Maximum-magnitude estimation of the object's power spectrum in stellar speckle interferometry

1984 ◽  
Vol 9 (11) ◽  
pp. 478 ◽  
Author(s):  
Douglas J. Granrath
Keyword(s):  
Power Spectrum ◽  
Magnitude Estimation ◽  
Speckle Interferometry ◽  
Maximum Magnitude ◽  
Stellar Speckle Interferometry

Maximum Magnitude Estimation for An Intraplate Setting - Example: The Giles County, Virginia, Seismic Zone

1992 ◽  
Vol 63 (2) ◽  
pp. 139-152 ◽  
Author(s):  
G. A. Bollinger ◽  
M. S. Sibol ◽  
M. C. Chapman
Keyword(s):  
Magnitude Estimation ◽  
Recurrence Relations ◽  
Value Theory ◽  
Seismogenic Zone ◽  
Maximum Magnitude ◽  
Seismic Zone ◽  
Historical Earthquake ◽  
Data Bases ◽  
Source Dimensions ◽  
Global Data

Abstract The process of maximum magnitude estimation is intrinsically subjective and depends directly on the experience and judgment of the analyst. Coppersmith et al. (1987; Table 1) discuss six methods for determining the maximum magnitude earthquake for a seismogenic zone. Those include: (I) Addition of an increment to the largest historical earthquake, (II) Extrapolation of magnitude recurrence relations, (III) Use of source dimensions to estimate magnitude, (IV) Statistical approaches (application of extreme value theory and maximum likelihood techniques), (V) Strain rate or moment release rate methods, and (VI) Reference to a global data base. Each technique has associated uncertainties in its applicability to the zone under consideration as well as in the specification of the key parameters involved. Of the six techniques listed above, only the first three are applicable to the data bases presently available for intraplate areas. Application of methods I, II, and III, to the Giles County, Virginia, seismic zone leads to the following results: MS,I = 6.9 (second subscript indicating which of the six methods was used) from adding a 1.0 increment to the maximum historical earthquake known to have occurred in the zone (May 31, 1897; MMI = VIII; mb = 5.8, MS = 5.9), MS,II = 7.0 from extension of the magnitude recurrence curve for the zone to a recurrence interval of 1000 years, and MS,III = 6.5 from the average of six estimates for the fault zone area. For a single estimate of maximum magnitude, the average of the above three values MS = 6.8 or equivalently, mb = 6.3 can be used.

Laboratory simulation of stellar speckle interferometry

1979 ◽  
Vol 18 (6) ◽  
pp. 828 ◽  
Author(s):  
Douglas P. Karo ◽  
Arthur M. Schneiderman
Keyword(s):  
Speckle Interferometry ◽  
Laboratory Simulation ◽  
Stellar Speckle Interferometry

Real-time processor for stellar speckle interferometry using microchannel spatial light modulator

1990 ◽  
Author(s):  
Junji Ohtsubo ◽  
Takeshi Utakouji ◽  
Tamiki Takemori ◽  
Katsuyoshi Fujita ◽  
Syuzo Isobe
Keyword(s):  
Real Time ◽  
Spatial Light Modulator ◽  
Speckle Interferometry ◽  
Light Modulator ◽  
Stellar Speckle Interferometry

scholarly journals The Signal to Noise Ratio in Speckle Interferometry

1979 ◽  
Vol 50 ◽  
pp. 23-1-23-18 ◽  
Author(s):  
J.C. Dainty ◽  
A.H. Greenaway
Keyword(s):  
Power Spectrum ◽  
Signal To Noise Ratio ◽  
Binary Star ◽  
Image Plane ◽  
Light Level ◽  
Speckle Interferometry ◽  
Signal To Noise ◽  
Speckle Image ◽  
Auto Correlation Function ◽  
Noise Ratio

AbstractRecent theoretical studies of the signal to noise ratio (SNR) of photon limited speckle (image plane) interferometry are reviewed. The SNR of an estimate of the object power spectrum is evaluated for both the single and double aperture cases, for arbitrary light levels. The SNR for the auto-correlation function method of analysis is also given for the low light level case and applied to the special case of binary star observations. The SNRs for the power spectrum and autocorrelation function analyses are compared and a comparison is also made between speckle (image plane) and amplitude (pupil or aperture plane) interferometry. Limiting observable magnitudes are estimated for some relevant cases.

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