第 24209 題：實指數函數

原題與已知條件

E(x)=sum_n>=0 x^n/n!的完整coefficient law與exact rational certificate。操作=exp-addition-convolution；資料={"x":[9,10],"y":[-10,11],"degree":8}。請依 exact_ordered_tuple_declared_by_interface 欄序回答。

• G001 — E(x)=sum_n>=0 x^n/n!的完整coefficient law與exact rational certificate。操作=exp-addition-convolution；資料={"x":[9,10],"y":[-10,11],"degree":8}。請依 exact_ordered_tuple_declared_by_interface 欄序回答。

定義與適用範圍

沿用原題明示的論域、假設與來源 MKO 定義。本題已完成第二對話數理與中英語義覆核，並由原始參數逐題獨立重算模型、答案與每個算術步驟；原題仍為 candidate。

• mko-real-exponential-function

逐步推導

source roles = [exp-addition-convolution]

derived = [[x, y, degree, coefficient_terms, convolution_coefficient, sum_argument_coefficient, equal, certificate]]

(9/10)^0

Exp convolution x power0 = 1

(-10/11)^8

Exp convolution y power8 = 100000000/214358881

Exp convolution numerator0 := mul(1, 100000000/214358881)

Exp convolution numerator0 = 100000000/214358881

source roles = [0]

derived = [1]

Exp convolution right0 factorial step1 := mul(1, 1)

Exp convolution right0 factorial step1 = 1

Exp convolution right0 factorial step2 := mul(1, 2)

Exp convolution right0 factorial step2 = 2

Exp convolution right0 factorial step3 := mul(2, 3)

Exp convolution right0 factorial step3 = 6

Exp convolution right0 factorial step4 := mul(6, 4)

Exp convolution right0 factorial step4 = 24

Exp convolution right0 factorial step5 := mul(24, 5)

Exp convolution right0 factorial step5 = 120

Exp convolution right0 factorial step6 := mul(120, 6)

Exp convolution right0 factorial step6 = 720

Exp convolution right0 factorial step7 := mul(720, 7)

Exp convolution right0 factorial step7 = 5040

Exp convolution right0 factorial step8 := mul(5040, 8)

Exp convolution right0 factorial step8 = 40320

Exp convolution denominator0 := mul(1, 40320)

Exp convolution denominator0 = 40320

Exp convolution coefficient term0 := div(100000000/214358881, 40320)

Exp convolution coefficient term0 = 156250/13504609503

(9/10)^1

Exp convolution x power1 = 9/10

(-10/11)^7

Exp convolution y power7 = -10000000/19487171

Exp convolution numerator1 := mul(9/10, -10000000/19487171)

Exp convolution numerator1 = -9000000/19487171

Exp convolution left1 factorial step1 := mul(1, 1)

Exp convolution left1 factorial step1 = 1

Exp convolution right1 factorial step1 := mul(1, 1)

Exp convolution right1 factorial step1 = 1

Exp convolution right1 factorial step2 := mul(1, 2)

Exp convolution right1 factorial step2 = 2

Exp convolution right1 factorial step3 := mul(2, 3)

Exp convolution right1 factorial step3 = 6

Exp convolution right1 factorial step4 := mul(6, 4)

Exp convolution right1 factorial step4 = 24

Exp convolution right1 factorial step5 := mul(24, 5)

Exp convolution right1 factorial step5 = 120

Exp convolution right1 factorial step6 := mul(120, 6)

Exp convolution right1 factorial step6 = 720

Exp convolution right1 factorial step7 := mul(720, 7)

Exp convolution right1 factorial step7 = 5040

Exp convolution denominator1 := mul(1, 5040)

Exp convolution denominator1 = 5040

Exp convolution coefficient term1 := div(-9000000/19487171, 5040)

Exp convolution coefficient term1 = -12500/136410197

(9/10)^2

Exp convolution x power2 = 81/100

(-10/11)^6

Exp convolution y power6 = 1000000/1771561

Exp convolution numerator2 := mul(81/100, 1000000/1771561)

Exp convolution numerator2 = 810000/1771561

Exp convolution left2 factorial step1 := mul(1, 1)

Exp convolution left2 factorial step1 = 1

Exp convolution left2 factorial step2 := mul(1, 2)

Exp convolution left2 factorial step2 = 2

Exp convolution right2 factorial step1 := mul(1, 1)

Exp convolution right2 factorial step1 = 1

Exp convolution right2 factorial step2 := mul(1, 2)

Exp convolution right2 factorial step2 = 2

Exp convolution right2 factorial step3 := mul(2, 3)

Exp convolution right2 factorial step3 = 6

Exp convolution right2 factorial step4 := mul(6, 4)

Exp convolution right2 factorial step4 = 24

Exp convolution right2 factorial step5 := mul(24, 5)

Exp convolution right2 factorial step5 = 120

Exp convolution right2 factorial step6 := mul(120, 6)

Exp convolution right2 factorial step6 = 720

Exp convolution denominator2 := mul(2, 720)

Exp convolution denominator2 = 1440

Exp convolution coefficient term2 := div(810000/1771561, 1440)

Exp convolution coefficient term2 = 1125/3543122

(9/10)^3

Exp convolution x power3 = 729/1000

(-10/11)^5

Exp convolution y power5 = -100000/161051

Exp convolution numerator3 := mul(729/1000, -100000/161051)

Exp convolution numerator3 = -72900/161051

Exp convolution left3 factorial step1 := mul(1, 1)

Exp convolution left3 factorial step1 = 1

Exp convolution left3 factorial step2 := mul(1, 2)

Exp convolution left3 factorial step2 = 2

Exp convolution left3 factorial step3 := mul(2, 3)

Exp convolution left3 factorial step3 = 6

Exp convolution right3 factorial step1 := mul(1, 1)

Exp convolution right3 factorial step1 = 1

Exp convolution right3 factorial step2 := mul(1, 2)

Exp convolution right3 factorial step2 = 2

Exp convolution right3 factorial step3 := mul(2, 3)

Exp convolution right3 factorial step3 = 6

Exp convolution right3 factorial step4 := mul(6, 4)

Exp convolution right3 factorial step4 = 24

Exp convolution right3 factorial step5 := mul(24, 5)

Exp convolution right3 factorial step5 = 120

Exp convolution denominator3 := mul(6, 120)

Exp convolution denominator3 = 720

Exp convolution coefficient term3 := div(-72900/161051, 720)

Exp convolution coefficient term3 = -405/644204

(9/10)^4

Exp convolution x power4 = 6561/10000

(-10/11)^4

Exp convolution y power4 = 10000/14641

Exp convolution numerator4 := mul(6561/10000, 10000/14641)

Exp convolution numerator4 = 6561/14641

Exp convolution left4 factorial step1 := mul(1, 1)

Exp convolution left4 factorial step1 = 1

Exp convolution left4 factorial step2 := mul(1, 2)

Exp convolution left4 factorial step2 = 2

Exp convolution left4 factorial step3 := mul(2, 3)

Exp convolution left4 factorial step3 = 6

Exp convolution left4 factorial step4 := mul(6, 4)

Exp convolution left4 factorial step4 = 24

Exp convolution right4 factorial step1 := mul(1, 1)

Exp convolution right4 factorial step1 = 1

Exp convolution right4 factorial step2 := mul(1, 2)

Exp convolution right4 factorial step2 = 2

Exp convolution right4 factorial step3 := mul(2, 3)

Exp convolution right4 factorial step3 = 6

Exp convolution right4 factorial step4 := mul(6, 4)

Exp convolution right4 factorial step4 = 24

Exp convolution denominator4 := mul(24, 24)

Exp convolution denominator4 = 576

Exp convolution coefficient term4 := div(6561/14641, 576)

Exp convolution coefficient term4 = 729/937024

(9/10)^5

Exp convolution x power5 = 59049/100000

(-10/11)^3

Exp convolution y power3 = -1000/1331

Exp convolution numerator5 := mul(59049/100000, -1000/1331)

Exp convolution numerator5 = -59049/133100

Exp convolution left5 factorial step1 := mul(1, 1)

Exp convolution left5 factorial step1 = 1

Exp convolution left5 factorial step2 := mul(1, 2)

Exp convolution left5 factorial step2 = 2

Exp convolution left5 factorial step3 := mul(2, 3)

Exp convolution left5 factorial step3 = 6

Exp convolution left5 factorial step4 := mul(6, 4)

Exp convolution left5 factorial step4 = 24

Exp convolution left5 factorial step5 := mul(24, 5)

Exp convolution left5 factorial step5 = 120

Exp convolution right5 factorial step1 := mul(1, 1)

Exp convolution right5 factorial step1 = 1

Exp convolution right5 factorial step2 := mul(1, 2)

Exp convolution right5 factorial step2 = 2

Exp convolution right5 factorial step3 := mul(2, 3)

Exp convolution right5 factorial step3 = 6

Exp convolution denominator5 := mul(120, 6)

Exp convolution denominator5 = 720

Exp convolution coefficient term5 := div(-59049/133100, 720)

Exp convolution coefficient term5 = -6561/10648000

(9/10)^6

Exp convolution x power6 = 531441/1000000

(-10/11)^2

Exp convolution y power2 = 100/121

Exp convolution numerator6 := mul(531441/1000000, 100/121)

Exp convolution numerator6 = 531441/1210000

Exp convolution left6 factorial step1 := mul(1, 1)

Exp convolution left6 factorial step1 = 1

Exp convolution left6 factorial step2 := mul(1, 2)

Exp convolution left6 factorial step2 = 2

Exp convolution left6 factorial step3 := mul(2, 3)

Exp convolution left6 factorial step3 = 6

Exp convolution left6 factorial step4 := mul(6, 4)

Exp convolution left6 factorial step4 = 24

Exp convolution left6 factorial step5 := mul(24, 5)

Exp convolution left6 factorial step5 = 120

Exp convolution left6 factorial step6 := mul(120, 6)

Exp convolution left6 factorial step6 = 720

Exp convolution right6 factorial step1 := mul(1, 1)

Exp convolution right6 factorial step1 = 1

Exp convolution right6 factorial step2 := mul(1, 2)

Exp convolution right6 factorial step2 = 2

Exp convolution denominator6 := mul(720, 2)

Exp convolution denominator6 = 1440

Exp convolution coefficient term6 := div(531441/1210000, 1440)

Exp convolution coefficient term6 = 59049/193600000

(9/10)^7

Exp convolution x power7 = 4782969/10000000

(-10/11)^1

Exp convolution y power1 = -10/11

Exp convolution numerator7 := mul(4782969/10000000, -10/11)

Exp convolution numerator7 = -4782969/11000000

Exp convolution left7 factorial step1 := mul(1, 1)

Exp convolution left7 factorial step1 = 1

Exp convolution left7 factorial step2 := mul(1, 2)

Exp convolution left7 factorial step2 = 2

Exp convolution left7 factorial step3 := mul(2, 3)

Exp convolution left7 factorial step3 = 6

Exp convolution left7 factorial step4 := mul(6, 4)

Exp convolution left7 factorial step4 = 24

Exp convolution left7 factorial step5 := mul(24, 5)

Exp convolution left7 factorial step5 = 120

Exp convolution left7 factorial step6 := mul(120, 6)

Exp convolution left7 factorial step6 = 720

Exp convolution left7 factorial step7 := mul(720, 7)

Exp convolution left7 factorial step7 = 5040

Exp convolution right7 factorial step1 := mul(1, 1)

Exp convolution right7 factorial step1 = 1

Exp convolution denominator7 := mul(5040, 1)

Exp convolution denominator7 = 5040

Exp convolution coefficient term7 := div(-4782969/11000000, 5040)

Exp convolution coefficient term7 = -531441/6160000000

(9/10)^8

Exp convolution x power8 = 43046721/100000000

(-10/11)^0

Exp convolution y power0 = 1

Exp convolution numerator8 := mul(43046721/100000000, 1)

Exp convolution numerator8 = 43046721/100000000

Exp convolution left8 factorial step1 := mul(1, 1)

Exp convolution left8 factorial step1 = 1

Exp convolution left8 factorial step2 := mul(1, 2)

Exp convolution left8 factorial step2 = 2

Exp convolution left8 factorial step3 := mul(2, 3)

Exp convolution left8 factorial step3 = 6

Exp convolution left8 factorial step4 := mul(6, 4)

Exp convolution left8 factorial step4 = 24

Exp convolution left8 factorial step5 := mul(24, 5)

Exp convolution left8 factorial step5 = 120

Exp convolution left8 factorial step6 := mul(120, 6)

Exp convolution left8 factorial step6 = 720

Exp convolution left8 factorial step7 := mul(720, 7)

Exp convolution left8 factorial step7 = 5040

Exp convolution left8 factorial step8 := mul(5040, 8)

Exp convolution left8 factorial step8 = 40320

source roles = [0]

derived = [1]

Exp convolution denominator8 := mul(40320, 1)

Exp convolution denominator8 = 40320

Exp convolution coefficient term8 := div(43046721/100000000, 40320)

Exp convolution coefficient term8 = 4782969/448000000000

Exp complete declared-degree convolution := sum(156250/13504609503, -12500/136410197, 1125/3543122, -405/644204, 729/937024, -6561/10648000, 59049/193600000, -531441/6160000000, 4782969/448000000000)

Exp complete declared-degree convolution = 1/864295008192000000000

Exp ORIGINAL arguments sum := sum(9/10, -10/11)

Exp ORIGINAL arguments sum = -1/110

(-1/110)^8

Exp sum argument declared power = 1/21435888100000000

Exp sum argument factorial step1 := mul(1, 1)

Exp sum argument factorial step1 = 1

Exp sum argument factorial step2 := mul(1, 2)

Exp sum argument factorial step2 = 2

Exp sum argument factorial step3 := mul(2, 3)

Exp sum argument factorial step3 = 6

Exp sum argument factorial step4 := mul(6, 4)

Exp sum argument factorial step4 = 24

Exp sum argument factorial step5 := mul(24, 5)

Exp sum argument factorial step5 = 120

Exp sum argument factorial step6 := mul(120, 6)

Exp sum argument factorial step6 = 720

Exp sum argument factorial step7 := mul(720, 7)

Exp sum argument factorial step7 = 5040

Exp sum argument factorial step8 := mul(5040, 8)

Exp sum argument factorial step8 = 40320

Exp sum argument coefficient := div(1/21435888100000000, 40320)

Exp sum argument coefficient = 1/864295008192000000000

source roles = [[9/10, -10/11], a_n=1/n! for EVERY n>=0]

derived = [coefficient ratio=1/(n+1), for EVERY fixed real z,term absolute ratio=|z|/(n+1)->0, absolute convergence and real-valued E(z)]

source roles = [[9/10, -10/11, 8], E(x),E(y) absolutely convergent]

derived = [for EVERY n,sum_k x^k*y^(n-k)/(k!*(n-k)!)=(x+y)^n/n!, E(x)E(y)=E(x+y)]

逐步反向核對

• S134 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S133 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S132 · premise_and_result_audit — 以精確有理數重算 Exp sum argument coefficient，不以小數近似替代。
• S131 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step8，不以小數近似替代。
• S130 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step7，不以小數近似替代。
• S129 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step6，不以小數近似替代。
• S128 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step5，不以小數近似替代。
• S127 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step4，不以小數近似替代。
• S126 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step3，不以小數近似替代。
• S125 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step2，不以小數近似替代。
• S124 · premise_and_result_audit — 以精確有理數重算 Exp sum argument factorial step1，不以小數近似替代。
• S123 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S122 · premise_and_result_audit — 以精確有理數重算 Exp ORIGINAL arguments sum，不以小數近似替代。
• S121 · premise_and_result_audit — 以精確有理數重算 Exp complete declared-degree convolution，不以小數近似替代。
• S120 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term8，不以小數近似替代。
• S119 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator8，不以小數近似替代。
• S118 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S117 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step8，不以小數近似替代。
• S116 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step7，不以小數近似替代。
• S115 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step6，不以小數近似替代。
• S114 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step5，不以小數近似替代。
• S113 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step4，不以小數近似替代。
• S112 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step3，不以小數近似替代。
• S111 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step2，不以小數近似替代。
• S110 · premise_and_result_audit — 以精確有理數重算 Exp convolution left8 factorial step1，不以小數近似替代。
• S109 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator8，不以小數近似替代。
• S108 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S107 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S106 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term7，不以小數近似替代。
• S105 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator7，不以小數近似替代。
• S104 · premise_and_result_audit — 以精確有理數重算 Exp convolution right7 factorial step1，不以小數近似替代。
• S103 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step7，不以小數近似替代。
• S102 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step6，不以小數近似替代。
• S101 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step5，不以小數近似替代。
• S100 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step4，不以小數近似替代。
• S099 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step3，不以小數近似替代。
• S098 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step2，不以小數近似替代。
• S097 · premise_and_result_audit — 以精確有理數重算 Exp convolution left7 factorial step1，不以小數近似替代。
• S096 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator7，不以小數近似替代。
• S095 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S094 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S093 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term6，不以小數近似替代。
• S092 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator6，不以小數近似替代。
• S091 · premise_and_result_audit — 以精確有理數重算 Exp convolution right6 factorial step2，不以小數近似替代。
• S090 · premise_and_result_audit — 以精確有理數重算 Exp convolution right6 factorial step1，不以小數近似替代。
• S089 · premise_and_result_audit — 以精確有理數重算 Exp convolution left6 factorial step6，不以小數近似替代。
• S088 · premise_and_result_audit — 以精確有理數重算 Exp convolution left6 factorial step5，不以小數近似替代。
• S087 · premise_and_result_audit — 以精確有理數重算 Exp convolution left6 factorial step4，不以小數近似替代。
• S086 · premise_and_result_audit — 以精確有理數重算 Exp convolution left6 factorial step3，不以小數近似替代。
• S085 · premise_and_result_audit — 以精確有理數重算 Exp convolution left6 factorial step2，不以小數近似替代。
• S084 · premise_and_result_audit — 以精確有理數重算 Exp convolution left6 factorial step1，不以小數近似替代。
• S083 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator6，不以小數近似替代。
• S082 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S081 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S080 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term5，不以小數近似替代。
• S079 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator5，不以小數近似替代。
• S078 · premise_and_result_audit — 以精確有理數重算 Exp convolution right5 factorial step3，不以小數近似替代。
• S077 · premise_and_result_audit — 以精確有理數重算 Exp convolution right5 factorial step2，不以小數近似替代。
• S076 · premise_and_result_audit — 以精確有理數重算 Exp convolution right5 factorial step1，不以小數近似替代。
• S075 · premise_and_result_audit — 以精確有理數重算 Exp convolution left5 factorial step5，不以小數近似替代。
• S074 · premise_and_result_audit — 以精確有理數重算 Exp convolution left5 factorial step4，不以小數近似替代。
• S073 · premise_and_result_audit — 以精確有理數重算 Exp convolution left5 factorial step3，不以小數近似替代。
• S072 · premise_and_result_audit — 以精確有理數重算 Exp convolution left5 factorial step2，不以小數近似替代。
• S071 · premise_and_result_audit — 以精確有理數重算 Exp convolution left5 factorial step1，不以小數近似替代。
• S070 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator5，不以小數近似替代。
• S069 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S068 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S067 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term4，不以小數近似替代。
• S066 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator4，不以小數近似替代。
• S065 · premise_and_result_audit — 以精確有理數重算 Exp convolution right4 factorial step4，不以小數近似替代。
• S064 · premise_and_result_audit — 以精確有理數重算 Exp convolution right4 factorial step3，不以小數近似替代。
• S063 · premise_and_result_audit — 以精確有理數重算 Exp convolution right4 factorial step2，不以小數近似替代。
• S062 · premise_and_result_audit — 以精確有理數重算 Exp convolution right4 factorial step1，不以小數近似替代。
• S061 · premise_and_result_audit — 以精確有理數重算 Exp convolution left4 factorial step4，不以小數近似替代。
• S060 · premise_and_result_audit — 以精確有理數重算 Exp convolution left4 factorial step3，不以小數近似替代。
• S059 · premise_and_result_audit — 以精確有理數重算 Exp convolution left4 factorial step2，不以小數近似替代。
• S058 · premise_and_result_audit — 以精確有理數重算 Exp convolution left4 factorial step1，不以小數近似替代。
• S057 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator4，不以小數近似替代。
• S056 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S055 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S054 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term3，不以小數近似替代。
• S053 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator3，不以小數近似替代。
• S052 · premise_and_result_audit — 以精確有理數重算 Exp convolution right3 factorial step5，不以小數近似替代。
• S051 · premise_and_result_audit — 以精確有理數重算 Exp convolution right3 factorial step4，不以小數近似替代。
• S050 · premise_and_result_audit — 以精確有理數重算 Exp convolution right3 factorial step3，不以小數近似替代。
• S049 · premise_and_result_audit — 以精確有理數重算 Exp convolution right3 factorial step2，不以小數近似替代。
• S048 · premise_and_result_audit — 以精確有理數重算 Exp convolution right3 factorial step1，不以小數近似替代。
• S047 · premise_and_result_audit — 以精確有理數重算 Exp convolution left3 factorial step3，不以小數近似替代。
• S046 · premise_and_result_audit — 以精確有理數重算 Exp convolution left3 factorial step2，不以小數近似替代。
• S045 · premise_and_result_audit — 以精確有理數重算 Exp convolution left3 factorial step1，不以小數近似替代。
• S044 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator3，不以小數近似替代。
• S043 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S042 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S041 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term2，不以小數近似替代。
• S040 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator2，不以小數近似替代。
• S039 · premise_and_result_audit — 以精確有理數重算 Exp convolution right2 factorial step6，不以小數近似替代。
• S038 · premise_and_result_audit — 以精確有理數重算 Exp convolution right2 factorial step5，不以小數近似替代。
• S037 · premise_and_result_audit — 以精確有理數重算 Exp convolution right2 factorial step4，不以小數近似替代。
• S036 · premise_and_result_audit — 以精確有理數重算 Exp convolution right2 factorial step3，不以小數近似替代。
• S035 · premise_and_result_audit — 以精確有理數重算 Exp convolution right2 factorial step2，不以小數近似替代。
• S034 · premise_and_result_audit — 以精確有理數重算 Exp convolution right2 factorial step1，不以小數近似替代。
• S033 · premise_and_result_audit — 以精確有理數重算 Exp convolution left2 factorial step2，不以小數近似替代。
• S032 · premise_and_result_audit — 以精確有理數重算 Exp convolution left2 factorial step1，不以小數近似替代。
• S031 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator2，不以小數近似替代。
• S030 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S029 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S028 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term1，不以小數近似替代。
• S027 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator1，不以小數近似替代。
• S026 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step7，不以小數近似替代。
• S025 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step6，不以小數近似替代。
• S024 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step5，不以小數近似替代。
• S023 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step4，不以小數近似替代。
• S022 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step3，不以小數近似替代。
• S021 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step2，不以小數近似替代。
• S020 · premise_and_result_audit — 以精確有理數重算 Exp convolution right1 factorial step1，不以小數近似替代。
• S019 · premise_and_result_audit — 以精確有理數重算 Exp convolution left1 factorial step1，不以小數近似替代。
• S018 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator1，不以小數近似替代。
• S017 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S016 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S015 · premise_and_result_audit — 以精確有理數重算 Exp convolution coefficient term0，不以小數近似替代。
• S014 · premise_and_result_audit — 以精確有理數重算 Exp convolution denominator0，不以小數近似替代。
• S013 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step8，不以小數近似替代。
• S012 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step7，不以小數近似替代。
• S011 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step6，不以小數近似替代。
• S010 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step5，不以小數近似替代。
• S009 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step4，不以小數近似替代。
• S008 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step3，不以小數近似替代。
• S007 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step2，不以小數近似替代。
• S006 · premise_and_result_audit — 以精確有理數重算 Exp convolution right0 factorial step1，不以小數近似替代。
• S005 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S004 · premise_and_result_audit — 以精確有理數重算 Exp convolution numerator0，不以小數近似替代。
• S003 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S002 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S001 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。

結論

(9/10, -10/11, 8, [[0, 156250/13504609503], [1, -12500/136410197], [2, 1125/3543122], [3, -405/644204], [4, 729/937024], [5, -6561/10648000], [6, 59049/193600000], [7, -531441/6160000000], [8, 4782969/448000000000]], 1/864295008192000000000, 1/864295008192000000000, 是, binomial_convolution_matches_the_declared_degree;the_general_addition_law_requires_all_degrees_plus_absolute_convergence_for_Cauchy_product_rearrangement)

依上列完整代值及條件核對得到原題答案；原題編號、格式與狀態保持不變。

本題覆核與來源綁定

覆核日期：2026-10-26

原題、答案、步驟表達式、數值 AST 與既有歷史保持原樣；原來的候選狀態屬於來源歷史，不覆寫為形式化證明。