Technical review draft · case 2026-001 · version 0.1 · 14 September 2026
Status and attribution. Prepared by the Zerone development assistant team, including separately tasked checking agents under the same operator. No external independent review, accountable human adoption, author response or institutional endorsement has yet been obtained. This is a technical draft, not a finding about anyone’s intent. No novelty is claimed.
We examine Lemma 3.3 and the origin-damping step in the proof of Theorem 3.4 of Hammad, Dafaalla and Abdalla, Creating a novel algorithm for studying the strong convergence to a sequence with applications, PLOS One (2025), DOI 10.1371/journal.pone.0319047. The publisher PDF, especially pp. 4–7, and its manuscript XML are the source versions inspected. Source hashes and locators accompany this report.
The result has four distinct scopes:
| Check | Supported conclusion | Boundary |
|---|---|---|
| Generalized-demimetric relaxation | An explicit continuous scalar map disproves the claimed implication to pairwise nonexpansiveness. | This implication alone does not refute convergence. |
| Lemma 3.3’s selected point | Its stated membership condition alone does not give the concluding projection inequality. | Adding the missing projection condition changes the statement. |
| Equation (13) and the recurrence in (9) | The displayed damping inequality fails; a coherent, explicitly specified interpretation of (9) converges to the wrong projected target. | The paper’s inconsistent weight and algorithm notation prevents presenting this as a witness satisfying every literal printed symbol. |
| Auxiliary repair | A self-contained fixed-family lemma recovers weak-limit identification and the projection inequality. | This does not repair or validate the full algorithm. |
The separate publisher expression of concern concerns the peer-review process. It is not evidence for these mathematical findings, and these findings do not establish misconduct.
Write the positive generalized-demimetric condition as
On the real line define
This map is continuous and its only fixed point is zero. Put . For , . For , , so . Thus the condition holds everywhere with . Continuity on the real line also makes demiclosed at zero.
Take two copies, weights , and . Then . Direct calculation gives
Nevertheless for all : the map is quasi-nonexpansive. Distances to fixed points and distances between arbitrary points are different requirements. A normalized finite average therefore does not justify the nonexpansiveness inference in the Lemma 3.3 proof.
The lemma chooses but concludes an inequality of the form
Set , all , all monotone operators , and . Every resolvent is and . Choose and for every . Every displayed residual vanishes, including either the literal repeated-prefix residual or the natural successive-prefix correction. The zero sequence also remains zero under the algorithm’s zero initialization. But
The additional condition would exclude this choice: here it selects zero. Theorem 3.4 does refer to a projected target, so this particular witness does not contradict that theorem’s conclusion.
The first inequality in (13) compares with using . For , and , it asserts . Scaling about the origin need not reduce distance to a different fixed point.
There is also an asymptotic witness for the explicit recurrence in (9), with the following declared interpretation: a fixed finite family, positive weights summing to one, their average, and the unambiguous line from (9). This interpretation resolves the source’s weight/index conflict; it is not a claim to satisfy the literal condition , which uses the iterate symbol. The algorithm line in (2) also contains an extra symbol absent from (9).
Set two with weights , two with resolvent parameters one, , , , , , inertial cap one, and , relabelling the two starting indices as zero and one. This index shift preserves the stated sequence-limit conditions. The constant is contractive with, for example, Lipschitz bound . Use
These satisfy , , and . With , define
The displayed minimum in (9) has a singleton; the capped version above is an explicitly declared interpretation for the numerical check. Taking that singleton literally instead gives when . Both versions have , and the argument below applies to each. Identity operators reduce (9) to
Consequently
For completeness, any nonnegative sequence satisfying , with and , tends to zero: after any index , iterate the inequality to bound it by ; then let and subsequently tend to infinity. Hence . But and the projected equation has the unique solution .
The same bound survives the increasing partial-sum reading with identical maps and weights : then and the additional factors in (9) lie between zero and one. Neither variant satisfies an interpretation that literally imposes summability of these positive iterates to one. Clarifying the intended weight condition and algorithm is therefore an essential question for the authors, not a typographical change we can hide.
Here is an explicitly stated replacement for the limit-identification step. The source prints where is a scalar; we expressly require the operator residual instead. We also specify a fixed family, normalized weights and well-defined resolvents, and derive the prefix residuals rather than relying on the source’s self-subtracting expression. Let be a real Hilbert space, satisfy the positive generalized-demimetric condition with fixed , and each be demiclosed at zero. Let be maximal monotone, with fixed , and assume
is nonempty, closed and convex. Let , , be fixed, and define
Let and choose with . Suppose is bounded, , and
Then every weak cluster point of belongs to , and
Proof. Fix , put and . Positivity gives
Every coefficient is fixed and positive, so each residual tends to zero. Along a weakly convergent subsequence of , has the same weak limit. Demiclosedness of each original residual puts that limit in every . No pairwise nonexpansiveness of is used.
For the resolvents let and . Firm nonexpansiveness and give the telescoping estimate
The last limit follows from boundedness and . Each prefix difference tends to zero. Since is nonexpansive,
Demiclosedness of therefore puts the common weak limit in for every . Finally choose a subsequence attaining the scalar limsup, and a weakly convergent subsubsequence, with limit . The metric projection condition gives , as required.
This proof needs no upper bound on for this particular closure argument. It does not assert quasi-nonexpansiveness of or convergence of the full iteration for arbitrary . Fixed positive coefficients, a common fixed point, and demiclosedness are substantive assumptions.
The residual strategy has an antecedent in the directly cited Song (2018), proof of Theorem 3.4, p. 208. Our argument is supplied in full for checking; it is not presented as a new general principle.
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An outside reviewer is asked to check the source transcription, each witness, the declared interpretations, and the repaired lemma separately. The authors should be asked which weights and algorithm line are intended, whether the projection condition should be explicit in Lemma 3.3, and how the origin damping preserves a nonzero target. No author has yet been contacted. A later response should be retained and assessed without treating silence as assent.
Removing or changing the damping may be a useful next hypothesis, but a complete replacement algorithm and convergence theorem have not been proved here. Other sections, applications and the broader literature remain outside this review. The draft does not establish novelty, fraud, a universal failure of fixed-point methods, or the invalidity of every result in the article.