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Exploring relationships between random physical events and mass human attention: Asking for whom the bell tolls

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Exploratory study of the outputs of continuously operating truly random number generators (RNG) located around the world indicated that the largest daily change in variance in the year 2001 occurred on an unprecedented day in United States history, September 11, 2001. Calculation of correlations between all possible pairs of RNG outputs on a per-day basis showed that the largest daily average correlation also took place on September 11. Comparison of daily RNG correlations for 250 days that made headline news in 2001 according to a commercial news service vs. similar measures for 115 non-eventful days showed a larger average RNG correlation on days with major news events (p 5 0.011). More generally, the correlation between an objective metric of daily news vs. the daily average RNG correlation was significantly positive (p 5 0.001). Potential environmental artifacts were examined and found to be implausible explanations for these results. One interpretation of these findings is that mind-matter interaction effects previously observed only in focused laboratory studies may be detectable outside the laboratory, potentially at a global scale.
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Exploring Relationships Between
Random Physical Events and Mass Human Attention:
Asking for Whom the Bell Tolls
DEAN RADIN
Institute of Noetic Sciences,
101 San Antonio Road, Petaluma, CA 94952,
DeanRadin@Noetic.org
Abstract—Exploratory study of the outputs of continuously operating truly
random number generators (RNG) located around the world indicated that the
largest daily change in variance in the year 2001 occurred on an unprecedented
day in United States history, September 11, 2001. Calculation of correlations
between all possible pairs of RNG outputs on a per-day basis showed that the
largest daily average correlation also took place on September 11. Comparison
of daily RNG correlations for 250 days that made headline news in 2001
according to a commercial news service vs. similar measures for 115 non-
eventful days showed a larger average RNG correlation on days with major
news events (p 50.011). More generally, the correlation between an objective
metric of daily news vs. the daily average RNG correlation was significantly
positive (p 50.001). Potential environmental artifacts were examined and
found to be implausible explanations for these results. One interpretation of
these findings is that mind-matter interaction effects previously observed only
in focused laboratory studies may be detectable outside the laboratory,
potentially at a global scale.
Keywords: randomness—attention—mind
Introduction
As I grew up I became increasingly interested in philosophy, of which [my family]
profoundly disapproved. Every time the subject came up they repeated with unfailing
regularity, ‘‘What is mind? No matter. What is matter? Never mind.’’ After some fifty or
sixty repetitions, this remark ceased to amuse me.
—Bertrand Russell
Generations of philosophers have vigorously debated the questions that taunted
Bertrand Russell, so far without much resolution. In an experimental approach to
this question, investigators have examined the outputs of electronic noise-based,
truly random number generators (RNG) before, during and after highly focused
or coherent group events. The group events studied included intense
psychotherapy sessions, captivating theater presentations, religious rituals,
popular sports competitions, like World Cup Soccer, and high-interest television
broadcasts like the Academy Awards (Bierman, 1996; Blasband, 2000; Nelson,
1995, 1997; Nelson et al, 1996, 1998a, 1998b; Radin, 1997; Radin et al, 1996;
Journal of Scientific Exploration, Vol. 16, No. 4, pp. 533–547, 2002 0892-3310/02
533
Rowe, 1998; Schwartz et al, 1997). Results of these studies suggest in general
that mind and matter are entangled in some fundamental way, and in particular
that focused mental attention in groups is associated with negentropic
fluctuations in streams of truly random data.
Unlike laboratory investigations of mind-matter interactions involving RNGs,
where typically one individual is asked to mentally intend the output of an RNG
to deviate from chance, the present experiments study groups of coherent minds
that are paying attention to external events and explore whether these moments
are associated with analogous states of coherence in matter. RNGs are used as
the ‘‘matter’’ in these experiments because methods for detecting statistical order
in sequences of random events are well established, techniques for generating
and recording truly random bits are well understood, and several hundred
independently replicated, previously reported laboratory studies provide support
for the hypothesis that under certain conditions, mental intention and random
events can become significantly correlated (Radin & Nelson, 1989, in press).
In 1998, Roger Nelson initiated the Internet-based Global Consciousness
Project (GCP) to significantly expand this line of research by providing
numerous parallel, continuous streams of truly random bits from well-calibrated,
noise-based RNGs located around the world (Nelson, 2001). In these studies,
mass mental coherence is inferred to take place as a result of major news events
which attract widespread attention, and it is around these times that negentropic
changes are predicted to occur in the RNGs. This hypothesis has been formally
tested in the GCP data by examining whether the cumulative deviation in
variance across the random bit streams shifts from chance expectation, usually
by examining RNG data from just before an event of widespread interest to a few
hours afterward. As of May 2002, some 104 such events had been formally
tested, with overall significant results (p ,3310
27
)
1
. With growing support
for the GCP mind-matter interaction hypothesis, I was motivated to examine the
data over longer time periods than had been previously studied, with special
interest in exploring how RNG outputs behaved on days with major news events
as compared to relatively uneventful days.
Devices and Data
A more detailed account of the hardware and software that comprises the GCP
network can be found in Nelson (2001, 2002). The following brief description
will suffice for the present analyses. The GCP RNGs are not software-generated
pseudorandom numbers, but hardware circuits that rely on inherent electronic
noise as a source of randomness. Of the three different types of RNGs employed
in the GCP network, one uses noise in resistors and the other two use quantum
tunneling in solid-state junctions. The RNGs are designed for professional
applications requiring highly reliable generation of truly random bits, and
each has passed standard tests for randomness (e.g., Marsaglias DIEHARD test,
no date) as well as calibration tests consisting of one million 200-bit trials.
534 D. Radin
All of the RNGs are solid-state circuits housed in electromagnetically shielded
boxes, and the noise-based random bit sequences are compared to an equal
number of 0 and 1 bits with a logical exclusive or (XOR) to ensure that the mean
output is unbiased regardless of environmental conditions, component interac-
tion, or aging.
Each RNG is attached to a personal computer which collects random bits into
one ‘‘trial’’ per second, where each trial is the sum of 200 random bits. These
trials theoretically follow a binomial distribution with mean 5100 and variance
550. Each computer records its trials into time-stamped files, and all computer
clocks are synchronized to standard Internet time servers. Packets of data with
RNG site identification, per-second timing information, and a checksum to
ensure data accuracy are assembled and transmitted over the Internet to a central
server in Princeton, New Jersey, USA, for archiving.
The GCP network of RNGs started with a few RNGs in 1998, and it has
slowly increased in size over time as individuals are found who are willing to
host an RNG on their personal computer. As of May 2002, the network consisted
of approximately 50 RNGs located throughout North America, Europe, South
America, Asia, Africa, and Australia. The number of RNGs reporting daily
fluctuates by one or two occasionally, when the computers hosting the RNG are
taken offline or used for other tasks.
Analyses
Never send to know for whom the bell tolls; it tolls for thee.
—John Donne
The analyses presented here were exploratory, and as such, the results will be
useful primarily in developing future hypotheses. A non-mathematical way of
thinking about these analyses is as follows: Imagine that each RNG is
continually generating numbers that, when collected into a histogram, form
a bell-shaped curve.
2
We are interested in how the shape of this bell curve
changes over time, and especially in how external events might be associated
with those changes. We are, in effect, studying relationships between the
‘‘ringing’’ of the bell during the course of human events. To borrow John
Donnes poetic phrase, we are asking for whom the bell tolls.
There are four simple ways that a bell curve can deviate from a theoretically
perfect bell shape. The curve can be (1) shifted to the left, (2) shifted to the right,
(3) squashed flat (i.e., the top of the bell pushed down), or (4) squashed thin (the
sides of the bell pushed toward the center). The first two possibilities are not
suitable for our purpose because we have no a priori way of predicting which
direction the curve might shift (or in our metaphor, which direction the bell
might swing). So our analyses focus on the second two methods.
In the analyses described below, the ‘‘variance’’ method is concerned with
how a bell-shaped curve formed by data from all of the RNGs fluctuates from
Exploring Relationships 535
one day to the next. The ‘‘intercorrelation’’ method is concerned with the
similarity in shapes among many bell-shaped curves, one curve for each RNG,
and how those similarities fluctuate from day to day.
Variance Analysis
This analysis explored changes in variance among all reporting RNGs for
each day in the year 2001. The procedure was as follows:
1) Download the daily raw data files for each day in 2001 from the GCP Web
site (http://noosphere.princeton.edu/data/extract.html as of May 21, 2002).
The data files are in the form of a matrix, where the columns identify the
RNGs and the rows list the per-second trial outputs.
2) Calculate the daily trial mean and standard deviation for each RNG
running each day. Exclude individual RNG trial values <50 or >150,
whole RNGs with daily empirical trial means .103 or ,97, or whole
RNGs with daily trial standard deviations .6or,8. Extreme individual
trials and deviant daily means and standard deviations were excluded from
further analysis to ensure that the data were being collected from properly
functioning RNGs. This is necessary because the RNGs are physical
devices connected to PCs and the Internet, and as such they are not
expected to perform perfectly all the time. Still, the GCP network has
proven to be remarkably reliable. In more than three years of continuously
collected data, over 99.5% of the database falls within expected thresholds
for truly random data. The few exceptions include RNGs with overly
restricted variance (typically due to RNG circuits that failed) or an
occasional impossibly high or low individual trial value (typically due to
a malfunctioning PC serial port).
3) Use the daily trial mean and standard deviation for each RNG to calculate
a Student t-score with 199 degrees of freedom (199 df) per RNG, per
second, where t5(x2
xx)/s,xis a per-second trial value from RNG
number r,
xx is the daily trial mean for RNG r, and sis the daily trial
standard deviation for RNG r. In practice these tscores are almost
identical to standard normal deviates, z5(x2100)/
ffiffiffiffiffi
50
p, where 100 is
the theoretically expected mean and s5
ffiffiffiffiffiffiffiffi
Npq
p5
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
200 3:53:5
p5
ffiffiffiffiffi
50
p, the theoretically expected standard deviation.
4) Because t(199 df) z, calculate one t
2
value per RNG per second. These
t
2
values are effectively chi-square distributed.
5) Sum the t
2
values from Step 4 across all reporting RNGs per second,
keeping track of the number of t
2
values that are summed. Call this
summed value T, and the number of summed t
2
values N; thus Tis chi-
square distributed with Ndf.
6) Sum 300 contiguous Tvalues from Step 5 to form a single value that
consolidates 5 minutes of the per-second data; call this value T
5
. Do the
same for the Nvalues; call this N
5
. Repeat this procedure to create a total
536 D. Radin
of 288 non-overlapping T
5
and N
5
values per day. This step is performed
to compress what is otherwise a very large daily data set (e.g., for 36
reporting RNGs, there are 86,400 seconds per day 336 RNGs 5
3,110,400 per second trials reported, vs. 288 5-minute periods per day 3
36 RNGs 510,368 data elements per day). T
5
is chi-square distributed
with N
5
df.
7) Sum 72 contiguous T
5
values from Step 6; do the same for the N
5
values.
Call these summed values W
T1
and W
N1
. Then shift right by 1, create
another sum of 72 T
5
values, call these W
T2
and W
N2
, and so on. This
procedure creates a sliding window (the equivalent of 6 hours of real-
time), where the W
T
values are chi-square distributed with W
N
df. A total
of 288 272 5216 sliding windows are created to cover each days data.
8) Calculate a zscore (standard normal deviate) for each sliding window in
Step 7 as z5
ffiffiffiffiffiffiffiffi
2WT
p2
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
2WN1
p(Guilford & Fruchter, 1973, p. 517),
where W
T
is the chi-square value and W
N
is the degrees of freedom.
Variance Results
To demonstrate that over long periods of time the composite RNG variance is
well-behaved, Figure 1 shows the distribution of zscores for each 5-minute
segment (i.e., the T
5
and N
5
values formed in Step 6 above) for all GCP random
data generated between January 1, 2001, and November 30, 2001. We expect to
see a normal, bell-shaped curve with mean approximately 0 and standard
deviation approximately 1, and this is what we observe.
To examine slower fluctuations in the time-varying RNG output variance, and
to consolidate the data into time lengths more appropriate to the way in which
humans tend to respond to important news events (i.e., in terms of hours rather
Fig. 1. Distribution of zscores associated with 5-minute summaries across all RNGs from January
1, 2001, through November 30, 2001.
Exploring Relationships 537
than minutes), the data are smoothed with a 6-hour sliding window, as described
in Step 8 above. Figure 2 illustrates the effects of this smoothing for data
collected between June 16, 2001, and September 20, 2001. This curve may be
thought of as (roughly) a visualization of the ‘‘ringing’’ of our bell.
The ordinate in Figure 2 is in terms of zscores. Values between z522
and 12 are basically noise, but values outside this range are statistically
interesting. In particular, in Figure 2 notice that something unusual happened
one day in September. On that day the curve deviated beyond z,23 and
z.13. Figure 3 shows this anomaly in more detail. It happens that this curve
peaks more than an hour before a jet hit World Trade Tower 1 in New York City
at 8:46 AM EDT, September 11, 2001, and the curve drops to its lowest point
around 2:30 PM, roughly 8 hours later.
3
A 6.5 (or greater) drop in zscores within
an 8-hour period, as observed on September 11, is unique throughout the year
2001. In metaphorical terms, our bell rang more loudly on this day than any
other day in 2001.
Intercorrelation Analysis
The GCP network of RNGs is analogous to a set of buoys that we scatter
across an ocean to detect a tsunami, a colossal singular wave. To continue our
bell motif, lets say we attach a little bell to each bouy, and we use a radio to
send the sound of each bell to a central monitoring location.
Because buoys are tossed about by local currents and winds, if we listen to
their collective sounds, most of the time we will hear nothing but random
tinklings. However, on rare occasions the bouys will sing out as one great chord.
Fig. 2. zScores associated with 6-hour sliding windows, as described in Steps 7 and 8 above, for
RNG data collected between June 16, 2001 (noted as ‘‘616’’ on the x-axis) and September
20, 2001. This 3-month time-span was used to place the September 11 results into context.
538 D. Radin
During such times we have an anomalously positive correlation among all the
bouys, and we have good reason to believe that a tsunami has occurred.
In a similar fashion, I examined all correlations among all possible pairs
of GCP RNGs to see how they behaved on a daily basis over the year 2001,
from January 1, 2001, through December 31, 2001. My expectation was that
September 11, 2001, might be the GCP equivalent of a tsunami given the
unprecedented degree of world-wide attention precipitated by the events of
that day.
Procedure
1. For each RNG, determine z-scores as z5(x2100)/
ffiffiffiffiffi
50
pfor each trial,
where xis the per-second RNG trial data. The very small percentage of
cases in the GCP database with known RNG data problems were, of
course, excluded from this step.
2. Create a z-squared value per RNG per second.
3. For each RNG, sum 300 contiguous z-squares to create a single, 5-minute
consolidation of the per-second trial, and repeat this for all 288 non-
overlapping 5-minute periods per day. As in the initial variance analysis,
call this sum of z-squares T
5
and the associated degrees of freedom N
5
.
Note that this step differs from the initial variance analysis because these
288 T
5
and N
5
values are created for each RNG separately.
4. Smooth these 5-minute segments, per RNG, using the equivalent of a
6-hour sliding window.
5. Calculate a Pearson product moment correlation rbetween all possible
pairs of smoothed curves, among all RNGs, per day; e.g., among 36 RNGs
there are 630 possible pairs.
6. Normalize each resulting rfrom Step 5 using a Fisher ztransform, then
Fig. 3. Smoothed z-scores across 36 RNGs running from 8:00 PM September 10, 2001, to 8:00 PM
September 11, 2001. No other day in the year 2001 showed as large a drop in zscores as
observed on this day. The x-axis is in hours, Eastern Daylight Time.
Exploring Relationships 539
determine the daily mean and standard deviation of these transformed
rvalues.
7. Use a Student t-test to compare each days daily mean normalized
ragainst the null hypothesis of r
0
50.
Intercorrelation Results
Figure 4 shows the daily mean Fisher zscores (i.e., daily intercorrelation
values) for each day between December 1, 2000, and December 31, 2001. Figure
5 shows the odds against chance associated with t-tests of the daily values. The
peak daily value occurred on September 11, 2001. This suggests that our ‘‘bell’’
rang loudest on this day because of the collective simultaneous bell tones issuing
from all of our RNGs around the world.
One question that may arise when examining these results is whether the large
intercorrelation value observed on September 11 may have been due to unusual
environmental artifacts, such as increased cell-phone usage, which affected
some RNGs. If this were the case, then we might expect to see a few very high
intercorrelations on that day for RNGs located in say, North American cities, but
most of the other intercorrelations, say for RNGs located in the South Pacific,
Australia or Asia, would be near chance. If this were the case, then we could
predict that the standard deviation of the RNG intercorrelation values on
September 11 would be inflated. However, Figure 6 shows that this stand-
ard deviation was unremarkable as compared to all other days; thus, from
this perspective there is no compelling reason to believe that the large
Fig. 4. Daily average RNG intercorrelations. The peak value is September 11, 2001.
540 D. Radin
intercorrelation observed on September 11 was due to localized environmental
artifacts.
This finding is supported by Figure 7, which shows the histogram of all RNG
intercorrelations on all days (the bell-shaped curve centered around 0) as
compared to the histogram of intercorrelations observed on September 11, 2001
(the jagged line). The environmental artifact hypothesis predicts that the
distribution of intercorrelations for September 11 would be skewed by a few
large high correlations among some neighboring RNGs. Instead, the histogram
shows what appears to be a normal distribution that is shifted to the right. A
t-test of the mean difference between these two distributions results in t53.714,
p50.0001 (one-tailed). This implies that all of the RNGs were ‘‘ringing’’ in
unison a bit more than usual, rather than just a few RNGs ringing in
exceptionally close synchrony.
One might argue that these results depend on a fortuitous selection of a 6-hour
smoothing window (Step 4 in the analytical procedure). To address this
possibility, I varied the window smoothing length from 5 minutes to 12 hours,
then determined t-scores of the difference between the Fisher zintercorrelation
means for September 11 vs. the grand mean for all other days. Figure 8 shows
the results. The value z53.7, associated with the difference between the two
distributions shown in Figure 7, appears on this graph at the window size of 6
hours. The analysis indicates that the optimal window length is actually about 8
hours rather than the 6 hours I employed, but more importantly it shows that all
window lengths greater than 10 minutes resulted in significant differences. This
suggests that the significant intercorrelation observed on September 11, 2001,
was not due to a fortuitous selection of window length.
Fig. 5. One-tailed odds against chance for values observed in Figure 4.
Exploring Relationships 541
News Analysis Method
Given the interesting exploratory results associated with September 11, 2001,
the next question I addressed was whether the GCP hypothesis would generalize
to less dramatic days. To investigate this question, I examined how the RNGs
behaved on 25 single-day events listed in the GCP event registry (multi-day
events were excluded from this analysis), from December 1, 2000, through
December 31, 2001. The GCP hypothesis predicts that the average daily
intercorrelations for these days, as compared to all other days, would be
significantly larger. A t-test supported the prediction, p 50.016 (one-tail),
and this difference remained significant after excluding September 11, 2001
(p 50.024).
While this result points in the right direction, many of the events entered into
the GCP registry were there because someone guessed that a given event might
be associated with a change in randomness in the RNGs. While such guesses
were valid because they were made in advance of examining the GCP data, one
could argue that this opportunistic method of registering events overlooked
many other events that also attracted mass attention, and more importantly it
provokes the criticism that the method of selecting newsworthy events was too
subjective.
Thus, to form an objective measure of ‘‘newsworthy events,’’ I took all news
events listed in the ‘‘Year in Review’’ month-by-month feature on the InfoPlease
Web site, www.infoplease.com, for the one year period from January 1, 2001,
through December 31, 2001. This Web site lists headline news in five
categories: world news, US national news, and a combined business, science and
society category. InfoPlease is affiliated with ESPN, Time, and the Reuters news
Fig. 6. Standard deviations for daily average Fisher zintercorrelations.
542 D. Radin
service; thus, the information on the site is assumed to be reasonably accurate.
Of greater importance, the news items were selected by the InfoPlease editors
completely independently of the GCP. This Web site was selected over other
potential online news sources, such as CNN, because it provides a comprehen-
sive day-by-day list of news events, whereas most other sites list important news
stories, such as ‘‘the economy,’’ without providing day-to-day historical details.
For the 1-year test period, a total of 394 news events were listed; these took
place on 250 days. The GCP hypothesis predicts that these 250 days would have
a larger mean intercorrelation value than the remaining 115 non-newsworthy
days. A t-test confirmed the prediction, p 50.011, one-tailed.
A still more generalized way of examining the GCP hypothesis is to see
whether the ‘‘amount’’ of daily news would be positively correlated with the
daily RNG intercorrelation means. To test this idea, I observed that in the
InfoPlease list of events, the minimum number of news events occurring on
a single day was 0, and the maximum was 5. Each of those events was
accompanied by a text description; the number of characters in those
descriptions summed over all events per day ranged from 72 to 1,193. I used
these text counts as indicators of the amount of news per day in the sense that
many news events on the same day would lead to larger values. I also explored
using the number of events per day as a simpler news metric (the correlation
between the total number of characters per day and the total number of events
per day was r50.90, so I used the text count value as the primary metric
because it provided a more continuous variable to work with).
News Analysis Result
Figure 9 shows the correlation between the daily news metric and the daily
mean intercorrelations. The correlation is small, but as predicted it was
Fig. 7. Histogram for all Fisher zintercorrelations from December 2000 through December 2001
(the smooth, bell-shaped curve), and the intercorrelations observed on September 11, 2001.
Exploring Relationships 543
significantly positive: r50.16, t(363 df) 53.08, p 50.001, one-tailed. If
September 11 is removed from consideration: r50.15, t(362 df) 52.88, p 5
0.002, one-tailed. And if all of the non-news days are removed (these are seen in
Figure 9 as a column of points at 0 on the x-axis), the correlation remains
significant: r50.11, t(248 df) 51.76, p 50.040, one-tailed. A Kendall tau
nonparametric correlation between the number of listed news events per day vs.
the daily RNG intercorrelation value was also significant: r50.062, n 5365,
p50.037, one-tailed.
Discussion
As mentioned above, one mundane explanation for the present results is that
world events that captured mass human attention were associated with unusual
surges of electrical power and use of telecommunications equipment, and this in
turn might have created unusual environmental conditions that influenced the
RNGs. While environmentally-induced artifacts are conceivable, there are four
main arguments against this explanation: (1) in the case of September 11, the
cross-RNG variance peaked over an hour before the terrorist events began to
unfold, (2) the RNG intercorrelations reflected common changes among RNGs
located around the world, (3) the RNGs are powered by voltage-regulated
computer power supplies, and many PCs are further isolated from line power
through surge suppressors and battery-powered, uninterruptible power supplies,
and (4) the RNGs are designed to exclude first-order biases (i.e., drifts of the
mean) through the use of XOR logic.
Fig. 8. Effect of window size length on differences between the distribution of all daily
intercorrelation values vs. the distribution for September 11, in terms of a one-tailed
z-score.
544 D. Radin
These items argue against an artifactual explanation, but we can indirectly test
the effects of electromagnetic interference on the RNGs by examining their
outputs according to local clock time. That is, if the electromagnetic
environment influenced the RNG circuits, then we would expect to see
differences in RNG behavior between night and day. During the day, human use
of electronic devices peaks, as does wide-spectrum electromagnetic noise,
electric field strength, non-ionizing radiation, etc. During the night, all of these
effects decline.
Figure 10 shows the z-score equivalent for variance across all RNGs,
consolidated in 0.1-hour bins according to the local time of each RNG, over the
entire month of September 2001. This graph summarizes 89.6 million 200-bit
samples from all RNGs reporting in September 2001, for a total of 17.9 billion
random bits. This provides enormous statistical power to identify diurnal
influences, but no day-night differences or trends are observed: between 8:00 PM
and 8:00 AM (night) and 8:00 AM and 8:00 PM (day), z(difference) 50.53, p 5
0.30, one-tailed. This provides no support for an electromagnetic artifact hypo-
thesis.
Besides possible environmental artifacts and a global mind-matter interaction
effect, what else might account for the observed results? One possibility is that
these results might be due to chance. Another is that the results are due to
a fortuitous choice of analysis methods. Follow-up tests with new data will help
evaluate the viability of these possibilities.
Conclusion
Throughout history, philosophers have debated the perplexing, dualistic
nature of subjective versus objective. In the 20th century, quantum theorists
Fig. 9. Correlation between daily news metric and daily RNG intercorrelation values, p 50.001,
one-tailed. September 11, 2001, is associated with a news metric value of 398 in this graph.
Exploring Relationships 545
found themselves forced to seriously reconsider classical assumptions about
observer vs. observed, and about mind vs. matter (Jahn, 1981; Jahn & Dunne,
1987; Stapp, 1999; Wilber, 1984). In the latter half of the 20th century,
investigators developed increasingly rigorous methods for explicitly testing
postulated mind-matter interactions (Radin & Nelson, 1989, in press). And as
the 21st century begins, it appears that a cautious answer to the question used to
taunt Bertrand Russell may be, ‘‘Yes, mind does matter.’’ As for the observations
discussed in this paper, whether they turn out to be a fluke due to the uncertainties
of exploratory data analysis or something more interesting will be resolved by
formalizing these analyses and testing them in future GCP data.
In sum, these analyses explored a new twist on the enduring riddle, ‘‘For
whom does the bell toll?’’ The answer according to this analysis resonates with
John Donnes words in the 16th century: ‘‘No man is an island. The bell tolls for
thee.’’
Notes
1
See the Web site http://noosphere.princeton.edu and Nelson (2001) for further
details.
2
More precisely, a normal distribution that approximates the underlying
binomial distribution.
3
There is no easy answer for why the peak in this curve occurred before the
terrorist attacks; the observable fact is that it did.
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Exploring Relationships 547
... [87] Dubbed experiments in "field consciousness," these studies were devised as a way to test the assumption that if mind and matter were intimately correlated in some way, then during periods when the attention of many minds became coherent, then aspects of the physical environment might reflect that coherence by also displaying coherent behavior. Many small-scale studies were conducted during meditation gatherings, choral groups, theatrical presentations, and so on; [88][89][90][91] most showed the predicted effects. ...
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We propose a non-substance dualism theory, following Heisenberg: The world consists of both ontologically real possibilities that do not obey Aristotle's Law of the Excluded Middle, and ontologically real Actuals that do o0bey the Law of the Excluded Middle. This quantum approach solves five issues in quantum mechanics and numerous puzzles about the mind-brain relationship. It raises the possibility that some aspects of mind are non-local, and that mind plays an active role in the physical world. We present supporting evidence.
... This effect is related to macroscopic entanglement (ME) (Palomaki et al., 2013), (Sperling and Walmsley, 2017), (Ockeloen-Korppi et al., 2018), (Vedral, 2008) and can be considered from several points of view: 1) as the ability to transmit signals between remote macro-systems; 2) to impose a nonlocal impact on a certain object; 3) to monitor remote objects. Most of technical papers are devoted to 1) and 2), in the area of distant monitoring it needs to mention early works (Russell, 1997), Soviet and US research (Ochatrin et al., 1997), (Akimov et al., 2000), (Dunne et al., 1988), and teams operating with RNG devices (Hirukawa and Ishikawa, 2004), (Radin, 2002), (Nelson et al., 1995); from the last 20 years -the works (Shkatov, 2010), (Kravchenko and Kalaschenko, 1994), (Gorbatych et al., 2009), (Schmieke, 2015), companies 'InfoScan' and 'GeoScan Systems' (Glowatzki and Haeder, 2015). Operatorbased phenomena, such as ESP (Hansel, 1969), (Swann, 1987) or quantum consciousness (Persinger and Lavallee, 2010) are not considered here. ...
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This study, conducted by the Dr. Edgar Mitchell Foundation for Research into Extraterrestrial and Extraordinary Experiences (FREE), represents the first comprehensive investigation on individuals (N = 3,256) who have reported various forms of contact experience (CE) with a non-human intelligent being (NHI) associated with or without an unidentified aerial phenomenon (UAP). Our research methodology utilized two comprehensive quantitative surveys totaling 554 questions administered to subjects with reported non-hypnotic memory recall of their CE. This survey addressed a diverse range of physical, psychological, perceptual, and paranormal aspects of reported non-hypnotic-based recall of both physical and/or non-physical interactions with an NHI. The results revealed complex reported CEs that involve both physical and non-physical events (psychological outcomes, non-ordinary states of consciousness, and paranormal experiences). What may be the most signif cant aspect of the interim results is that approximately 70% (N = 2,279) of the study population claimed that their CE changed their life in a "positive way." In contrast, only 15-20% reported a "negative" impact from their CE. Further, the majority of subjects did not report events typically associated with the traditionally held beliefs regarding the "alien-abduction" phenomena. That is, the results suggest that the reported CE with an NHI is largely non-physical and can occur via telepathy, during an out-of-body experience, being floated into a "matrix-like" reality, as well as through physical interaction on board a craft. Consequently, the results suggest that a non-physical ("contactee") CE is distinctly different from a physical ("abduction") CE and should be studied as separate but interrelated anomalous events. In fact, the CE associated with a UAP is not the predominant form of CE, and sighting a UAP is not necessarily associated with a CE. Consequently, future studies should not focus exclusively on the analysis of UAP sightings and traces alone which, based on decades of research, have not advanced our understanding of the possible force that governs and regulates this complex phenomenon. This is an important consideration since the FREE study dispels the notion that contact with NHIs must always entail either a physical abduction or a landed craft with beings interacting with humans. This study may serve as a needed foundation for researchers to build upon for validation purposes to better understand a unique and diverse range of reported physical and non-physical type CEs with an NHI associated with or without a UAP. © 2018 Society for Scientific Exploration. All rights reserved.
... Going back to the data from September 11th, the order appearing in the randomness of the RNGs was detected 4 hours and peaked 2 hours before the first plane hit the first tower (Radin, 2002;. This means that the coherence in the human consciousness field all around the world occurred before people became consciously aware of the event. ...
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In Theory U, Otto Scharmer suggests that by working at the bottom of the U we can align with a positive future, which can then manifest through us. It requires our transcending our individual perspectives and analytic approaches. Instead, we access the implicit, intuitive wisdom of the larger Consciousness Field. This chapter examines two issues unaddressed by Scharmer, suggesting first that there is evidence that such a consciousness field exists through which we can access the emergent future and, secondly, that there are innovative practices that help us experience and function at the bottom of the U, in time on a reliable basis.
... The notion that intuitive perception is purely a function of the unconscious mind accessing forgotten prior experience has been challenged by several recent studies. Using rigorous experimental protocols and electrophysiological instrumentation, these studies have shown that the body often responds to a future emotionally arousing stimulus four to seven seconds prior to experiencing the stimulus (La Pira & Gillin 2004, Radin, 1997Bierman, 2000;Radin, 2002;Spottiswoode and May, 2003). ...
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This paper reports the results of an empirical study of intuition. The study includes the testing a new experimental protocol to measure the psychophysiological basis of entrepreneurial intuition—that part of entrepreneurial decision and action that is not based on reason or memory. A multi-methods approach incorporating electrophysiological measures was used to investigate intuition in a sample of repeat entrepreneurs. The results of the Cognitive Style Instrument (CSI) and interviews showed a propensity for entrepreneurs to use their intuition. The electro-physiological results were promising: the mean pattern of recordings for all subjects show that informational input was received 6 to 7 seconds before the outcome of the investment choice was known. Also random permutation analysis of individual recordings identified five instances in which the physiological measures had significant or marginally significant predictive power in discriminating future win/loss outcomes. Overall, the physiological measures were able to detect intuitive perception of a future outcome in four of the eight entrepreneurs.
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Purna - The Fullness Coherence and Synchronicity - How we are connected with each other and with the whole History of synchronicity research: C G Jung and W Pauli Synchronicity and spontaneous healing in psychotherapy, case reports Quantum mechanics and consciousness - field theories Coherence measurement with the Random Number Generator RNG Philosophy of "zeros" and "ones" - Sunya in the Vedas and in Buddhism RNG Measurements: A collection from reality
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Purna - Die Fülle - Kohärenz und Synchronizität - Wie wir miteinander und mit dem Ganzen verbunden sind- Geschichte der Synchronizitätsforschung: C G Jung und W Pauli Synchronizität und Spontanheilung in der Psychotherapie, Fallberichte Quantenmechanik und Bewusstsein - Feldtheorien Kohärenzmessung mit dem Random Number Generator RNG Philosophie der "Nullen" und "Einsen" - Sunya in den Veden und im Buddhismus RNG-Messungen: Eine Sammlung aus der Realität Purna - The Fullness Coherence and Synchronicity - How we are connected with each other and with the whole History of synchronicity research: C G Jung and W Pauli Synchronicity and spontaneous healing in psychotherapy, case reports Quantum mechanics and consciousness - field theories Coherence measurement with the Random Number Generator RNG Philosophy of "zeros" and "ones" - Sunya in the Vedas and in Buddhism RNG Measurements: A collection from reality
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Introduction Previously reported experiments suggest that aspects of the physical environment, in particular measures of negentropy (i.e., order) associated with the statistical outputs of truly random number generators, may be affected during periods of focused mental attention. The present study was designed to conceptually replicate those reports during energy medicine sessions. Method A custom-built “quantum noise generator” (QNG) was used to continuously record and digitize (at 1 KHz) 16 independent channels of random samples (i.e., noise) produced by electron tunneling and avalanche effects in Zener diodes. One metric was developed to quantify temporal dependencies in the noise samples aggregated across the 16 channels, and a second metric was formed that measured spatial dependencies among the 16 channels. The two metrics were combined into a single “spacetime” variable used to measure fluctuations in entropy during 110 half-hour energy medicine sessions. As a control, the same measure was examined in data recorded eight hours after each energy medicine session took place, when no one was in the laboratory. Results QNG data recorded during the half-hour sessions showed significant deviations from chance expectation, with a peak deviation observed at 24 minutes into the half-hour (z = 4.24, p < 0.00003, two-tail), and with deviations associated with p < 0.05 from 20 to 29 min, after correction for multiple comparisons. By comparison, data recorded eight hours after each session showed uniformly null results. This outcome is consistent with previously reported studies, suggesting that during periods of focused attention negentropic deviations emerge in random physical systems. Counterarguments to this interpretation are discussed, as well as recommendations for future studies.
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The Global Consciousness Project (GCP) is a cooperative, international venture involving more than 2 dozen researchers interested in anomalies associated with consciousness. A correlation is predicted between characteristics of data from a world-spanning network of random event generators (REGs) and specified "global events" that are expected to create an unusual coherence of interest and attention. To test the prediction, special-purpose software collects data at host sites around the world continuously and sends it over the Internet to a dedicated server running software to archive and process the data. Broadly engaging global events are identified using relatively objective criteria such as intensity and depth of media coverage. The primary analyses address the distribution of deviations of the mean of the REG output during the identified events. Over the first 16 months of continuous running, the network grew to include 28 active "eggs" (as the remote REG devices are called), with host sites in Europe, the United States, India, New Zealand, Fiji, Brazil, and Indonesia. A total of 43 events had been formally specified as of January 2000. The overall cumulative chi-square for all events was 7290.6 on 6920 degrees of freedom, with an associated probability of .00096. These results indicate a small but consistent excess of deviation corresponding to the predictions.
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Portable random event generators with software to record and index continuous sequences of binary data in field situations are found to produce anomalous outputs when deployed in various group environments. These “FieldREG” systems have been operated under formal protocols in ten separate venues, all of which subdivide naturally into temporal segments, such as sessions, presentations, or days. The most extreme data segments from each of the ten applications, after appropriate correction for multiple sampling, compound to a collective probability against chance expectation of 2 × 10−4. Interpretation remains speculative at this point, but logbook notes and anecdotal reports from participants suggest that high degrees of attention, intellectual cohesiveness, shared emotion, or other coherent qualities of the groups tend to correlate with the statistically unusual deviations from theoretical expectation in the FieldREG sequences. If sustained over more extensive experiments, such effects could add credence to the concept of a consciousness “field” as an agency for creating order in random physical processes.
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During the period from May 11, 1995 to May 21, 1995 disturbing events, like apparent anomalous movements of objects were reported at the home of a family in Druten (The Netherlands)1. A few days after the phenomena started, a hardware random number generator connected to a computer was installed on the premises. As measures for the non-randomness of the RNG, two coherence variables, one representing first order non randomness and one representing 8-bit patterned forms of non randomness, were used. Comparison of epochs during which disturbances occurred and control epochs showed a decrease in first order RNG coherence (sum of z2 scores was: 78.4 with df=107; p < 0.05 two tailed; in the control periods sum of z 2 was 4724 with df= 4771, n.s.) while the more general RNG coherence measure did not show an effect - On Wednesday May 24, 1995, when the field RNG was still running at the home, the major European sports event, the European soccer cup final, was played between a Dutch and an Italian team. During the 90 minutes of the match, the RNG showed a significant increase in first order non-randomness (sum of z2 scores = 343.6 , df=297, p < 0.05 one tailed) while during the preceding control period the RNG showed its normal behavior (sum of z2 scores = 284, df=297,n.s.). The global coherence measure testing all possible 8 bit patterns decreased non significantly during the match. - Two minutes before the end of the match, the only goal was scored by the Dutch team. Comparison of the 10 minutes before the goal and the 4 minutes after the goal suggests that after the goal the RNG shows a decrease in global coherence (mean chi2 before = 258.4, mean chi2 after = 245.2, t = -1.94, df = 54, p
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The Global Consciousness Project (GCP) is an international collaboration of researchers studying interactions of consciousness with the environment. The GCP maintains a network of random event generators (REGs) located in over 40 host sites around the world. These devices generate random data continuously and send it for archiving to a dedicated server in Princeton, New Jersey. The data are analyzed to determine whether the fundamentally unpredictable array of values contains periods of detectable non-random structure that may be correlated with global events. In this paper we examine the data from September 11, 2001, for evidence of an anomalous interaction driving the REGs to non-random behavior. Two formal analyses were made, testing hypotheses based on standardized procedures for making predictions and performing a statistical evaluation. A number of post hoc and exploratory studies, including work by five independent analysts, provide additional perspective and examine the context of several days before and after the major events. The results show that a substantial increase in structure was correlated with the most intense and widely shared periods of emotional reactions to the events. Further analysis indicates that the non-random behavior cannot be attributed to ordinary sources such as electrical disturbances or high levels of mobile phone use. The evidence suggests that the anomalous structure is somehow related to the unusually coherent focus of human attention on these extraordinary events.
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Speculations about the role of consciousness in physical systems are frequently observed in the literature concerned with the interpretation of quantum mechanics. While only three experimental investigations can be found on this topic in physics journals, more than 800 relevant experiments have been reported in the literature of parapsychology. A well-defined body of empirical evidence from this domain was reviewed using meta-analytic techniques to assess methodological quality and overall effect size. Results showed effects conforming to chance expectation in control conditions and unequivocal non-chance effects in experimental conditions. This quantitative literature review agrees with the findings of two earlier reviews, suggesting the existence of some form of consciousness-related anomaly in random physical systems.
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Edited proceedings of an interdisciplinary symposium on consciousness held at the University of Cambridge in January 1978. The purpose of the Cambridge conference was to encourage distinguished scientists to express their views on the relationship of conscious experience to the physical world. The book is available in a number of formats at https://www.repository.cam.ac.uk/handle/1810/245189.
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Recent works [1], [2], [3], [4] have raised the possibility that a quantum formalism can describe both unconscious mechanical brain processes connected with the complex patterns of neuronal activity as well as the conscious activity of the brain. A Hilbert structure has been assumed in order to describe an evolution equation like the Schroedinger equation.
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Episodes of Focused Group Energy (FGE) occur when two or more people are focused on some objective and become coherently attuned to that focus. Most people have experienced this phenomenon at one time or an- other when everybody was ª on the same wavelength.º Anecdotal episodes of this phenomenon have been reported in business meetings, in sporting events, in concerts and in prayer and healing. Many people are quite sensitive to this phenomenon; and when people are informed about it, they become more sen- sitive to it. Focused Group Energy episodes cannot be scheduled. However, they are more likely to occur in situations where intense group focus is required. We have conducted a series of experiments to measure FGE episodes physically (objective measurements) as well as having sensitive participants simultane- ously recording the episodes (subjective measurements). The meetings were chosen because of previous reports of intense FGE activities by sensitive par- ticipants. A field deployable Princeton Engineering Anomalies Research (PEAR) Random Number Generator (FieldRNG) was used to monitor the space in which these meetings took place before, during, and after the episodes. The FieldRNG is used to detect if the random number sequence is entrained by the FGE episode to behave non-randomly. We have conducted eleven such experiments to date with consistent, repeat- able results. After FGE episodes have been reported and recorded by sensitive participants, the FieldRNG results were compared after the fact and consis- tently were greater than two and sometimes three standard deviations from the mean for the whole time period of the episode (some lasted for hours). Other time periods where no FGE occurs are also examined to determine if there are false positive excursions in the data. A true positive case is counted only if the FieldRNG results are over the two sigma level for the duration of the episode for both the objective measurement and simultaneous subjective reports.