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At least 19 records

Mechanistic Pathways for N 2 O Elimination from trans -R 3 Sn-O-N=N-O-SnR 3 and for Reversible Binding of CO 2 to R 3 Sn-O-SnR 3 (R = Ph, Cy)

The rate and mechanism of the elimination of N 2 O from trans-R 3 Sn-O-N=N-O-SnR 3 (R = Ph ( 1 Ph ) and R = Cy ( 1 Cy )) to form R 3 Sn-O-SnR 3 (R = Ph ( 2 Ph ) and R = Cy ( 2 Cy )) have been studied using both NMR and IR techniques to monitor the reactions in the temperature range of 39–79 °C in C 6 D 6 . Activation parameters for this reaction are ΔH ‡ = 15.8 ± 2.0 kcal·mol –1 and ΔS ‡ = –28.5 ± 5 cal·mol –1 ·K –1 for 1 Ph and ΔH ‡ = 22.7 ± 2.5 kcal·mol –1 and ΔS ‡ = –12.4 ± 6 cal·mol –1 ·K –1 for 1 Cy . Addition of O 2 , CO 2 , N 2 O, or PPh 3 to sealed tube NMR experiments did not alter in a detectable way the rate or product distribution of the reactions. Computational DFT studies of elimination of hyponitrite from trans-Me 3 Sn-O-N=N-O-SnMe 3 ( 1 Me ) yield a mechanism involving initial migration of the R 3 Sn group from O to N passing through a marginally stable intermediate product and subsequent N 2 O elimination. Reactions of 1 Ph with protic acids HX are rapid and lead to formation of R 3 SnX and trans-H 2 N 2 O 2 . Reaction of 1 Ph with the metal radical •Cr(CO) 3 C 5 Me 5 at low concentrations results in rapid evolution of N 2 O. At higher •Cr(CO) 3 C 5 Me 5 concentrations, evolution of CO 2 rather than N 2 O is observed. Addition of 1 atm or less CO 2 to benzene or toluene solutions of 2 Ph and 2 Cy resulted in very rapid reaction to form the corresponding carbonates R 3 Sn-O-C(=O)-O-SnR 3 (R = Ph ( 3 Ph ) and R = Cy ( 3 Cy )) at room temperature. Evacuation results in fast loss of bound CO 2 and regeneration of 2 Ph and 2 Cy . Variable temperature data for formation of 3 Cy yield ΔH o = –8.7 ± 0.6 kcal·mol –1 , ΔS o = –17.1 ± 2.0 cal·mol –1 ·K –1 , and ΔG o 298K = –3.6 ± 1.2 kcal·mol –1 . Furthermore, DFT studies were performed and provide additional insight into the energetics and mechanisms for the reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusive electron acceleration at SNR shock fronts and the observed SNR radio spectral indices

The radio synchrotron emission from relativistic electrons in shell supernova remnants (SNRs) provides a unique opportunity to probe the energy distribution of energetic electrons at their acceleration site (SNR shock fronts). This information provides insight into the acceleration mechanism(s). The implications of these observations for the diffusive (first-order Fermi) acceleration of electrons at the SNR shock fronts are discussed.

Bogdan, T. J.↗

Study of the GeV to TeV morphology of the γ Cygni SNR (G 78.2+2.1) with MAGIC and Fermi-LAT

Context: Diffusive shock acceleration (DSA) is the most promising mechanism that accelerates Galactic cosmic rays (CRs) in the shocks of supernova remnants (SNRs). It is based on particles scattering caused by turbulence ahead and behind the shock. The turbulence upstream is supposedly generated by the CRs, but this process is not well understood. The dominant mechanism may depend on the evolutionary state of the shock and can be studied via the CRs escaping upstream into the interstellar medium (ISM). Aims: Previous observations of the γ Cygni SNR showed a difference in morphology between GeV and TeV energies. Since this SNR has the right age and is at the evolutionary stage for a significant fraction of CRs to escape, our aim is to understand γ-ray emission in the vicinity of the γ Cygni SNR. Methods: We observed the region of the γ Cygni SNR with the MAGIC Imaging Atmospheric Cherenkov telescopes between 2015 May and 2017 September recording 87 h of good-quality data. Additionally, we analysed Fermi-LAT data to study the energy dependence of the morphology as well as the energy spectrum in the GeV to TeV range. The energy spectra and morphology were compared against theoretical predictions, which include a detailed derivation of the CR escape process and their γ-ray generation. Results: The MAGIC and Fermi-LAT data allowed us to identify three emission regions that can be associated with the SNR and that dominate at different energies. Our hadronic emission model accounts well for the morphology and energy spectrum of all source components. It constrains the time-dependence of the maximum energy of the CRs at the shock, the time-dependence of the level of turbulence, and the diffusion coefficient immediately outside the SNR shock. Further, while in agreement with the standard picture of DSA, the time-dependence of the maximum energy was found to be steeper than predicted, and the level of turbulence was found to change over the lifetime of the SNR.

79 ASTRONOMY AND ASTROPHYSICS↗

Late-Time Evolution of Composite Supernova Remnants: Deep Chandra Observations and Hydrodynamical Modeling of a Crushed Pulsar Wind Nebula in SNR G327.1-1.1

In an effort to better understand the evolution of composite supernova remnants (SNRs) and the eventual fate of relativistic particles injected by their pulsars, we present a multifaceted investigation of the interaction between a pulsar wind nebula (PWN) and its host SNR G327.1-1.1. Our 350 ks Chandra X-ray observations of SNR G327.1-1.1 reveal a highly complex morphology; a cometary structure resembling a bow shock, prong-like features extending into large arcs in the SNR interior, and thermal emission from the SNR shell. Spectral analysis of the non-thermal emission offers clues about the origin of the PWN structures, while enhanced abundances in the PWN region provide evidence for mixing of supernova ejecta with PWN material. The overall morphology and spectral properties of the SNR suggest that the PWN has undergone an asymmetric interaction with the SNR reverse shock(RS) that can occur as a result of a density gradient in the ambient medium and or a moving pulsar that displaces the PWN from the center of the remnant. We present hydrodynamical simulations of G327.1-1.1 that show that its morphology and evolution can be described by a approx. 17,000 yr old composite SNR that expanded into a density gradient with an orientation perpendicular to the pulsar's motion. We also show that the RSPWN interaction scenario can reproduce the broadband spectrum of the PWN from radio to gamma-ray wavelengths. The analysis and modeling presented in this work have important implications for our general understanding of the structure and evolution of composite SNRs.

Evolution↗

SNR estimation for the baseband assembly

The expected value and the variance of the Baseband Assembly symbol signal-to-noise ratio (SNR) estimation algorithm are derived. The SNR algorithm treated here is designated as the Split Symbol Moments Estimator (SSME). It consists of averaging the first two moments of the integrated half symbols. The SSME is a biased, consistent estimator. The SNR degradation factor due to the jitter in the subcarrier demodulation and symbol synchronization loops is taken into account. Curves of the expected value of the SNR estimator versus the actual SNR are presented.

Simon, M. K.↗

ASCA and Bepposax Observations of the Newly Discovered SNR RX J0852-4622

The NASA Grant supported analysis of X-ray data from the supernova remnant (SNR) G266.2-1.2, a newly discovered SNR in the direction of Vela. Our observations reveal that the X-ray emission from this remnant is nonthermal, making this the third shell-type SNR for which the X-ray emission is dominated by synchrotron processes. The interpretation is that the SNR is an efficient accelerator of cosmic rays, with direct evidence of electrons at energies approaching 100 TeV. Our spectral analysis indicates a higher absorption than for the Vela SNR, indicating that G266.2-1.2 is more distant. However, we conclude that the lack of high amounts of absorption place the remnant closer than the Vela molecular ridge at a distance of 1-2 kpc. We observe a compact X-ray source at the remnant center, surrounded by diffuse emission, which may be an associated neutron star.

Oliversen, Ronald J.↗

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

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.

Johnson, Hans↗

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

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.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-rate convolutional code construction with the minimum required SNR criterion

New short constraint length, high-rate convolutional codes which minimize the required signal to noise ratios (SNR) are found and tabulated for rates 2/3, 3/4, and 4/5, and for constraint length K up to 10. When compared with previously reported codes, most of the new codes reduce the required SNR only slightly. However, there are some pairs of K and code rate for which the new codes require considerably less SNR. The most significant one is the new K = 8, ate 4/5 code which requires 1.2 dB less SNR than the known code with the same parameters, for a desired bit error rate of 0.000001.

Lee, P. J.↗

X-ray spectrum of Kepler's SNR

Observations made with the solid state spectrometer aboard the Einstein Observatory confirm Kepler's SNR as an X-ray source with an intensity between 1-3 KeV of 7.2 x 10 to the-11th power ergs/sq cm-s. The X-ray spectrum is similar to those of Cas A and Tycho, with strong line emission from the helium-like species of Si, S, and Ar. Direct comparisons to Tycho's SNR suggest a distance of Kepler's SNR of greater than or equal to 5 kpc.

Becker, R. H.↗

Optimal filters - A unified approach for SNR and PCE

A unified approach for a general metric that encompasses both the signal-to-noise ratio (SNR) and the peak-to-correlation (PCE) ratio in optical correlators is described. In this approach, the connection between optimizing SNR and optimizing PCE is achieved by considering a metric in which the central correlation irradiance is divided by the total energy of the correlation plane. The peak-to-total energy (PTE) is shown to be optimized similarly to SNR and PCE. Since PTE is a function of the search values G and beta, the optimal filter is determined with only a two-dimensional search.

Juday, Richard D.↗

Towards optimum demodulation of bandwidth-limited and low SNR square-wave subcarrier signals

The optimum phase detector is presented for tracking square-wave subcarriers that have been bandwidth limited to a finite number of harmonics. The phase detector is optimum in the sense that the loop signal-to-noise ratio (SNR) is maximized and, hence, the rms phase tracking error is minimized. The optimum phase detector is easy to implement and achieves substantial improvement. Also presented are the optimum weights to combine the signals demodulated from each of the harmonics. The optimum weighting provides SNR improvement of 0.1 to 0.15 dB when the subcarrier loop SNR is low (15 dB) and the number of harmonics is high (8 to 16).

Feria, Y.↗

HRI Observations of Balmer Dominated Filaments in the SNR RCW86

The objective of this project was to use the ROSAT HRI to study the recently discovered optical Balmer-dominated filaments in the young SNR R-CW86. The observations provide complete high-resolution X-ray coverage of the shell of the SNR. These X-ray observations are combined with new optical observations (both imaging and spectroscopic), and new high resolution radio observations to provide a better overall understanding of the state of the remnant (Sedov or reverse shock), its history (as the possible SNR of SN 185 AD), and the physics of non-radiative shocks.

Long, Knox S.↗

Galactic SNR Candidates in the ROSAT All-Sky Survey

Identified radio supernova remnants (SNRS) in the Galaxy comprise an incomplete sample of the SNR population due to various selection effects. ROSAT performed the first all-sky survey with an imaging X-ray telescope, and thus provides another window for finding SNRS and compact objects that may reside within them. Performing a search for extended X-ray sources in the ROSAT all-sky survey database about 350 objects were identified as SNR candidates in recent years. Continuing this systematic search, we have reanalyzed the ROSAT all-sky survey (BASS) data of these candidates and correlated the results with radio surveys like NVSS, ATNF, Molonglo, and Effelsberg. A further correlation with SIMBAD and NED were used for subsequent identification purpose. About 50 of the 350 candidates turned out to be likely galaxies or clusters of galaxies. We found 14 RASS sources which are very promising SNR candidates and are currently subject of further follow-up studies. We will provide the details of the identification campaign and present first results.

Schaudel, Daniel↗

ASCA and Bepposax Observations of the Newly Discovered SNR RX J0852-4622

This grant supports an investigation of the supernova remnant RX J0852-4622 (G266.1-1.2), a large-diameter, nearby SNR for which the X-ray emission is dominated by nonthermal processes. As only the third such SNR discovered, for which there is direct evidence of cosmic-ray acceleration dominating the SNR dynamics, this is an exceptionally important object. Our progress on this study to date has been good. We have published the results of a spectral mapping of the XNR as well as the identification of a compact X-ray source which may be the associated neutron star. Our final work involves modeling of the emission using limits from the radio flux in order to estimate the inverse-Compton flux that might be observable in the TeV gamma-ray regime. We have just completed similar modeling of the emission from G347.3-0.5 (Lazendic et al. - submitted to ApJ), and the results have drawn considerable interest in the gamma-ray community (Slane 2002; astro-ph/0212353). Extensive observations of G266.1--1.2 with the CANGAROO TeV gamma-ray telescope have been carried out, and our modeling of the broad-band emission characteristic are of importance for such studies.

Slane, Patrick↗

Real-time Signal-to-noise Ratio (SNR) Estimation for BPSK and QPSK Modulation Using the Active Communications Channel

Method and apparatus for estimating signal-to-noise ratio (SNR) gamma of a composite input signal e(t) on a phase modulated (e.g., BPSK) communications link. A first demodulator receives the composite input signal and a stable carrier signal and outputs an in-phase output signal; a second demodulator receives the composite input signal and a phase-shifted version of the carrier signal and outputs a quadrature-phase output signal; and phase error theta(sub E)(t) contained within the composite input signal e(t) is calculated from the outputs of the first and second demodulators. A time series of statistically independent phase error measurements theta(sub E)(t(sub 1)), theta (sub E)(t(sub 2)),..., theta (sub E)(t(sub k)) is obtained from the composite input signal subtending a time interval delta t = t(sub k) - t(sub 1) whose value is small enough such that gamma(t) and sigma(t) can be taken to be constant in delta t. A biased estimate gamma(sup *) for the signal-to-noise ratio (SNR) gamma if the composite input signal is calculated using maximum likelihood (ML) estimation techniques, and an unbiased estimate gamma(sup ^) for the signal-to-noise ratio (SNR) gamma of the composite input signal is determined from the biased estimate gamma(sup *), such as by use of a look-up table.

Manning, Robert M.↗

A Modeling and Simulation Study for the GeoXO Atmospheric Composition Instrument (ACX): System Level SO2 and O3 Retrieval Performance as a Function of SNR

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral UV/visible atmospheric composition instrument in geostationary orbit slated for operations by the early 2030s. Trace gas retrievals provide critical information about our Earth’s system as it relates to both natural and anthropogenic activity. This work focused on the impacts of the signal-to-noise ratio (SNR) on the retrieval uncertainty of SO2 and O3. An end-to-end physics-based imaging system and scene modeling and simulation framework was developed to assess instrument performance considerations in support of the planned GeoXO atmospheric composition instrument (ACX). The framework is composed of three primary components: 1) simulated at-sensor radiance via radiative transfer models of a known atmospheric composition, 2) a noise model driven by previous and planned sensor specifications, and 3) a physical retrieval algorithm. In this analysis, the tropospheric concentrations of SO2 and O3 in the atmospheric column were varied in the boundary layer (0-3 km) and at an elevation of 5 km with a thickness of 1-2 km; the uncertainty in retrieval was studied for various SNR levels for multiple viewing geometries and solar zenith angles. This effort supports the development of the GeoXO ACX instrument by providing a simulated ACX performance assessment of the system-level retrieval performance as a function of SNR, particularly with respect to the wavelength range of interest (approximately 305 – 340 nm) for SO2 and O3 trace gas retrievals.

Monica Cook↗

Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models

We derive an asymptotic expansion for the log-likelihood of Gaussian mixture models (GMMs) with equal covariance matrices in the low signal-to-noise regime. The expansion reveals an intimate connection between two types of algorithms for parameter estimation: the method of moments and likelihood optimizing algorithms such as Expectation-Maximization (EM). We show that likelihood optimization in the low SNR regime reduces to a sequence of least squares optimization problems that match the moments of the estimate to the ground truth moments one by one. This connection is a stepping stone towards the analysis of EM and maximum likelihood estimation in a wide range of models. A motivating application for the study of low SNR mixture models is cryo-electron microscopy data, which can be modeled as a GMM with algebraic constraints imposed on the mixture centers. We discuss the application of our expansion to algebraically constrained GMMs, among other example models of interest. © 2022 The Authors. Communications on Pure and Applied Mathematics published by Wiley Periodicals LLC.

97 MATHEMATICS AND COMPUTING↗