Newsgroups: alt.ufo.reports
From: MrPostingRobot@kymhorsell.com
Subject: REDACTED! evidence of tampering with telescope databases

[uploaded 46 times; last 31/10/2024]

EXECUTIVE SUMMARY
- Space telescope images seem to be edited to remove "certain things"
  from the view even of research scientists.
- The editing follows 2 patterns -- the day before a UFO flap is
  registered at e.g. NUFORC the number of images acked in public
  databases is consistently smaller than usual. We suspect some
  images have been removed.  For those images remaining, in areas of
  the sky and at times were "certain things" can be predicted to be
  likely seen, images seem to be consistently blacked out. Leaving the
  empty file in the database may be a method to avoid holes in the
  database being observable to casual view. Only after uploading the
  full-sized (in this case 30+ MB) file does the researcher find it is
  blacked out apart from the information in the file header that
  otherwise gives the meta information for the data that was once there.
- We find there is a statistically strong link between the number of
  images listed in log files for at least one telescope and reported
  UFO activity the following day. Images taken near the position of
  Neptune (RA near 0 or 360 for most of the period the telescope has
  been operating) on key dates also seem to be consistently "blacked out".
- The stats programs find the best match-up between UFO counts and
  image counts shifts the UFO data back 1 day and takes logs.  The log
  model is consistent with the problem of N objects randomly allocated
  to M images. The fraction of images without any of the objects in it
  would tend to a function of log(N).  So both the time-shift in the
  model and the functional form is consistent with someone trying to
  hide something related to contemporaneous UFO activity.
- We can't assign blame to NASA or govt scientists. It is perfectly
  possible they all act in good faith and do not notice these patterns
  in their everyday work. NASA administrators must be aware they
  operate in an informal branch of the military and are directly
  subject to national security concerns. They may even know that
  certain steps are taken as a matter of course without being fully
  aware what those steps might entail.  But the effect of "invisible
  changes" to public data may threaten to invalidate a growing amount
  of research that relies on it.  While scientists reaching certain
  wrong conclusions is likely "part of the plan", the errors are not
  contained to just that part of scientific work. No matter how
  careful and planned the editing, an obvious and spreading bias has
  been introduced. If this same methodology is used in all govt
  science (for the same or even other reasons) that research can't be
  regarded as totally reliable and the gobs of public money that go
  into it are intentionally "partly wasted".


I mentioned some time back I'd found some evidence that images
available in key NASA databases seem to have been tampered with to
remove evidence of "certain things".

While NASA administrators maintain the organisation is a straight die
it may well be the case that some actions are undertaken with or
without its cooperation to remove "material of national security
significance" from NASA's public data. More interestingly, some of the
public involved are other science organisations around the world.
Whoever is doing what is also tampering with scientific research.
Removing evidence with "security implications" inevitably is biasing
the types of data scientists everywhere get to use to advance their
understanding of the universe. That understanding therefore becomes
more and more skewed from reality over time. The tampering is
producing arguable damage to society.

But before I fly off the handle and start frothing at the mouth, let's
look at the evidence. See if you find it as convincing as I do.

In researching the goings-on in the sky over N America and my own neck
of the woods I began looking at telescope data gathered by several
organisations and available via the web. Initially I looked at light
curves from individual stars. That work found that the average light
from stars in certain parts of the sky varied suspiciously like the
activity reported much closer to the ground in the sky over N America.
The patterns were so clear you could work up a predictive model that
would tell you to quite high certainty when and where such near-ground
activity would occur just by looking at the avg brightness of the
stars in certain parts of the sky over the course of hours before that
activity was due to happen.

Using a simple machine learning model my programs predicted from the
initial upoloadings of 1000s of light curves where and when and in
what direction you should be able to look to find even more
interesting things than just the odd bunch of stars suddenly going a
little dimmer over the course of a few hours and then going brighter
again.  At that time -- and this is the way AI stuff works -- I had no
real simple mental model of what the machine learning algorithm had
found.  It just told me get data about this part of the sky at this
time and you will see something interesting.

So I expanded my uploads to include actual full-frame images of
parts of the sky gathered by various space telescopes. The most
convenient for my monthly Internet bill were TESS images that came in
30 MB FITS files (FITS is a format beloved of astronomers to bundle up
all the information about some part of the sky and can include tables,
gobs of meta-information about the camera and telescope used, and even
tables of sub-images and graphs as well as the meat-in-the-sandwich
32-bit gray-scale detailed images of the part of the sky in question;
it's like the astronomers version of a ZIP file).

So I went about uploading modest numbers of these things from my
favourite space telescope archive and storing them on a big disk on my
local machine. To allow for possible 1000s or millions of images -- I
didn't know how many I would need -- I compressed all the FITS files
with a super compression algorithm. That algorithm took those FITS
files and reduced them by 50% or so. Pretty good performance given
FITS are already somewhat compressed.

But as the work progressed I suddenly found some of these compressed
files were amazingly small. With a normal compressed FITS was 25MB,
some of them were only 4KB long! What had happened?

After some checking it turned out those small FITS files were
"perfectly intact" -- all their heading information was correct and
all the internal checksums were right -- but the actual images in the
file were blank. All zeros. Equal to "perfect black".

Although I'd collected 100s of these images up to this point it
seemed I found a cluster where most of them got zapped somehow.  Then
the correlation started to stick out. Only the FITS files
related to the most interesting areas as predicted by the AI programs
seemed to be affected.

I now know those initial files came from a part of the sky near
Neptune's then-current position. It seemed when the telescope pointed
near Neptune "something" went wrong with the machine and its output
got all screwed up.

Neptune, as I've pointed out in some prev posts, seems to highly
correlate with "certain activity". As the earth gets closer and
further away during the course of a normal year it seems UFO
sightings go up and down "in sympathy". And a little too exactly to be
due to just chance, according to various stats tests.

The AI's later told me there was another stunning coincidence.  Given
the ups and downs of the numbers of UFO's reported day to day over N
America, it was an amazing co-incidence that on the day (in GMT time)
just before a day where the number was much higher than average the
number of images apparently taken (or, at least, the number available
for upload at the public web site) was always down.  That finding also
passed a number of stats tests at high levels of significance.

I now have collected all the data published for TESS since 2018 and
can report these associations continue. Not only do images "go
missing" -- i.e. they do not appear in even the records although we
strongly suspect those images must have been taken and the telescope
was not just broken on that day -- but images that are left on the
website sometimes seem to be blacked out. The TESS telescope consists
of 4 cameras each with 4 sensors of around 2k by 2k pixels. It has an
overall aperture something like 24 by 96 degrees and takes in a good
chunk of the sky. On *some* days you can find images for SOME of these
cameras and SOME of their sensors; others "go missing" or are blacked
out.  Seemingly a high proportion of this tampering happens "only"
when the telescope, or just those sensors of those cameras, are
pointing at a part of the sky on a day when certain things were
reported down here on Earth.

The pattern repeats over and over in the course of the telescope's
5+ years of operation. It's not just noise.

We can take the number of images logged for a particular camera/sensor
combination. These logs are provided as separate (large) files on the
relevant website. They're intended to be used to bulk download massive
numbers of images for any research group that wants them.  They
*should* contain the designations of all images actually taken by the
telescope. But the number of images for each day/time goes up and down
quite a bit.

Here's a sample from the somewhat large summary file I gathered from
counting up how many times each day/time was mentioned in the names of
the FITS files that contain those images.

2018.631 48
2018.634 48
2018.637 31
2018.639 20
2019.631 48
2019.634 48
2019.637 48
2019.639 48
2020.631 144
2020.634 144
2020.637 144
2020.639 144
2021.631 10
2021.634 118
2021.637 144
2021.639 144
2022.631 144
2022.634 144
2022.637 144
2022.639 144

The date in col 1 is the year/day as a decimal number.  I only
grabbed those entries in the file where the decimal part was ".63...",
just to get a sample for you. Col 2 is the number of images attributed
to sensor 1 of camera 1 -- designed on the website by "-1-1-"
appearing in the FITS filename.

The above is typical of the other 15 sensor/camera combinations.

We can see *some* days saw only 10 images "apparently" taken.  While
the usual number seems to be 144. I.e. 1 image every 10 minutes during
a normal 24 hour day. So the camera is clicking quite a bit to grab
what we assume is normally 9.216 gigapixels of images per day.
Sure. Some days the thing might get a bit hot and have to be
feathered.  But there is a consistent pattern to the "feathering" and
it doesn't seem to entirely relate to conditions out there between
Earth and Moon where TESS orbits every 2 wks.

For each day from 2018 we can look at the number of UFO reports at the
NUFORC. For the dates listed above we find (e.g.):


2018.631 9
2018.634 6
2018.637 4
2018.639 10
2019.631 9
2019.634 7
2019.637 8
2019.639 18
2020.631 27
2020.634 27
2020.637 10
2020.639 25
2021.631 5
2021.634 1
2021.637 5
2021.639 6
2022.631 12
2022.634 11
2022.637 18
2022.639 13

But now the magic happens. If we take the image counts and the UFO
counts we can ask a stats package if there is a statistically robust
association between them. We can allow the program to manipulate the
data a bit -- as long as we are careful about the stats so it just
doesn't MAKE something happen that really isn't there -- to increase
the association to make it obvious even to a blind man it finds the
best match involves taking the log of the number of UFOs, shifting it
back in time 1 day, and grouping like days together after taking into
account "serial correlation" that happens in most data involving time
we find:

Dates similar to:     UFO count   Image count    Power law model
2021.467                     1          144      187.058
2022.194                  2.24        135.3      141.815
2020.956                     3          104      128.281
2022.544               4.50679      136.652      111.553
2022.645               7.07508      131.778      95.5504*(model under-estimates)
2022.658               10.4476      99.1785      83.5816
2018.577                    13           48      77.5388*
2022.656               14.4653      86.5891       74.747
2022.634               17.4138      74.6724      70.1346
2022.601                20.268      64.5361      66.5734
2019.768                    23           48      63.7449
2022.590               23.6296           68      63.1566
2022.298               26.3684      61.5789      60.8228
2022.626               29.7647      69.4118      58.3446
2019.735                    33           48      56.3138
2021.918               33.5714      73.7857      55.9829
2021.383                    37         80.4      54.1447*(under)
2022.459               39.3333          112      53.0197**(under, a lot)
2020.333                  42.4           48      51.6705
2020.284                    45           48      50.6254
2020.295                    47           48      49.8752
2020.328                    50           48      48.8268
2020.320               55.6667           47      47.0598
2019.388                    58           48       46.401
2020.503                    62           48      45.3506
2020.314               65.6667           48      44.4647
2020.290                    68         41.5      43.9349
2021.915                 71.75        32.25      43.1325*(over)
2020.169                    80           46      41.5505
2020.287                    91           17      39.7527**(over, a lot)

Model:
y = 187.058 * x^-0.343336
beta in -0.343336 +- 0.0803521 (90% CI)
alpha in 5.23142 +- 0.270108 
T-test: P(beta<0) = 1.000000
r2 = 0.65361507
calculated Spearman corr = -0.757063
Critical Spearman = 0.432000 2-sided at 1%; reject H0:not_connected

It seems there is a consistent pattern. On the day before a "UFO flap"
somehow the number of images available from TESS are less than usual.

We are forced to conclude that "some process" is involved that removes
images from the TESS database. Where this happens is unclear.

But we can also look at the pattern of "damaged TESS files" -- those
that seem to be blacked out without acknowledgement. Only AFTER you
download them and happen to notice (maybe) they have valid headers but
zero data it seems these also have a beyond-chance pattern.  They
associate with times and parts of the sky where something can be
predicted to have happened.

Someone or something is "editing" the telescope database and acting to
remove images that apparently show something they don't want even
scientists to process, let alone maybe take a look at.

Since the patterns are so clear (to the stats programs) it seems such
tampering is creating false patterns in the remaining images that
scientists in the US and around the world rely on to validate their
theories. A growing amount of scientific speculation may be garbage
because of this tampering.

--
"Nothing in life is to be feared, it is only to be understood.
Now is the time to understand more, so that we may fear less."
- Marie Curie

We are not afraid to entrust the American people with unpleasant facts,
foreign ideas, alien philosophies, and competitive values. For a nation that
is afraid to let its people judge the truth and falsehood in an open market
is a nation that is afraid of its people.
-- JFK

A vast array of our most sophisticated sensors, including space-based
platforms, have been utilized by different agencies, typically in
triplicate, to observe and accurately identify the out-of-this-world
nature, performance, and design of these anomalous machines, which are
then determined not to be of earthly origin.
-- Jonathan Grey, NASIC intel officer, Wright Patterson AFB, 06 Jun 2023

[Secret UFO recovery program blown open:]
I hope this revelation serves as an ontological shock sociologically
and provides a generally uniting issue for nations of the world to
re-assess their priorities.
-- David Grusch, 05 Jun 2023
[Talking to Les Kean et al for The Debrief, Grusch called for an end to
nearly a century of global UFO secrecy and warned that humanity needed to
prepare itself for "an unexpected, non-human intelligence contact scenario"].

[David Grusch's] assertion concerning the existence of a terrestrial arms
race occurring sub-rosa over the past eighty years focused on reverse
engineering technologies of unknown origin is fundamentally correct, as
is the indisputable realization that at least some of these technologies
of unknown origin derive from non-human intelligence.
-- Col Karl Nell (ret), 06 Jun 2023

The US government portrays itself as the world's preeminent
superpower, so to acknowledge that there are things in their
airspace, whatever they are, that are faster and more manoeuvrable
and run rings around fast jets doesn't play very well.
So there's the embarrassment factor, and maybe a little bit of
fear that either an adversary has made a quantum leap in
development, which has left the US in a poor second place, or, as
some believe, this really is extra terrestrial, in which case we're
not at the top of the food chain anymore.
-- Nick Pope, 02 May 2023

Most Sun-like stars formed billions of years before the Sun, a time lag
much longer than the time it takes chemical rockets to cross the Milky
Way disk. If only one out of the tens of billions of Earth-Sun systems
in the Milky Way galaxy gave rise to a peaceful, space-exploring
technological civilization over the past 10 billion years, and if that
civilization launched probes at an annual cost of 2 trillion dollars
for a million years, then there would be ten thousand objects from this
spectacular civilization within the solar system now.
-- Avi Loeb, "The Allegory of the Cave: An Interstellar Interpretation",
The Debrief, 15 Mar 2023

The most extreme life-forms in the universe
New Scientist, 26 June 2008
There's hardly a niche on Earth that hasn't been colonised. Life can be
found in scalding, acidic hot pools, in the driest deserts, and in ...
[Interestingly, if life is *not* found in the warm salty sub-surface
oceans of some of our system's moons it gives more weight to the idea
that life could not have formed spontaneously on Earth but came from
"outside" e.g. via meteorites aka Panspermia].