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Global Consciousness Project

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Title: Global Consciousness Project


1
Anomalous CorrelationsIn Networked Random Data
Evidence for Consciousness Fields? PPPL
Colloquium, Oct 11 2006 Roger NelsonPrinceton,
New Jersey
  • Global Consciousness Project
  • http//noosphere.princeton.edu

2
Tools for Anomalies Research PEAR Laboratory,
Princeton University The Benchmark REG Experiment
Aircraft engineering
3
Random Event Generator REGReverse Current in
Diode White Noise Electron Tunneling A
Quantum ProcessSample Resulting Voltage, Record
200-Bit Sums
It is like flipping 200 coins and counting the
heads
Binomial Distribution of DataCompared to
Theoretical Normal
Trial Scores 100 7.071 Plotted as a sequence,
1 trial per sec
100 is expected mean
4
Laboratory Experiments, PEARIntention to Change
the REG Behavior High and Low Both Depart From
Expectation
HI
BL
LO
5
Portable Random Event Generator (REG or RNG)
Mindsong REG
Orion RNG
6
Field REG Experiments Take Portable REG With
Palmtop Computer Into the FieldResonant Vs
Mundane Situations
7
Extend to Global Dimensions Global Consciousness
Project (aka The EGG Project)
  • The People An international collaboration of
  • 100 Scientists, Engineers, Researchers
  • The Tools REG technology, Field applications,
  • Internet communication, Canonical statistics
  • The Question Is there evidence for Non-random
  • Structure where there should be none?

8
A World Spanning Network Yellow dots are host
sites for Eggs
http//noosphere.princeton.edu
9
Internet Transfer to Data Archive in Princeton
Here are data plotted as sequences of 15-minute
block means, for a whole day, from 48 eggs
10
We begin to see whats happening If we plot the
Cumulative Deviations
11
If we average the cumulative deviations Across
REGs we may see a meaningful trend
Cumulative deviation is a Graphical tool to
detect change Process control engineering
Expected Trend is Level Random Walk
12
Three Independent statistics
  The netvar is Mean(zz). It measures the
average pair correlation of the regs ltzzgt
ltzizkgt where i k are different regs and z
is trials for one second. The devvar is Var(z)
the variance across regs Calculated for each
second. The covar is Var(zz). It represents the
variance of the reg pair products zizk
- ltzzgt2 
13
First, how good are the data?
  • Equipment Research quality Design, Materials,
    Shielding, XOR, Calibration standards
  • Errors and Corrections Electrical supply
    failures, component failures. Rare but
    identifiable
  • Normalization All data standardized empirical
    parameters facilitate comparison and
    interpretation
  • Empirical vs Theoretical Mean is theoretical,
    but tiny differences in Variance (expected)

14
Identify and exclude Bad Trials lt55 or gt145 and
Device failures, Rotten Eggs gtgt Empirical
Normalization
Identify Individual Rotten Egg
Calculate Empirical Variance for Individual Eggs
REG device failure
Effect of Rotten Eggs on the Full Network
Fully vetted, normalized data
REG device failure
15
Theoretical vs Empirical Distribution (We also
assess pseudorandom clone data, and use
resampling and permutation analyses)
Note These are (0,1) Normal Z-scores The Diffs
are TINY
Negative difference Means that formal Tests are
conservative
16
A Replication Series Of Formal Tests
The Hypothesis Global Events Correlate
with Structure in the Random Data Test
Procedure Pre-defined events, Standardized
Analysis Bottom Line Composite Statistical
Yield
17
Current Result Formal Database, 8 Years 212
Rigorously Defined Global EventsOdds About 1
part in 500,000
9/11
18
Examples Tragedies and Manmade Disasters
19
Examples Tragedies and Manmade
Disasters(Sometimes we see no apparent effect
when we think we should)
Signal to Noise ratio Is small, so Effects may Be
buried Noise may Masquerade As signal
20
Examples Natural disasters too Indonesian
Earthquake on May 27 2006 (Note that the response
seems to begin early)
21
Examples New Years CelebrationDevice Variance
Decreases Near Midnight
One especially clear case
Average over 8 years
22
Examples Effects of Large Scale Organized
Meditations?
Correlation
Replication
Application
23
Examples September 11 2001Extreme deviations
from expectation
Largest spike in 3 years
24
A Deeper ExaminationSuggestions of Precursor
EffectsIn Data for Sept 11 2001 Terror Attacks
Stouffer Z across REGs per second Cumulative sum
of deviations from expectation
Variance across REGs per second Cumulative sum of
deviations from expectation
Attacks
Attacks
Attacks
Attacks
Moderately persuasive suggestion that trend may
begin before event
Strong and precise indication that change begins
4 hours before event
25
Rigorous look at Possible Anticipatory Response
  • Suggestive single cases but low S/N ratio
  • Need replication in multiple samples
  • Impulse events are sharply defined
  • E.g. crashes, bombs, earthquakes

26
51 Impulse events, Covar epoch averageDeviation
may begin 2 hours before T0
Approx Slope
27
Impulse events vary need more
consistencyEarthquakes are a precisely
defined,Prolific subset of impulse events They
show similar responses
Impulse events shown as Red, Earthquakes as Blue
trace
Netvar
Covar
28
All Earthquakes, Richter 6 or More Select those
on Land with People and Eggs
Selected regions outlined in orange Included
quakes shown as grey dots
Eggs shown as orange spots
Controls shown as blue dots
29
Strong covar response in populated Land areas
where we have eggs
North America and Eurasia
But not when the quakes Are in the oceans
Significant Z-scores Pre post
30
Major earthquakes in populated areas Compared
with quakes in the oceans Covar measure, epoch
average Cum Dev T0 30 hours
Ocean Quakes No structure around T0 Scale of
departure 40 units
North America and Eurasia Significant structure
around T0 Scale of departure 80 units
31
Data split T0 8 Hrs North American vs
Eurasian Quakes Similar structure, independent
subsets
32
The case for an anticipatory response
Magnified central portion
T0 50 hr Raw data
T0
3-Hour Gaussian smooth
Same data as a cumulative deviation
Estimating significance The drop between
T-8 Hrs and T0 Corresponds to a Z score of 4.6
? After Bonferroni correction Compare slope with
3 ? envelope
33
CAUTIONARY NOTES
  • The effects we see are very small, buried in a
    sea of
  • noise. Is signal an appropriate term?
  • Statistical and correlational measures. Need to
  • understand inconsistencies.
  • Fundamental questions remain unanswered.
  • E.g., effects of N of eggs, Distance, Time.
  • We need the balance of independent perspectives
  • and replication.
  • We invite efforts to confirm or deny these
    indications.
  • The data are all available online.

34
New Work Sliding the Event TimeTwo independent
measures track In subset of events engaging
large numbers
Netvar blue
Covar red
Analysis Peter Bancel, Oct 2006
35
Sliding the Event TimeIndependent measures do
not track In simulated events created by
resampling
Netvar Z0.3
covar
Analysis Peter Bancel, Oct 2006
36
A Surprising, Long-term TrendIndependent
CorrelationWith a Sociological Measure?
9/11
37
GCP Homepage
http//noosphere.princeton.edu
Special Links
Status Day Sum Results Extract
Complementary Perspectives
Web Design Rick Berger
38
An example of new perspectivesIs there evidence
of periodicity?The generalized short answer is
no. But formal events may show FFT spikes
39
Fourier Spectra and Event EchoesDec 26 2004
Tsunami vs Pseudo Data
Analysis by William Treurniet
The pre-event frame shows a substantial peak
(black trace) Compared with the pseudorandom
data (right panel). And check out post-event
frame 3 (pale bluegreen).
40
Epoch or Signal AveragingA tool for revealing
structureIn repeated low S/N ratio events
41
Graphical presentation Cumulative Deviation
Used in Statistical Process Control Engineering
Example, Raw data
Dev from Expectation
Begin Cum Dev from Expectation
42
Subset of formal series 51 impulse events Epoch
average for covar and devvar mayDepart from
expectation prior to T0
Covar
Devvar
The suggestion of early shift is clearest in
covar
Netvar
43
In the Earthquake database, the covar measure
appears to be the most usefulof our three
independent statistics
44
Closer look T0 /- 10 hours
North America Europe and Asia
Unpopulated Ocean regions
Significant structure around T0 Scale of
departure gt 50 units
No structure around T0 Scale of departure 20
units
45
For quakes Rgt6 (grey dots) the covar measure
Responds before and after the primary temblor
Before Mostly Negative
-8 hrs
After Mostly Positive
8 hrs
Average location of quakes in grid square marked
as a colored point Size is cum Z-score Red
positive Blue negative Green no calc, less
than 2 quakes
46
Many questions remain, e.g., Fatal quakes should
be test case. Subset with N gt 5 fatalities and R
gt 5 The picture is less clear.
47
POSSIBILITIES
  • The GCP database of networked random events is
    unique. No other resource like it exists.
  • Opportunity for useful questions and answers.
    Probably holds surprises.
  • Fundamental questions that should be asked are
    known (e. g., N of eggs, Distance, Time).
  • A couple of years of supported analytical
    research would break new ground.
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