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REVIEW 3 major objections 4 minor 128 references

Fanpy 2.0 makes implementing a new wavefunction ansatz as simple as writing a single overlap function, then reuses the same optimization and analysis tools for every method.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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2026-07-31 23:38 UTC pith:WA2H7ZI3

load-bearing objection A credible, well-architected software release that would benefit from a validation section; the central claim (the code works) is plausible but not demonstrated numerically. the 3 major comments →

arxiv 2607.23358 v1 pith:WA2H7ZI3 submitted 2026-07-25 physics.chem-ph

Fanpy 2.0: Wavefunction Implementation and Analysis Tools for Flexible Ansatz Design

Krisztina Zsigmond , Rugwed Lokhande , Carlos E. V. de Moura , Pratiksha B. Gaikwad , Marco Mart\'inez-Gonz\'alez , Michelle Richer , Daniel F. Calero-Osorio , Paul W. Ayers
show 1 more author
Ram\'on Alain Miranda-Quintana
This is my paper
classification physics.chem-ph
keywords FanpyFANCIwavefunction prototypingcoupled-cluster geminalsseniority-restricted coupled clusterFANPTprojected Schrödinger equationquantum chemistry software
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents Fanpy 2.0, a Python library built on the FANCI idea that any multideterminant wavefunction is fully specified by its overlap with each Slater determinant. It claims that a researcher can turn a new mathematical ansatz into working code by writing just that overlap function (and its derivatives), reusing the same Hamiltonian, objective, solver, and analysis modules. Version 2.0 adds several new wavefunction families — coupled-cluster-inspired geminals, seniority-restricted coupled cluster, extended-hierarchy CI, and a neural-network ansatz — plus a perturbative continuation method (FANPT) for finding good starting parameters, a redesigned PySCF interface, an optional PyCI backend, and an analysis module. If true, the platform lowers the barrier to testing new wavefunction methods, especially for strongly correlated systems where initialization is hard.

Core claim

The central claim is that Fanpy 2.0 is a working, modular platform for prototyping arbitrary multideterminant wavefunctions. The FANCI formalism expresses any wavefunction as a parameterized expansion in Slater determinants whose coefficient function f(m,P)=⟨m|Ψ⟩ is the overlap with a determinant; implementing a new ansatz reduces to writing get_overlap. The release delivers four new wavefunction families, an implementation of FANPT as a continuation layer on top of projected Schrödinger objectives, an optional PyCI interface that offloads expensive determinant-space operations, and initial analysis tools such as natural-orbital computation and human-readable parameter printers. The BeH2 exa

What carries the argument

The central object is the FANCI overlap function f(m,P)=⟨m|Ψ⟩ (Eq. 2), which defines a wavefunction by its overlaps with Slater determinants. Because objectives (variational energy, projected Schrödinger equation, local energy) are built from overlaps and Hamiltonian matrix elements alone, the entire optimization and analysis pipeline depends only on a wavefunction exposing get_overlap and parameter derivatives. The paper also introduces FANPT, which solves a linear response equation J(λ)x(n)=b(n) with J the Jacobian of the projected FANCI equations, to propagate parameters along a Hamiltonian interpolation; the Jacobian and response machinery are the mechanism that makes the perturbative co

Load-bearing premise

FANPT's usefulness as a convergence aid assumes that the Jacobian J(λ) stays invertible along the path and that the perturbation expansion converges for the strongly correlated systems where the tool is most needed; the paper offers no error bounds or numerical demonstration of either condition.

What would settle it

Run the documented BeH2 example exactly as written: if the new AP1roGSDGeneralized wavefunction class, the FANPT driver, or the analysis printers fail to run or the energies do not match the reported nonvariational projected-Schrödinger solution, the paper's central claim of a working, extensible platform fails. Alternatively, apply FANPT to a molecule with a known strongly correlated regime and check whether the propagated parameters actually satisfy the projected Schrödinger equation at λ=1; singular Jacobians or diverging energies would refute the convergence-aid claim.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • A researcher can implement a new wavefunction ansatz by writing one overlap function and immediately use all existing objectives, solvers, and analysis tools without modification.
  • The new coupled-cluster-inspired geminal family generalizes pCCD to broader excitation spaces and yields sixteen newly supported wavefunction forms via s_type and singles variants.
  • Seniority-restricted CC wavefunctions let users interpolate between pair-based and full CC expansions by filtering the cluster operator by excitation rank and seniority.
  • FANPT provides a systematic way to build initial guesses for projected Schrödinger equations by propagating parameters from a Fock reference to the full Hamiltonian, which should reduce initialization sensitivity for strongly correlated systems.
  • The optional PyCI backend allows computationally demanding determinant-space operations to be offloaded while keeping Fanpy's prototyping flexibility.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The paper does not include numerical benchmark results for the new wavefunctions or for FANPT beyond a single example; if the new ansätze are accurate on strongly correlated test systems, Fanpy 2.0 would become a convenient testbed for comparing pair-based and excitation-based correlation treatments at scale.
  • FANPT's success hinges on the invertibility of the projected-equation Jacobian and on convergence of the perturbation series; if those fail in difficult regimes, the continuation strategy could be supplemented by homotopy or resummation methods, which the paper leaves open.
  • The analysis module's natural-orbital and parameter-printing tools lay groundwork for more interpretative features; one likely extension is automatic detection of dominant excitations or geminals across a calculation, which would make the workflow more useful for method development.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The paper describes version 2.0 of Fanpy, an open-source Python library for prototyping multideterminant wavefunctions based on the FANCI formulation. The authors claim new wavefunction families (coupled-cluster-inspired geminals, seniority-restricted coupled cluster, extended-hierarchy CI, and neural-network ansätze), a FANPT perturbative-continuation module, redesigned PySCF and new PyCI interfaces, an analysis module, and an improved development environment. The only worked example is a BeH2 AP1roGSD calculation presented as a code listing; no total energy, convergence diagnostic, or comparison to reference results is reported.

Significance. If the implementation lives up to its description, Fanpy 2.0 would be a valuable platform for quickly prototyping wavefunction methods. Strengths of the manuscript are the modular FANCI architecture, the explicit design that reduces new ansatz implementation to writing an overlap function, the availability of source code on GitHub, and the automated test pipeline. However, the paper's central claim that these features are working and usable is not supported by any numerical evidence in the manuscript. The FANPT convergence-aid claim in particular is purely asserted. Because the manuscript is a software paper, the absence of benchmarks or even a printed energy from the BeH2 example prevents the reader from verifying correctness, and the theoretical content is otherwise a summary of the authors' prior work.

major comments (3)
  1. [III, Example calculation] The only numerical demonstration is a code listing that ends with the least_squares call. No total energy, gradient norm, or comparison to FCI or pCCD is printed. A software paper claiming 'working' implementations must show at least one complete, reproducible calculation with a verifiable output. Please add the computed energy and a reference comparison for this example, and ideally a small benchmark for each new wavefunction family.
  2. [II.B, Eq. (6)] FANPT's advertised role as a convergence aid for strongly correlated systems is not demonstrated. Each step requires solving J(lambda)x^(n)=b^(n); if J is singular or ill-conditioned along the homotopy path, the propagated guess is undefined or unstable. No condition numbers, step-size selection, or fallback behavior are reported, and no numerical comparison of optimization with vs. without FANPT is given. Provide a concrete case study and report these diagnostics.
  3. [II.D, New wavefunctions] The four new wavefunction families (geminal CC-inspired, sr-CC, ehCI, NN) are described with equations and code snippets, but no validation is presented. For each family there is no test calculation showing that overlaps/derivatives are correct or that optimization converges to a sensible energy. Since the paper's thesis is that users can rely on this infrastructure to prototype new ansätze, at least one representative numerical test per family is required to support the claim.
minor comments (4)
  1. [II.B, Figure reference] 'The overall workflow is shown in Fig 2' should refer to Fig. 3; Fig. 2 is the bitstring illustration.
  2. [I, II.A, II.E] Typos: 'easly' -> 'easily', 'flexibilty' -> 'flexibility', 'sensivity' -> 'sensitivity', 'safe guard' -> 'safeguard', 'numpyarrays' -> 'numpy arrays'.
  3. [II.D.4] The claim that the multiplicative readout 'ensures size consistency' is stated without proof or demonstration; at minimum give a short explanation or a numerical check.
  4. [Note 61] Reference 61 is incomplete: 'The Journal of Physical Chemistry A0, null (0)' lacks volume and page numbers.

Circularity Check

0 steps flagged

No circular reduction: Fanpy 2.0 is a software implementation paper; its central claims are supported by the public code and test suite, while the heavy self-citation pattern (refs 59–63) is not load-bearing for any derivation in this manuscript.

full rationale

The paper's central claim is that Fanpy 2.0 exists as an extensible platform implementing new wavefunction families (geminal CC, sr-CC, ehCI, NN) and FANPT within the FANCI framework. No equation in this paper is fitted to an output of the same paper, and no 'prediction' is obtained by construction from a fitted parameter. Equations (5)–(6) restate the FANPT continuation equations from the authors' prior work (ref. 59), but the paper presents them as an implementation of that method, not as an independent derivation; the availability of the source code and automated tests makes the software claim checkable independently. The new wavefunction implementations are instantiations of the FANCI overlap representation (Eq. 2), which is a definitional software-abstraction identity rather than a circular scientific derivation. The ansatz forms (Eqs. 7, 10–13) are inherited from prior literature, including several same-group papers, but citing prior theoretical work for an implementation is standard practice and does not reduce the current paper's deliverable to its own inputs. The self-citation pattern (refs 59–63) is heavy but non-load-bearing: the paper's contribution is working code, not a theorem forced by those citations. The absence of a reported final energy in the only example (§III) and the lack of a Jacobian-conditioning/convergence study for FANPT are validation gaps, not circularity. Correctness risk is therefore a separate concern from the circularity score. Overall, I find no circular step that would require a score above 2; the minor credit reflects the unusually heavy same-group citation pattern, not a reduction of the central claim.

Axiom & Free-Parameter Ledger

0 free parameters · 6 axioms · 0 invented entities

The paper introduces no new physical entities or fitted parameters. Its content is implementation of previously published methods, mostly by the same authors, so the ledger is light.

axioms (6)
  • domain assumption Any multideterminant wavefunction can be represented as a linear combination of Slater determinants with coefficient function f(m,P) (Eq. 1).
    Standard FCI expansion; presented as FANCI framework from ref 7.
  • standard math The Hamiltonian acts via one- and two-electron integrals in the determinant basis (Eq. 3).
    Second-quantized electronic Hamiltonian; standard.
  • domain assumption The new geminal ansätze are defined by the excitation pools in Eqs. (8)-(9) and their APG/APsetG/APIG variants.
    These operator pools are taken from prior literature (refs 60, 69); the paper treats them as definitions.
  • domain assumption The FANPT update assumes the projected-equation Jacobian J(λ) in Eq. (6) is invertible along the λ path.
    No proof or numerical check of invertibility/well-posedness is given.
  • standard math Neural networks can represent the overlap function f(m) (universal approximation).
    Invoked with refs 83-86; standard result.
  • domain assumption Seniority number and excitation degree organize the CI space in ehCI (Eq. 12).
    Definitional from refs 62, 82.

pith-pipeline@v1.3.0-alltime-deepseek · 18503 in / 10271 out tokens · 93501 ms · 2026-07-31T23:38:08.004922+00:00 · methodology

0 comments
read the original abstract

Fanpy is a Python library for developing new wavefunction methods. It enables users to quickly convert mathematical expressions into working code through a modular design based on the Flexible Ansatz for N-electron Configuration Interaction (FANCI) theory. This architecture facilitates a straightforward extension of the codebase. Here we present version 2.0 of the Fanpy package. This release includes several new wavefunction implementations, including coupled- cluster-inspired geminal approaches. A new analysis module enables a more detailed inspection of computational results and lays the groundwork for future features. In addition, the PySCF interface has been redesigned, and an interface to the PyCI package has been introduced to offload computationally expensive components. Finally, we introduce an improved software development environment, including automated testing and issue tracking.

Figures

Figures reproduced from arXiv: 2607.23358 by Carlos E. V. de Moura, Daniel F. Calero-Osorio, Krisztina Zsigmond, Marco Mart\'inez-Gonz\'alez, Michelle Richer, Paul W. Ayers, Pratiksha B. Gaikwad, Ram\'on Alain Miranda-Quintana, Rugwed Lokhande.

Figure 1
Figure 1. Figure 1: FIG. 1. Modularity of [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Bitstring representation in the FanPy package. The example [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Schematic workflow of the FANPT implementation in [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗

discussion (0)

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Reference graph

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