White Paper on Software Infrastructure for Advanced Nuclear Physics Computing

A. Boehnlein; A. Bulgac; A. Dubey; A. Majumder; A. Panta; A. Walker-Loud; B. Nachman; B. Sawatzky; B. Schenke; C. Ratti

REVIEW 3 major objections 5 minor 1 cited by

White Paper on Software Infrastructure for Advanced Nuclear Physics Computing

T0 review · 3 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read This white paper argues that the US nuclear physics program will only fully exploit current and future high-performance computing if funding moves from short-term project grants to sustained support for software stewardship, data…

desk verdict A well-organized workshop white paper that consolidates the NP computing landscape and its policy asks; the representativeness evidence behind the consensus is thin, but the central recommendation stands. read the letter →

arxiv 2501.00905 v2 pith:5EX77XF5 submitted 2025-01-01 nucl-th hep-phnucl-ex

P. M. Jacobs , A. Boehnlein , B. Sawatzky , J. Carlson , I. Cloet , M. Diefenthaler , R. G. Edwards , K. Godbey

show 44 more authors

W. R. Hix K. Orginos T. Papenbrock M. Ploskon C. Ratti R. Soltz T. Wenaus L. Andreoli J. Brodsky D. Brown A. Bulgac G. D. Chung S.J. Coleman J. Detwiler A. Dubey R. Ehlers S. Gandolfi G. Heyes G. R. Jansen F. Jonas S. R. Klein R. Kreucken D. Lee S. N. Liddick H.-W. Lin A. Majumder T. A. Manning O. E. B. Messer H. Monge-Camacho T. Munson B. Nachman W. Nazarewicz E.G. Ng A. Panta J. Putschke T. Reed F. Salazar N. Sato M. Savage B. Schenke L. Schwiebert C. Shen G. Vujanovic A. Walker-Loud

This is my paper · ORCID

classification nucl-thhep-phnucl-ex

keywords softwareinfrastructurenuclearphysicscomputingstewardshipdatapreservationworkforcedevelopmenthigh-performanceFAIRprinciplescommunityconsensus

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This white paper argues that the US nuclear physics program is leaving scientific results on the table: software and data infrastructure built with public money are not being maintained long enough to keep pace with new supercomputers, new analysis methods, and new facilities. The core claim is that sustained support for software stewardship is vital for the community to fully use current and future high-performance computing resources and to maximize scientific output at manageable cost. The paper draws on a 2024 community workshop that brought together theorists, experimentalists, data scientists, and funding agency representatives, and it frames its recommendations around the FAIR principles for data. If the argument is right, funding agencies should shift from time-limited project grants toward longer-term instruments covering software, data curation, and career paths for scientific software developers.

What carries the argument

The central machinery is the workshop consensus process itself: three parallel working groups (theory, experiment, and joint theory/experiment) plus plenary talks surveying funded projects, followed by a unified synthesis of observations and opportunities. The synthesis is organized around the FAIR data principles (findability, accessibility, interoperability, and reusability), which give the recommendations a common yardstick. The load-bearing survey is a representative cross-section of term-funded projects, not a complete list, and it is used to argue that the community's needs are diverse but converge on sustained stewardship.

What would settle it

A systematic census of US nuclear physics computing projects, including small collaborations, university groups, and emerging areas such as quantum computing that were not core workshop participants, would test the claim: if a large fraction of those projects reports that term-limited funding already suffices and that long-term stewardship is not their bottleneck, the consensus priorities would not generalize. More directly, comparing scientific output per dollar over a decade between projects with sustained multi-year support and matched term-funded projects would settle whether sustained stewardship changes outcomes.

Watch

Extended reading notes

Core claim

The paper's central claim is that the nuclear physics community has built a large body of community software and infrastructure representing significant long-term investment, and that this asset is currently at risk because the funding instruments that created it do not sustain it. The workshop participants reached consensus that sustained support for software stewardship is vital for the NP community to fully utilize current and future HPC and other computing resources, and to maximize their scientific output at manageable cost. The claim extends to the full lifecycle of data and software: raw data, analysis workflows, calibration metadata, and ML models must be preserved along with the expert knowledge needed to interpret them, and the people who do this work need stable career paths. The paper does not propose a single funding mechanism; it identifies a portfolio of mechanisms (multi-disciplinary collaborations, industry partnerships, longer-term awards, and standing community coordination) that together would allow existing and new software to evolve onto new hardware and keep publicly funded science reproducible.

Load-bearing premise

The recommendations rest on the assumption that the workshop participants and the surveyed projects represent the full US nuclear physics computing community, even though the survey is explicitly a representative cross-section rather than a complete list.

Editorial extensions

If this is right

Funding agencies would need to create multi-year instruments that support software stewardship and data curation, not just project-scoped grants.
Community software frameworks would be adapted to new HPC architectures and AI/ML libraries as those evolve, instead of being abandoned when grant terms end.
Data preservation would include not only raw data but analysis workflows, calibration metadata, ML models, and the expert knowledge needed to re-analyze old datasets.
Scientific software developers would gain recognized career paths, mentorship, and training, reducing the current outflow of computing expertise from nuclear physics.
A standing committee representing the broad nuclear physics computing community would coordinate guidance, meetings, and cross-project support.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

If the workshop sample over-represents large, well-resourced collaborations, the recommended priorities may fit those groups better than small theory groups or emerging quantum-computing efforts, whose needs the paper explicitly says are underrepresented.
A testable extension would compare scientific output and software survival rates between projects funded by sustained instruments and otherwise similar term-funded projects over a five-to-ten-year window; the paper's claims predict a measurable gap in both.
The same stewardship logic likely applies outside nuclear physics to other data-intensive, publicly funded sciences, so a successful sustained-support experiment in nuclear physics could serve as a template for those fields.
The paper's emphasis on preserving expert knowledge suggests that re-analysis of archived data should be treated as an ongoing scientific activity with dedicated personnel, not as an archival afterthought.

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

This is a white paper, not a research preprint: there are no new results, equations, or falsifiable claims. Its value is as a consolidated record of the SANPC 24 workshop and as a brief to funding agencies. If you work in nuclear physics computing, it gives a coherent picture of the current landscape and the shared concerns about software sustainability, data preservation, and workforce retention.

The paper does several things well. The survey of nine term-funded projects is a useful snapshot, with enough detail to see the range of scales (USQCD at 180 people down to IQuS with roughly 10). The sections on theory and experiment summarize the computing needs across lattice QCD, nuclear structure, heavy ion, FRIB, JLab, and neutrino experiments. The recommendations—sustained stewardship, long-term data curation, career paths—are concrete and align with the 2023 NSAC LRP. The prose is clear and the structure is easy to navigate.

The main soft spot is representativeness. The Executive Summary claims attendees represented all sub-areas of the US Nuclear Physics portfolio, but no participant roster, affiliation counts, or sampling rationale is given. The project survey is admittedly not a complete list, yet the nine projects are almost all large, well-funded collaborations. The text explicitly acknowledges that smaller collaborations and small experiments have fewer resources and need support, but those groups are not in the survey. So the paper cannot fully distinguish a community-wide consensus from a large-project caucus. That matters more for the specific priorities—a standing committee, data preservation mechanisms—than for the headline claim, which would hold up even with perfect representation. Steady support for software stewardship is widely agreed to be necessary; the open question is how to distribute it fairly.

One additional minor gap: consensus is asserted without documenting how it was reached. The workshop agenda and working-group structure are described, but there is no statement of how disagreements were handled or whether any dissenting views were recorded. That is typical for white papers, but a referee could reasonably ask for more transparency.

Overall, this is a useful and honest document. It is not a scientific contribution, so standard research-review categories do not apply. I would treat the representativeness concern as a serious but non-fatal limitation, and the central recommendation as sound. The paper deserves engagement: I would send it to peer review if the venue publishes white papers or policy documents, and I would cite it as a reference for the state of NP software infrastructure.

Referee Report

3 major / 5 minor

Summary. This white paper reports the discussions and consensus recommendations of the SANPC 24 workshop (Jefferson Lab, June 2024) on software infrastructure for advanced nuclear physics computing. It identifies five priority areas: innovation in software ecosystems, cross-cutting and multi-disciplinary initiatives, software stewardship, data curation and preservation, and career paths and talent retention. The supporting material surveys nine currently funded term projects (BAND, ENAF, IQuS, JAM, JETSCAPE, MUSES, NUCLEI, QuantOm, USQCD), outlines relevant DOE and NSF funding instruments, and sketches the advanced computing landscape in NP theory, experiment, and tools. The paper's central recommendation is that sustained funding for software stewardship is vital for the NP community to exploit current and future HPC resources effectively.

Significance. As a consensus white paper, the manuscript offers a useful synthesis of the NP computing community's stated priorities and provides concrete, citable descriptions of active projects and funding mechanisms. Its strengths include a well-organized structure, a detailed workshop agenda, and explicit alignment with the 2023 NSAC Long Range Plan. The recommendations—especially on software stewardship, data preservation, and career paths—are actionable and will likely inform agency planning. However, the document's value as a 'consensus' statement hinges on the representativeness of the workshop and of the surveyed projects, a claim that is asserted but not empirically supported. The paper contains no technical derivations, so the soundness standard is that of a community statement; its credibility rests on transparency about who was present and how the consensus was reached.

major comments (3)

[I (Executive Summary) and Appendix B] The Executive Summary states that 'Workshop attendees represented all sub-areas of the US Nuclear Physics portfolio,' but the paper provides no participant roster, affiliation counts, or description of the invitation process. Appendix B lists the organizing committee and the agenda but no attendees. Because the paper's recommendations rest on this claimed representation, the absence of supporting data is load-bearing: the reader cannot verify that the conclusions are not shaped by a self-selected subset. Please add an appendix with participant affiliations (at least by institution and career stage) and describe the invitation and working-group process.
[IV.E] The project survey is described as 'a representative cross-section' of US-funded NP advanced computing projects, yet the nine projects listed are predominantly large, term-funded collaborations (USQCD with ~180 members, MUSES with 134, JETSCAPE with ~60, NUCLEI with 57, and so on). Section III.C.1 explicitly emphasizes the needs of smaller collaborations and small experiments, but no such groups appear in the survey. Since specific priorities in Section III (standing committee, data preservation, career paths) are derived from workshop discussion anchored by these presentations, the representativeness claim is a structural evidence gap. Please either provide data supporting the claim (e.g., a comparison with a broader inventory) or soften the claim and explicitly discuss how the survey's composition limits the recommendations.
[III] The document repeatedly invokes 'strong consensus' (III.A.1), 'workshop consensus' (III.D.2, III.H.2), and 'consensus conclusions' (Abstract) without documenting the consensus process. The three parallel working groups and the plenary are described, but there is no account of how disagreements were resolved, whether any dissenting views were recorded, or how 'consensus' was operationalized. As a white paper whose primary claim is that these recommendations represent the community view, a short methods subsection in Appendix B explaining the synthesis process would substantially strengthen the document.

minor comments (5)

[IV.B.3] In 'whose background in usually not in computing science,' 'in' should be 'is'; also in the same paragraph 'the development new codes' should be 'the development of new codes'.
[IV.D.2] The sentence 'Despite the importance of MC event generators to the NP program and their large user community, support for the writing and stewardship of MC event generators has traditionally been challenging to obtain' is an important claim, but it is presented without supporting evidence or references. Adding a citation or a brief explanation would improve the argument.
[Appendix A] The acronym list defines 'QED: Quantum Electro-Dynamics'; the conventional spelling is 'Quantum Electrodynamics.'
[References] Several URLs have formatting issues, such as the missing closing parenthesis in reference [23]; please check the reference formatting for the final version.
[III.C.2] The recommendation that 'funding for project effort should be accompanied by an HPC allocation' is a concrete policy suggestion; cross-referencing the relevant funding instruments in Section IV.A would help contextualize it.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the white paper derives no formal results, fits no parameters, and makes no predictions; its recommendations are grounded in workshop discussion and external program descriptions.

full rationale

This document is a community white paper, not a technical derivation. It contains no equations, no fitted parameters, and no quantitative predictions whose outcome could be forced by construction. The central recommendation, namely that sustained support for software stewardship is vital (Sec. III.B.2), is presented as the consensus of a workshop and as a response to external programmatic realities, not as a result derived from first principles. The survey of term-funded projects in Sec. IV.E is explicitly described as 'not a complete list' but 'a representative cross-section,' and the paper supplies descriptive project sketches rather than statistical inference from the survey. The representativeness concern raised by a skeptic is an evidence gap about sampling, not circular reasoning: even if the sample were unrepresentative, the recommendations would not reduce to their own inputs by definition. Self-citations appear (e.g., collaboration papers by the authors), but none is load-bearing in the sense of supporting a derivation or forbidding alternatives; they are ordinary references to prior work. Therefore the circularity score is 0.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

No free parameters or invented entities; the document makes policy recommendations. The axioms are community and policy assumptions, not mathematical postulates.

assumptions (3)

domain assumption The 2023 NSAC Long Range Plan's vision for advanced computing in NP is the correct strategic basis.
Section II states the workshop addresses implementation of the LRP vision; the recommendations are framed as realizing that vision.
domain assumption The workshop attendees and the surveyed term-funded projects constitute a representative cross-section of the US NP computing community.
Section IV.E notes the survey is 'not a complete list' but 'representative'; the consensus recommendations generalize from this sample.
domain assumption Sustained financial support is the primary mechanism that will lead to the desired software sustainability, data preservation, and career outcomes.
The white paper's recommendations consistently call for new or sustained funding; the causal link between funding and scientific outcomes is assumed, not demonstrated.

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Cite this review

Pith. "Pith review of White Paper on Software Infrastructure for Advanced Nuclear Physics Computing." pith.science (2026). https://pith.science/paper/5EX77XF5

@misc{pith2026250100905,
  author       = {Pith},
  title        = {Pith review of: White Paper on Software Infrastructure for Advanced Nuclear Physics Computing},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5EX77XF5}},
  note         = {Machine review of arXiv:2501.00905}
}

read the original abstract

This White Paper documents the discussion and consensus conclusions of the workshop "Software Infrastructure for Advanced Nuclear Physics Computing" (SANPC 24), which was held at Jefferson Lab on June 20-22, 2024. The workshop brought together members of the US Nuclear Physics community with data scientists and funding agency representatives, to discuss the challenges and opportunities in advanced computing for Nuclear Physics in the coming decade. Opportunities for sustainable support and growth are identified, within the context of existing and currently planned DOE and NSF programs.

Discussion (0). Continue with ORCID to comment.

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Reference graph

Works this paper leans on

157 extracted references · 30 canonical work pages · cited by 1 Pith paper

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Observations NP research encompasses theoretical, experimental, and joint th eory/experiment eﬀorts with a broad range in scope and size. Some collaborations are funded speciﬁcally to develop software-as-a-service to the community, while others are primar ily science-driven, with the software a by-product to some degree. A collaborative approach is beneﬁc...
[2]

Additional ﬂexibility in such programs, in terms of scope and size of award, would expand their reach and impact

Opportunities Multi-disciplinary programs such as SciDAC are highly beneﬁcial to the NP research enterprise. Additional ﬂexibility in such programs, in terms of scope and size of award, would expand their reach and impact. Close collaboration with industry has proven to be highly productive, cost-eﬀective, and mutually beneﬁcial. Such collaborations shoul...
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Collaboration between these teams provides continuous im provement and immediate feedback, promoting software robustness and functionality

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As the complexity of scientiﬁc workﬂows grows, the re-analysis of data and reproducibility of results become signiﬁcant challenges

Observations Curation and preservation of data and analysis are essential to en sure the longevity and reproducibility of scientiﬁc research. As the complexity of scientiﬁc workﬂows grows, the re-analysis of data and reproducibility of results become signiﬁcant challenges. For many projects, the focus during their active phase is primarily on immediat e p...

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Opportunities Support is vital for the development and maintenance of robust fr ameworks for the preser- vation of data and associated metadata, including research softw are and workﬂows, to ensure their long-term accessibility and the reproducibility of scientiﬁc resu lts. Investment in decentralized storage networks would be valuable, t hereby leveragin...
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The High Performance Data Facility (HPDF) Project[24] has been es tablished to address gaps in data curation, preservation, and time-critical discovery a t existing ASCR facilities

Observations The US Department of Energy has initiated the Integrated Resear ch Infrastructure (IRI) Program to integrate its experimental facilities, data assets, and advanced computing re- sources. The High Performance Data Facility (HPDF) Project[24] has been es tablished to address gaps in data curation, preservation, and time-critical discovery a t e...
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Dat a physicists provide special- ized skills in data management and curation, algorithm development, a nd software engineer- ing

Observations Nuclear Physics is increasingly dependent upon high-performance c omputing and large- scale data analysis to address forefront research problems. Dat a physicists provide special- ized skills in data management and curation, algorithm development, a nd software engineer- ing. Scientiﬁc software developers drive innovation through the ad optio...
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The ﬁeld should acknowledge prominently that software and comput ing are essential components of many projects and experiments, to help ensure th at they receive adequate funding

Opportunities The workshop consensus advocated for the support of long-ter m positions for nuclear physicists, both theorists and experimentalists, with the skills and in terest in the develop- ment and stewardship of software. The ﬁeld should acknowledge prominently that software and comput ing are essential components of many projects and experiments, t...

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Specia l emphasis is placed on emerging computing systems and novel computing architecture s

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SciDAC is a partnership of sever al DOE Oﬃce of Science programs, including Nuclear Physics

NP-SciDAC partnership The SciDAC program (Scientiﬁc Discovery Through Advanced Compu ting, [37]) develops the scientiﬁc computing software and hardware infrastructure n eeded to advance scientiﬁc discovery using supercomputers. SciDAC is a partnership of sever al DOE Oﬃce of S...
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There are t hree classes of awards: • Elements: small-group awards for the creation and deployment of s ervices for a tar- 21 geted need

CSSI/NSF The Cyberinfrastructure for Sustained Scientiﬁc Innovation pro gram (CSSI) [40] of the National Science Foundation supports multi-disciplinary (multi-direc torate) projects in the development of cyberinfrastructure (CI), emphasizing integrat ed CI services, quantitati...
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Current research areas includ e the modeling of complex systems, measurements with sparse and noisy data, and reliable de tection of rare events

DNN/NNSA The Oﬃce of Defense Nuclear Nonproliferation (DNN) [41], in the DOE National Nuclear Security Administration (NNSA) [42], supports R&D in data analysis an d AI for nuclear non- proliferation and nuclear security. Current research areas includ e the modeling of complex...
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Simons Foundation The Simons Foundation Scientiﬁc Software Research Faculty Award [43] supports scien- tiﬁc software-focused research professor positions in existing a cademic programs, by provid- ing 50% support. The goal of this program is to stimulate the develop ment and m...
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The non-linear nature of QCD results in rich phenomenology, including the conﬁneme nt of quarks and gluons in hadrons

Lattice QCD Quantum Chromodynamics (QCD) is by its nature non-linear because the gluon, the QCD force moderator, carries color charge and interacts with oth er gluons. The non-linear nature of QCD results in rich phenomenology, including the conﬁneme nt of quarks and gluons in...
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QCD evolution

Partonic structure of hadrons The partonic structure of hadrons is of fundamental importance in physics, and its experi- mental and theoretical study are at the forefront of modern re search in Quantum Chromody- namics (QCD). Theoretical QCD calculations predict with precision...
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Nuclear properties Accurate calculations of nuclear properties, including structure, nuclear ﬁssion and fusion, electro-weak transitions, and response to electron- and neutrin o-scattering, require exten- sive computing resources. Signiﬁcant methodological advances fo r the nu...
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We are isolated from the stellar events that are resp onsible for this nu- cleosynthesis by distances measured in kiloparsecs and times measu red in billions of years

Nuclear astrophysics The lives and deaths of stars play an essential role in the origin of the chemical ele- ments [70, 71]. We are isolated from the stellar events that are resp onsible for this nu- cleosynthesis by distances measured in kiloparsecs and times measu red in bil...
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IV C 4) have generated vast, high-precision datasets to st udy the Quark-Gluon Plasma and to quantify its properties

Heavy-ion physics Experimental measurements of relativistic heavy-ion collisions at RH IC and the LHC (Ref. IV C 4) have generated vast, high-precision datasets to st udy the Quark-Gluon Plasma and to quantify its properties. High-energy nuclear collisions likewise probe the p...
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FRIB FRIB (Facility for Rare Isotope Beams), on the campus of Michigan S tate University, is the newest scientiﬁc user facility of the DOE SC Oﬃce of Nuclear Phys ics, with more than 1,800 registered users (FRIBUO [75]). FRIB enables scientists to ma ke discoveries in the prop...

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CEBAF hosts about 1900 users from around the world

JLab The Continuous Electron Beam Accelerator Facility (CEBAF) at Jeﬀe rson Lab (JLab)[76] is a unique facility for detailed exploration of the structure of hadro ns and atomic nuclei, and other aspects of QCD and the Standard Model. CEBAF hosts about 1900 users from around th...

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It has signiﬁcant overlap with the HEP neutrino and dark matter progr ams, and with other Fundamental Symmetry eﬀorts

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The data pipeline of modern detectors is typically continuous-streaming readout, with multiple levels of on-the-ﬂy data reduction, analysis, and event tagging

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Bayesian Inference A broad range of problems in NP require the determination of phenom enological con- straints on multidimensional model parameters from complex exper imental measurements, generically labeled “inverse problems.” One such example is the recons truction of the ...
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Event generators Theoretical calculations of physical processes which are of intere st in NP research are often not amenable to direct comparison with experimental measur ements. For example, high-energy QCD processes such as jet production are measured by experiments at RHIC ...
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Quantum information science Nuclear physicists are at the forefront of advancing quantum info rmation science, en- gineering and technology, through their close collaborations among technology companies, national laboratories and universities. These collaborations have s igniﬁ...
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Signiﬁcant emphasis is p laced on code sus- tainability, code stewardship, and the reproducibility of results

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MUSES creates software communities through short–term grants to academic groups for software developmen t related to their research

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Key questions inclu de the momentum and spatial distribution of quarks and gluons, and the dynamical gener ation of proton mass

QuantOm The QuantOm Collaboration [108] (QUAntum chromodynamics Nuclear TOMography) develops novel approaches to the femtoscale imaging of protons a nd nuclei in terms of their three-dimensional quark and gluon structure. Key questions inclu de the momentum and spatial distrib...
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Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.

[1] [1]

Observations NP research encompasses theoretical, experimental, and joint th eory/experiment eﬀorts with a broad range in scope and size. Some collaborations are funded speciﬁcally to develop software-as-a-service to the community, while others are primar ily science-driven, with the software a by-product to some degree. A collaborative approach is beneﬁc...

[2] [2]

Additional ﬂexibility in such programs, in terms of scope and size of award, would expand their reach and impact

Opportunities Multi-disciplinary programs such as SciDAC are highly beneﬁcial to the NP research enterprise. Additional ﬂexibility in such programs, in terms of scope and size of award, would expand their reach and impact. Close collaboration with industry has proven to be highly productive, cost-eﬀective, and mutually beneﬁcial. Such collaborations shoul...

[3] [3]

Collaboration between these teams provides continuous im provement and immediate feedback, promoting software robustness and functionality

Opportunities Software development and operations in large projects should not be regarded as separate eﬀorts. Collaboration between these teams provides continuous im provement and immediate feedback, promoting software robustness and functionality. The integration of innovative tools developed outside the traditiona l NP community can enhance software c...

[4] [4]

As the complexity of scientiﬁc workﬂows grows, the re-analysis of data and reproducibility of results become signiﬁcant challenges

Observations Curation and preservation of data and analysis are essential to en sure the longevity and reproducibility of scientiﬁc research. As the complexity of scientiﬁc workﬂows grows, the re-analysis of data and reproducibility of results become signiﬁcant challenges. For many projects, the focus during their active phase is primarily on immediat e p...

2000

[5] [5]

Opportunities Support is vital for the development and maintenance of robust fr ameworks for the preser- vation of data and associated metadata, including research softw are and workﬂows, to ensure their long-term accessibility and the reproducibility of scientiﬁc resu lts. Investment in decentralized storage networks would be valuable, t hereby leveragin...

[6] [6]

The High Performance Data Facility (HPDF) Project[24] has been es tablished to address gaps in data curation, preservation, and time-critical discovery a t existing ASCR facilities

Observations The US Department of Energy has initiated the Integrated Resear ch Infrastructure (IRI) Program to integrate its experimental facilities, data assets, and advanced computing re- sources. The High Performance Data Facility (HPDF) Project[24] has been es tablished to address gaps in data curation, preservation, and time-critical discovery a t e...

[7] [7]

Dat a physicists provide special- ized skills in data management and curation, algorithm development, a nd software engineer- ing

Observations Nuclear Physics is increasingly dependent upon high-performance c omputing and large- scale data analysis to address forefront research problems. Dat a physicists provide special- ized skills in data management and curation, algorithm development, a nd software engineer- ing. Scientiﬁc software developers drive innovation through the ad optio...

[8] [8]

The ﬁeld should acknowledge prominently that software and comput ing are essential components of many projects and experiments, to help ensure th at they receive adequate funding

Opportunities The workshop consensus advocated for the support of long-ter m positions for nuclear physicists, both theorists and experimentalists, with the skills and in terest in the develop- ment and stewardship of software. The ﬁeld should acknowledge prominently that software and comput ing are essential components of many projects and experiments, t...