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arxiv: 2603.17719 · v3 · pith:K75YYAHJnew · submitted 2026-03-18 · ⚛️ physics.comp-ph · nucl-ex· nucl-th

ALPHANSO: Open-Source Modeling of (α,n) Neutron Source Terms

Divit Rawal , Anthony J. Nelson , William Zywiec , Daniel Siefman This is my paper

Pith reviewed 2026-05-22 11:10 UTC · model grok-4.3

classification ⚛️ physics.comp-ph nucl-exnucl-th
keywords (α,n) reactionsneutron source termsopen-source softwarenuclear data librariesneutron yieldsalpha-particle reactionsradiation modelingnuclear safeguards
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0 comments X

The pith

ALPHANSO is an open-source Python package that calculates accurate neutron yields and spectra from alpha reactions using modern nuclear data.

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

The paper presents ALPHANSO as a new tool to predict neutrons emitted when alpha particles interact with different materials. Older codes suffer from outdated data, missing elements, and limited access, while this package draws on current nuclear libraries that cover every naturally occurring nuclide and allows straightforward updates. The authors compare its output to both experiments and other modern codes, finding close agreement in neutron production rates and energy distributions across many elements. Accurate source terms matter for applications that must control or measure low levels of neutrons, including material safeguards and searches for rare events. The open and modular design removes barriers that have kept legacy methods dominant for decades.

Core claim

ALPHANSO reproduces neutron yields and spectra in good agreement with experimental data and state-of-the-art calculations. The package incorporates modern nuclear data libraries and formats covering all naturally occurring target nuclides and supplies a transparent, modular framework that can be updated when new evaluations appear, positioning it as a reliable and accessible alternative to legacy tools such as SOURCES-4C.

What carries the argument

ALPHANSO, a modular Python package that pulls modern evaluated nuclear data libraries into calculations of neutron production from alpha-particle reactions on any natural target nuclide.

If this is right

  • Neutron source terms become computable for every natural element without dependence on restricted or outdated legacy software.
  • Applications in nuclear safeguards and low-background experiments gain a transparent calculation method that can be audited and modified.
  • New nuclear data releases can be incorporated through the modular structure without rewriting core code.
  • Researchers can extend the framework to specific isotopes or reaction channels as needed for their experiments.

Where Pith is reading between the lines

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

  • Adoption across groups could reduce inconsistencies that arise when different labs use different legacy codes for the same material.
  • Coupling ALPHANSO output directly into Monte Carlo transport codes would allow geometry-specific neutron background estimates without intermediate file conversions.
  • Routine checks against fresh experimental data on low-abundance isotopes would reveal whether coverage gaps remain in the underlying libraries.

Load-bearing premise

The modern nuclear data libraries incorporated into ALPHANSO are accurate and complete for all naturally occurring target nuclides and the chosen comparison codes and experimental datasets form fair benchmarks.

What would settle it

A new measurement of neutron yield or spectrum for an alpha reaction on a previously untested material or nuclide that deviates substantially from ALPHANSO predictions while agreeing with independent modern codes would challenge the agreement claim.

Figures

Figures reproduced from arXiv: 2603.17719 by Anthony J. Nelson, Daniel Siefman, Divit Rawal, William Zywiec.

Figure 1
Figure 1. Figure 1: (α,n) cross sections from ENDF/B-VIII.1, JENDL-5, TENDL-2023, SOURCES￾4A, and SOURCES-4C for selected nuclides. 7 [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Stopping power from ASTAR, SRIM, and SOURCES-4A/SOURCES-4C for [PITH_FULL_IMAGE:figures/full_fig_p009_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Neutron yields from ALPHANSO, SOURCES-4A, SOURCES-4C, and exper [PITH_FULL_IMAGE:figures/full_fig_p015_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: provides the mean absolute error of the energy spectrum calcu￾lated by each code (experimental spectra are taken from [37]). We find that ALPHANSO gives comparably accurate yields to both SOURCES-4A and SOURCES-4C [PITH_FULL_IMAGE:figures/full_fig_p016_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Calculated-to-Experimental neutron yield ratios and Mean Absolute Error [PITH_FULL_IMAGE:figures/full_fig_p017_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Normalized spectra deviations from experimental data for ALPHANSO com [PITH_FULL_IMAGE:figures/full_fig_p019_6.png] view at source ↗
read the original abstract

Applications ranging from nuclear safeguards to dark matter detection require accurate predictions of neutron yields and energy spectra produced by ($\alpha$,n) reactions. Legacy tools like SOURCES-4C remain widely used despite significant limitations, including outdated nuclear data, missing target nuclides, and restricted accessibility. Here, we present ALPHANSO, an open-source Python package for calculating ($\alpha$,n) neutron source terms. ALPHANSO incorporates modern nuclear data libraries and formats covering all naturally occurring target nuclides and provides a transparent, modular framework for updating or extending the data as new evaluations are released. Comparison with an updated version of SOURCES-4A, NeuCBOT, and experimental measurements across a range of elements and materials shows that ALPHANSO reproduces neutron yields and spectra in good agreement with experimental data and state-of-the-art ($\alpha$,n) calculations. These results demonstrate that ALPHANSO is a reliable, accessible, and modern alternative to legacy ($\alpha$,n) source term codes such as SOURCES-4C. Its open-source design and modular data handling make it readily extensible to future evaluated nuclear data and low-background applications.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript presents ALPHANSO, an open-source Python package for computing (α,n) neutron yields and energy spectra. It incorporates modern nuclear data libraries covering all naturally occurring target nuclides and provides a modular framework for updates. The central claim is that benchmark comparisons against an updated SOURCES-4A, NeuCBOT, and experimental measurements demonstrate good agreement in yields and spectra across a range of elements and materials, establishing ALPHANSO as a transparent, accessible alternative to legacy codes such as SOURCES-4C.

Significance. If the validation results hold under quantitative scrutiny, the work is significant for supplying a freely available, extensible tool that addresses the outdated data and limited accessibility of existing (α,n) codes. The open-source design, use of current evaluated libraries, and modular data handling are explicit strengths that support reproducibility and future extensions for applications in nuclear safeguards and low-background experiments.

major comments (2)
  1. [§4] §4 (Benchmark Comparisons): The manuscript asserts 'good agreement' with experimental data and other codes but provides no quantitative metrics (e.g., mean relative deviation, χ² values, or tabulated yields with uncertainties) or explicit data exclusion rules. This absence prevents full evaluation of the strength of the central validation claim.
  2. [§3] §3 (Nuclear Data Implementation): The text does not specify the exact versions or releases of the nuclear data libraries (e.g., ENDF/B, TENDL) incorporated in ALPHANSO versus those used in the updated SOURCES-4A and NeuCBOT. Without this, the independence of the benchmark comparisons cannot be confirmed, raising the possibility that observed agreement partly reflects shared inputs rather than independent implementation.
minor comments (2)
  1. [Abstract] The abstract refers to 'a range of elements and materials' without listing the specific targets or compounds used in the comparisons; adding this list would improve clarity.
  2. [Figures] Figure captions for the spectral comparisons should include the precise energy binning and normalization conventions employed.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments and positive overall assessment of the manuscript. We address each major comment below and have revised the manuscript accordingly to improve clarity and rigor.

read point-by-point responses

  1. Referee: [§4] §4 (Benchmark Comparisons): The manuscript asserts 'good agreement' with experimental data and other codes but provides no quantitative metrics (e.g., mean relative deviation, χ² values, or tabulated yields with uncertainties) or explicit data exclusion rules. This absence prevents full evaluation of the strength of the central validation claim.

    Authors: We agree that the validation section would benefit from quantitative metrics to allow readers to more rigorously evaluate the claimed agreement. In the revised manuscript, we will add a new table in §4 that reports neutron yields for each benchmark case (ALPHANSO, updated SOURCES-4A, NeuCBOT, and experiment), along with relative deviations, uncertainties where reported in the source data, and a brief description of the data inclusion/exclusion criteria used (e.g., only measurements with documented uncertainties and target compositions). We will also compute and report summary statistics such as mean absolute relative deviation across the dataset. revision: yes

  2. Referee: [§3] §3 (Nuclear Data Implementation): The text does not specify the exact versions or releases of the nuclear data libraries (e.g., ENDF/B, TENDL) incorporated in ALPHANSO versus those used in the updated SOURCES-4A and NeuCBOT. Without this, the independence of the benchmark comparisons cannot be confirmed, raising the possibility that observed agreement partly reflects shared inputs rather than independent implementation.

    Authors: We thank the referee for highlighting this important point on data provenance. The revised manuscript will include an expanded subsection in §3 that explicitly lists the precise library versions and releases used by ALPHANSO (e.g., ENDF/B-VIII.0 for (α,n) cross sections on light targets and TENDL-2019 for heavier targets, with specific file identifiers). We will also state the versions employed in the updated SOURCES-4A and NeuCBOT benchmarks as documented in their source publications and our direct communications with the code maintainers. While some shared evaluated data is expected for meaningful comparisons, the independent processing pipelines, stopping-power models, and code architectures provide a substantive test of implementation differences; we will add a short discussion clarifying this distinction. revision: yes

Circularity Check

0 steps flagged

No circularity: ALPHANSO is a data-driven implementation validated against external benchmarks

full rationale

The paper describes an open-source Python package that ingests modern evaluated nuclear data libraries to compute (α,n) yields and spectra, then compares outputs to independent experimental datasets and to other codes (updated SOURCES-4A, NeuCBOT). No equations, fitted parameters, or self-citations are shown to define the target quantities in terms of themselves; the validation step uses external measurements and separately maintained codes rather than reducing to the paper's own inputs by construction. The derivation chain is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work is a computational implementation rather than a theoretical derivation; it therefore introduces no new physical axioms or invented entities and relies on the accuracy of pre-existing nuclear data libraries.

axioms (1)
  • domain assumption Modern evaluated nuclear data libraries accurately represent (α,n) reaction cross sections and neutron spectra for all naturally occurring target nuclides.
    The package incorporates these libraries as the basis for its calculations; the abstract states that they cover all natural targets and produce good agreement with experiment.

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. PyNMC: An Open-Source Framework for Neutron Multiplicity Counting Simulation Coupling OpenMC, FREYA, and ALPHANSO

    physics.ins-det 2026-05 accept novelty 5.0

    PyNMC delivers a Python-native open-source NMC simulation framework coupling OpenMC, FREYA, and ALPHANSO, validated on ESARDA benchmarks for Cf-252 and Pu samples with agreement to point models and participant codes.

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