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Thinking with shapes
Brendan Larvor
University of Hertfordshire
Phimsamp3 – May 2008
Is Mathematics Special?
• How is mathematics different from other
enquiries?
• A mathematician is said to have answered,
when asked whether he believed in God:
“Yes, up to isomorphism.”
• So it’s something to do with structure, form
or shape
We naturally turn to:
• Hilbert
• Bourbaki
• Resnik
• Shapiro
Too many experts present!
Goes against our practice-oriented
grain
Both pre-occupied with ontology
rather than practice
• Resnik, M. Mathematics as a Science of
Patterns (Oxford: Clarendon, 1997)
• Shapiro, S. Philosophy of Mathematics:
Structure and Ontology (New York: OUP,
1997)
Both directed at established mathematical
knowledge rather than mathematics in the
making.
Claim
Pattern, form, structure and (generally)
shape have roles in mathematical practice
(and, arguably, in mathematical practice
only) that escape the attention of
ontologically-focused structuralisms
(But may contribute to the plausibility
of these views)
Speculative Corollary
If these heuristic uses of structure really
are unique to mathematics, they may offer
a clue to its unique epistemological status.
Drawing on Serfati:
Shapes in notation
Two sorts of case
• Substitution
• Extension
There are lots of others…
    nnnnn
yxyx
nn
ynxyxyx 02210
...
2.1
1


 
Leibniz’s general product formula
    yxppyxpp
nn
yxpnpyxppyxp nnnnn 022110
...
2.1
1


 
    yxddyxdd
nn
yxdndyxddxyd nnnnn 022110
...
2.1
1


 
A case of substitution:
There are structural analogies in natural science
Rutherford ‘planetary’ model of lithium
…but in the notation?
Seven Extensions
1. Factorial of a positive real number
2. Exponential of a complex number or
square matrix
3. Trigonometric functions of complex
numbers
4. Matrix pseudo-inverses
5. Derivative of a non-differentiable function
6. Derivative of a function on normed
vector-spaces
7. Union and intersection of r-partitions
Case 1: Factorial of a positive
real number
• How can n! mean anything unless n is a
natural number?
• Ask Euler!
• n!= n.(n-1)!
)1(.)(  xxx
  
























1
1
1
1
1
2
1
n
x
n
x
n
x
   
    







 x
n
nxxx
n
nx
1...1.
1...2.1
lim
…which satisfies the functional equation and
equates to x! when x is a natural number
Case 2: Exponential of a complex
number or square matrix (Euler again)
1. ba
e a, b both real
    ...
!
1.
...
!2
1.
!1
1.
1
2
1.







n
bababa
e
n
ba
...
!
...
!2!1
1
2

n
xxx
e
n
x
…then treat complex numbers as square matrices
Case 3: Trigonometric functions
of complex numbers (still Euler)
 1.cos  ba a, b both real
   
 


n
nn
n
x
x
!2
1
cos
2
     
 


n
nn
n
ba
ba
!2
1.1
1.cos
2
Case 4: Matrix pseudo-inverses
• Can we give a sense to A-1 when A is not
invertible?
• Yes, and there are several options (unlike
in physics…)
• All coincide with the usual inverse in the
case of invertible matrices
Moore-Penrose pseudo inverse
Four trivial identities for invertible matrices:
AA-1A = A
A-1AA-1 = A-1
(AA-1)* = AA-1
(A-1A)* = A-1A
Become the definition of the pseudo-inverse
(* is the adjoint)
Moore-Penrose pseudo inverse
Penrose proved that for every matrix A there
is a unique matrix X such that:
AXA = A
XAX = X
(AX)* = AX
(XA)* = XA
Another pseudo-inverse
Provide the vector space of matrices with
a norm. Note that if a square matrix is
invertible, its inverse is the unique matrix B
such that:
0 IAB
Again, we take a trivial identity in the
original case, and make it the definition of
the extension.
Another pseudo-inverse
Now let A be any complex matrix. The
right-hand pseudo-inverse is the unique
matrix B such that:
Note how this reduces to the
original case (=0), and proving
uniqueness is again the hard part
IAB is minimal
Case 5: Derivative of a non-
differentiable function
• Integration by parts plays the role of the
‘bridge’
• Thus differentiation is extended to locally
integrable functions
• Laurent Schwartz won a Fields medal for
it…
Case 6: Derivative of a function
on normed vector-spaces
The derivative is originally conceived at
the limit of a quotient:
ax
afxf
axxf



)()(
lim)(
But vectors don’t form quotients… so:
)()()()( hohafafhaf 
Case 7: Union and intersection
of r-partitions
Enough already!
There are cases of pattern-completion in natural science:
But without the mathematician’s latitude
(recall the choice of pseudo-inverses)

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Thinking with shapes

  • 1. Thinking with shapes Brendan Larvor University of Hertfordshire Phimsamp3 – May 2008
  • 2. Is Mathematics Special? • How is mathematics different from other enquiries? • A mathematician is said to have answered, when asked whether he believed in God: “Yes, up to isomorphism.” • So it’s something to do with structure, form or shape
  • 3. We naturally turn to: • Hilbert • Bourbaki • Resnik • Shapiro Too many experts present! Goes against our practice-oriented grain Both pre-occupied with ontology rather than practice
  • 4. • Resnik, M. Mathematics as a Science of Patterns (Oxford: Clarendon, 1997) • Shapiro, S. Philosophy of Mathematics: Structure and Ontology (New York: OUP, 1997) Both directed at established mathematical knowledge rather than mathematics in the making.
  • 5. Claim Pattern, form, structure and (generally) shape have roles in mathematical practice (and, arguably, in mathematical practice only) that escape the attention of ontologically-focused structuralisms (But may contribute to the plausibility of these views)
  • 6. Speculative Corollary If these heuristic uses of structure really are unique to mathematics, they may offer a clue to its unique epistemological status.
  • 8. Two sorts of case • Substitution • Extension There are lots of others…
  • 9.     nnnnn yxyx nn ynxyxyx 02210 ... 2.1 1     Leibniz’s general product formula     yxppyxpp nn yxpnpyxppyxp nnnnn 022110 ... 2.1 1         yxddyxdd nn yxdndyxddxyd nnnnn 022110 ... 2.1 1     A case of substitution:
  • 10. There are structural analogies in natural science Rutherford ‘planetary’ model of lithium …but in the notation?
  • 11. Seven Extensions 1. Factorial of a positive real number 2. Exponential of a complex number or square matrix 3. Trigonometric functions of complex numbers 4. Matrix pseudo-inverses 5. Derivative of a non-differentiable function 6. Derivative of a function on normed vector-spaces 7. Union and intersection of r-partitions
  • 12. Case 1: Factorial of a positive real number • How can n! mean anything unless n is a natural number? • Ask Euler! • n!= n.(n-1)! )1(.)(  xxx
  • 13.                            1 1 1 1 1 2 1 n x n x n x                  x n nxxx n nx 1...1. 1...2.1 lim …which satisfies the functional equation and equates to x! when x is a natural number
  • 14. Case 2: Exponential of a complex number or square matrix (Euler again) 1. ba e a, b both real     ... ! 1. ... !2 1. !1 1. 1 2 1.        n bababa e n ba ... ! ... !2!1 1 2  n xxx e n x …then treat complex numbers as square matrices
  • 15. Case 3: Trigonometric functions of complex numbers (still Euler)  1.cos  ba a, b both real         n nn n x x !2 1 cos 2           n nn n ba ba !2 1.1 1.cos 2
  • 16. Case 4: Matrix pseudo-inverses • Can we give a sense to A-1 when A is not invertible? • Yes, and there are several options (unlike in physics…) • All coincide with the usual inverse in the case of invertible matrices
  • 17. Moore-Penrose pseudo inverse Four trivial identities for invertible matrices: AA-1A = A A-1AA-1 = A-1 (AA-1)* = AA-1 (A-1A)* = A-1A Become the definition of the pseudo-inverse (* is the adjoint)
  • 18. Moore-Penrose pseudo inverse Penrose proved that for every matrix A there is a unique matrix X such that: AXA = A XAX = X (AX)* = AX (XA)* = XA
  • 19. Another pseudo-inverse Provide the vector space of matrices with a norm. Note that if a square matrix is invertible, its inverse is the unique matrix B such that: 0 IAB Again, we take a trivial identity in the original case, and make it the definition of the extension.
  • 20. Another pseudo-inverse Now let A be any complex matrix. The right-hand pseudo-inverse is the unique matrix B such that: Note how this reduces to the original case (=0), and proving uniqueness is again the hard part IAB is minimal
  • 21. Case 5: Derivative of a non- differentiable function • Integration by parts plays the role of the ‘bridge’ • Thus differentiation is extended to locally integrable functions • Laurent Schwartz won a Fields medal for it…
  • 22. Case 6: Derivative of a function on normed vector-spaces The derivative is originally conceived at the limit of a quotient: ax afxf axxf    )()( lim)( But vectors don’t form quotients… so: )()()()( hohafafhaf 
  • 23. Case 7: Union and intersection of r-partitions Enough already!
  • 24. There are cases of pattern-completion in natural science: But without the mathematician’s latitude (recall the choice of pseudo-inverses)