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Exploring Global Mind. Dean Radin, Ph.D. Speculations. What if Einstein was right? God does not play dice with the universe What if mind and matter are deeply interrelated? What if there are hidden causes for apparent randomness?. mind. information. matter. - PowerPoint PPT Presentation
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Exploring Global Mind Dean Radin, Ph.D.
Speculations What if Einstein was right?
God does not play dice with the universe
What if mind and matter are deeply interrelated?
What if there are hidden causes for apparent randomness?
matter
information
mind
Testing Mind-Matter Interaction
… 0 1 1 0 1 0 0 1 0 0 0 1 1 1 ...
random walk
Instructions: “Aim high”
100+ subjects
12 years
5 investigators
800K samples
1 laboratory
What do the skeptics say?
Carl Sagan (1987) ESP = the Loch Ness monster; flying
saucers; an elephant that talks fluent Russian….
Carl Sagan (1995) There are three claims in the ESP
field which deserve serious study: 1) that by thought alone humans can
affect random number generators
216 publications, 1959 – 2000 journals, abstracts, unpublished
reports, in all languages85 investigators~20 laboratories515 experiments
RNG meta-analysis
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1959
1971
1972
1975
1976
1977
1978
1979
1980
1981
1982
1984
1985
1986
1987
1990
1995
1999
year of publication
cum
ulat
ive
mea
n z
scor
e up to 1987 after 19871959- 1987 1988-2000
RNG average Z
Summary: Evidence for Mind-Matter Interaction with RNGs
RNG results are in alignment with quantum measurement speculations
Results are not chance, poor quality, selective reporting, or non-repeatable
Effects are weak in magnitude Effects are not force-like at the bit
level, or simple causal mechanisms
Prediction
If mind and matter are related …
… then fluctuations in “mass mind” might be
reflected as fluctuations in “mass matter”
October 1995 - OJ Simpson Verdict
OJ Simpson Verdict
odds against chance for behavior of 5 random number generators located in US (4) and Europe (1)
1
10
100
1000
8:37
8:45
8:53
9:01
9:08
9:16
9:24
9:31
9:39
9:47
9:54
10:0
2
10:1
0
10:1
8
time (PST)
odds
aga
inst
cha
nce
TV preshows begin broadcastbegins
verdictannounced
More ordered
More random
… 0 1 1 0 1 0 0 1 0 0 0 1 1 1 ...
-5
-4
-3
-2
-1
0
1
2
3
4
5
1 601 1201 1801 2401 3001 3601 4201 4801 5401
samples
Z sc
ores
An internet-based experiment
“well-behaved” noise
used to measure entropy
Devices and Controls
High quality, EM-shielded, hardware RNGs Randomness is based on quantum noise Pass standard randomness tests Analyses checked with pseudorandom
database Analyses checked by independent analysts
Distribution of 1000 200-bit trials, compared to theoretical
normal distribution
expected
Global Consciousness Project50 truly random RNGs around the world
Synchronized to net-time
200 bits / second / RNG 864 M bits / day
http://noosphere.princeton.edu
Events studied Predictable events of mass interest
New Years celebrations, sports events Unpredictable events of mass interest
Earthquakes, terrorist attacks
Formal predictions Exploratory analyses
Example formal events DisasterWestern Indian Earthquake DisasterVolcanic Eruption, Congo Meditation WorldPuja Webcast Meditation Ramadan Muslim Prayer Violence Terrorist Disaster, Sept 11 Sports World Series, Yankee Stadium Sports Winter Olympic Opening Funeral George Harrison Tribute Celebration Earth Day, 2001 Celebration Beijing Gets 2008 Olympics Celebration Buddhist Stupa Ceremony Celebration New Year 2001-2002
Full formal database105 global events over 3 years 9 months
actual data
p =.05 threshold
chance expectation
z score by event types
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
natur
al dis
aster
politi
cal e
vent
funera
l
accid
ent
medita
tion
violen
ce
celeb
ration
z sc
ore
September 11, 2001
-5-4-3-2-1012345
630
705
710
715
720
725
730
804
809
814
819
824
829
903
908
913
date
z sc
ore
June 30,2001 – September 20,2001
sliding window
Formal predictions
-4
-3
-2
-1
0
1
2
3
4
0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18
time (EDT)
z sc
ore9/8/01 9/14/019/11/01
6:30 AM
noise
Sept 8 – Sept 14
“signal”
“signal”
0
1000
2000
3000
4000
50009/
1/01
9/4/
01
9/7/
01
9/10
/01
9/13
/01
9/16
/01
9/19
/01
9/22
/01
9/25
/01
9/28
/01
odds
aga
inst
cha
nce
September 1 September 31
-3
-2
-1
0
1
2
3
4
20 21 22 23 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
hour
z sc
ore
Sept 11 detail
6.5 drop
Daily variance: 1998 - 2002
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
1 101 201 301 401 501 601 701 801 901 1001 1101 1201 1301
days
vari
ance
September 11, 2001
-3
-2
-1
0
1
2
3
4
0.83
1.92
3.00
4.08
5.17
6.25
7.33
8.42
9.50
10.5
8
11.6
7
12.7
5
13.8
3
14.9
2
16.0
0
17.0
8
18.1
7
hour
z sc
ore
September 11, 2001: 36 RNGs
Average Daily RNG Intercorrelation metric = RIC
RIC Asymmetry
r > 0positive
coherence relationshi
p
r = 0zero
coherence
r < 0negative
coherence relationship
RIC distribution and “coherence”
0
20
40
60
80
100
120
140
160
180
200-2
.0-1
.8-1
.5-1
.3-1
.0-0
.8-0
.5-0
.3 0.0
0.3
0.5
0.8
1.0
1.3
1.5
1.8
2.0
2.3
2.5
2.8
3.0
freq
uenc
y
positive coherence
negative coherence
|RIC|
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
0.101/
1/01
2/1/
01
3/1/
01
4/1/
01
5/1/
01
6/1/
01
7/1/
01
8/1/
01
9/1/
01
10/1
/01
11/1
/01
aver
age
Fish
er z
RIC: Year 2001
-3
-2
-1
0
1
2
30 2 4 6 8 10 12 14 16 18 20 22
local time
z sc
ore
night day night
Effects of EM interference
All RNGs for the month of September 2001
Date Length Events Description12/1/2000 129 1 Mexico President Inaugurated
12/2/2000 0 0 -
12/3/2000 0 0 -
12/4/2000 463 2 Chilean Judge Orders Pinochet's Arrest,
Europe Acts to Curb Mad Cow Disease
www.infoplease.com
Towards generalizationNews analysis
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
1998 1999 2000 2001 2002 1998-2002
corr
elat
ion
RIC vs. News
Year = 1998 1999 2000 2001 2002 1998-2002 p = 0.10 0.02 0.38 0.01 0.56 0.002
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
1998 1999 2000 2001 2002 1998-2002
corr
elat
ion
Outlier analysis
0
2
4
6
8
10
12
0 200 400 600 800 1000 1200 1400 1600
news characters
z(in
terc
orre
latio
n)
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
1 3 5 7 9 11 13 15 17 19
outliers removed
corr
elat
ion
z(r)news
How robust is this correlation? Does it depend on extreme values of news or |RIC|?
Is the observed correlation meaningful? Cross correlation test
news metric|RIC|
May 2002August 1998
news metric|RIC|
RIC vs. News cross correlation
-0.10
-0.05
0.00
0.05
0.10
0.15
-100 -90
-80
-70
-60
-50
-40
-30
-20
-10 0 10 20 30 40 50 60 70 80 90 100
lag
cros
s co
rrel
atio
n
RIC vs. News cross-correlation odds
1
10
100
1000
-100 -90
-80
-70
-60
-50
-40
-30
-20
-10 0 10 20 30 40 50 60 70 80 90 100
lag
odds
RIC Cross Correlation Europe (12) vs. North America
(27)
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
-100 -90
-80
-70
-60
-50
-40
-30
-20
-10 0 10 20 30 40 50 60 70 80 90 100
lag
corr
elat
ion
Europe vs. USA odds
0
2000
4000
6000
8000
10000
12000
14000
16000
18000-1
00 -90
-80
-70
-60
-50
-40
-30
-20
-10 0 10 20 30 40 50 60 70 80 90 100
lag
corr
elat
ion
News Spectral AnalysisSpectral analysis: EVENTS
No. of cases: 1314
Log Period
Per
iodo
gram
Val
ues
0
5
10
15
20
0
5
10
15
20
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5
ln(1.95) = 7 days
News events have a 7 day period
News by day of the week
100
120
140
160
180
200
220
240
260
280
300
Mon Tues Wed Thurs Fri Sat Sun
new
s m
etric
News x RIC Cross Spectral AnalysisCross Periodogram (Real)
X:Z Y:CHARSNo. of cases: 1314 (trunc.)
Hamming weigths:.0357 .2411 .4464 .2411 .0357
Log Period
Cro
ss P
erio
dogr
am (R
eal)
-2000
-1500
-1000
-500
0
500
1000
1500
2000
2500
-2000
-1500
-1000
-500
0
500
1000
1500
2000
2500
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5
News & RIC both have 7 day cycles. Are they in phase?
RIC vs. news by weekday
r = 0.63t = 1.80N = 7p = 0.07
100
120
140
160
180
200
220
240
260
280
-0.10 -0.05 0.00 0.05 0.10 0.15
weekday intercorrelation average
new
s m
etric
Speculations
Mind & Matter are complementary aspects of a more fundamental, self-reflective reality
Mind
Matter Inside
Outside
Conclusions Laboratory MMI-RNG scales up Support for Einstein’s Objection:
God does not play dice with the universe Future research:
Role of the analyst? Improved global coherence (news) measures Independent sources of random data New types of “detectors” Theoretical model development