"Journal of Mathematical Chemistry" (sharan.ravi@springernature.com) Tue, Sep 1, 12:21 PM to "me" (lorentz.jantschi@gmail.com) Ref: Submission ID 09cee074-fad1-4975-a016-66439c630ac2 Dear Dr JÄNTSCHI, Your manuscript "Discrimination of Benzenoid Graphs by Topological Polynomials" has now been assessed. Quoting the opinion of a well-respected reviewer: the adjacency matrix of a molecular graph for a molecule of n atoms contains less than nxn/2 independent bits, so, without extensive labelling of the graph, this is a very-very small amount of information, ignoring most features of such a complicated thing like a molecule, hence, except in some special cases, such an approach appears rather simplistic. Based on this, this manuscript is rejected. Regrettably, your manuscript has been rejected for publication in Journal of Mathematical Chemistry. Thank you for the opportunity to review your work. I'm sorry that we cannot be more positive on this occasion and hope you will not be deterred from submitting future work to Journal of Mathematical Chemistry. Kind regards, Paul Mezey Editor
This document examines the scientific rationale presented in the rejection of the manuscript "Discrimination of Benzenoid Graphs by Topological Polynomials", submitted to the Journal of Mathematical Chemistry. The purpose is not to dispute the editorial right to reject manuscripts, but to evaluate whether the reasoning reported by the reviewer is logically consistent with the foundations of mathematical chemistry and with the actual objectives of the manuscript.
The manuscript investigated the discriminatory power of twenty topological polynomials for benzenoid graphs. The study included complete computational enumeration of all non-isomorphic benzenoid systems containing between four and seven fused hexagons and evaluated the ability of various graph invariants to distinguish structural isomers.
The principal findings showed that several polynomial descriptors, including characteristic-polynomial-based and distance-based descriptors, achieved complete discrimination of all 333 benzenoid isomers containing seven hexagons. The work therefore addressed a classical problem of mathematical chemistry: the distinction of molecular structures through graph-theoretical invariants.
The adjacency matrix of a molecular graph for a molecule of n atoms contains less than n×n/2 independent bits, so, without extensive labelling of the graph, this is a very-very small amount of information, ignoring most features of such a complicated thing like a molecule, hence, except in some special cases, such an approach appears rather simplistic.
The reviewer criticism is notable because it is directed not primarily toward the manuscript itself but toward molecular graph theory as a whole. The statement effectively argues that the adjacency matrix contains too little information to represent molecular complexity adequately.
However, molecular graph theory is founded precisely on the representation of molecules through graph structures and derived invariants. If the limited information content of graph adjacency is considered sufficient grounds to dismiss graph-based descriptors, then a substantial portion of the historical literature of mathematical chemistry would be subject to the same criticism.
The manuscript did not claim that molecular graphs encode all chemical information. Instead, it investigated a much narrower mathematical question: Which topological polynomials are most effective at distinguishing benzenoid graph structures? This question concerns graph discrimination, not complete molecular representation.
The reported criticism focuses on the limited information content of adjacency matrices. However, the manuscript's central result demonstrated that certain topological polynomials uniquely distinguished every benzenoid isomer examined.
Even if one accepts the premise that molecular graphs do not encode all chemical information, that premise does not invalidate a study whose explicit objective is structural discrimination within graph space.
The review seems to assume that limited information content necessarily implies weak discriminatory ability. This implication is not generally valid. Compact representations can possess substantial distinguishing power. The effectiveness of a descriptor is determined by its ability to separate objects of interest, not merely by the raw size of its representation.
For decades, mathematical chemistry has employed graph-based representations, topological indices, characteristic polynomials, distance measures, matching theory, spectral descriptors, and related invariants. The manuscript belongs directly to this tradition.
The review contains no identified errors regarding proofs, computations, enumeration procedures, numerical results, theoretical arguments, or reproducibility. The critique instead focuses on a general philosophical position regarding molecular graph representations.
The statement that an adjacency matrix contains fewer than n²/2 independent bits is formally true for a simple undirected graph. However, this observation alone does not establish that the information is insufficient for structural discrimination. Many successful graph invariants are computed from exactly this information source.
The reviewer evaluates the work largely from the perspective of molecular realism, whereas the manuscript evaluates graph discrimination. These are distinct questions.
The issue documented here is not that the manuscript was rejected. The concern arises from the rationale provided. The reviewer criticism is directed toward the limited information content of molecular graphs, whereas the manuscript investigated the discriminatory performance of topological polynomials defined on such graphs.
From a methodological perspective, the manuscript should have been assessed on the correctness, novelty, mathematical rigor, computational validity, and discriminatory performance of the proposed topological polynomials. The reviewer comment, however, appears focused on a general critique of molecular graph representations rather than on the actual scientific results presented in the submitted work.