baseline: the published sim-numerics artifact as it stands (490 tests, verify_article.py checks all 72 paper numbers against sweep_full.json)
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
Claude Opus 5
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"""Stage 10 - checking the technical claims independently.
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Five of them change the content of the paper rather than its wording, so none
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is accepted on authority. Each is recomputed here from scratch.
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A. The proposed similarity IS the one Table 1's last row calls degenerate,
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and the degeneracy is specific to the CHOSEN scale.
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B. Proposition 1 is true for the ratio form only, not for similarity rules
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in general.
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C. The bracket-endpoint divided difference plus the tent similarity is
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regula falsi exactly - so the words "most recent" in the definition of
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f-hat are load-bearing.
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D. Table 1's c = 0 rows report a window artefact; the true behaviour is
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sublinear, e_n ~ sigma^2 / (c2 f'(r)^2 |D| n).
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E. The order of a Newton step with an O(h^2) derivative estimate is 2, not
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the 1.84 the paper claims.
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"""
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from __future__ import annotations
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import math
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r2 = math.sqrt(2.0)
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f = lambda x: x * x - 2.0
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TENT = lambda z: max(0.0, 1.0 - abs(z))
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RATIO = lambda z: 1.0 / (1.0 + abs(z))
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RAT_SQ = lambda z: 1.0 / (1.0 + z * z)
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EXP_SQ = lambda z: math.exp(-z * z)
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COSINE = lambda z: 1.0 / math.sqrt(1.0 + z * z)
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def iterate(S, n, sigma=2.0, x0=0.0, xfar=2.0):
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x, errs = x0, []
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for _ in range(n):
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x = x + (1.0 - S(f(x) / sigma)) * (xfar - x)
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errs.append(abs(x - r2))
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return errs
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def main():
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print("=" * 76)
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print("A. the tent similarity under the CHOSEN scale")
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print("=" * 76)
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e = iterate(TENT, 200)
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print(f" z at x=0 is {f(0.0) / 2.0:+.1f}, so S = {TENT(f(0.0) / 2.0):.1f} "
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f"and the step is the whole bracket")
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print(f" |e| after 1 step: {e[0]:.4f} after 200: {e[-1]:.4f} "
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f"{'CAPTURED at the far end' if abs(e[0] - e[-1]) < 1e-15 else 'moves'}")
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print(" => the paper proposes, in section 3, the function its own")
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print(" Table 1 calls degenerate. CONFIRMED.")
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print("\n but under the DERIVED scale the clip never engages:")
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# replay the proposed configuration and record how often |f|/sigma >= 1
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from simroot.pure import _slope3
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clipped = total = 0
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a, b = 0.0, 2.0
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fa, fb = f(a), f(b)
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A, FA, B = a, fa, b
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x, fx, xp, fp = a, fa, b, fb
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xp2 = fp2 = None
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for _ in range(40):
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if abs(B - A) <= 1e-12:
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break
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far = B if abs(B - x) >= abs(A - x) else A
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slope = _slope3(x, fx, xp, fp, xp2, fp2)
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sc = abs(slope) * abs(far - x)
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if sc == 0.0:
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break
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z = abs(fx) / sc
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total += 1
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clipped += z >= 1.0
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xn = x + min(1.0, z) * (far - x)
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lo, hi = min(A, B), max(A, B)
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if not (lo < xn < hi):
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xn = 0.5 * (A + B)
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fn = f(xn)
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xp2, fp2, xp, fp, x, fx = xp, fp, x, fx, xn, fn
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if FA * fn < 0.0:
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B = xn
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else:
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A, FA = xn, fn
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print(f" steps {total}, of which clipped at z>=1: {clipped}")
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print("\n" + "=" * 76)
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print("B/C. Proposition 1: which similarity reproduces regula falsi?")
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print("=" * 76)
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a, b = 1.0, 4.0
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fa, fb = f(a), f(b)
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falsi = (a * fb - b * fa) / (fb - fa)
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print(f" regula falsi point on [1,4]: {falsi:.6f}\n")
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print(f" {'similarity':14s}{'scale = |f(x_far)|':>22s}{'match':>8s}")
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print(" " + "-" * 44)
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for name, S in (("1/(1+|z|)", RATIO), ("exp(-|z|)", lambda z: math.exp(-abs(z))),
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("1/(1+z^2)", RAT_SQ), ("1/sqrt(1+z^2)", COSINE),
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("tent", TENT)):
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pt = a + (1.0 - S(f(a) / abs(fb))) * (b - a)
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print(f" {name:14s}{pt:>22.6f}{'YES' if abs(pt - falsi) < 1e-12 else 'no':>8s}")
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print("\n => the identity holds for the ratio form only. The paper's")
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print(" conclusion 'a similarity rule whose scale is taken from the")
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print(" bracket is not a new method' is too broad. CONFIRMED.")
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sigma = abs((fb - fa) / (b - a)) * abs(b - a)
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pt = a + min(1.0, abs(fa) / sigma) * (b - a)
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print(f"\n tent + divided difference over the BRACKET ENDS: {pt!r}")
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print(f" equals regula falsi exactly: {pt == falsi}")
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print(" => 'most recent' in the definition of f-hat is load-bearing:")
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print(" ends give regula falsi, recent iterates give the secant.")
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print("\n" + "=" * 76)
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print("D. Table 1, the c = 0 rows")
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print("=" * 76)
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print(f" {'n':>6s}" + "".join(f"{s:>14s}" for s in
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("1/(1+z^2)", "exp(-z^2)", "1/sqrt(1+z^2)")))
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print(" " + "-" * 48)
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seqs = {n: iterate(S, 4001) for n, S in
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(("1/(1+z^2)", RAT_SQ), ("exp(-z^2)", EXP_SQ),
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("1/sqrt(1+z^2)", COSINE))}
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for n in (5, 10, 15, 40, 100, 1000, 4000):
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row = "".join(f"{seqs[k][n] / seqs[k][n - 1]:>14.4f}" for k in seqs)
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print(f" {n:>6d}{row}")
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print("\n the ratio creeps to 1 - there is no rate to measure, and the")
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print(" paper's 0.9357 / 0.9444 / 0.9327 are the value at n ~ 10-15.")
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print("\n the real law: 1 - S = c2 z^2 + O(z^4) gives")
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print(" e_{n+1} = e_n - c2 f'(r)^2 |D| e_n^2 / sigma^2 + ...")
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print(" => e_n ~ sigma^2 / (c2 f'(r)^2 |D|) . 1/n")
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fp, D, sig = 2.0 * r2, 2.0 - r2, 2.0
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# c2 is measured, not transcribed from a Taylor expansion done by hand:
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# a verification script carrying my own derived constant would be checking
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# my arithmetic against itself.
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for name, S in (("1/(1+z^2)", RAT_SQ), ("exp(-z^2)", EXP_SQ),
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("1/sqrt(1+z^2)", COSINE)):
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h = 1e-4
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c2 = (1.0 - S(h)) / (h * h)
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pred = sig * sig / (c2 * fp * fp * D)
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meas = 4000 * seqs[name][4000]
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print(f" {name:14s} predicted n.e_n -> {pred:7.4f} "
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f"measured at n=4000: {meas:7.4f}")
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print("\n" + "=" * 76)
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print("E. the order of the three-point rule")
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print("=" * 76)
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print(" Newton with a derivative estimate of error O(h^2):")
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print(" e' = e - f/f-hat = e - (e - c e^2 + ...)(1 + O(e^2)) = c e^2")
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print(" so the order is 2, not the 1.84 of Muller's method, which uses")
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print(" the quadratic's ROOT rather than its DERIVATIVE.")
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from simroot.pure import pure_root
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from stage5_three_point import PROBLEMS, order_of
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ps = [order_of(lambda f_, a_, b_, xt, mx: pure_root(
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f_, a_, b_, 1e-12, 200, scale="derived3", guard="project"),
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fn, aa, bb, rr) for _n, fn, aa, bb, rr in PROBLEMS]
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ps = [p for p in ps if math.isfinite(p) and 0.5 < p < 5.0]
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print(f" measured median over the eight problems: "
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f"{sorted(ps)[len(ps) // 2]:.3f} predicted: 2")
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if __name__ == "__main__":
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main()
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