scholarly journals MODELING PULSAR TIME NOISE WITH LONG TERM POWER LAW DECAY MODULATED BY SHORT TERM OSCILLATIONS OF THE MAGNETIC FIELDS OF NEUTRON STARS

2013 ◽  
Vol 22 (11) ◽  
pp. 1360012 ◽  
Author(s):  
SHUANG-NAN ZHANG ◽  
YI XIE
Keyword(s):  
Magnetic Fields ◽  
Neutron Stars ◽  
Power Law ◽  
Initial Surface ◽  
Radio Pulsars ◽  
Short Term ◽  
Power Law Decay ◽  
Pulsar Timing ◽  
Model Predictions

We model the evolution of the magnetic fields of neutron stars as consisting of a long term power-law decay modulated by short term small amplitude oscillations. Our model predictions on the timing noise [Formula: see text] of neutron stars agree well with the observed statistical properties and correlations of normal radio pulsars. Fitting the model predictions to the observed data, we found that their initial parameter implies their initial surface magnetic dipole magnetic field strength B0 ~ 5 × 1014 G when t0 = 0.4 yr and that the oscillations have amplitude K ~ 10-8 to 10-5 and period T on the order of years. For individual pulsars our model can effectively reduce their timing residuals, thus offering the potential of more sensitive detections of gravitational waves with pulsar timing arrays. Finally our model can also re-produce their observed correlation and oscillations of [Formula: see text], as well as the "slow glitch" phenomenon.

scholarly journals Modeling pulsar time noise with long term decay modulated by short term oscillations of the magnetic fields of neutron stars

2012 ◽  
Vol 8 (S291) ◽  
pp. 561-561
Author(s):  
Yi Xie ◽  
Shuangnan Zhang
Keyword(s):  
Magnetic Fields ◽  
Neutron Stars ◽  
Radio Pulsars ◽  
Short Term ◽  
Pulsar Time ◽  
Power Law Decay ◽  
Pulsar Timing ◽  
Model Predictions ◽  
Timing Noise

AbstractWe model the evolution of the magnetic fields of neutron stars as consisting of a long term power-law decay modulated by short term small amplitude oscillations. Our model predictions on the timing noise of neutron stars agree well with the observed statistical properties and correlations of normal radio pulsars. For individual pulsars our model can effectively reduce their timing residuals, thus offering the potential of more sensitive detections of gravitational waves with pulsar timing arrays. Finally our model can also re-produce their observed correlation and oscillations of second derivative of frenquency, as well as the “slow glitch” phenomenon.

Double Power Law in the Japanese Financial Market

2019 ◽  
Vol 7 (1) ◽  
pp. 28-35
Author(s):  
Sudhir Jain ◽  
Takuya Yamano
Keyword(s):  
Time Dependence ◽  
Financial Market ◽  
Power Law ◽  
Power Laws ◽  
Recent Analysis ◽  
Short Term ◽  
Power Law Decay ◽  
Long Time ◽  
Ising Spins

The authors study the persistence phenomenon in the Japanese stock market by using a novel mapping of the time evolution of the values of shares quoted on the Nikkei Index onto Ising spins. The method is applied to historical end of day data from the Japanese financial market. By studying the time dependence of the spins, they find clear evidence for a double-power law decay of the proportion of shares that remain either above or below ‘starting' values chosen at random. The results are consistent with a recent analysis of the data from the London FTSE100 market. The slopes of the power-laws are also in agreement. The authors estimate a long time persistence exponent for the underlying Japanese financial market to be 0.5. Furthermore, they argue that the presence of a double power law in the decay of the persistence probability could be the signature of the presence of both speculative (short-term) and long-term traders in the market.

scholarly journals On the peculiarities in the spin-down of isolated radio pulsars

2012 ◽  
Vol 8 (S291) ◽  
pp. 208-208
Author(s):  
Augustine Chukwude
Keyword(s):  
Radio Astronomy ◽  
Time Resolution ◽  
Local Phase ◽  
Astronomy Observatory ◽  
Radio Pulsars ◽  
Short Term ◽  
Radio Astronomy Observatory ◽  
Long Term Changes ◽  
Timing Data

AbstractWe investigate the spin-down behaviour of a sample of 25 radio pulsars on decadal timescales (~ 18 years) using a continuous timing data obtained over a period of at Hartebeesthoek Radio Astronomy Observatory (HartRAO). Particular attention is placed on achieving a better time resolution of both the short-term and long-term changes in pulsar spin-down using local phase-coherent measurements of the spin-down rates (). We demonstrate that the spin-down of radio pulsars is generally complicated by a superposition of processes that may or may not be related. Specifically, our results show that (i) for 7 pulsars, the observed spin-down variation is largely stochastic, characterized by random and sustained jumps in of varying amplitudes, (ii) for 9 objects, the spin-down evolution shows dominant monotonic variations in superimposed on short-term stochastic jumps in the parameter, and (iii) for the remaining 9 pulsars, the long-term spin-down evolution is non-monotonic, dominated by some systematic excursion in the measured spin-down rates.

Power-law correlations, related models for long-range dependence and their simulation

2000 ◽  
Vol 37 (04) ◽  
pp. 1104-1109 ◽  
Author(s):  
Tilmann Gneiting
Keyword(s):  
Long Range ◽  
Power Law ◽  
Long Memory ◽  
Stationary Time Series ◽  
Long Range Dependence ◽  
Short Term ◽  
Permissible Range ◽  
Simultaneous Fitting ◽  
Straightforward Proof

Martin and Walker ((1997) J. Appl. Prob. 34, 657–670) proposed the power-law ρ(v) = c|v|-β, |v| ≥ 1, as a correlation model for stationary time series with long-memory dependence. A straightforward proof of their conjecture on the permissible range of c is given, and various other models for long-range dependence are discussed. In particular, the Cauchy family ρ(v) = (1 + |v/c|α)-β/α allows for the simultaneous fitting of both the long-term and short-term correlation structure within a simple analytical model. The note closes with hints at the fast and exact simulation of fractional Gaussian noise and related processes.

scholarly journals On The Critical Phenomena in The Dynamics of Asteroids

1999 ◽  
Vol 172 ◽  
pp. 383-386
Author(s):  
Ivan I. Shevchenko
Keyword(s):  
Phase Space ◽  
Critical Phenomena ◽  
Power Law ◽  
Anomalous Transport ◽  
Selection Effects ◽  
Recurrence Times ◽  
Statistical Selection ◽  
Power Law Decay ◽  
Statistical Effects

AbstractTwo statistical effects in the long-term chaotic asteroidal dynamics are considered, namely the power-law character of the dependence of recurrence times on local Lyapunov times and the power-law decay in the tails of the recurrence distributions. The dependences in both cases are shaped by effects of anomalous transport, due to the presence of the chaos border in phase space, and by statistical selection effects.

scholarly journals Matter and Radiation in Superstrong Magnetic Fields and Thermal Emission from Neutron Stars

2003 ◽  
Vol 214 ◽  
pp. 181-190
Author(s):  
Dong Lai ◽  
Wynn C.G. Ho
Keyword(s):  
Radiative Transfer ◽  
Magnetic Fields ◽  
Neutron Stars ◽  
Thermal Emission ◽  
Surface Composition ◽  
Strong Field ◽  
The Novel ◽  
Radio Pulsars ◽  
Strong Magnetic Fields ◽  
Proper Interpretation

Thermal surface emissions have now been detected from more than a dozen isolated neutron stars, including radio pulsars, radio-quiet neutron stars and magnetars. These detections can potentially provide important information on the interior physics, magnetic fields, and surface composition neutron stars. Understanding the properties of matter and radiative transfer in strong magnetic fields is essential for the proper interpretation of the observations. We review current theoretical works on modeling magnetized neutron star atmospheres/surface layers, discussing some of the novel properties of matter and radiative transfer in strong magnetic fields. Of particular interest is the effect of the strong-field vacuum polarization, which dramatically changes the radiative transfer and the emergent X-ray spectra from magnetars.

Height Extrapolation of Wind Data

1985 ◽  
Vol 107 (1) ◽  
pp. 10-14 ◽  
Author(s):  
A. S. Mikhail
Keyword(s):  
Wind Speed ◽  
Power Law ◽  
Wind Data ◽  
Power Law Model ◽  
Short Term ◽  
Shape Factors ◽  
Wind Speeds ◽  
Average Wind ◽  
Modified Power Law

Various models that are used for height extrapolation of short and long-term averaged wind speeds are discussed. Hourly averaged data from three tall meteorological towers (the NOAA Erie Tower in Colorado, the Battelle Goodnoe Hills Tower in Washington, and the WKY-TV Tower in Oklahoma), together with data from 17 candidate sites (selected for possible installation of large WECS), were used to analyze the variability of short-term average wind shear with atmospheric and surface parameters and the variability of the long-term Weibull distribution parameter with height. The exponents of a power-law model, fit to the wind speed profiles at the three meteorological towers, showed the same variability with anemometer level wind speed, stability, and surface roughness as the similarity law model. Of the four models representing short-term wind data extrapolation with height (1/7 power law, logarithmic law, power law, and modified power law), the modified power law gives the minimum rms for all candidate sites for short-term average wind speeds and the mean cube of the speed. The modified power-law model was also able to predict the upper-level scale factor for the WKY-TV and Goodnoe Hills Tower data with greater accuracy. All models were not successful in extrapolation of the Weibull shape factors.

Power-law correlations, related models for long-range dependence and their simulation

2000 ◽  
Vol 37 (4) ◽  
pp. 1104-1109 ◽  
Author(s):  
Tilmann Gneiting
Keyword(s):  
Long Range ◽  
Power Law ◽  
Long Memory ◽  
Stationary Time Series ◽  
Long Range Dependence ◽  
Short Term ◽  
Permissible Range ◽  
Simultaneous Fitting ◽  
Straightforward Proof

Martin and Walker ((1997) J. Appl. Prob.34, 657–670) proposed the power-law ρ(v) = c|v|-β, |v| ≥ 1, as a correlation model for stationary time series with long-memory dependence. A straightforward proof of their conjecture on the permissible range of c is given, and various other models for long-range dependence are discussed. In particular, the Cauchy family ρ(v) = (1 + |v/c|α)-β/α allows for the simultaneous fitting of both the long-term and short-term correlation structure within a simple analytical model. The note closes with hints at the fast and exact simulation of fractional Gaussian noise and related processes.

NASCENT ENTREPRENEURS AND THE TRANSITION TO ENTREPRENEURSHIP: WHY DO PEOPLE START NEW BUSINESSES?

2012 ◽  
Vol 17 (01) ◽  
pp. 1250001 ◽  
Author(s):  
STELIOS H. ZANAKIS ◽  
MAIJA RENKO ◽  
AMANDA BULLOUGH
Keyword(s):  
Social Support ◽  
Multivariate Analyses ◽  
Institutional Environment ◽  
Nascent Entrepreneurs ◽  
Short Term ◽  
Social Contacts ◽  
Financial Outcomes ◽  
Model Predictions ◽  
Successful Business

What makes nascent entrepreneurs get their businesses up and running? We answer this by examining in a broad and unifying way: motivation and cognition, knowledge and experience and social support. We apply extensive multivariate analyses to a sample of 338 nascent entrepreneurs from the PSED database. Interestingly, most of our long-term (4½-year) model predictions of startup transition based on early antecedents are more accurate than the short-term ones — a practical strength of these models. Findings indicate that experienced, persistent, confident individuals, motivated mostly by non-financial outcomes, perceiving support from their social contacts and institutional environment, are likely to make the transition to a successful business.

Power-Law Persistence in the Atmosphere: An Ideal Test Bed for Climate Models

2004 ◽  
Author(s):  
Armin Bunde ◽  
Jan Eichner
Keyword(s):  
Power Law ◽  
Climate Models ◽  
Rare Events ◽  
Global Climate ◽  
Temperature Fluctuations ◽  
Global Climate Models ◽  
Test Bed ◽  
Short Term ◽  
Weather Changes

We review recent results on the appearance of long-term persistence in climatic records and their relevance for the evaluation of global climate models and rare events. The persistence can be characterized, for example, by the correlation C(s) of temperature variations separated by s days. We show that, contrary to previous expectations, C(s) decays for large s as a power law, C(s) ~ s<sup>- γ</sup>. For continental stations, the exponent γ is always close to 0.7, while for stations on islands γ ≌ 0.4. In contrast to the temperature fluctuations, the fluctuations of the rainfall usually cannot be characterized by long-term power-law correlations but rather by pronounced short-term correlations. The universal persistence law for the temperature fluctuations on continental stations represents an ideal (and uncomfortable) test-bed for the state-of-the-art global climate models and allows us to evaluate their performance. In addition, the presence of long-term correlations leads to a noval approach for evaluating the statistics of rare events. The persistence of weather states on short terms is a well-known phenomenon: a warm day is more likely to be followed by a warm day than by a cold day and vice versa. The trivial forecast that the weather of tomorrow is the same as the weather of today was, in previous times, often used as a "minimum skill" forecast for assessing the usefulness of short-term weather forecasts. The typical time scale for weather changes is about one week, a time period which corresponds to the average duration of so-called "general weather regimes" or "Grosswetterlagen," so this type of short-term persistence usually stops after about one week. On larger scales, other types of persistence occur, one of them is related to circulation patterns associated with blocking [5]. A blocking situation occurs when a very stable high-pressure system is established over a particular region and remains in place for several weeks. As a result, the weather in the region of the high remains fairly persistent throughout this period. Furthermore, transient low-pressure systems are deflected around the blocking high so that the region downstream of the high experiences a larger than usual number of storms.

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