This is the second time I have looked for local sidereal time (LST) based influences on the GCP

data. My first exploration made some assumptions that may have weakened the effect, and also

ignored some fundamental issues involving what was being looked at. I had initially looked at

only two years of data, and had lumped the data into two groups: Northern and Southern

hemispheres. If there is a galactic effect related to either the galactic center or to the angle

relative to the galactic axis it would be much preferred to take the actual angle from each

generator to the influence source rather then simply lump generators at different latitudes

together based only on local sidereal time. The angles are formed by finding the three

dimensional angle between the observer [right ascension(LST) and declination(latitude)] and the

source [right ascension and declination]. The angles to the galactic center and the galactic axis

will change dramatically for observers at the same LST but at different latitudes. Here are three

graphs illustrating the differences for +45, 0 and -45 degree declinations (latitude).

If there is a source of influence that is not related to the previous two galactic elements it may be

found by making a star chart with the x axis consisting of right ascension(LST), the y axis

consisting of declination(latitude) and filled with colors based on the results of the tests Z-score

for each point.

The GCP data consists of 1 second samples of 200 random bits with each bit having a

probability of 0.5. Therefore the theoretical mean will be 100, and the theoretical standard

deviation will be 7.071. For the purposes of this study I have taken each of these samples and

have converted them to a z score using the empirically determined standard deviation of the

samples generator. I then took two approaches to arrive at a testable value. First I square the z

score samples and add these products to find the variance. I then increment a count for keeping

track of the number of products (N) placed in that particular bin. The second approach was to

get the autocorrelation sum and N of the samples using lags from one to ten seconds. For each

type of test I added product data and then incremented the N count to one of 1440 bins based on

the individual generators LST in minutes. When all of the data had been placed in bins I saved

the bins to a file for use latter in making a star chart like graph. I then made common bins that

all the generators would use and went through each generators LST minute bins and placed its

data in common bins according to degrees to galactic axis and then in bins according to degrees

to galactic center. I ran this procedure eight times, once for each year 1999-2006 and these

yearly common bins were then saved with the sum and N values so that the data could be

examined for the year or combined with data from other years.

The number of samples in the bins was very consistent for the LST minutes bins, however, the

number of samples in the degrees to galactic center and axis bins varies. Here are the values of

N for the variance measurement for the degrees to galactic center and axis bins.

Here are the graphs for the variance measurements with each point being the center of a 15

degree average window.

These are the graphs for the autocorrelation lag = 1 measurements with each point being the

center of a 15 degree average window.

There does not seem to be any large deviations from chance in the variance tests, but the

autocorrelation graph for degrees to galactic center seems to have an unusually negative slope.

The calculated slope using all available data points of the unaveraged data is -0.003924. I

generated 100 random slopes from random data of the same number of unaveraged samples used

to find the slope and found that indeed the slope is more negative then usual. The graph of the

results of this control test is presented here.

The graph for autocorrelation lag 1 also has two extreme values one positive and one negative

that are not surpassed in the same charts for lags 2 to 10, although one point in lag 8 comes

close. It is also very interesting that the negative most point is also the point closest to 180

degrees, and the positive most point is near zero degrees. Here are the simplified charts for the

autocorrelation lags 1 to 10 of the degree to galactic center charts.

In order to test for other possible influences of Celestial origin I have created a sort of star chart

for each of the two test types. Each point is an average of 15 degrees in both the right ascension

and declination directions with the averages wrapping around the zero hour of right ascension.

It must be stated that this was an exploration so a lot of different things could have been present

in the data that would have been considered interesting and that the findings reported must be

replicated. It should also be noted that there is a geometric relationship between the degrees to

galactic center and degrees to galactic axis. When the degrees to galactic center is at zero or at

180 degrees, the degrees to galactic axis will always be at 90 degrees so if there is an effect from

either it may show up the others data.