How To Catch a Lion in the Sahara Desert.

Reader Advisory: this node features heavy math geek humor (as well as plain geek humor too). Don't say you were not warned.

A useful and exhaustive listing of the scientific methods for catching lions in the Sahara desert was published in 1938 in an American Mathematical Monthly article entitled A contribution to the mathematical theory of big game hunting by "H.W.O Pétard, of Princeton NJ" (in reality, Princeton mathematician Ralph Boas).

It quickly became a classic among the nerdish scientific community of the time, up until our days, undergoing many a modification, edition, addition and overall alterations that are the fate of every cult texts unleashed on the Internet.

Although a certain knowledge of both the scientific theories used and their historical context is required to fully appreciate some slightly obscure references, most of this text can still be (thoroughly) enjoyed by anybody with reasonable recollections of basic college-level Physics and Math or a mere good common sense and a will to understand (I painstakingly added -hopefully- meaningful pipe links to every single paragraph title: don't be afraid to use them).

Here is the original first edition of this text in an unadulterated form (formatting is mine, of course):

1. Mathematical Methods

1.1 The Hilbert (axiomatic) method

We place a locked cage onto a given point in the desert. After that we introduce the following logical system:

  • Axiom 1: The set of lions in the Sahara is not empty.
  • Axiom 2: If there exists a lion in the Sahara, then there exists a lion in the cage.
  • Procedure: If P is a theorem, and if the following is holds: "P implies Q", then Q is a theorem.
  • Theorem 1: There exists a lion in the cage.

    1.2 The geometrical inversion method

    We place a spherical cage in the desert, enter it and lock it from inside. We then perform an inversion with respect to the cage. Then the lion is inside the cage, and we are outside.

    1.3 The projective geometry method

    Without loss of generality, we can view the desert as a plane surface.
    We project the surface onto a line and afterwards the line onto an interior point of the cage. Thereby the lion is mapped onto that same point.

    1.4 The Bolzano-Weierstrass method

    Divide the desert by a line running from north to south. The lion is then either in the eastern or in the western part. Let's assume it is in the eastern part.
    Divide this part by a line running from east to west. The lion is either in the northern or in the southern part. Let's assume it is in the northern part.
    We can continue this process arbitrarily and thereby constructing with each step an increasingly narrow fence around the selected area. The diameter of the chosen partitions converges to zero so that the lion is caged into a fence of arbitrarily small diameter.

    1.5 The set theoretical method

    We observe that the desert is a separable space. It therefore contains an enumerable dense set of points which constitutes a sequence with the lion as its limit. We silently approach the lion in this sequence, carrying the proper equipment with us.

    1.6 The Peano method

    In the usual way construct a curve containing every point in the desert. It has been proven (1) that such a curve can be traversed in arbitrarily short time. Now we traverse the curve, carrying a spear, in a time less than what it takes the lion to move a distance equal to its own length.

    1.7 A topological method

    We observe that the lion possesses the topological gender of a torus. We embed the desert in a four dimensional space. Then it is possible to apply a deformation (2) of such a kind that the lion when returning to the three dimensional space is all tied up in itself. It is then completely helpless.

    1.8 The Cauchy method

    We examine a lion-valued function f(z). Let ζ be the cage. Consider the integral

              1        f(z)
           -------  ------- dz
             2 πi  C   z - ζ
                  
    

    where C represents the boundary of the desert. Its value is f(ζ), i.e. there is a lion in the cage (3).

    1.9 The Wiener-Tauber method

    We obtain a tame lion, L0, from the class L(-∞,∞), whose Fourier transform vanishes nowhere. We put this lion somewhere in the desert. L0 then converges toward our cage. According to the general Wiener-Tauber theorem (4) every other lion L will converge toward the same cage.
    (Alternatively we can approximate L arbitrarily close by translating L0 through the desert (5).)

    2 Theoretical Physics Methods

    2.1 The Dirac method

    We assert that wild lions can ipso facto not be observed in the Sahara desert. Therefore, if there are any lions at all in the desert, they are tame. We leave catching a tame lion as an exercise to the reader.

    2.2 The Schroedinger method

    At every instant there is a non-zero probability of the lion being in the cage. Sit and wait.

    2.3 The Quantum Measurement Method

    We assume that the sex of the lion is ab initio indeterminate. The wave function for the lion is hence a superposition of the gender eigenstate for a lion and that for a lioness. We lay these eigenstates out flat on the ground and orthogonal to each other. Since the male lion has a distinctive mane, the measurement of sex can safely be made from a distance, using binoculars. The lion then collapses into one of the eigenstates, which is rolled up and placed inside the cage.

    2.4 The nuclear physics method

    Insert a tame lion into the cage and apply a Majorana exchange operator (6) on it and a wild lion.

    As a variant let us assume that we would like to catch (for argument's sake) a male lion. We insert a tame female lion into the cage and apply the Heisenberg exchange operator (7), exchanging spins.

    2.5 A relativistic method

    All over the desert we distribute lion bait containing large amounts of the companion star of Sirius. After enough of the bait has been eaten we send a beam of light through the desert. This will curl around the lion so it gets all confused and can be approached without danger.

    3 Experimental Physics Methods

    3.1 The thermodynamics method

    We construct a semi-permeable membrane which lets everything but lions pass through. This we drag across the desert.

    3.2 The atomic fission method

    We irradiate the desert with slow neutrons. The lion becomes radioactive and starts to disintegrate. Once the disintegration process is progressed far enough the lion will be unable to resist.

    3.3 The magneto-optical method

    We plant a large, lens shaped field with cat mint (nepeta cataria) such that its axis is parallel to the direction of the horizontal component of the earth's magnetic field. We put the cage in one of the field's foci. Throughout the desert we distribute large amounts of magnetized spinach (spinacia oleracea) which has, as everybody knows, a high iron content. The spinach is eaten by vegetarian desert inhabitants which in turn are eaten by the lions. Afterwards the lions are oriented parallel to the earth's magnetic field and the resulting lion beam is focused on the cage by the cat mint lens.

    (1) After Hilbert, cf. E. W. Hobson, "The Theory of Functions of a Real Variable and the Theory of Fourier's Series" (1927), vol. 1, pp 456-457
    (2) H. Seifert and W. Threlfall, "Lehrbuch der Topologie" (1934), pp 2-3
    (3) According to the Picard theorem (W. F. Osgood, Lehrbuch der Funktionentheorie, vol 1 (1928), p 178) it is possible to catch every lion except for at most one.
    (4) N. Wiener, "The Fourier Integral and Certain of its Applications" (1933), pp 73-74
    (5) N. Wiener, ibid, p 89
    (6) cf e.g. H. A. Bethe and R. F. Bacher, "Reviews of Modern Physics", 8 (1936), pp 82-229, esp. pp 106-107
    (7) ibid


    Among the common additions found to the original document, the influence of modern day computer geeks is the most noticeable. Here it is, in the form of an additional -apocryphal- section:

    4 Contributions from Computer Science.

    4.1 The search method

    We assume that the lion is most likely to be found in the direction to the north of the point where we are standing. Therefore the REAL problem we have is that of speed, since we are only using a PC to solve the problem.

    4.2 The parallel search method.

    By using parallelism we will be able to search in the direction to the north much faster than earlier.

    4.3 The Monte-Carlo method.

    We pick a random number indexing the space we search. By excluding neighboring points in the search, we can drastically reduce the number of points we need to consider. The lion will according to probability appear sooner or later.

    4.4 The practical approach.

    We see a rabbit very close to us. Since it is already dead, it is particularly easy to catch. We therefore catch it and call it a lion.

    4.5 The common language approach.

    If only everyone used ADA/Common Lisp/Prolog, this problem would be trivial to solve.

    4.6 The standard approach.

    We know what a Lion is from ISO 4711/X.123. Since CCITT have specified a Lion to be a particular option of a cat we will have to wait for a harmonized standard to appear. $20,000,000 have been funded for initial investigations into this standard development.

    4.7 Linear search.

    Stand in the top left hand corner of the Sahara Desert. Take one step east. Repeat until you have found the lion, or you reach the right hand edge. If you reach the right hand edge, take one step southwards, and proceed towards the left hand edge. When you finally reach the lion, put it the cage. If the lion should happen to eat you before you manage to get it in the cage, press the reset button, and try again.

    Optionally, experienced programmers will place a pink elephant in Johannesburg as a sentinel value. (thanks ariels)

    4.8 The Dijkstra approach:

    The way the problem reached me was: catch a wild lion in the Sahara Desert. Another way of stating the problem is:

           Axiom 1: Sahara elem deserts
           Axiom 2: Lion elem Sahara
           Axiom 3: NOT(Lion elem cage)
    

    We observe the following invariant:

           P1:     C(L) v not(C(L))
    

    where C(L) means: the value of "L" is in the cage.

    Establishing C initially is trivially accomplished with the statement

           ;cage := {}
    Note 0:
    This is easily implemented by opening the door to the 
    cage and shaking out any lions that happen to be there 
    initially.
    (End of note 0.)
    

    The obvious program structure is then:

           ;cage:={}
           ;do NOT (C(L)) ->
                   ;"approach lion under invariance of P1"
                   ;if P(L) ->
                           ;"insert lion in cage"
                     not P(L) ->
                           ;skip
                   ;fi
           ;od
    
    where P(L) means: the value of L is within arm's reach.
    
    Note 1:
    Axiom 2 ensures that the loop terminates.
    (End of note 1.)
    
    Exercise 0:
    Refine the step "Approach lion under invariance of P1".
    (End of exercise 0.)
    
    Note 2:
    The program is robust in the sense that it will lead to
    abortion if the value of L is "lioness".
    (End of note 2.)
    
    Remark 0: This may be a new sense of the word "robust" for you.
    (End of remark 0.)
    
    Note 3:
    
    From observation we can see that the above program leads to the
    desired goal. It goes without saying that we therefore do not 
    have to run it.
    (End of note 3.)
    (End of approach.) 
    (End of document)
    
             

    You can find an infinity of variations on the above theme floating around in the cyberspace (and probably in dead tree format too), but some of them tend to wear the concept a bit thin...

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