Optimal Span - AMAZING Intersection of Hierarchy, Information, and Complexity Theories

I presented "Optimal Span - The AMAZING Intersection of Hierarchy Theory, Information Theory, and Complexity Theory" to The Villages Science and Technology Club today.

You may download my PowerPoint Show that should run on any Windows PC here:
https://sites.google.com/site/iraclass/my-forms/SciTechOptimalSpan10Feb2014.pps?attredirects=0&d=1

I began the presentation with Kurt Vonnegut's great poem that tells us about Tigers, Birds, and Humans and what they are compelled, by their Nature, to do. Of course: "MAN got to sit and wonder 'why, why, why?'" and then, after some study and contemplation, "MAN got to tell himself he understand!"

This Topic and my PowerPoint Show are based on my PhD dissertation: "Hierarchy Theory - Some Common Properties of Competitively-Selected Systems", System Science Department, Binghamton University, NY, 1996. If you wish to pursue further research in this area please contact me at ira@techie.com. A few copies of my dissertation are available.


The material that follows contains more detail than the PowerPoint Show.


Most complex structures are compositional or control hierarchies. An example of a compositional hierarchy is written language. A word is composed of characters. A simple sentence is composed of words. A paragraph is composed of simple sentences, and so on. An example of a control hierarchy is a management structure, where a manager controls a number of foremen or team leaders, and they, in turn, control a number of workers.


Optimal Span Hypothesis:

Optimal Span is about the same, between five and nine, for virtually all complex structures that have been competitively selected.




That includes the products of Natural Selection (Darwinian evolution) and the products of Artificial Selection (Human inventions that competed for acceptance by human society).
The hypothesis is supported by empirical data from varied domains and a derivation from Shannon’s Information Theory and Smith and Morowitz’s concept of intricacy.

What is a Hierarchy?

Hierarchy (fromGreek:ἱερός — hieros, ‘sacred’, and ἄρχω — arkho, ‘rule’) originally denoted the holy rule ranking of nine orders of angels, from God to Seraphims to Cherubims and so ondown to the Archangels and plain old Angels at the lowest level. Kind of like the organization of God’s Corporation!

The seminal book on this topic is Hierarchy Theory: The Challenge of Complex Systems[ Pattee, 1973 ]. This book includes a chapter by Nobel laureate Herbert A. Simon on “The Organization of Complex Systems”. Other chapters: James Bonner “Hierarchical Control Programs in Biological Development”; Howard H. Pattee “The Physical Basis and Origin of Hierarchical Control” and “Postscript: Unsolved Problems and Potential Applications of Hierarchy Theories”; Richard Levins “The Limits of Complexity”, and Clifford Grobstein “Hierarchical Order and Neogenesis”.
A more recent book, Complexity – The Emerging Science at the Edge of Order and Chaos, observes that the “hierarchical, building-block structure of things is as commonplace as air.” [ Waldrop, 1992 ]. Indeed, a bit of contemplation will reveal that nearly all complex structures are hierarchies.
There are two kinds of hierarchy. A few well-known examples will set the stage for more detailed examination of modern Hierarchy Theory:

Examples

1 -Management Structure (Control Hierarchy)

Workers at the lowest level are controlled by Team Leaders (or Foremen), teams are controlled by First-Level Managers who report to Second-Level managers and so on up to the Top Dog Executive. At each level, the Management Span of Control is the number of subordinates controlled by each superior.

2 -Software Package (Control Hierarchy)

Main Line computer program controls Units (or Modules, etc.) and the Units control Procedures that control Subroutines that control Lines of Code. At each level, the Span of Control is the number of lower-level software entities controlled by a higher-level entity.

3 – Written Language (Containment Hierarchy)

Characters at the lowest level are contained in Words. Words are contained in Simple Sentences. Simple Sentences in Paragraphs, and so on up to Sections, Chapters and the Entire Document. At each level, theSpan of Containment is the number of smaller entities contained by each larger.

4 – “Chinese boxes” (Containment Hierarchy)

A Large Box contains a number of Smaller Boxes which each contain Still Smaller Boxes down to the Smallest Box. At each level, the Span of Containment is the number of smaller entities contained by each larger.

Traversing a Hierarchy

Note that Examples 1 and 3 above were explained starting at the bottom of the hierarchy and traversing up to the top while Examples 2 and 4 were explained by starting at the top and traversing to the bottom.

Simple hierarchies of this type are called “tree structures” because you can traverse them entirely from the top or the bottom and cover all nodes and links between nodes.

"Folding” a “String”

A tree structure hierarchy can also be thought of an a one-dimensional “string” that is “folded” (or parsed) to create the tree structure. What does “folding” mean in this context?

As an amusing example, please imagine the Chief Executive of a Company at the head of a parade of all his or her employees. Behind the Chief Exec would be Senior Manager #1 followed by his or her First-Level Manager #1. Behind First-Level Manager #1 would be his or her employees. Behind the employees would be the First-level Manager #2 with his or her employees. After all the First-levels and their employees, Senior Manager #2 would join the parade with his or her First-Levels and their employees, and so on. If you took the long parade and called it a “string”, you could “fold” it at each group of employees, then again at each group of First-Level Managers, and again at the group of Senior Managers, and get the familiar management tree structure!

The above “parade” was described with the Chief Exec at the head of it, but you could just as well turn it around and have the lowest-level employees lead and the Chief Exec at the rear. When military hierarchies go to war, the lowest-level soldiers are usually at the front and the highest-level Generals well behind.

A more practical example is the text you are reading right now! It was transmitted over the Internet as a string of “bits” – “1″ and “0″ symbols. Each group of eight bits denotes a particular character. Some of the characters are the familiar numbers and upper and lower-case letters of our alphabet and others are special characters, such as the space that demarks a word (and is counted as a character that belongs to the word), punctuation characters such as a period or comma or question mark, and special control characters that denote things like new paragraph and so on.

You could say the string of 1′s and 0′s is folded every eight bits to form a Character. The string is folded again at each Space Character to form Words. Each group of Words is folded yet again at each comma or period symbol that denotes a Simple Sentence. Each group of Simple Sentences is again folded to make Paragraphs, and so on.

You could lay out a written document as a tree structure, similar to a Management hierarchy. The Characters would be at the bottom, the Words at the next level up, the Simple Sentences next, the Paragraphs next, and so on up to the whole Section, Chapter, and Book.

What is Optimal Span?

With all these different types of hierarchical structures, each with its own purpose and use, you might think there is no common property they share other than their hierarchical nature. You might expect a particular Span of Control that is best for Management Structures in Corporations and a significantly different Span of Containment that is best in Written Language.

If you expected the Optimal Span to be significantly different for each case, you would be wrong!
According to System Science research and Information Theory, there is a single equation that may be used to determine the most beneficial Span. Thatoptimum value maximizes the effectiveness of the resources. A Management Structure should have the Span of Control that makes the best use of the number of employees available. A Written Language Structure should have the Span of Containment that makes the best use of the number of characters (or bits in the case of the Internet) available, and so on.

The simple equation for Optimal Span derived by [ Glickstein, 1996 ] is:

S_o= 1 + De
(Where D is the degree of the nodes and e is the Natural Number 2.71828459)

In the examples above, where the hierarchical structure may be described as a single-dimensional folded string where each node has two closest neighbors, the degree of the nodes is, D = 2, so the equation reduces to:

S_o= 1 + De = 1 + 2 x 2.71828459 = 6.43659

“Take home message”: OPTIMAL SPAN, S_o = ~ 6.4

Also see Quantifying Brooks Mythical Man-Month (Knol) , [Glickstein, 2003 ] and [ Meijer, 2006 ] for the applicability of Optimal Span to Management Structures.

[Added 4 April 2013: The Meijer, 2006 link no longer works. His .pdf document is available at http://repository.tudelft.nl/assets/uuid:843020de-2248-468a-bf19-15b4447b5bce/dep_meijer_20061114.pdf ]

Examples of Competitively-Selected Optimal Span

Management Span of Control

Management experts have long recommended that Management Span of Control be in the range of five or six for employees whose work requires considerable interaction. Depending upon the level of interaction, experts recommend up to nine employees per department.This recommendation comes from experience with organizations with different Spans of Control. The most successful tend to have Spans in the recommended range, five to nine,an example of competitive-selection.

When the lowest level consists of service-type employees, whose interaction with each other is less complex, there may be a dozen or two or more in a department, but there will usually be one or more foremen or team leaders to reduce the effective Management Span of Control to the range five to nine.Corporate hierarchies usually haveabout the same range of first-level departments reporting to the next level up and so on.

Say you had a budget for 49 employees and had to organize them to make most effective use of your human resources. Which of the following seems most reasonable?

(A) you have ONE manager and 48 workers, which is a BROAD hierarchy. Management experts would say a Management Span of Control of 48 is way too much for anyone to handle!

(B) you have a third-level chief executive, three executive-level managers, each with three department managers, totaling THIRTEEN managers in a three-level management hierarchy and only 36 workers, which is a TALL hierarchy with an average Management Span of Control of only 3.3. Management experts would say this is way too inefficient with too many managers!

(C) you have a second-level manager and six department managers, totaling SEVEN managers and 42 workers in a MODERATE hierarchy with an average Management Span of Control of about 6.5. Management experts would say this is about right for most organizations where the workers have to interact with each other. Optimal Span theory supports this common-sense belief!

Human Span of Absolute Judgement

Evolution and Natural Selection have produced the human brain and nervous system and our senses of vision, hearing, and taste. It turns out that these senses are generally limited to five to nine gradations that can be reliably distinguished. It is also the case that we can remember about five to nine chunks of information at any one time. This is another example of competitive-selection, where, over the eons of evolutionary development, biological organisms competed and those that best fit the environment were selected to survive and reproduce.



George A Miller wrote a classic paper titled The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information [ Miller, 1956 ]. He showed that human senses of sight, hearing, and taste were generally limited to five to nine gradations that could be reliably distinguished. Miller’s paper begins as follows:



"My problem is that I have been persecuted by an integer [7 +/- 2]. For seven years this number has followed me around, has intruded in my most private data, and has assaulted me from the pages of our most public journals. This number assumes a variety of disguises, being sometimes a little larger and sometimes a little smaller than usual, but never changing so much as to be unrecognizable. The persistence with which this number plagues me is far more than a random accident. There is, to quote a famous senator, a design behind it, some pattern governing its appearances. Either there really is something unusual about the number or else I am suffering from delusions of persecution.Miller’s paper is well worth reading and is available on the Internet at this link [Miller, 1956]"

Glickstein’s Theory of Optimal Span

Miller’s number also pursued me (Ira Glickstein) until I caught it and showed, as part of my PhD research,[ Glickstein, 1996 ]that, based on empirical data from varied domains, the optimal span for virtually all hierarchical structures falls into Miller’s range, five to nine. Using Shannon’s information theory, I also showed that maximum intricacy is obtained when the Span for single-dimensional structures is S_o = 1 + 2e = 6.4 (where e is the natural number, 2.71828459). My “magical number” is not the integer 7, but 6.4, a more precise rendition of Miller’s number!

Hierarchy and Complexity

Howard H. Pattee, one of the early researchers in hierarchy theory, posed a serious challenge:

Is it possible to have a simple theory of very complex, evolving systems? Can we hope to find common, essential properties of hierarchical organizations that we can usefully apply to the design and management of our growing biological, social, and technological organizations? [Pattee, 1973]

Pattee was the Chairman of my PhD Committee and I took the challenge very seriously!

The hypothesis at the heart of my PhD dissertation is that the optimal span is about the same for virtually all complex structures that have been competitively selected. That includes the products of Natural Selection (Darwinian evolution) and the products of Artificial Selection (Human inventions that competed for acceptance by human society).

Weak Statement of Hypothesis

In  the “weak” statement of the hypothesis, it is scientifically plausable to believe that diverse structures tend to have spans in the range of five to nine, based on empirical data from six domains plus a computer simulation.

The domains are:

Human Cognition: Span of Absolute Judgement (one, two and three dimensions), Span of Immediate Memory, Categorical hierarchies and the fine structure of the brain. These all conform to the hypothesis.

Written Language: Pictographic, Logographic, Logo-Syllabic, Semi-alphabetic, and Alphabetic writing. Hierarchically-folded linear structures in written languages, including English, Chinese, and Japanese writing. These all conform to the hypothesis.

Organization and Management of Human Groups: Management span of control in business and industrial organizations, military, and church hierarchies. These all conform to the hypothesis.

Animal and Plant Organization and Structure: Primates, schooling fish, eusocial insects (bees, ants), plants. These all conform to the hypothesis.

Structure and Organization of Cells and Genes: Prokaryotic and eukaryotic cells, gene regulation hierarchies. These all conform to the hypothesis.

RNA and DNA: Structure of nucleic acids. These all conform to the hypothesis.

Computer Simulations: Hierarchical generation of initial conditions for Conway’s Game of Life. (Two-dimensional ). These all conform to the hypothesis.

Strong Statement of Hypothesis

Shannon’s information theory, andthe concept of intricacy of a graphical representation of a structure [ Smith and Morowitz, 1982 ] can be used to derive a formula for the optimal span of a hierarchical graph.

This work extended the single-dimensional span concepts of management theory and Miller’s “seven plus or minus two” concepts to a general equation for any number of dimensions. I derived an equation that yields Optimal Span for a structure with one-, two-, three- or any number of dimensions!

The equation for Span (optimal) is:

S_o= 1 + De

(Where D is the degree of the nodes and e is the Natural Number 2.71828459)

NOTE: For a one-dimensional structure, such as a management hierarchy or the span of absolute judgement for a single-dimensional visual, taste or sound, the degree of the nodes, D = 2 . This is because each node is a link in a one-dimensional chain or string and so each node has two closest neighbors.

For a two-dimensional structure, such as a 2D visual or the pitch and intensity of a sound or a mixture of salt and sugar, D = 4. Each node is a link in a 2D mesh and so each node has four closest neighbors.

For a 3D structure, D = 6 because each node is a link in a 3D egg crate and has six closest neighbors.

Some of the examples in Miller’s paper were 2D and 3D and his published data agreed with the results ofthe formula. The computer simulation was 2D and also conformed well to the hypothesis.

In normal usage, complexity and intricacy are sometimes used interchangeably. However, there is an important distinction between them according to [ Smith and Morowitz, 1982 ].

COMPLEXITY - Something is said to be complex if it has a lot of different parts, interacting in different ways. To completely describe a complex system you would have to completely describe each of the different types of parts and then describe the different ways they interact. Therefore, a measure of complexity is how long a description would be required for one person competent in that domain of knowledge to explain it to another.

INTRICACY - Something is said to be intricate if it has a lot of parts, but they may all be the same or very similar and they may interact in simple ways. To completely describe an intricate system you would only have to describe one or two or a few different parts and then describe the simple ways they interact. For example, a window screen is intricate but not at all complex. It consists of equally-spaced vertical and horizontal wires criss-crossing in a regular pattern in a frame where the spaces are small enough to exclude bugs down to some size. All you need to know is the material and diameter of the wires, the spacing betwen them, and the size of the window frame. Similarly, a field of grass is intricate but not complex.

If you think about it for a moment, it is clear that, given limited resources, they should be deployed in ways that minimize complexity to the extent possible, and maximize intricacy!

Using [ Smith and Morowitz, 1982 ] concepts of inticacy, it is possible to compute the theoretical efficiency and effectiveness of a hierarchical structure. If it had the Optimal Span, it is 100% efficient, meaning that it attains 100% of the theoretical intricacy given the resources used.If not, the percentage of efficiency can be computed. For example, a one-dimensional tree structure hierarchy is 100% efficient (maximum theoretical intricacy) with a Span of 6.4. For a Span of five, it is 94% efficient (94% of maximum theoretical intricacy).It is also 94% efficient with a Span of nine. For a Span of four or twelve, it is 80% efficient.

Ira Glickstein

A Practical View of Bayesian Inference

Bayes Theorem has practical applications. Use it to make real world decisions. [Updated 8 Sep 2013]

Bayes Theorem is not just an obscure artifact of the statistics of probability handed down to us from centuries ago. You can use it now to make decisions that will affect your financial well-being.

A relatively simple Excel-based tool helps you choose the right course of action in the face of uncertain probabilities and inexact test results. It is available for FREE.

[Presented to the Science-Technology Club, The Villages, FL, 9 September 2013. For a copy of my PowerPoint slide show, send an email to ira@techie.com.]

What can the Bayesian Inference Advisor Tool do for You?

I know you are probably not in the oil business (and neither am I), but the best way to understand an abstract concept is to go through a practical example. The example below has to do with oil exploration and drilling, but the Bayesian Inference Advisor can handle any problem where you know:

1) the probability of success if you take action without doing further testing,
2) the cost of further testing and the probability the test results will be reliable,
3) the cost of taking some action,
4) the financial benefit to you if the action is successful, and
5) the compensation you expect for taking the risk.

You can download the Bayesian Inference Advisor at:
https://sites.google.com/site/bigira/stuff-ira-knows/BayesianInferenceAdvisorV3.xls?attredirects=0&d=1

The Bayesian Inference Advisor will compute the most likely financial implications of your actions. What if you proceed without further testing? What if you get a positive test result and proceed? What if you get a negative test result and proceed? Several other examples in very different domains are included later in this posting, but for now, put on your hard hat and let us imagine we are in the oil business!

What is Time? Alan Alda's 2013 "Flame Challenge"

Time - the fourth dimension (2013 Flame Challenge) from Ira Glickstein on Vimeo.

My entry for Alan Alda's 2013 Flame Challenge was submitted last week. It is in the form of a short video  answering the deceptively simple question "What is Time?" (click above to view the video).

Alan Alda is on a mission to help youngsters become interested in science. In conjuction with the Center for Communicating Science at SUNY Stony Brook, he started the Flame Challenge in 2012 with the question "What is Flame?" They received some 800 entries.

I expect they will get even more this year with the question "What is Time?"

ABOUT MY ENTRY

I think I've come up with a unique way of viewing "Time - the fourth dimension".  Due to a strict limit on the length of the video, and the fact that it is aimed at 11-year old students, I have had to greatly simplify the material. This Blog posting includes additional material that will be useful to adult readers and science teachers who wish to know more about my way of viewing Time.

There are three big ideas here:

1. TIME is NOT a clock (any more than Space is a ruler or Heat is a thermometer), nor is it rotation of the Earth or motion or the order of events, etc.  
2. TIME is the fourth dimension, plain and simple. It appears different to us because the whole Universe is speeding along the Time axis at the speed of light.  
3. TIME slows down when we move in Space because nothing can move faster than the speed of light, so any motion in Space must take away from the speed in Time such that the vector sum of the Space and Time velocities exactly equals the speed of light.

WHAT TIME IS NOT

Time is not the tick, tick, tock of a click, click, clock, any more than Space is a ruler or Heat is  a thermometer!

 

Nor is Time the rotation of the Earth on its axis that gives us day and night divided into 24 hours. Nor is it the movement of the tilted Earth in orbit around the Sun that gives us the seasons, nor any other kind of motion. Nor is it the spontaneous decay of certain atoms that give radioactive materials a half-life. Nor is it simply the ordering of events.

WHAT TIME IS

Time, plain and simple, is the fourth dimension, very much like the first three dimensions of Space.

 

The Time dimension appears different to us because you and I and the whole Universe are hurtling along it at very nearly the speed of light as a consequence of the “Big Bang” expansion some 13.7 billion years ago, in which our Universe, along with the dimensions of Space and Time, originated.

Since Time itself originated with the "Big Bang" it may not be meaningful to even ask the question "What happened before the Big Bang?" In any case, we may never know what caused it.

 

The Universe originated as an incredibly energetic and dense point of Energy/Matter that suddenly expanded. During the initial moments of the expansion, it is not clear if there was anything like the sub-atomic and atomic particles of Matter or the radiation of Energy with which we are familiar today. However, when Matter and Energy, as we know it, formed, all particles with mass were expelled along the Time axis, or at very tiny angles with respect to that axis. You and I, along with everyone and everything else, are still moving along or near that dimension at very close to the speed of light, c, which is as fast as anything can go.

 

We do not notice our ultra-rapid travel along the Time dimension as motion because the whole Universe is moving along with us. Therefore, we notice only relative motion between ourselves and other people and between ourselves and other things.

 

For example, people on the equator are happily unaware that they are moving Eastward at about 1,000 miles per hour due to the rotation of the Earth on its axis. Unless you live in one of the polar regions, you are moving Eastward at hundreds of miles per hour. Even if you are on an airplane, travelling  "Westward" from New York to Chicago or Los Angeles at 500 miles per hour, your net velocity is Eastward, due to the rotation of the Earth! We are equally unaware that the whole Earth is speeding along at over 67,000 miles per hour on its orbit around the Sun!
 

WHY TIME CAN BE SLOWED A BIT
 

We live in four-dimensional SpaceTime where everything must move at the speed of light, c, either along the Time axis, along a Space axis, or in a combination of Time and Space at an angle, Θ, to the Time axis. If movement is totally aligned with the Time axis, Θ = 0 and we are said to be “at rest” in Space, and we move along the Time axis at the normal rate (c, about one foot per nanosecond).

 

If we are not "at rest" in Space, Θ > 0, and we move through SpaceTime in a combination of Space and Time such that the vector sum of our Space and Time velocities is exactly c. Since nothing can go faster than c, any movement in Space must slow down our movement in Time. This was recognized over 100 years ago by Lorentz, Minkowski, and Einstein, who use the terms "Dilation of Time" and "Contraction of Space". This is usually expressed in terms of the Lorentz factor:

where c is the velocity of light and v is the velocity of an object in Space.

As an engineer, I found that way of expressing relativistic effects of travel at significant fractions of the speed of light not to be "understandable" from my physical (and perhaps anal) point of view.

After knocking my head against the wall over an inordinate amount of Time, I finally realized that I could get an exactly equivalent Lorentz factor by considering the angle Θ, between the Time axis and the velocity vector of an object through SpaceTime.

[above image modified 12 April 2013]

It turns out that v (the velocity of the object in Space) divided by c is equal to the Sin Θ, and that 1/ϒ, the Lorenz factor, is equal to the Cos Θ.  

WHAT ARE DIMENSIONS?

 

This may sound like a simple question, and the answer is pretty simple, but, just to be sure we are all on the same page (see figure below):

 

0 - A POINT has ZERO dimensions

1 - Drag the point along the FIRST dimension ("x" of Space) and you get a LINE, that has ONE dimension.

2 - Drag the line along the SECOND dimension ("y" of Space) and you get a SQUARE (or rectangle) that has TWO dimensions.

3 - Drag the square along the THIRD dimenson ("z" of Space) and you get a CUBE (or rectangular solid) that has THREE dimensions.

4 - Drag the cube along the FOURTH dimension ("t" of Time) and you get a HYPER-CUBE (or hyper-rectangular solid) that has FOUR dimensions.



 

SUMMARY

When movement is a combination of Time and Space, and the velocity in Space is v, an object is moving through SpaceTime at an angle Θ, such that: v/c = SinΘ, and 1/ϒ (the Lorentz factor) = Cos Θ.

The figure below shows the situation for seven different values for the angle of travel through SpaceTime, from Θ = 0⁰ to Θ = 90⁰ .

Θ = 0⁰  [Sin Θ = 0.0000,  Cos Θ = 1.0000]   AT REST IN SPACE
For an object that is "at rest" in Space, Θ = 0⁰. Even when an object is not moving along the Space axis, it is moving along the Time axis. Since everything in SpaceTime must have a speed of c, an object "at rest" in Space must be moving at speed c in Time. Note that for this condition, v/c = 0 and the Lorentz factor ϒ = 1. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ.

Even the fastest rockets and satellites developed so far go only a tiny, tiny fraction of c. Therefore, for all practical purposes, the angle, Θ, is ≈ 0⁰ (approximately equal to ZERO degrees). For example, the Earth is travelling around the Sun at a speed of 67,000 miles per hour, faster than any rocket, but that is only 0.001 % of the speed of light. At 67,000 miles per hour, v/c =  0.00001 and  Θ = 0.0000017⁰.

Θ = 15⁰ [Sin Θ = 0.2588, Cos Θ = 0.9659]    MOVING 26% OF c IN SPACE
An object is moving through SpaceTime at an angle of Θ = 15⁰. It moves through Space at 26% of c and through Time at 97% of c. Note that for this condition, v/c = 0.2588 and the Lorentz factor ϒ = 0.9659. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ.

Θ = 30⁰ [Sin Θ = 0.5000, Cos Θ = 0.8660]   MOVING 50% OF c IN SPACE
An object is moving through SpaceTime at an angle of Θ = 30⁰. It moves through Space at 50% of c and through Time at 87% of c. Note that for this condition, v/c = 0.5000 and the Lorentz factor ϒ = 0.8660. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ.

Θ = 45⁰ [Sin Θ = 0.7071, Cos Θ = 0.7071] MOVING 71% OF c IN SPACE
An object is moving through SpaceTime at an angle of Θ =45⁰. It moves through Space at 71% of c and through Time at 71% of c. Note that for this condition, v/c = 0.7071 and the Lorentz factor ϒ = 0.7071. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ.

Θ = 60⁰ [Sin Θ = 0.8660, Cos Θ = 0.5000] MOVING 87% OF c IN SPACE
An object is moving through SpaceTime at an angle of Θ = 60⁰. It moves through Space at 87% of c and through Time at 50% of c. Note that for this condition, v/c = 0.8660 and the Lorentz factor ϒ = 0.5000. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ.

Θ = 75⁰ [Sin Θ = 0.9659, Cos Θ = 0.2558]   MOVING 97% OF c IN SPACE
An object is moving through SpaceTime at an angle of Θ = 75⁰. It moves through Space at 97% of c and through Time at 26% of c. Note that for this condition, v/c = 0.9659 and the Lorentz factor ϒ = 0.2558. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ.

Θ = 90⁰ [Sin Θ = 1.0000, Cos Θ = 0.0000]      TIME STANDS STILL 
Light (and other forms of electro-magnetic radiation) move through SpaceTime at an angle of Θ = 90⁰. Light moves through Space at 100% of c and, therefore, since nothing can go faster than c, Time stands still. Note that for this condition, v/c = 1.0000 and the Lorentz factor ϒ = 0.0000. Note also that, for this case Sin Θ is equal to v/c and Cos Θ is equal to 1/ϒ. Anything with mass cannot achieve this speed in Space because it would take an infinite amount of energy to get it up to this speed in Space.
 
[ADDED 11 March 2013] In response to some skepticism about my contention that the whole known Universe is speeding along the Time dimension at nearly the speed of light, I did more research and found support from Brian Greene, Professor of Physics and Mathematics at Columbia U, who has been featured on the PBS Nova series. He writes:

“Special relativity declares a similar law for all motion: the combined speed of any object’s motion through space and its motion through time is always precisely equal to the speed of light” [Excerpt From: Greene, Brian. “The Fabric of the Cosmos.” Vintage Books, 2007. See http://www.pbs.org/wgbh/nova/physics/fabric-of-cosmos.htm for his PBS series.]

I have provided more detail in the first comment below.

Ira Glickstein

Global Warming Debate

I participated in a Joint Presentation on Global Warming at the Science-Technology Club, The Villages, FL, on 08 September 2011. My friend Bob Miller was on the AFFIRMATIVE side, which maintains that Global Warming due to unprecedented use of fossil fuels DOES constitute a substantial, near-term danger to human civilization on Earth. I took the NEGATIVE side that it DOES NOT.




Our combined PowerPoint chart set is available for anyone to download at https://sites.google.com/site/bigira/climate-related-ppt/SciTechGWDebateUpload.pptx?attredirects=0&d=1. Please use SLIDE SHOW mode to view the presentation because some of the charts are animated.

As indicated in the second graphic above, the debate follows the traditional 1858 Lincoln and Douglas debate format. (The photos show Bob in his younger days and me before I grew my beard :^).

The main difference in the format is that an Audience Participation Question and Comment period has been added between the initial presentations by each side and the rebuttal presentations.

To keep this debate on track, and prevent it from degenerating into a pointless argument about whether the so-called "Greenhouse effect" is real (it is), whether the Earth has been warming over the past century (it has) and, whether humans have any role in that warming (we do), both participants have agreed to the stipulations listed in the third graphic.

In short, we both agree that the "Greenhouse Effect" is real and rising CO2 levels do contribute to that effect, that it has indeed warmed, and that humans actions have some responsibility for the warming.

That leaves the much more important questions for debate:

• How much has the Earth actually warmed over the past century?

• How much of that is due to human activities, primarily rising CO2 levels?

• Does the temperature rise pose any substantial, near-term danger to human civilization?

• What, if any, drastic action is required to ameliorate human-caused Global Warming?

Ira Glickstein

Climate Change (aka Global Warming)

This posting is based on a talk to the Technology, Engineering, Science Plus Club, The Villages, FL, 26 May 2011. This group is a well-educated audience familiar with science and technology, but not necessarily fully cognizant regarding the current controversy.

Powerpoint charts available for download here

Skeptic Strategy for Talking About Global Warming

This Powerpoint chart set may be used as the basis for a skeptic-oriented talk or debate about Climate Change (aka Global Warming). Talking points are provided in the Notes section of each chart to help understand the main points made.

My “credentials” for preparing this slide set include:

• Guest Contributor to the most popular climate website in the world, http://wattsupwiththat.com/author/iraglickstein/


• Associate Professor of System Engineering at University of Maryland


• System Engineer (Advanced Avionics and Visionics, Route Planning, Decision Aiding, Five Patents ... at IBM, Lockheed-Martin)


• PhD in System Science (Binghamton University, 1996); MS in System Science (Binghamton); Bachelors in Electrical Engineering (CCNY)

If you saw the highly-rated 2006 movie An “Inconvenient” Truth you probably remember the scene depicted in the photo above.

Former VP Al Gore shows the ice core record of carbon dioxide (CO2 – in red) and temperature (in blue) over the past 600,000 years and he points out the obvious correlation between the two curves. When one goes up, so does the other. When one goes down, so does the other.

He then mounts a platform and is lifted high on the stage, showing how high CO2 levels are getting. He is then raised even higher to indicate where CO2 levels will be 30 years hence at the rate we are going if nothing is done about them.

The implication is that, if CO2 reaches that level, temperatures, which are clearly well-correlated, will rise as well. OMG ! At those high temperatures, the Arctic and Antarctic ice caps will melt, exposing the bare Earth beneath, reducing the albedo of the Surface and causing still more short-wave Solar energy to be absorbed. That could lead to still more warming and a “tipping point” catastrophe of major proportions. As the ice melts, low-lying islands and coastal areas will be submerged, killing and displacing billions of people.

Clearly, something needs to be done on a worldwide basis to stop further burning of fossil fuels and land use activities that reduce the albedo.

The message was so powerful that it earned Al Gore and his movie an Oscar and a Nobel prize in 2007. It came to be known as Catastrophic Anthropomorphic Global Warming (CAGW).

But wait, there is more to the story! If we examine the ice core data carefully, we discover that the temperatures rise about 800 years or more before the CO2 goes up. Temperature also falls 800 or more years before CO2 goes down. This lag of temperature behind CO2 is true for the entire 600,000 year ice core record. OOPS, is this another “inconvenient” truth?

Yes, there is correlation and possibly causation. But, in which direction?

HMMM .. If A “causes “ B, then A has to happen before B. Right? If, as Gore implies, CO2 “causes” temperatures to rise, then one would expect CO2 to rise before temperatures. Right?

Thus, all the ice core data proves is that temperature “causes” CO2 –or– that something else causes both temperature and CO2.

Those who believe that higher CO2 will cause temperatures to rise, due to the Atmospheric “greenhouse effect” point to the unprecedented levels of burning of fossil fuels and the undoubted rise of CO2. But, if it is unprecedented, and due to human activities, what does the ice core record have to tell us about the current situation? Humans could have had absolutely no role in the Global Warming and Global Cooling cycles of the ice ages. So, why did Gore bring it up?

Ira Glickstein