HorizonMath / numerics /box_integral_b7_1.py
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Add data, numerics, and validators
848d4b7
from mpmath import mp
mp.dps = 110
def compute():
n = 7
K = 40 # series terms for small-t evaluation of L(t)
with mp.extradps(50):
# Precompute moments E[D^(2k)] for D = X-Y with X,Y ~ U(-1,1)
# E[D^(2k)] = 2^(2k+1) / ((2k+1)(2k+2)), k>=1; and moment_0 = 1
moments = [mp.mpf(0)] * (K + 1)
facts = [mp.mpf(0)] * (K + 1)
moments[0] = mp.mpf(1)
facts[0] = mp.mpf(1)
for k in range(1, K + 1):
moments[k] = mp.power(2, 2*k + 1) / ((2*k + 1) * (2*k + 2))
facts[k] = facts[k - 1] * k
def L_series(t):
s = mp.mpf(1)
p = -t
for k in range(1, K + 1):
s += p * moments[k] / facts[k]
p *= -t
return s
def L(t):
if t == 0:
return mp.mpf(1)
# Use series where the closed form has cancellation (t -> 0)
if t < mp.mpf("0.02"):
return L_series(t)
rt = mp.sqrt(t)
term1 = mp.sqrt(mp.pi) * mp.erf(2 * rt) / (2 * rt)
term2 = -mp.expm1(-4 * t) / (4 * t) # (1 - exp(-4t)) / (4t)
return term1 - term2
def integrand(u):
if u == 0:
# limit u->0 of (1 - L(t)^n)/u^2 with t=(u/(1-u))^2:
# 1 - L(t)^n ~ n*E[D^2]*t, E[D^2]=2/3, and t~u^2
return mp.mpf(14) / 3
if u == 1:
return mp.mpf(1)
a = u / (1 - u)
t = a * a
Lt = L(t)
if abs(Lt - 1) < mp.mpf("0.1"):
logLt = mp.log1p(Lt - 1)
else:
logLt = mp.log(Lt)
one_minus_phi = -mp.expm1(n * logLt) # 1 - Lt^n, stable for Lt~1
return one_minus_phi / (u * u)
# E[||D||] = 1/sqrt(pi) * ∫_0^1 (1 - E[e^{-t||D||^2}]) / u^2 du
val = mp.quad(integrand, [0, mp.mpf("0.5"), mp.mpf("0.9"), mp.mpf("0.99"), mp.mpf("0.999"), 1])
return +(val / mp.sqrt(mp.pi))
if __name__ == "__main__":
print(str(compute()))