Global Consciousness Project noosphere.princeton

1. Anomalous Anticipatory ResponsesIn Networked Random DataRoger NelsonPrinceton, New JerseyFrontiers of Time: Reverse Causation -- Experiment and TheoryAAAS Symposium, University of San Diego, June 2006 Global Consciousness Project http://noosphere.princeton.edu

2. 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?

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 Trial Scores: 100 ± 7.071 Plotted as a sequence, 1 trial per sec Binomial Distribution of DataCompared to Theoretical Normal 100 is expected mean

4. A World Spanning Network Yellow dots are host sites for Eggs http://noosphere.princeton.edu

5. 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

6. We begin to see what’s happening If we plot the Cumulative Deviations

7. 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

8. 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

9. Current Result: Formal Database, 7.5 Years 204 Rigorously Defined Global EventsOdds: About 1 part in 300,000 9/11

10. 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

11. Identify and exclude “Bad Trials” <55 or >145 Identify and exclude device failures, “Rotten Eggs” 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

12. Theoretical vs Empirical Distribution(We also assess pseudorandom clonedata, 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

13. Three Independent statistics The netvaris 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

14. Suggestions of precursor effectsSept 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

15. And very recently, the Indonesian earthquake on May 27 this year also seems to show evidence of a precursor response

16. 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

17. Subset of formal series: 51 impulse events Epoch average for covar and devvar mayDepart from expectation prior to T=0 Covar Devvar The suggestion of early shift is clearest in covar Netvar

18. 51 Impulse events, Covar epoch averageDeviation may begin ~ 2 hours before T=0 Approx Slope

19. 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

20. Earthquakes: Important to People, Numerous, Accurately Located, Rigorously Scaled, Precisely Timed

21. 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

22. In the Earthquake database, the covar measure appears to be the most usefulof our three independent statistics

23. For quakes R>6 (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

24. Strong covar response in populated Land areas where we have eggs North America and Eurasia Symmetrical, Significant Z-scores Pre & post

25. 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

26. 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

27. 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

28. Data split: T=0 ± 8 Hrs North American vs Eurasian Quakes Similar structure, independent subsets

29. The case for an anticipatory response Magnified central portion T=0 ± 50 hr Raw data T=0 3-Hour Gaussian smooth Same data as a cumulative deviation Estimating significance: The drop between T-7 Hrs and T=0 Corresponds to a Z score of 4.6  After Bonferroni correction Compare slope with 3  envelope

30. Many questions remain, e.g., Fatal quakes should be test case. Subset with N > 5 fatalities and R > 5 The picture is less clear.

31. 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). Selectivity of analyses needs balance of independent perspectives and replication. We invite efforts to confirm or deny these indications.

32. 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.

33. GCP Homepage http://noosphere.princeton.edu Special Links Status Day Sum Results Extract Complementary Perspectives Web Design Rick Berger

34. The following are extras. Some are explanatory, some provide additional info.

35. An example of new perspectives:Is there evidence of periodicity?The generalized short answer is no. But formal events may show FFT spikes

36. 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).

37. EGG Network Response (Quakes on Land) Cumulative Deviation of CovariancePrimary Temblor +/– 30 Hours Control Data: Oceans & Low Population Zones North America and Eurasia Note: This is an early figure with somewhat different Circumscription and hence a different N of quakes.

38. Epoch or Signal AveragingA tool for revealing structureIn repeated low S/N ratio events

39. Graphical presentation: Cumulative Deviation Used in Statistical Process Control Engineering Example, Raw data Dev from Expectation Begin Cum Dev from Expectation

40. Raw data and Gaussiansmoothed data Quakes on land T=0 ± 30 hours Raw 3 Hour Largest spikes are near T=0 1 Hour The crossover is exactly at T=0 The minimum is -3 sigma and The maximum is +3 sigma

41. 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, and No structure Related to T=0 Range is 1/2 to 1/3 of Land quakes

42. A very early suggestion that the REG data might show evidence of Precursor response to major events -5 minutes T = 0 +5 Cumulative Deviation From Expectation 95% confidence Expectation Assassination of Prime Minister Rabin, 1995