Newsgroups: alt.astronomy
From: kymhorsell@gmail.com
Subject: how to predict mars quakes

[uploaded 54 times; last 16/10/2024]

  (I usually put an executive summary on these things. 
  But this is a shaggy dog story so we can't do that today. 
  This is not a late April fools joke.  All of the data and stats is 100% real. 
  I've left a tarball with the basic numbers at <kym.massbus.org/DATA/marsquake.tgz>
   if anyone wants to run them through their own spreadsheets or whatever).


The SEIS instrument package of the Insight mission has been measuring
the "pulse" of Mars for the past 6m.

The public release of the dataset show more than 2000 "events" some of
which (~200) are full-on Mars quakes, with the others mostly
unclassifiable thuds and squeaks made by the planet or wider
environment in one way or another.

The data I've looked at so far runs day by day from Aug through Sept of 2021.

And the second thing any data scientists would like to find out is --
what other daily data series highly correlate with Mars quakes so they
might be in some one predicted and/or understood.

My first run has not bothered to extract the (many!) features of each
individual event. So all the bumps and squeaks are lumped together
into daily totals with quakes and misc crustal movements.

For your enjoyment, should you wish to run your own analyses, the data
looks like this:

Date	Number of events
2021.585 13
2021.587 42
2021.590 58
2021.593 50
2021.596 29
2021.598 33
2021.601 34
2021.604 25
2021.607 25
2021.609 30
2021.612 20
2021.615 24
2021.617 21
2021.620 29
2021.623 37
2021.626 28
2021.628 13
2021.631 29
2021.634 29
2021.637 36
2021.639 48
2021.642 45
2021.645 53
2021.648 17
2021.650 32
2021.653 39
2021.656 17
2021.658 25
2021.661 26
2021.664 45
2021.667 20
2021.669 33
2021.672 22
2021.675 55
2021.678 57
2021.680 42
2021.683 33
2021.686 42
2021.689 60
2021.691 37
2021.694 33
2021.697 85
2021.699 10
2021.702 10
2021.705 33
2021.708 26
2021.710 79
2021.713 40
2021.716 17
2021.719 10
2021.721 40
2021.724 25
2021.727 46
2021.730 17
2021.732 57
2021.735 29
2021.738 50
2021.740 25
2021.743 42

The "date" is my software's idiosyncratic way of rendering dates.
The fraction part is the Julian day less 1, divided by 366 and rounded
to 3 places. (Unf I've found different s/w packages do their
printing-rounding in slightly different ways meaning they are slightly
incompatible with the C version of the above algorithm; be warned that
lining up the above data with other daily data that superficially
looks similar might not exactly match up each day with those other datasets).

I use some AI-boosted stats algorithms that try to ensure even a very
very large collection of statistical procedures will produce robust
answers. You need this kind of thing when you're doing what used to be
called "statistical exploration" (as opposed to "hypothesis testing").
When you churn through 1000s of datasets looking for matches you
can find some that are entirely spurious simply due to probability.
Remember the old bar trick of selecting 4 "pat" hands from just 21
random cards. Seems difficult. But there are just so many different
ways to select the 4 hands probability favors the task being easy.

So the S/W does a simple timeseries (ARMA11) regression against a
"target" dataset (in this case the above mars quake series) and 10s of
1000s of other daily datasets it has on hand. It finds the closest
matches using robust statistics and a little bit of reasoning based on
the metadata for each dataset to decide which matches are
statistically robust (generally to "4 9s" -- 99.99% likely aka .01%
unlikely) and also "make sense" based on what is being compared.

With Mars quakes the S/W knows about Mars, that it is a planet, and
that things relate logically to similar things so the best things to
look at with 1000s of choices are daily timeseries of planetary
motions.  It further deduces "space weather" and other dataseries
related to the Sun might be appropriate things to check.

And this is what its first pass through the 5 TB of data it has on
hand turns up:

Suspect         Lag     Trans   R2            Beta (90% CI +/-)
                (d)
electron        16      -x -y   0.15241521    0.80137         0.505885 
venus-RA        20      -y      0.13320002    -0.000936876    0.000639781 
mercury-RA      5       -y      0.12643742    -0.000925927    0.00065767 
mercury-v       16      -x -y   0.12541261    0.193645        0.139516 
SN              1       -y      0.09657677    0.00405686      0.00332155 
saturn-FV       16      -x -y   0.08995776    0.133218        0.113427 
mercury-elong   16      -x -y   0.08980298    0.169894        0.144792 
saturn-mag      16      -x -y   0.08434787    0.258611        0.228095 
mercury-FV      16      -x -y   0.08122965    0.170773        0.153747 
mercury-r       20      -x -y   0.06947440    0.656052        0.648802 
uranus-phase    8       -x -y   0.04872648    897.788         1061.9 
mercury-diam    8       -x -y   0.04815920    0.650431        0.77408 
geomag          2       -y      0.03965379    0.28968         0.385224 


The list includes most of the thing we might (in general) think are
related to causing "thuds" on Mars. The S/W has allowed some leeway
for the regression results with the "suspect" dataseries allowed to
slip up to 30 days so it finds the best match (largest R2) allowing
the delay between the "suspect" changing values to the time the
"target" (i.e. the Mars quake data, at the top) changes values.

The "trans" column shows which data transformations found the best R2.
"-x" means logs were taken for the suspect. "-y" means logs were taken
for the target.

The "R2" column gives the "explanation power" of the found timeseries
model. The suspect, with the given transformations and lag is said to
"explain" the relevant proportion of the target data. So, for example,
the first model above marked "electron" (a type of space weather
monitored above Earth) shows the electron events explain about 15% of
the day-to-day changes in Mars quakes. This is just the strength of he
match. The statistical procedures ensure there is only a very very
tiny chance -- from 1 in 1000 to 1 in 10000 -- the number of times a
change in the suspect data corresponds consistently with a change in
the target data might be just due to luck, even given the huge number
of datasets we trolled through to find it.

The Beta column shows how the transformed suspect predicts the daily
value of the number of Mars events. Unfortunately, interpreting this
depends on the transformations that were applied. For the models
marked "-x -y" it means Mars quakes rise or fall as a power law of the
respective suspect series. For the "-y" (only) models you can
interpret small Beta values as a percentage change (because exp(x) ~=
1+x for small x).  E.g. the SN model says for each change (+/-) in 1
unit of the suspect the Mars quake data changes about (+/-) 0.4%. The
"SN" data is the daily sunspot number take from the Royal Belgian
Observatory series.

With these considerations in hand we can look at WHAT the S/W found
and why.  For "electron events", which are just the daily number of
published Alerts for that kind of space weather without examining how
strong the event is predicted to be, the model finds more alerts in 16
days time predict more Mars seismic events. The link seems to be the
best found -- explaining 15% of seismic events. Electron events are
significant steams of electrons coming from the Sun -- a kind of solar
storm. They can interfere with satellites but generally don't do much
at the surface of the Earth.  It "stands to reason" (according to the
AI) that events at the Earth that are caused by the Sun might also
affect things at Mars.  So it is "logical" that particular type of
solar weather might be the "cause" of some of the seismic events seen
on Mars in late 2021 by SEIS.

Solar activity is the cause of electron weather. So it also "makes
sense" that Sunspot Numbers that predict overall solar activity, also
predict Mars seismic events and are a possible "cause".  The S/W finds
changes in SN after 1 day are likely to predict changes in Mars
seismic events 1 day later. This makes sense.  While electron events
might take 16 days to get from the Earth's orbit to Mars, other kings
of things including raw heat resulting from increased solar activity
might take only 1 day to get there and kick off some kind of surface
creaking or even the odd rock tumble and be detected by the SEIS
instrument.

The last item on our list, above, is another kind of space weather --
geomagnetic storms expected over Earth. Again, a possible source of
disruption to power grids and satellites here. But the S/W says it's
also one of the "logical" things that might cause seismic events on
Mars and is found to "explain" about 4% of them using the relevant
robust statistical model. Unlike slow old electrons, EM events take
only 2 days between Earth orbit and Mars orbit. But that makes some
kind of sense.  Not quite as fast a reaction as changes on Sunspot
Number, but faster than electrons. All the effects take a
characteristic time to build up at Mars as well as travel the distance
between Earth orbit (where they are generally measured) and Mars.

The other items are planetary parameters. It's first of all
surprising that Jupiter is not found to contribute anything to Mars
seismic events.  The S/W checked. But it didn't find anything
significant.

The position of Venus is found to explain 13% of Mars seismic events
after a 20 day lag. Venus' Right Ascension -- its position relative
to the celestial equator as seen from Earth with its 23 deg tilt --
seems to predict Mars quakes. The S/W notes with a big (*) this is
unusual because a similar metric -- Venus' ecliptic latitude -- is
found NOT to predict Mars events. Somehow the position of Venus as
seen from Earth is a better predictor of Mars quakes than a "neutral"
measure of the same kind of thing as seen from the Sun.  Why this
should be is a bit of a mystery. Unless you keep reading. :)

The RA of Mercury is the next-most relevant thing. It also predicts
13% of Mars quakes but after only a 5 day delay. Somehow it seems
"information" is leaking from Mercury to Mars in 5 days but it takes
the same kind of information 20 days to travel from Venus to Mars. But
of course Mercury might be closer to Mars in late 2021 when the Mars
data was gathered. It orbits every ~100 days so 1/2 the time it's
bound to be fairly close to Mars while Venus and its slower orbit
might have been stuck on the other side of the Sun at that time.

Mercury makes other appearances in our list. The "elongation" -- the
angle between the Sun and Mercury as seen from Earth -- predicts about
8% of Mars quakes. The Beta shows the further Mercury appears from the
Sun predicts more Mars quakes. If it appears close to the Sun --
i.e. tending to be between the Sun and Earth -- there are fewer Mars quakes.

The distance between Mercury and the Sun ("mercury-r") predicts 7% of
Mars quakes. The Beta shows the further the very eccentric Mercury is
from the Sun the more Mars quakes are predicted.  It's hard to credit
such a tiny planet even at its closest to Mars can affect anything,
but the data shows otherwise. Maybe Mercury when it gets in the way of
solar wind going to Mars it blocks some of it?

Even more puzzlingly, the positions of Saturn and Uranus also seem to
be linked with Mars quakes. The phase as each planet as seen from
Earth seems to relate to 9% and 5% resp of Mars quakes. The phase
angle is determined by the relative positions of the Earth, the Sun
and the relevant planet. How can this affect Mars quakes? What
"information" is travelling between these planets and Mars to knock
rocks over somewhere?

Puzzles puzzles puzzles.

But now we get into very weird areas. You can also ask the S/W if any
other data explains Mars quakes better than the "logical" datasets it
already selected and tested.

And, oops, there are a LOT of them. All seemingly statistically
strong yet having no logical basis for suspecting they might be related.

The first one is the stock price of Exxon. The match it finds looks like:

Suspect         Lag     Trans   R2            Beta (90% CI +/-)
                (d)
xom-price	18	-x -y	0.12567289	-4.90575   3.49659 

I.e. 18 days after XOM changes value (+/-) on the NYSE about 13% of
the time you find Mars quakes change (-/+). When prices rise Mars
quakes tend to sharply go down 18 days later (the model is a power law
with the power equal about -5).  (There is no particular reason Exxon
was selected -- it's the only stock I have daily data on).

Why? The data statistically matches across almost 90 days of data. It
can't be a "fluke". Can it?

Letting the S/W look even further and relax some of its logic finds
another bunch of datasets that match. All related to COVID.  It seems
daily covid data on Earth more closely predicts Mars quakes than any
planetary positions or space weather we found above.

The best matches look like:

Suspect         Lag     Trans   R2            Beta (90% CI +/-)
                (d)
posAL           2       -y      0.33508070    -0.0735234   0.0277253 
deaths-cameroon 9       -y      0.25051859    0.229019     0.106041 
posCO           9       -x -y   0.22372041    -2.38069     1.20989 
posME           9       -x -y   0.22265019    -10.0426     4.97705 
posCA           12      -x -y   0.22073639    -3.72928     1.87574 
posPA           16      -x      0.21461976    62.1162      31.8091 
posOK           9       -x -y   0.20922472    1.66281      0.890644 
deaths-kenya    4       -y      0.19769733    -0.0233502   0.012711 
posTN           5       -x -y   0.19662649    2.79513      1.49854 
cases-uruguay   0       -y      0.19618060    0.0100669    0.00545494 

Why daily covid cases or deaths or positivity rates of certain US
states should relate to mars quakes is "unclear". Especially given
e.g.  positivity rates in late 2021 delayed by 2 days matches up with
34% of Mars quakes -- 2x better than any "logical" planetary
parameter.  Even the worst match of our list above is better than most
of the "logical" causes of Mars quakes.

Puzzle puzzle puzzle.

This is the problem with AI's. They can find things you never imagined
and then refuse to explain why they found them!

But we can go even further and just ask to find the best 3-39s
statistical model that matches the 90 days of Mars quakes we have.

And it spits out:

Suspect         Lag     Trans   R2            Beta (90% CI +/-)
                (d)
ufoOK          0       -x -y   0.37411028    6.19028    2.18447 
ufoID          19      -y      0.28173884    4.02872    1.72197 
ufoRectangle   20      -x -y   0.27809017    4.40445    1.9361 
ufoChevron     9       -y      0.23750037    6.58536    3.1587 
ufoEgg         4       -y      0.23364850    17.035     8.41709 
ufoAR          18      -y      0.21302682    5.07945    2.58946 
ufoCT          14      -y      0.20908356    2.85133    1.51301 
ufoMA          15      -x -y   0.19997567    1.70376    0.929735 
ufoFL          0       -y      0.19744907    -0.446339  0.243162 
ufoblack       11      -y      0.19097419    3.05637    1.6999 

OK. Now it's becoming clearer! The unibers is jus totes f*ked up!

Somehow the solar wind is linked with 15% of Mars quakes after days of
"travel time" between the orbits of Earth and Mars but but some Okie
sees some weird sh*t in the sky and within a day Mars is registering
beyond 99% confidence some bump or grind 37% of the time.

--
"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

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