🍟 🧒🏻 🦀 Space as a database 🌍 ✌🏻 🙊

The article provides a method for constructing the projection of the galactic orbit of the solar system through the analysis of the spatial difference of the cosmological redshift. In addition to the known rotational movements around the center of the Galaxy and up and down displacements relative to its disk, the axis wobble is clearly visible on the results.

.0. () – . – X ( ), – Y ( ), – Z ( ). – (RA 10, DEC -30) – . – - (RA 266, DEC -29), .

I was always interested in what was at the very beginning - to remove the veil from the secret of creation. Probably, before such people became archaeologists, and dug the earth, sand, clay. Now everything has changed, and you have to dig the data.

Not so long ago, I came across the results of the work of the Saul Perlmutter group, for which he, Brian Schmidt and Adam Riess received the Nobel Prize in Physics for the 2011th year. You probably heard about this if you are interested in cosmology.

Fig. 1. Graph of the redshift (abscissa axis) and the conformal distance (ordinate axis) for objects of type Ia supernova.

A supernova is a rather rare phenomenon, especially a concrete type Ia, therefore, in the sample presented in the work, there are only 582 positions.
The uniqueness of this phenomenon for space exploration is that it occurs over a known period of time, with a known curve of luminosity changes. This is on the one hand. On the other hand, in gigantic distances from which it can be fixed and explored.
Thus, type Ia supernovae act as a kind of calibrator of the distance ladder , with the help of which it can be significantly increased.
To put it more simply, Perlmutter's study compared the values of the cosmological redshift (hereinafter referred to as the SCS) with the distances, as a result of which a disproportionate growth of the SCC was discovered, with the conclusion about the accelerated expansion of the Universe following the standard cosmological model .
Here it’s well and clearly written aboutformation of a modern cosmological model .

Perlmutter’s study did not have much data, but good data with reliable distances. I thought, why, contrary to Seneca’s advice, do not look for a diamond in manure: rummage through the “bad” data, where KKS of some sources can only be compared with KKS of other sources, taking into account their spatial orientation.

Moreover, such “manure” is many times more, and the tools are automated. For many years, astronomers around the world have been collecting bit by bit data on all kinds of space objects, dividing them into types and classes, calculating heliocentric positions, measuring luminosities, redshifts, and so on.

The ZCAT base consists of data on 929,094 space objects.

Of these, we will use the data on only 895,441 objects — with the known CSF measured at a conditionally single point (on cosmic scales, our offset over the measurement intervals is negligible). For some of them - 563 objects - even the distance calculated by methods unrelated to the CCS is known.

Tools

Information about the used software products.

Database Management System: Microsoft SQL Server Management Studio 10.0.1600.22 ((SQL_PreRelease) .080709-1414) Data Access Components (MDAC) 10.0.16299.15 (WinBuild.160101.0800)
Microsoft MSXML 3.0 4.0 5.0 6.0
Microsoft Internet Explorer 9.11.16299.0
Microsoft .NET Framework 2.0.50727.8838
Operating system 6.3.16299
MS Office ver.10.

DB Description

Each element in the database has many fields, of which we will only be interested in its position in the sky in the second equatorial coordinate system and its KKS, which in most cases was given as speed and recounted in accordance with the source (according to the formula v = zc).

Fig. 2. The second equatorial coordinate system. Right ascension is deposited at the equator from the vernal equinox. Declination - to the poles (positive inclination - to the north, negative - to the south).
A couple of comments. The database contains heliocentric values, therefore, in the center of Figure 2, the Sun should be represented.

The database also contains values relative to the solar system, excluding the rotation of the latter around Sagittarius-A. This will be clearly visible from the results.

In general, it fascinates me to observe, even on graphs and charts, the processes that took place billions of years ago. It is amazing how, according to the characteristics of photons reaching us, it is possible to reconstruct pictures of the deep past. Even if these paintings are far from the quality of beautiful, color photographs, to which we are now accustomed.

Columns of the source base:

RA_HR - right ascension (hours)
RA_MIN - right ascension (minutes)
RA_SEC - not used
DEC_Sign - inclination (sign)
DEC_DEG - inclination (degrees)
DEC_MIN - inclination (minutes)
DEC_SEC - not used
Z is the value of CCS, z.

Calculated values:

Xd, Yd, Zd - calculated value of the projection of a unit vector along the direction line (d from direction, destination) of the element on the x, y, z axis, respectively.

Half method

If we divide the space into two hemispheres by any plane passing through the Sun, we will get two sets of elements A and B, each of which will have a certain number of elements [QuantityA] and [QuantityB] with some total KKS [RSh_SumA] and [RSh_SumB], and as a result, the average number of KKS per element [RSh_midA] and [RSh_midB], and their difference [RSh_dif].

For convenience, it would be nice to fix the coordinate system.

Axis X is a straight line containing the origin (the Sun) and a point with a right ascension of 0 hours 0 minutes and an inclination of 0 degrees, that is, coinciding with the direction to the point of the vernal equinox. The Y axis will also lie in the equatorial plane - right ascension 9 hours 0 minutes 0 seconds, inclination 0 degrees. Z axis - 90 degree inclination, any right ascension.

We also define three reference planes. It is convenient to do this with perpendicular lines: the

plane α is perpendicular to z, contains x and y;
the plane β is perpendicular to y, contains x and z;
the plane γ is perpendicular to x, contains y and z.

And look at the difference in the average displacement for these planes:

α = 0.07491884 = 22 460.1 km / s
β = 0.012127832 = 3 635.8 km / s
γ = -0.034180049 = -10 246.9 km / sec.

I focus the reader on the values of the average deviation of the cosmic coordinate system for each object: each space object in the northern hemisphere (hereinafter, the second equatorial coordinate system relative to the Sun), or the upper half-space, approximately 0.075 shifted in spectrum to red than every object in the southern hemisphere.

As if we were moving relative to it, moving away, at a speed of about 11,230 km / s (we divide the value of the difference relative to α = 22,460.1 km / s by two). The division into two here is due to the fact that we took the redshift values relative to the opposite side of space, to the objects of which we would get a shift in the violet direction, equal to the redshift in magnitude, which would cause a twofold difference in the displacements in the directions.

But such a difference in the mean value “on the cardinal points” is very large in comparison with the known peculiar velocities of the Solar system and the Milky Way, the maximum of which, relative to the relict, reaches only 627 ± 22 km / s.

It is well laid out.

At first, I assumed that the main reason for this difference is the lack of separation of the scale component of the redshift in accordance with the Friedmann-Robertson-Walker metric .

That is, due to the fact that as the distance from the source increases, the redshift increases nonlinearly in time, it contains a considerable component of the expansion of the Universe, and the peculiar velocity of the receiving point relative to the "old layers" of radiation is expressed "brighter".
However, the peculiar velocity of the receiving point relative to radiation of any age will give the same, unscaled result.

The main reason for the difference lies in the repeated and co-directional movements (rotation) around the center of the Milky Way, which occurred on the scale of their era, and therefore, now make a huge contribution to the fixed difference, while at the same time providing us with the potential to separate the grains from the chaff. And also, probably, in the presence of even longer directed movements.

About this later in the chapter "The effect of the memory of the COP", but for now we dig deeper, again referring to the data. How could we improve our understanding of physical phenomena?

Firstly, the given data on the planes can make projections of a certain motion vector, which in absolute value should turn out to be more than the given values. That is, if we want to check the assumption that there is such a movement (for example, within the framework of phenomenadark stream or a great attractor ), it is worth turning the dividing plane in search of maximum values.
Secondly, we can perform an action from one point - rotation by a plane, gradually reducing the selection of objects on each side, limiting it by eliminating elements located in the toroidal region around the vector defining the dividing plane. As if we were narrowing the spotlight beam to each side of the dividing plane.

If the redshift difference is due to the movement of the observation point relative to the sides of outer space, then such a narrowing should consistently increase the average redshift, due to the fact that the excluded objects have a smaller contribution to the redshift of this nature.

Thirdly, during the rotation of the dividing plane, we can take into account only part of the KKS range in order to try to trace how the maxima and their directions changed. And combine this with the trick from the second paragraph.

Rotation of the dividing plane

This is only a test of some assumptions, because I facilitated the work of my laptop by reducing one time pass to 15-20 minutes as follows: angular seconds of objects are excluded (their contribution to the values is negligible); the plane rotates in increments of 5 °.

The rotation mechanism is as follows: the right ascension value passes from 0 ° to 360 ° in increments of 5 ° for each inclination value from 0 ° to 90 ° in 5 ° increments.

Thus, we pass the hemisphere at all possible angles. There is no point in passing the second hemisphere - it is completely mirrored with the opposite sign (as, for example, the first passage of the right ascension for an inclination of 0 °).

Here is an example of the text of one of the queries (I do not specialize in DB, do not judge strictly):

create table [RedShiftResearch].[dbo].[RShField6](
	[QNum1] [int] NULL,
	[QNum2] [int] NULL,
	[RA_surface_ort_angle] [float] NULL,
	[DEC_surface_ort_angle] [float] NULL,
	[X_ort] [float] NULL,
	[Y_ort] [float] NULL,
	[Z_ort] [float] NULL,
	[Ort_sum] [float] NULL,
	[QuantityA] [int] NULL,
	[QuantityB] [int] NULL,
	[CheckQSum] [int] NULL,
	[RSh_sumA] [float] NULL,
	[RSh_sumB] [float] NULL,
	[RSh_sumCheck] [float] NULL,
	[RSh_midA] [float] NULL,
	[RSh_midB] [float] NULL,
	[RSh_dif] [float] NULL)

DECLARE @DIAPASON_L float = -3;
DECLARE @DIAPASON_H float = 20;
DECLARE @counter1 int = 0;
DECLARE @counter2 int = 0;
DECLARE @Q1 int;
DECLARE @Q2 int;
DECLARE @RA_surf_ort_angle float;
DECLARE @DEC_surf_ort_angle float;
DECLARE @X_ort float;
DECLARE @Y_ort float;
DECLARE @Z_ort float;
DECLARE @X_ort_neg float;
DECLARE @Y_ort_neg float;
DECLARE @Z_ort_neg float;
DECLARE @Ort_sum float;
DECLARE @RA_surf_step float = 5.0;
DECLARE @DEC_surf_step float = 5.0;
DECLARE @QuantityA int;
DECLARE @QuantityB int;
DECLARE @CheckQSum int;
DECLARE @RSh_sumA float;
DECLARE @RSh_sumB float;
DECLARE @RSh_sumCheck float;
DECLARE @RSh_midA float;
DECLARE @RSh_midB float;
DECLARE @RSh_dif float;
DECLARE @threshold float = 2.0;

WHILE (@counter1 < 19)
begin
	WHILE (@counter2 < 72)
	begin
		SET @Q1 = @counter1;
		SET @Q2 = @counter2;
		SET @RA_surf_ort_angle = @counter2 * @RA_surf_step;
		SET @DEC_surf_ort_angle = @counter1 * @DEC_surf_step;
		SET @Z_ort = SIN(@DEC_surf_ort_angle/180.0*PI());
		SET @X_ort = ROUND(COS(@RA_surf_ort_angle/180.0*PI())*COS(ASIN(@Z_ort)),15);
		SET @Y_ort = ROUND(SIN(@RA_surf_ort_angle/180.0*PI())*COS(ASIN(@Z_ort)),15);
		SET @X_ort_neg = -1 * @X_ort;
		SET @Y_ort_neg = -1 * @Y_ort;
		SET @Z_ort_neg = -1 * @Z_ort;
		SET @Ort_sum = @X_ort*@X_ort+@Y_ort*@Y_ort+@Z_ort*@Z_ort;
		SELECT @QuantityA = COUNT(*) FROM dbo.RSh8 where ([Z]>@DIAPASON_L) AND ([Z]<@DIAPASON_H) AND ([Z]<>0) AND ((SQUARE([Xd]+@X_ort)+SQUARE([Yd]+@Y_ort)+SQUARE([Zd]+@Z_ort))>@threshold);
		SELECT @QuantityB = COUNT(*) FROM dbo.RSh8 where ([Z]>@DIAPASON_L) AND ([Z]<@DIAPASON_H) AND ([Z]<>0) AND ((SQUARE([Xd]+@X_ort_neg)+SQUARE([Yd]+@Y_ort_neg)+SQUARE([Zd]+@Z_ort_neg))>@threshold);
		SET @CheckQSum = @QuantityA+@QuantityB;
		SELECT @RSh_sumA = SUM([Z]) FROM dbo.RSh8 where ([Z]>@DIAPASON_L) AND ([Z]<@DIAPASON_H) AND ([Z]<>0) AND ((SQUARE([Xd]+@X_ort)+SQUARE([Yd]+@Y_ort)+SQUARE([Zd]+@Z_ort))>@threshold);
		SELECT @RSh_sumB = SUM([Z]) FROM dbo.RSh8 where ([Z]>@DIAPASON_L) AND ([Z]<@DIAPASON_H) AND ([Z]<>0) AND ((SQUARE([Xd]+@X_ort_neg)+SQUARE([Yd]+@Y_ort_neg)+SQUARE([Zd]+@Z_ort_neg))>@threshold);
		SET @RSh_sumCheck = @RSh_sumA+@RSh_sumB;
		SET @RSh_midA = @RSh_sumA / @QuantityA;
		SET @RSh_midB = @RSh_sumB / @QuantityB;
		SET @RSh_dif = @RSh_midA - @RSh_midB;
	
		insert into RShField6(QNum1, QNum2, RA_surface_ort_angle, DEC_surface_ort_angle, X_ort, Y_ort, Z_ort, Ort_sum, QuantityA, QuantityB, CheckQSum, RSh_sumA, RSh_sumB, RSh_sumCheck, RSh_midA, RSh_midB, RSh_dif)
		values (@counter1,
		@counter2,
		@RA_surf_ort_angle,
		@DEC_surf_ort_angle,
		@X_ort,
		@Y_ort,
		@Z_ort,
		@Ort_sum,
		@QuantityA,
		@QuantityB,
		@CheckQSum,
		@RSh_sumA,
		@RSh_sumB,
		@RSh_sumCheck,
		@RSh_midA,
		@RSh_midB,
		@RSh_dif
		);
		
		set @counter2 = @counter2+1;
	end
	
	set @counter1 = @counter1+1;
	set @counter2 = 0;
end

select *
from [dbo].[RShField6];

At the output, for the full range of redshift, we obtain a table comparing the difference value with the direction of the vector defining the dividing plane. Then, already in MS Excel, it is reduced to a form that allows you to visualize the data, as shown in the diagram below.

Fig. 3. The spatial distribution of the average values of the redshift difference per object, depending on the direction of the reference vector for the full range of redshift from minus three to twenty without narrowing the sample.

Absolute minimum: minus 0.03535 at 0 ° inclination 10 ° (40 minutes) right ascension.
Absolute maximum: 0.078 at 85 ° inclination 125 ° (8 hours 20 minutes) right ascension.
In total in the sample for a maximum of 895439 objects.

Figure 3 shows how the average value changes as the direction changes.
One closed curve - 360 ° pass with constant inclination. The darker the color of the curve, the closer it is to the equator, and vice versa, the lighter - the closer to the north pole.

A convenient interpretation of the diagram is as follows: we are as if looking at the solar system from the south pole of coordinates; the rays coming along the equator to an imaginary sphere with the center - the Sun, form darker lines than the rays fading as the distance to the north pole of the sphere.

The diagram for the southern hemisphere will be a mirror diagram of the northern hemisphere with the opposite sign.

The maximum, indeed, turned out to be greater than any of the previously given values for the reference planes α, β, and γ, and is aligned with α. However, it is not a vector sum of their values, because the values of α and γ, as can be seen from the diagram, are the results of different processes. There are three such trends. I will mark two of them in green and yellow in the following figure.

Fig. 4. The spatial distribution of the average values of the redshift difference per object, depending on the direction of the reference vector for the full range of redshift from minus three to twenty without narrowing the sample. With the designation of trends in green and yellow.

Not depicted trend remains red. She is like a hat on the chart and the shape of two other trends. This is an increase in the average difference of the CS with an increase in inclination.
The large red arrow points from the south pole through the Sun to the north. Almost. Maximum - inclination 85 ° right ascension 125 ° (8 hours 20 minutes).

Again, set aside the analysis, continue the journey according to the data.

Change the nature of the sample

Those who read the sample request will be more understandable, but I will try as much as possible.

Here is the right piece:

SELECT @QuantityA = COUNT(*) FROM dbo.RSh8 where ([Z]>@DIAPASON_L) AND ([Z]<@DIAPASON_H) AND ([Z]<>0) AND ((SQUARE([Xd]+@X_ort)+SQUARE([Yd]+@Y_ort)+SQUARE([Zd]+@Z_ort))>@threshold);
SELECT @QuantityB = COUNT(*) FROM dbo.RSh8 where ([Z]>@DIAPASON_L) AND ([Z]<@DIAPASON_H) AND ([Z]<>0) AND ((SQUARE([Xd]+@X_ort_neg)+SQUARE([Yd]+@Y_ort_neg)+SQUARE([Zd]+@Z_ort_neg))>@threshold);

The condition for matching the set A or B in the query program is that the length of the vector sum of the unit vector of the location of the object and the unit vector, perpendicular to the dividing plane, matches the requirement> @threshold (threshold).

Simply put, if the direction to the object is on the same side of the reference plane, for example, α, as the uniting unit x directed at the vernal equinox, then the length of their vector sum must be greater than the root of two.

It’s inconvenient to work with the root, so just leave two and leave the left side of the equation squared, as in the example above. This is the threshold for many objects A.

For a set of objects B, the threshold will also be two, but for the sum with the unit vector inverse x:

SET @X_ort_neg = -1 * @X_ort;
		SET @Y_ort_neg = -1 * @Y_ort;
		SET @Z_ort_neg = -1 * @Z_ort;

For clarity, I will give the conditions of two samples in the plane in Figures 5 and 6.

Fig. 5. The first condition: the sum of the extreme direction vector (0; 1) and unit vector (1; 0) is a vector of length SQRT (2)

Fig. 6. The first condition: the sum of the extreme direction vector and unit vector (1; 0) is a vector of length SQRT (3.8). The second condition: the coordinates of the unit vector are always the legs of the triangle with the hypotenuse equal to one. As a result (in green), all points whose direction coincides with the unit vector defining the plane and get no more than the point of intersection of the two previous conditions fall into the sample. That is, no more than an angle of ≈25.8 °, for a narrowing coefficient of 3.8.

If for both cases in Figs. 5 and 6 we rotate the region around the abscissa axis by 180 °, then we obtain the spatial restriction of the sample in the form of a bottomless cone for Figure 6, and its degenerate version - half-space - for Figure 5.

For the opposite sample, the condition is mirror symmetrical with respect to ordinate axis.
That is, if we begin to increase the narrowing coefficient, then objects that are in the toroidal growth around the axis of the defining vectors, symmetric with respect to the dividing plane, cease to fall into the sample.

Now let's check how the established green, yellow and red trends behave with the narrowing of the sample in the above way.

Distribution diagrams of average redshift differential values for sample narrowings with a threshold from 2.2 to 3.8

. 7. 2.2.

: 0,035112483 0° 15° (1 ) .
: 0,088327442 85° 340° (22 40 ) .

662 761 .

. 8. 2.4.

: 0,034270309 0° 5° (20 ) .
: 0,085673496 90° .

572 258 .

. 9. 2.6.

: 0,030690323 0° 5° (20 ) .
: 0,085673496 85° 140° (9 20 ) .

527 397 .

. 10. 2.8.

: 0,0328635 0° 305° (20 20 ) .

: 0,180024201 70° 10° (40 ) .
341 945 .

. 11. 3.0.

: 0,037789532 0° 310° (20 40 ) .

: 0,187621081 70° 340° (22 20 ) . 260 398 .

. 12. 3.2.

: 0,037522009 0° 280° (18 40 ) .

: 0,204479206 70° 30° (2 0 ) . 156 482 .

. 13. 3.4.
: 0,058609459 0° 285° (19 0 ) .

: 0,221096202 75° 15° (1 0 ) . 92 908 .

. 14. 3.6.
: 0,084653998 0° 290° (19 20 ) .

: 0,2319195 85° 25° (1 40 ) . 72 887 .

. 15. 3.8.
: 0,09141836 0° 290° (19 20 ) .

: 0,242047091 80° 125° (8 20 ) . 45 782 .

Explanation of Table 1. The value of the narrowing coefficient 2.0 corresponds to the sampling limit to the half-space limited by the dividing plane; 2.0 <narrowing <4.0 - the sample is limited to objects located inside the conical shape obtained by rotating the line relative to the unit vector defining the dividing plane (90 °> line angle to unit vector> 0 °, respectively); 4.0 - the selection is limited to objects located on a straight line coinciding in direction with the unit vector defining the dividing plane.

We call this technique focusing.

I repeat, the physical meaning of reducing the sample according to the applied geometric principle is such that it should enhance the differential indicators for trends due to the relative movement of objects if its path is longitudinal to the “spotlight beam”.

It turns out that focusing - the narrowing of the "spotlight beam" - separates significant long-term trends among themselves, due to the relative movement of the observation point and proceeding without changing the direction of movement. This technique makes such trends clearer, reducing their mutual influence and overwriting other weak effects.

And even more specifically, the smaller the angle of the trajectory of the observation point to the direction of radiation of the region falling into the sample, the higher the fixed average differential CS will be.

As can be seen from the diagrams, the severity of the yellow trend with the narrowing of the beam fades, which can be observed, for example, by the change in the value / direction of the minimum in table 1. This process loses its severity to the value of the narrowing coefficient 2.8 (corresponds to an angle of ≈70 °).
And it seems to be replaced by a green trend (or close in direction to it), which becomes the only visible at the equator to the value of the narrowing factor 3.0, and then only increases with the narrowing coefficient, demonstrating rotation symmetry.
The red trend also becomes less pronounced in the range of the narrowing coefficient from 2.0 to 2.6 (corresponds to an angle of ≈75 °), and then it sharply intensifies and further only grows.
However, at the same time, although it does not fundamentally change directions, it still acquires a significant deviation of the direction to the maximum point from value to value.
At the time of the sharp increase in the value of the narrowing coefficient of 2.8: the number of elements in the sample is 341,945, which is more than a third of the total number of objects. And the difference in the average value of the redshift per object in the samples is already ≈0.18.

The fact of a sequential increase in the average difference in the CS for an object with a narrowing of the sample speaks in favor of the peculiar velocity of the observation point, even despite some fermentation of the maximum orientation. In the standard cosmological model, I cannot find other reasons.

Thus, if this phenomenon is interpreted as the result of the peculiar velocity of the observation point relative to one third of the known space objects, then the speed will be ≈27 thousand km / s (0.18 x 299 792.458 / 2).

This is already a tenth of the speed of light, and this fact seems very significant, but I would not be seduced, because, I recall, this is the result of the full range of redshifts without taking into account the time scale.

Range change

Looking at the diagrams given so far, the reader may have a false idea that our solar system is delivering pies to its grandmother : an increase in the angle of inclination of the dividing plane always led to an increase in the redshift.

However, if we take only part of the range, for example, from 1.8 to 2.2 (see Fig. 16), then it becomes obvious that this was not always the case. Little Red Riding Hood is wearing the equator here.

Fig. 16. The spatial distribution of the average values of the redshift difference per object depending on the direction of the reference vector for the redshift range from 1.8 to 2.2 without narrowing the sample (with a threshold of 2.0).

Absolute minimum: minus 0.017505519 at 85 ° inclination 230 ° (15 hours 20 minutes) right ascension.

Absolute maximum: 0.013703 at 0 ° inclination 20 ° (1 hour 20 minutes) right ascension. In total in the sample for a maximum of 14,533 objects.

Before continuing to build mental constructions, we will answer the question of the most attentive and inquisitive readers: will there be an increase in the redshift when focusing for the given range?

Frankly, I make requests in parallel with the writing of the article, and at the time of writing these lines I do not know the answer. I will not make assumptions, let's just look at Figure 17.

Fig. 17. The spatial distribution of the average values of the redshift difference per object, depending on the direction of the reference vector for the redshift range from 1.8
to 2.2 with a narrowing of the sample with a threshold of 3.0.

Absolute minimum: minus 0.051811403 at 65 ° inclination 50 ° (3 hours 20 minutes) right ascension.

Absolute maximum: 0.016826963 at 5 ° incline 55 ° (3 hours 40 minutes) right ascension. There are a total of 6,983 objects in the sample.

There is an increase, but at the same time, the direction changes significantly while maintaining the general shape. The reason for this data configuration may be hidden in the curvature of the motion path, if this is the motion underlying the red trend. This is probably a current with a very large radius.

We will come back to this, but for now I will summarize: the magnitude of the red trend obtained as a result of focusing (at the end of the previous chapter), as a result of taking fully into account the trajectory of the receiving point - the Sun - relative to Sagittarius-A, is likely to be even more significant.
Let's talk about this in detail.

COP memory effect

As I wrote earlier, those color trends that we saw in Figure 4 have a character that depends on both the speed of the point at the time of reception and its movement in the past.

In the general case, several factors influence the magnitude of the absolute value of the redshift:

the peculiar velocity of the source, which is not taken into account in the applied method, but is accepted as an inevitable error (the speed of the solar system relative to objects in its own galaxy is an order of magnitude lower than, for example, the detected difference in the red trend);
the gravitational potential of observation and reception points , which is also completely not taken into account by the technique due to an even smaller influence than peculiar velocities;
speed and direction of movement of the observation point at the time of reception;
, , , .

It is this last factor that interests us. Its presence creates the prerequisites for tracking the trajectory of the observation point using the relative (compared with the same) redshift of the surrounding radiation.

As in the example from the BBC movie with a drop of dye dissolved in the sink. Knowing thoroughly the state of all physical particles in the shell, it is possible to retrospectively restore how long ago, at what angle, with what speed and acceleration, and so on, a drop with a dye entered the sink. Even if by now its molecules are evenly distributed among others.
So the spatial displacement of the receiving point is recorded in increasingly distant radiation regions in the form of the influence of relative displacement on the redshift. Moreover, both geometrical displacement and spatial orientation.

To simplify, the effect is shown in the following figure 18.

Fig. 18. The effect of "memory" redshift of cosmic radiation.

Take some conditional sphere 1 and the observation point. The concept of a sphere is very arbitrary, because in terms of determining the distance to its points from the center, we rely on the same indicator that we use in comparison to determine the difference - heterogeneity - redshift. That is, in the end, the radii of the sphere are measured in terms of redshift, and the sphere itself is a sample of all objects in a certain range of redshifts. Even so, spatial heterogeneity is quite distinguishable for fairly narrow ranges.
1 1, , 1 .
2 – , 1, . .

This is only a hypothesis for the next article.

So, in Figure 4, in fact, the main averaged trends for the full range of redshift values are displayed, which means their relative constancy over a large interval of the existence of visible space.

Two unconditional contenders for spatial displacements that form such perturbations of the “redshift field” (I will allow myself to continue to work with it as a field, in abbreviated form - PKS) as in Figure 4 - this is the rotation of the solar system around Sagittarius-A and the cyclic upward movement of the solar system - down relative to the galactic equator.
The approximate period of the first is 190-250 million years (different sources and orbits), of the second - 33 million years.

The size of red even without taking into account the detected rotation, that is, without taking into account the fact that it is smeared on the full diagram, is several times higher than the intragalactic speeds of the solar system, which indicates its duration and relative constancy. Therefore, suppose that the green and yellow trends are the result of the intragalactic movement of the solar system. We need to deal with them, then, after evaluating their trajectories and speeds, recalculate the diagrams relative to Sagittarius-A.

Ultimately, this should allow us to consider the movement of the Milky Way galaxy relative to deep space.

Fig. 19. Combined general diagram of the difference in the average redshift values per object for the northern and southern hemispheres.

Figure 19 shows the spatial contours of the difference in the CS values for the northern and southern hemispheres for clarity, although the contours of the southern hemisphere are the same contours of the northern hemisphere, with the same inclination, but with a negative sign and rotated through 180 °. This follows from the description of the technique.

The yellow tendency is seen as an almost vertical deformation squeezed out with a finger at an angle of 10 ° right ascension (40 minutes). The pit is created by contours with an inclination index from minus 55 ° to plus 10 °, that is, in the center there is a contour with an inclination of minus 30 °.
Moreover, we know that the ecliptic plane of the solar system is at an angle of 60 ° to the plane of the galactic equator, that is, the north pole of the second equatorial coordinate system is directed to the galactic equator at the specified angle(fig. 20).

Fig. 20. The angle between the plane of the ecliptic and the galactic equator.

Looking at Figure 20, it is not difficult to guess that at any point in the circular trajectory of the solar system relative to the center of the galaxy, the component orthogonal to the galactic plane in the second equatorial coordinate system will always have an inclination of either 30 ° for upward motion or minus 30 ° - for the downward.

But if it’s difficult, then here is figure 21.

Fig.21. The angle of inclination in the second equatorial coordinate system for the component of the motion of the solar system, orthogonal to the plane of the galaxy.

Accordingly, the right ascension angle of 10 ° of the yellow trend indicates the actual spatial orientation of the coordinate system, however, it is not enough to orient its movement relative to the center of the galaxy.

Sagittarius-A is now at around 17 hours 45 minutes (≈266 °), 29 ° declination. It turns out that we are now approximately in the plane of the disk of the Milky Way, approximately in the middle of the thirty-three millionth period of “decline”.

It would be necessary to finish writing the article faster, while this data is still relevant.

Obviously, the yellow trend is an almost instantaneous indignation of the PKC, due to the instantaneous movement at the time of reception.

First, all previous sun passes up and down relative to the galactic disk are approximately mutually compensated.

Secondly, let's take another look at table 1: contrary to a linear trajectory, the effect of the trend fades away significantly when the sample is narrowed down due to its short duration. That is, the ratio of the CS value of the short, relatively slow motion that is currently occurring, to the CS values of the far layers of the PCB decreases rapidly and nonlinearly (nonlinearly due to the scale factor of the Friedman-Robertson-Walker metric).

Green as a result of focusing, on the contrary, becomes sharply defined, because its path is a circle. It is not compensated in the past, and therefore, although it does not fall into the narrowed sample along its entire path lengthwise, it contains passages in the far layers of the PCB, the distortion of the CS from which in relation to the absolute values of the CS of the corresponding period grows linearly, that is, much higher than the yellow trend, because the movement occurred at the same scale factor.

Let's try to build a curve using the minimum points associated with this rotation. For clarity, I showed them in the following figure.

Fig. 22. Combined general diagram of the difference in the average values of the redshift per object for the northern and southern hemispheres (Fig. 19) with the highlighted points of deformation of the PCB due to the green trend.

Table 2. Minimum green trend values.

Fig. 23. Visual representation of the minima (green) and their corresponding maxima (dark blue) of the green trend on the sphere. The black axis is X (positive to the right), the red axis is Y (positive inward), the blue axis is Z (positive up). Yellow ball - the direction of movement according to the yellow trend (RA 10, DEC -30). The black ball is the current direction on Sagittarius-A (RA 266, DEC -29).

Have you noticed? Green balls do not fit in a line. In the following figure, this is clearly visible. Such an arrangement of minima can cause a change in the angle of inclination of the axis of rotation of the solar system relative to the disk of the Milky Way as it rotates.

Superimposing on one another the redshift of the many passages of rotation would not give such an effect, because the ups and downs of the solar system relative to signal sources are negligible. So I am inclined to change the spatial orientation of the trajectory of the solar system, but finally it will be possible to speak only after a thorough “combing” of the data with a large scallop and their comprehensive analysis.

Fig. 24. A visual representation of the minima of the green trend on the sphere in the representation of the development of the trend. The black axis is X (positive down), the red axis is Y (positive to the right), the blue axis is Z (positive up).

In the view in Figure 24, the “wobble” of the trajectory is clearly visible. I could not find any mention of this feature of the movement of the solar system through the galaxy. All references to this are very vague and approximate, so the fact of discovering such sources is remarkable in itself, and is worth further careful consideration.

The following view shows the relative position of the green rotation and the yellow movement.

Actually, the fact that they are close to the perpendicular arrangement was already visible on the diagram, but it was more clear.

Fig. 25. Visual representation of the lows of the green trend on the sphere in the view with the direction of yellow movement. The black axis is X (positive up), the red axis is Y (positive to the right), the blue axis is Z (positive up).

Well, the bonus is such a combined view for those who have not yet fully understood the physical meaning of the diagrams.

Fig. 26. Combined view of spatial representation and diagram.

I will summarize the intermediate result. The database of space objects with information about the spatial position and redshift provides a very good tool for analyzing cosmological processes, and is very promising in terms of creating new tools and data representations.

The intended areas of the following articles are:

Red shift as a field. The second method for identifying spatial uneven redshift.
Using data from 563 objects with known distances measured without redshift (using the distance ladder based on Cepheids, the Sunyaev-Zeldovich effect, etc.).
Representation of the movement of the solar system inside the Milky Way in an analytical form to recalculate the initial data on the location and redshift into a coordinate system with a beginning in the center of the Milky Way to determine its trajectory and speed.

This red trend is very red. We'll figure out.

Space as a database