Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics. Patrick Muldowney

Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics - Patrick Muldowney


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ellipsis comma m EndSet"/> and StartSet 1 comma ellipsis period n EndSet, respectively, ensures measurability in omega and t. It also ensures measurability for the conditional cases of upper Y Subscript t (or f left-parenthesis upper Y Subscript t Baseline right-parenthesis) with upper Y Subscript t prime already determined as known real numbers when t prime less-than t.

      Let y Subscript j i represent sample values (or potential occurrences) of the random variables upper Y Subscript j. For any given j, i can have value

i equals i Subscript j Baseline comma 1 less-than-or-equal-to i Subscript j Baseline less-than-or-equal-to m comma 1 less-than-or-equal-to j less-than-or-equal-to n semicolon

      so left-brace i Subscript j Baseline right-brace is the set of permutations, with repetition, of the numbers i equals 1 comma ellipsis comma m taken n at a time.

      The ideas in I1, I2, I3, I4) suggest the following sample values for the stochastic integral integral Subscript 0 Superscript tau Baseline f left-parenthesis upper Y Subscript t Baseline right-parenthesis d upper Y Subscript t (or “integral Subscript 0 Superscript tau Baseline f left-parenthesis upper Y Subscript j Baseline right-parenthesis d upper Y Subscript j”):

sigma-summation Underscript j equals 1 Overscript m Endscripts f left-parenthesis y Subscript j i Sub Subscript j Subscript Baseline right-parenthesis left-parenthesis y Subscript j i Sub Subscript j Subscript Baseline minus y Subscript j minus 1 comma i Sub Subscript j minus 1 Subscript Baseline right-parenthesis period

      The subscript i Subscript j labels the random variability in this calculation, and demonstrates that this version of the stochastic integral can take m Superscript n possible values; though not all of the possible values are necessarily distinct.

      For further simplification, take m equals 2 and n equals 3; so, at each of times tau Subscript j (j equals 1 comma 2 comma 3), the random variable upper Y Subscript j can take one of two possible values, y Subscript j Baseline 1 Baseline comma y Subscript j Baseline 2 Baseline. Then, by enumerating the permutations with repetition of m equals 2 things taken n equals 3 at a time , the 8 possible sample values of the stochastic integral integral Subscript 0 Superscript tau Baseline f left-parenthesis upper Y Subscript t Baseline right-parenthesis d upper Y Subscript t are:

StartLayout 1st Row 1st Column f left-parenthesis y 11 right-parenthesis left-parenthesis y 11 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 21 right-parenthesis left-parenthesis y 21 minus y 11 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 31 right-parenthesis left-parenthesis y 31 minus y 21 right-parenthesis comma 2nd Row 1st Column f left-parenthesis y 11 right-parenthesis left-parenthesis y 11 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 21 right-parenthesis left-parenthesis y 21 minus y 11 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 32 right-parenthesis left-parenthesis y 32 minus y 21 right-parenthesis comma 3rd Row 1st Column f left-parenthesis y 11 right-parenthesis left-parenthesis y 11 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 22 right-parenthesis left-parenthesis y 22 minus y 11 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 31 right-parenthesis left-parenthesis y 31 minus y 22 right-parenthesis comma 4th Row 1st Column f left-parenthesis y 11 right-parenthesis left-parenthesis y 11 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 22 right-parenthesis left-parenthesis y 22 minus y 11 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 32 right-parenthesis left-parenthesis y 32 minus y 22 right-parenthesis comma 5th Row 1st Column f left-parenthesis y 12 right-parenthesis left-parenthesis y 12 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 21 right-parenthesis left-parenthesis y 21 minus y 12 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 31 right-parenthesis left-parenthesis y 31 minus y 21 right-parenthesis comma 6th Row 1st Column f left-parenthesis y 12 right-parenthesis left-parenthesis y 12 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 21 right-parenthesis left-parenthesis y 21 minus y 12 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 32 right-parenthesis left-parenthesis y 32 minus y 21 right-parenthesis comma 7th Row 1st Column f left-parenthesis y 12 right-parenthesis left-parenthesis y 12 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 22 right-parenthesis left-parenthesis y 22 minus y 12 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 31 right-parenthesis left-parenthesis y 31 minus y 22 right-parenthesis comma 8th Row 1st Column f left-parenthesis y 12 right-parenthesis left-parenthesis y 12 minus 0 right-parenthesis 2nd Column plus 3rd Column f left-parenthesis y 22 right-parenthesis left-parenthesis y 22 minus y 12 right-parenthesis 4th Column plus 5th Column f left-parenthesis y 32 right-parenthesis left-parenthesis y 32 minus y 22 right-parenthesis period EndLayout

      Now suppose that the deterministic function f is exponentiation to the power of 2 (so f left-parenthesis y right-parenthesis equals y squared); and suppose the random variable upper Y Subscript t (or upper Y Subscript j above) has sample values negative 1 and plus 1 with equal probabilities 0.5. Calculating each of the above expressions, the 8 sample evaluations of the stochastic integral upper X equals integral Subscript 0 Superscript tau Baseline upper Y Subscript t Superscript 2 Baseline d upper Y Subscript t Baseline are, respectively,

negative 1 comma 1 comma negative 1 comma 1 comma negative 1 comma 1 comma <hr><noindex><a href=Скачать книгу