Download PPPL.061011 - The Global Consciousness Project

Anomalous Correlations
In Networked Random Data
Evidence for Consciousness Fields?
PPPL Colloquium, Oct 11 2006
Roger Nelson
Princeton, New Jersey
Global Consciousness Project
http://noosphere.princeton.edu
Tools for Anomalies Research
PEAR Laboratory, Princeton University
The Benchmark REG Experiment
Aircraft engineering
Random Event Generator – REG
Reverse Current in Diode: White Noise
Electron Tunneling – A Quantum Process
Sample Resulting Voltage, Record 200-Bit Sums
It is like flipping 200 coins and counting the heads
Trial Scores: 100 ± 7.071
Plotted as a sequence, 1 trial per sec
Binomial Distribution of Data
Compared to Theoretical Normal
100 is expected mean
Laboratory Experiments, PEAR:
Intention to Change the REG Behavior
High and Low Both Depart From Expectation
HI
BL
LO
Portable Random Event Generator
(REG or RNG)
Mindsong REG
Orion RNG
Field REG Experiments: Take Portable REG
With Palmtop Computer Into the Field
Resonant Vs Mundane Situations
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?
A World Spanning Network
Yellow dots are host sites for Eggs
http://noosphere.princeton.edu
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
We begin to see what’s happening
If we plot the Cumulative Deviations
If we average the cumulative deviations
Across REGs we may see a meaningful trend
Expected
Trend is
Level
Random
Walk
Cumulative deviation is a
Graphical tool to detect change
Process control engineering
Three Independent statistics
The netvar is Mean(zz). It measures the
average pair correlation of the regs:
<zz> = <z[i]*z[k]>
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:
{ z[i]*z[k] - <zz>}^2
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)
Identify and exclude “Bad Trials” <55 or >145 and
Device failures, “Rotten Eggs” >> Empirical Normalization
Identify Individual “Rotten Egg”
Calculate Empirical Variance for Individual Eggs
REG device failure
Effect of “Rotten Eggs” on the Full Network
REG device failure
Fully vetted, normalized data
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
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
Current Result: Formal Database, 8 Years
212 Rigorously Defined Global Events
Odds: About 1 part in 500,000
9/11
Examples:
Tragedies and Manmade Disasters
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
Examples: Natural disasters too:
Indonesian Earthquake on May 27 2006
(Note that the response seems to begin early)
Examples: New Year’s Celebration
Device Variance Decreases Near Midnight
One especially clear case
Average over 8 years
Examples: Effects of
Large Scale Organized Meditations?
Correlation
Replication
Application
Examples: September 11 2001
Extreme deviations from expectation
Largest spike in 3 years
A Deeper Examination:
Suggestions of Precursor Effects
In Data for Sept 11 2001 Terror Attacks
Stouffer Z across REGs per second
Variance across REGs per second
Cumulative sum of deviations from expectation
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
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
51 Impulse events, Covar epoch average
Deviation may begin ~ 2 hours before T=0
Approx Slope
Impulse events vary – need more consistency
Earthquakes are a precisely defined,
Prolific subset of impulse events
They show similar responses
Impulse events shown as Red, Earthquakes as Blue trace
Netvar
Covar
All Earthquakes, Richter 6 or More
Select those on Land with People and Eggs
Eggs shown as
orange spots
Selected regions outlined in orange
Included quakes shown as grey dots
Controls shown
as blue dots
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
Major earthquakes in populated areas
Compared with quakes in the oceans
Covar measure, epoch average
Cum Dev T=0 ± 30 hours
North America and Eurasia
Significant structure around T=0
Scale of departure ~ 80 units
Ocean Quakes
No structure around T=0
Scale of departure ~ 40 units
Data split: T=0 ± 8 Hrs
North American vs Eurasian Quakes
Similar structure, independent subsets
The case for an anticipatory response
Magnified central portion
T=0 ± 50 hr
Raw data
T=0
3-Hour
Gaussian
smooth
Estimating significance:
The drop between T-8 Hrs and T=0
Corresponds to a Z score of 4.6 
After Bonferroni correction
Compare slope with 3  envelope
Same data as a cumulative deviation
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.
New Work: Sliding the Event Time
Two independent measures track
In subset of events engaging large numbers
Netvar blue
Covar red
Analysis Peter Bancel, Oct 2006
Sliding the Event Time:
Independent measures do not track
In simulated events created by resampling
Netvar: Z=0.3
covar
Analysis: Peter Bancel, Oct 2006
A Surprising, Long-term Trend
Independent Correlation
With a Sociological Measure?
9/11
GCP Homepage
http://noosphere.princeton.edu
Special Links
Status
Day Sum
Results
Extract
Complementary
Perspectives
Web Design
Rick Berger
An example of new perspectives:
Is there evidence of periodicity?
The generalized short answer is no.
But formal events may show FFT spikes
Fourier Spectra and Event Echoes
Dec 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).
Epoch or Signal Averaging
A tool for revealing structure
In repeated low S/N ratio events
Graphical presentation: Cumulative Deviation
Used in Statistical Process Control Engineering
Example, Raw data
Dev from Expectation
Begin Cum
Dev from
Expectation
Subset of formal series: 51 impulse events
Epoch average for covar and devvar may
Depart from expectation prior to T=0
Covar
The suggestion
of early shift is
clearest in covar
Devvar
Netvar
In the Earthquake database, the covar
measure appears to be the most useful
of our three independent statistics
Closer look: T=0 +/- 10 hours
North America Europe and Asia
Unpopulated Ocean regions
Significant structure around T=0
Scale of departure > 50 units
No structure around T=0
Scale of departure ~ 20 units
For quakes R>6 (grey dots) the covar measure
Responds before and after the primary temblor
Before
-8 hrs
Mostly
Negative
After
Mostly +8 hrs
Positive
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
Many questions remain, e.g.,
Fatal quakes should be test case.
Subset with N > 5 fatalities and R > 5
The picture is less clear.
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.