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Anomalous Anticipatory Responses In Networked Random Data Roger Nelson Princeton, New Jersey Frontiers of Time: Reverse Causation -- Experiment and Theory AAAS Symposium, University of San Diego, June 2006. Global Consciousness Project http://noosphere.princeton.edu. - PowerPoint PPT Presentation
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Global Consciousness ProjectGlobal Consciousness Projecthttp://noosphere.princeton.eduhttp://noosphere.princeton.edu
Anomalous Anticipatory ResponsesAnomalous Anticipatory ResponsesIn Networked Random DataIn Networked Random Data
Roger NelsonPrinceton, New Jersey
Frontiers of Time: Reverse Causation -- Experiment and TheoryAAAS Symposium, University of San Diego, June 2006
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?
Random Event Generator – REGReverse Current in Diode: White Noise
Electron Tunneling – A Quantum ProcessSample Resulting Voltage, Record 200-Bit Sums
Binomial Distribution of DataCompared to Theoretical Normal
Trial Scores: 100 ± 7.071Plotted as a sequence, 1 trial per sec
100 is expected mean
It is like flipping 200 coins and counting the heads
A World Spanning NetworkYellow 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
ExpectedTrend isLevelRandomWalk
Cumulative deviation is a Graphical tool to detect change
Process control engineering
A Replication Series Of Formal Tests The Hypothesis:Global Events Correlate withStructure in the Random Data
Test Procedure:Pre-defined events,Standardized AnalysisBottom Line:Composite Statistical Yield
Current Result: Formal Database, 7.5 Years 204 Rigorously Defined Global Events
Odds: About 1 part in 300,000
9/11
Now we proceed to new questionsFirst, how good are the data?
Equipment: Research quality Design, Materials, Shielding, XOR, Calibration standards
Errors and Corrections: Electrical supply failure, component failure. Rare but identifiable
Empirical vs Theoretical: Mean is theoretical, but tiny differences in Variance (expected)
Normalization: All data standardized; empirical parameters facilitate comparison and interpretation
Identify and exclude “Bad Trials” <55 or >145 Identify and exclude device failures, “Rotten Eggs”
Identify Individual “Rotten Egg”
Effect of “Rotten Eggs” on the Full Network Fully vetted, normalized data
Calculate Empirical Variance for Individual Eggs
REG device failure REG device failure
REG device failure REG device failure
Theoretical vs Empirical Distribution (We also assess pseudorandom clone data,
and use resampling and permutation analyses)
Negative differenceMeans that formal
Tests are conservative
Note: These are (0,1)Note: These are (0,1)Normal Z-scoresNormal Z-scores
The Diffs are The Diffs are TINYTINY
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
Suggestions of precursor effectsSept 11 2001 Terror Attacks
Stouffer Z across REGs per secondStouffer Z across REGs per second Cumulative sum of deviations from expectationCumulative sum of deviations from expectation
Variance across REGs per secondVariance across REGs per secondCumulative sum of deviations from expectationCumulative sum of deviations from expectation
Moderately persuasive suggestion Moderately persuasive suggestion that trend may begin before eventthat trend may begin before event
Strong and precise indication that Strong and precise indication that change begins 4 hours before eventchange begins 4 hours before event
AttacksAttacks
AttacksAttacksAttacksAttacksAttacksAttacks
And very recently, the Indonesian earthquake on May 27 this year also seems to show
evidence of a precursor response
To go further we need a better database
Suggestive single cases but low S/N ratio
Need replication in multiple samples
“Impulse” events are sharply defined
E.g. crashes, bombs, earthquakes
Subset of formal series: 51 impulse events Epoch average for covar and devvar may
Depart from expectation prior to T=0
The suggestion of early shift isclearest in covar
Netvar
DevvarCovar
51 Impulse events, Covar epoch averageDeviation may begin ~ 2 hours before T=0
Approx Slope
Impulse events vary -- We need 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
Earthquakes: Important to People, Numerous, Accurately Located,
Rigorously Scaled, Precisely Timed
All Earthquakes, Richter 6 or More Select those on Land with People and Eggs
Eggs shown asorange spots
Selected regions outlined in orange Included quakes shown as grey dots
Controls shown as blue dots
In the Earthquake database, the covar measure appears to be the most useful
of our three independent statistics
For quakes R>6 (grey dots) the covar measure Responds before and after the primary temblor
Average location of quakes in grid square marked as a colored pointSize is cum Z-score; Red: positive; Blue: negative; Green: no calc, less than 2 quakes
-8 hrs
+8 hrs
BeforeMostlyNegative
AfterMostlyPositive
Strong covar response in populated Land areas where we have eggs
North America and Eurasia
Symmetrical, Significant Z-scores Pre & post
Null covar response in unpopulated Regions (ocean) and areas where we have few eggs
Control: Quakes in the Oceans
All Z-scores less than 0.5
Major earthquakes in populated areasCompared with quakes in the oceans
Covar measure, epoch average Cum Dev T=0 ± 30 hours
Ocean QuakesNo structure around T=0
Scale of departure ~ 40 units
North America and EurasiaSignificant structure around T=0
Scale of departure ~ 80 units
Closer look: T=0 +/- 10 hours
North America Europe and Asia
Significant structure around T=0Scale of departure > 50 units
No structure around T=0Scale of departure ~ 20 units
Unpopulated Ocean regions
Data split: T=0 ± 8 Hrs North American vs Eurasian Quakes
Similar structure, independent subsets
T=0 ± 50 hrRaw data
Magnified central portion
Same data as a cumulative deviation
Estimating significance:Estimating significance:The drop between T-7 Hrs and T=0The drop between T-7 Hrs and T=0Corresponds to a Z score of 4.6 Corresponds to a Z score of 4.6 After Bonferroni correctionAfter Bonferroni correction
Compare slope with 3 Compare slope with 3 envelope envelope
The case for an anticipatory response
T=0
3-Hour Gaussian smooth
Many questions remain, e.g., Fatal quakes should be test case.
Subset with N > 5 fatalities and R > 5 The picture is less clear.
CAUTIONARY NOTESCAUTIONARY NOTESThe 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).
Selectivity of analyses needs balance of independent perspectives and replication.
We invite efforts to confirm or deny these indications.
POSSIBILITIESPOSSIBILITIESThe 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.
GCP Homepage
StatusDay Sum ResultsExtract
Special Links
Complementary Perspectives
http://noosphere.princeton.edu
Web DesignRick Berger
The following are extras. Some are explanatory, some provide additional info.
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 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).
EGG Network Response (Quakes on Land) Cumulative Deviation of Covariance
Primary Temblor +/– 30 Hours
Control Data: Oceans &Low Population Zones
North America and Eurasia
Note: This is an early figure with somewhat differentCircumscription and hence a different N of quakes.
Epoch or Signal AveragingA tool for revealing structure
In repeated low S/N ratio events
Graphical presentation: Cumulative Deviation
Used in Statistical Process Control Engineering
Begin CumBegin CumDev from Dev from ExpectationExpectation
Example, Raw dataExample, Raw data
Dev from ExpectationDev from Expectation
The crossover is exactly at T=0The crossover is exactly at T=0The minimum is -3 sigma and The minimum is -3 sigma and
The maximum is +3 sigmaThe maximum is +3 sigma
Raw data and Gaussian smoothed
data Quakes on land
T=0 ± 30 hours
Largest spikes are near T=0Largest spikes are near T=0
Raw
3 Hour
1 Hour
Cumulative deviation of covar for unpopulated regions (ocean) and areas where we have fewer eggs
South America Nippon, East Asia
Control: Quakes in the Oceans
No trends, andNo structureRelated to T=0
Range is 1/2 to 1/3 of Land quakes
A very early suggestion that the REG data might show evidence of
Precursor response to major events-5 minutes T = 0 +5-5 minutes T = 0 +5
95% confidence
Expectation
Assassination of Prime Minister Rabin, 1995
Cumulative DeviationFrom Expectation