate a noise signal from a measured signal, and detect a noise signature match by comparing the noise signal with at least one stored baseline noise signature associated with the sensor. A sensor authentication system comprises a sensor authentication unit and a data acquisition unit. At least one of the sensor authentication unit and the data acquisition unit is configured to compare a noise signal with a baseline noise signature to authenticate the at least one sensor from among a plurality of sensors.
We have developed a high-resolution x-ray spectrometer for measuring the shapes of spectral lines produced from laser-irradiated targets on the Orion laser facility. The instrument utilizes a spherically bent crystal geometry to spatially focus and spectrally analyze photons from foil or microdot targets. The high photon collection efficiency resulting from its imaging properties allows the instrument to be mounted outside the Orion chamber, where it is far less sensitive to particles, hard x-rays, or electromagnetic pulses than instruments housed close to the target chamber center in ten-inch manipulators. Moreover, Bragg angles above 50° are possible, which provide greatly improved spectral resolution compared to radially viewing, near grazing-incidence crystal spectrometers. These properties make the new instrument an ideal lineshape diagnostic for determining plasma temperature and density. We describe its calibration on the Livermore electron beam ion trap facility and present spectral data of the K-shell emission from highly charged sulfur produced by long-pulse as well as short-pulse beams on the Orion laser in the United Kingdom.
Statistical method estimates signal-to-noise ratios in an observed random voltage, such as the output of a telemetry receiver. Signals from a distant transmitting source, overlaid by noise signals, are monitored continuously.