scholarly journals Dispersion measure variability for 36 millisecond pulsars at 150 MHz with LOFAR

2020 ◽  
Vol 644 ◽  
pp. A153
Author(s):  
J. Y. Donner ◽  
J. P. W. Verbiest ◽  
C. Tiburzi ◽  
S. Osłowski ◽  
J. Künsemöller ◽  
...  
Keyword(s):  
Time Series ◽  
Low Frequency ◽  
Propagation Delay ◽  
Dispersion Measure ◽  
Millisecond Pulsars ◽  
Low Frequencies ◽  
Pulsar Timing ◽  
Variable Dispersion ◽  
Delay Variations ◽  
Plasma Dispersion

Context. Radio pulses from pulsars are affected by plasma dispersion, which results in a frequency-dependent propagation delay. Variations in the magnitude of this effect lead to an additional source of red noise in pulsar timing experiments, including pulsar timing arrays (PTAs) that aim to detect nanohertz gravitational waves. Aims. We aim to quantify the time-variable dispersion with much improved precision and characterise the spectrum of these variations. Methods. We use the pulsar timing technique to obtain highly precise dispersion measure (DM) time series. Our dataset consists of observations of 36 millisecond pulsars, which were observed for up to 7.1 yr with the LOw Frequency ARray (LOFAR) telescope at a centre frequency of ~150 MHz. Seventeen of these sources were observed with a weekly cadence, while the rest were observed at monthly cadence. Results. We achieve a median DM precision of the order of 10−5 cm−3 pc for a significant fraction of our sources. We detect significant variations of the DM in all pulsars with a median DM uncertainty of less than 2 × 10−4 cm−3 pc. The noise contribution to pulsar timing experiments at higher frequencies is calculated to be at a level of 0.1–10 μs at 1.4 GHz over a timespan of a few years, which is in many cases larger than the typical timing precision of 1 μs or better that PTAs aim for. We found no evidence for a dependence of DM on radio frequency for any of the sources in our sample. Conclusions. The DM time series we obtained using LOFAR could in principle be used to correct higher-frequency data for the variations of the dispersive delay. However, there is currently the practical restriction that pulsars tend to provide either highly precise times of arrival (ToAs) at 1.4 GHz or a high DM precision at low frequencies, but not both, due to spectral properties. Combining the higher-frequency ToAs with those from LOFAR to measure the infinite-frequency ToA and DM would improve the result.

scholarly journals Millisecond pulsars at low frequencies

2017 ◽  
Vol 13 (S337) ◽  
pp. 311-312
Author(s):  
N. D. Ramesh Bhat ◽  
Steven E. Tremblay ◽  
Franz Kirsten
Keyword(s):  
South African ◽  
Southern Hemisphere ◽  
Low Frequency ◽  
Pulsar Emission ◽  
Millisecond Pulsars ◽  
Low Frequencies ◽  
Pulsar Timing ◽  
Wide Range ◽  
Propagation Effects ◽  
Murchison Widefield Array

AbstractLow-frequency pulsar observations are well suited for studying propagation effects caused by the interstellar medium (ISM). This is particularly important for millisecond pulsars (MSPs) that are part of high-precision timing applications such as pulsar timing arrays (PTA), which aim to detect nanoHertz gravitational waves. MSPs in the southern hemisphere will also be the prime targets for PTAs with the South African MeerKAT, and eventually with the SKA. The development of the Murchison Widefield Array (MWA) and the Engineering Development Array (EDA) brings excellent opportunities for low-frequency studies of MSPs in the southern hemisphere. They enable observations at frequencies from 50 MHz to 300 MHz, and can be exploited for a wide range of studies relating to pulsar emission physics and probing the ISM.

scholarly journals Gravitational wave research using pulsar timing arrays

2017 ◽  
Vol 4 (5) ◽  
pp. 707-717 ◽  
Author(s):  
George Hobbs ◽  
Shi Dai
Keyword(s):  
Gravitational Wave ◽  
High Precision ◽  
Low Frequency ◽  
Millisecond Pulsars ◽  
Pulsar Timing ◽  
Distributed Array ◽  
The Status ◽  
Wave Research ◽  
Near Future ◽  
Pulsar Timing Array

Abstract A pulsar timing array (PTA) refers to a program of regular, high-precision timing observations of a widely distributed array of millisecond pulsars. Here we review the status of the three primary PTA projects and the joint International Pulsar Timing Array project. We discuss current results related to ultra-low-frequency gravitational wave searches and highlight opportunities for the near future.

scholarly journals Tracking dispersion measure variations of timing array pulsars with the GMRT

2012 ◽  
Vol 8 (S291) ◽  
pp. 432-434 ◽  
Author(s):  
Ujjwal Kumar ◽  
Yashwant Gupta ◽  
Willem van Straten ◽  
Stefan Osłowski ◽  
Jayanta Roy ◽  
...  
Keyword(s):  
Solar Wind ◽  
Solar Corona ◽  
Radio Telescope ◽  
Line Of Sight ◽  
Dispersion Measure ◽  
Millisecond Pulsars ◽  
Preliminary Comparison ◽  
Pulsar Timing ◽  
Single Epoch ◽  
Pulsar Timing Array

AbstractWe present the results from nearly three years of monitoring of the variations in dispersion measure (DM) along the line-of-sight to 11 millisecond pulsars using the Giant Metrewave Radio Telescope (GMRT). These results demonstrate accuracies of single epoch DM estimates of the order of 5 × 10−4 cm−3 pc. A preliminary comparison with the Parkes Pulsar Timing Array (PPTA) data shows that the measured DM fluctuations are comparable. We show effects of DM variations due to the solar wind and solar corona and compare with the existing models.

scholarly journals Technical Note: Remote sensing of sea surface salinity using the propagation of low-frequency navigation signals

2014 ◽  
Vol 11 (6) ◽  
pp. 2971-2978
Author(s):  
I. Astin ◽  
Y. Feng
Keyword(s):  
Remote Sensing ◽  
Low Frequency ◽  
Potential Method ◽  
Propagation Delay ◽  
Technical Note ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Delay Variations ◽  
Navigation Signals

Abstract. This paper introduces a potential method for the remote sensing of sea surface salinity (SSS) using measured propagation delay of low-frequency Loran-C signals transmitted over an all-seawater path between the Sylt station in Germany and an integrated Loran-C/GPS receiver located in Harwich, UK. The overall delay variations in Loran-C surface waves along the path may be explained by changes in sea surface properties (especially the temperature and salinity), as well as atmospheric dynamics that determine the refractive index of the atmosphere. After removing the atmospheric and sea surface temperature (SST) effects, the residual delay revealed a temporal variation similar to that of SSS data obtained by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite.

Kinematics of Eddy–Mean Flow Interaction in an Idealized Atmospheric Model

2013 ◽  
Vol 70 (8) ◽  
pp. 2574-2595 ◽  
Author(s):  
Sergey Kravtsov ◽  
Sergey K. Gulev
Keyword(s):  
Time Series ◽  
Storm Track ◽  
Low Frequency ◽  
Atmospheric Model ◽  
Life Cycles ◽  
Mean Flow ◽  
Atmospheric Variability ◽  
Low Frequencies ◽  
The North ◽  
Position Time Series

Abstract The authors analyze atmospheric variability simulated in a two-layer baroclinic β-channel quasigeostrophic model by combining Eulerian and feature-tracking analysis approaches. The leading mode of the model's low-frequency variability (LFV) is associated with the irregular shifts of the zonal-mean jet to the north and south of its climatological position accompanied by simultaneous intensification of the jet, while the deviations from the zonal-mean fields are dominated by propagating anomalies with wavenumbers 3–5. The model's variability is shown to stem from the life cycles of cyclones and anticyclones. In particular, synthetic streamfunction fields constructed by launching idealized composite-mean eddies along the actual full-model-simulated cyclone/anticyclone tracks reproduce nearly perfectly not only the dominant propagating waves, but also the jet-shifting LFV. The composite eddy tracks conditioned on the phase of the jet-shifting variability migrate north or south along with the zonal-mean jet. The synoptic-eddy life cycles in the states with poleward (equatorward) zonal-jet shift exhibit longer-than-climatological lifetimes; this is caused, arguably, by a barotropic feedback associated with preferred anticyclonic (cyclonic) wave breaking in these respective states. Lagged correlation and cross-spectrum analyses of zonal-mean jet position time series and the time series representing mean latitudinal location of the eddies at a given time demonstrate that jet latitude leads the storm-track latitude at low frequencies. This indicates that the LFV associated with the jet-shifting mode here is more dynamically involved than being a mere consequence of the random variations in the distribution of the synoptic systems.

Empirical and theoretical analysis of the extremely low frequency arterial blood pressure power spectrum in unanesthetized rat

2006 ◽  
Vol 291 (6) ◽  
pp. H2816-H2824 ◽  
Author(s):  
David R. Brown ◽  
Lisa A. Cassis ◽  
Dennis L. Silcox ◽  
Laura V. Brown ◽  
David C. Randall
Keyword(s):  
Blood Pressure ◽  
Time Series ◽  
Power Spectrum ◽  
Arterial Blood Pressure ◽  
Low Frequency ◽  
Absolute Difference ◽  
Frequency Range ◽  
Low Frequencies ◽  
Extremely Low Frequency ◽  
Arterial Blood

The slope of the log of power versus the log of frequency in the arterial blood pressure (BP) power spectrum is classically considered constant over the low-frequency range (i.e., “fractal” behavior), and is quantified by β in the relationship “1/ fβ.” In practice, the fractal range cannot extend to indefinitely low frequencies, but factor(s) that terminate this behavior, and determine β, are unclear. We present 1) data in rats ( n = 8) that reveal an extremely low frequency spectral region (0.083–1 cycle/h), where β approaches 0 (i.e., the “shoulder”); and 2) a model that 1) predicts realistic values of β within that range of the spectrum that conforms to fractal dynamics (∼1–60 cycles/h), 2) offers an explanation for the shoulder, and 3) predicts that the “successive difference” in mean BP (mBP) is an important parameter of circulatory function. We recorded BP for up to 16 days. The absolute difference between successive mBP samples at 0.1 Hz (the successive difference, or Δ) was 1.87 ± 0.21 mmHg (means ± SD). We calculated β for three frequency ranges: 1) 0.083–1; 2) 1–6; and 3) 6–60 cycles/h. The β for all three regions differed ( P < 0.01). For the two higher frequency ranges, β indicated a fractal relationship (β6–60/h = 1.27 ± 0.01; β1–6/h = 1.80 ± 0.16). Conversely, the slope of the lowest frequency region (i.e., the shoulder) was nearly flat (β0.083–1 /h = 0.32 ± 0.28). We simulated the BP time series as a random walk about 100 mmHg with ranges above and below of 10, 30, and 50 mmHg and with Δ from 0.5 to 2.5. The spectrum for the conditions mimicking actual BP time series (i.e., range, 85–115 mmHg; Δ, 2.00) resembled the observed spectra, with β in the lowest frequency range = 0.207 and fractal-like behavior in the two higher frequency ranges (β = 1.707 and 2.057). We suggest that the combined actions of mechanisms limiting the excursion of arterial BP produce the shoulder in the spectrum and that Δ contributes to determining β.

scholarly journals Technical Note: Remote sensing of sea surface salinity using the propagation of low-frequency navigation signals

Ocean Science ◽  
2015 ◽  
Vol 11 (5) ◽  
pp. 695-698
Author(s):  
I. Astin ◽  
Y. Feng
Keyword(s):  
Remote Sensing ◽  
Low Frequency ◽  
Potential Method ◽  
Propagation Delay ◽  
Technical Note ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Delay Variations ◽  
Navigation Signals

Abstract. This paper introduces a potential method for the remote sensing of sea surface salinity (SSS) using the measured propagation delay of low-frequency Loran-C signals transmitted over an all-seawater path between the Sylt station in Germany and an integrated Loran-C/GPS receiver located in Harwich, UK. The overall delay variations in Loran-C surface waves along the path may be explained by changes in sea surface properties (especially the temperature and salinity), as well as atmospheric properties that determine the refractive index of the atmosphere. After removing the atmospheric and sea surface temperature (SST) effects from the measured delay, the residual delay revealed a temporal variation similar to that of SSS data obtained by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite.

scholarly journals Multiscale Decomposition and Spectral Analysis of Sector ETF Price Dynamics

2021 ◽  
Vol 14 (10) ◽  
pp. 464
Author(s):  
Tim Leung ◽  
Theodore Zhao
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Financial Time Series ◽  
Low Frequency ◽  
Ensemble Empirical Mode Decomposition ◽  
Price Dynamics ◽  
Exchange Traded Funds ◽  
Intrinsic Mode Functions ◽  
Low Frequencies ◽  
Financial Time

We present a multiscale analysis of the price dynamics of U.S. sector exchange-traded funds (ETFs). Our methodology features a multiscale noise-assisted approach, called the complementary ensemble empirical mode decomposition (CEEMD), that decomposes any financial time series into a number of intrinsic mode functions from high to low frequencies. By combining high-frequency modes or low-frequency modes, we show how to filter the financial time series and estimate conditional volatilities. The results show the different dynamics of the sector ETFs on multiple timescales. We then apply Hilbert spectral analysis to derive the instantaneous energy-frequency spectrum of each sector ETF. Using historical ETF prices, we illustrate and compare the properties of various timescales embedded in the original time series. Through the new metrics of the Hilbert power spectrum and frequency deviation, we are able to identify differences among sector ETF and with respect to SPY that were not obvious before.

scholarly journals First detection of frequency-dependent, time-variable dispersion measures

2019 ◽  
Vol 624 ◽  
pp. A22 ◽  
Author(s):  
J. Y. Donner ◽  
J. P. W. Verbiest ◽  
C. Tiburzi ◽  
S. Osłowski ◽  
D. Michilli ◽  
...  
Keyword(s):  
Frequency Dependence ◽  
High Precision ◽  
Low Frequency ◽  
Time Variable ◽  
Small Scale ◽  
Dispersion Measure ◽  
Electron Content ◽  
Frequency Dependent ◽  
Pulsar Timing

Context. High-precision pulsar-timing experiments are affected by temporal variations of the dispersion measure (DM), which are related to spatial variations in the interstellar electron content and the varying line of sight to the source. Correcting for DM variations relies on the cold-plasma dispersion law which states that the dispersive delay varies with the squared inverse of the observing frequency. This may, however, give incorrect measurements if the probed electron content (and therefore the DM) varies with observing frequency, as is predicted theoretically due to the different refraction angles at different frequencies. Aims. We study small-scale density variations in the ionised interstellar medium. These structures may lead to frequency-dependent DMs in pulsar signals. Such an effect could inhibit the use of lower-frequency pulsar observations as tools to correct time-variable interstellar dispersion in higher-frequency pulsar-timing data. Methods. We used high-cadence, low-frequency observations with three stations from the German LOng-Wavelength (GLOW) consortium, which are part of the LOw-Frequency ARray (LOFAR). Specifically, 3.5 yr of weekly observations of PSR J2219+4754 are presented. Results. We present the first detection of frequency-dependent DMs towards any interstellar object and a precise multi-year time-series of the time- and frequency-dependence of the measured DMs. The observed DM variability is significant and may be caused by extreme scattering events. Potential causes for frequency-dependent DMs are quantified and evaluated. Conclusions. We conclude that frequency dependence of DMs has been reliably detected and is indeed caused by small-scale (up to tens of AUs) but steep density variations in the interstellar electron content. We find that long-term trends in DM variability equally affect DMs measured at both ends of our frequency band and hence the negative impact on long-term high-precision timing projects is expected to be limited.

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

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