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REVIEW 5 major objections 7 minor 54 references

The Evolution of Heavy-Ion Physics: A Data-Driven Analysis of Quark Matter Conferences

T0 review · 5 major / 7 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read Across 10,000+ Quark Matter presentations, heavy-ion physics shows growing diversity, a shift from facility-focused to phenomenon-focused research, and an increasingly integrated theory/experiment balance.

desk verdict Useful new dataset and honest descriptive stats, but the abstract's 'increasing integration' claim overreaches the paper's own stable 45-55 split. read the letter →

arxiv 2509.00160 v1 pith:2UZBQ2M5 submitted 2025-08-29 physics.soc-ph hep-exhep-phhep-thnucl-ex

Dong Jo Kim , Tero Lappeteläinen This is my paper · ORCID
classification physics.soc-phhep-exhep-phhep-thnucl-ex
keywords QuarkMatterconferencesheavy-ionphysicsconferenceanalyticsresearchtopictrendstheory-experimentbalancegeographicdiversityHerfindahl-Hirschmanindexscientometrics
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 paper is a quantitative meta-study of the Quark Matter conference series, the main meeting for heavy-ion physics, based on more than 10,000 presentations from 2011 to 2025. It tries to establish that the field is maturing in three measurable ways: participation is becoming more geographically and institutionally diverse, research focus is moving from naming facilities and detectors toward naming physical phenomena, and theory and experiment have settled into a stable, mutually reinforcing balance around an approximately 45–55 split. If true, this gives the heavy-ion community an evidence base for how its conference system distributes visibility and shapes research directions. It also offers other scientific communities a transferable template for tracking their own conference-driven evolution.

What carries the argument

The carrying object is the compiled Quark Matter corpus: more than 10,000 presentation records from official conference pages, each with title, authors, affiliations, and talk category (plenary, parallel, poster). The analysis runs on three machinery pieces built from that corpus: an affiliation-resolution system that maps institution strings to countries and cuts unknown affiliations below 3 percent; a keyword counter that removes stop words and tracks the relative frequency of physics concepts across years; and a binary theory/experiment classifier that labels a talk 'experimental' only if its title contains a detector or collaboration name (ALICE, ATLAS, CMS, STAR, PHENIX, and similar), o

What would settle it

Take a random sample of several hundred talks from the full period and label them from their abstracts or full texts instead of their titles, then compare with the paper's title-based theory/experiment labels; if a substantial share of titles without detector names turn out to be experimental, the 44–58 percent balance and the integration narrative would need revision. The facility-to-phenomenon trend can be tested the same way: recomputing keyword trends from abstract text would show whether the shift is a real change in research focus or only a naming convention.

Watch

Extended reading notes

Core claim

The paper's central claim is that the recent evolution of heavy-ion physics can be read directly from its conference record. Using titles, author affiliations, talk categories, and venue information from Quark Matter 2011–2025, the authors find a gradual shift from detector- and facility-branded presentations to phenomenon-centered ones: QGP properties and flow remain steady anchors, while small systems, ultra-peripheral collisions, machine learning, and Bayesian analyses rise in later years. They find that the number of countries and institutes represented has grown, that the Herfindahl-Hirschman index of country concentration has generally declined, and that Asian participation is rising,

Load-bearing premise

The load-bearing premise, stated by the authors in Section 3.4, is that a presentation's title is a faithful and complete proxy for its content: talks count as experimental only if the title names a detector or collaboration, and topics are read from title keywords after stop-word removal; if experimenters increasingly use phenomenon-based titles while theorists mention detectors for comparison, the reported theory/experiment balance and topic trends would misstate the field'

Editorial extensions

If this is right

  • If the observed trends continue, future Quark Matter programs will feature more phenomenon-branded, cross-cutting sessions and fewer detector-specific titles.
  • The theory/experiment ratio should stay near parity: after each new experimental run causes a temporary swing, the split returns to roughly 45–55.
  • Geographic diversification will likely continue gradually and mainly from Asia, because venue rotation and host-region effects tend to reproduce the current center-heavy distribution.
  • Machine learning and Bayesian inference have become recognized topic categories in the field's public vocabulary, not just private methods, so they will keep appearing as named tools in conference programs.

Reading between the lines

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

  • Editorial: because the theory/experiment split is derived from detector names in titles, experimental talks with phenomenon-based titles are counted as theoretical; re-running the classification on abstracts would likely shift the split, though the convergence pattern might persist in weaker form.
  • Editorial: the paper's balance-of-talk-types evidence is a proxy for integration, not a direct measure of collaboration; a sharper test would track co-authorship across theory and experiment groups or count presentations citing both theoretical and experimental references.
  • Extension: if the host-region effect is causal, holding Quark Matter in South America or Africa should measurably raise that region's talk share and plenary representation in that same year.
  • Extension: the metadata pipeline is transferable to other conference series, but the detector-name classification rule is field-specific and would need a domain-specific classifier.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

5 major / 7 minor

Summary. The paper compiles data from Quark Matter conference Indico pages for 2011–2025 (over 10,000 presentations) and reports descriptive statistics on venue rotation, country and institution representation, talk-type distributions, research-topic keywords, a theory/experiment classification based on title keywords, and a gender classification based on first names. The authors claim three main findings: the conference series has become more geographically diverse; research emphasis has shifted from facility-focused to phenomenon-focused topics; and theoretical and experimental approaches have become increasingly integrated, reflecting a maturing field.

Significance. If the findings are taken at face value, the paper provides a useful quantitative description of a major conference series over a 15-year period. The assembled dataset is large, the visualizations are mostly clear, and the diversity metrics (country counts, HHI, representation ratios) are appropriate tools for the descriptive claims about participation. The paper also acknowledges several data-quality limitations, which is commendable. However, the headline claim of 'increasing integration between theoretical and experimental approaches' is not supported by the evidence presented in Fig. 6, and the title-keyword classification used for that claim is an unvalidated proxy. The topic-trend claims similarly rest on hand-selected keyword dictionaries without statistical tests or uncertainty quantification. The paper's value is therefore conditional: the descriptive statistics on geography, institutions, and diversity are plausible, but the interpretive claims need to be either substantially revised or supported by additional validated measurements.

major comments (5)
  1. [Abstract; §3.4, Fig. 6] The central claim of 'increasing integration between theoretical and experimental approaches over time' is not supported by the data shown in Fig. 6. The figure displays experimental shares fluctuating between roughly 42% and 58% with no monotonic trend; the text itself reports 'typically a roughly 45-55 split' and notes that the most recent conferences show a 'balanced distribution' with experimental presentations at 49-54%. No trend test, uncertainty band, or collaboration metric is provided. At best, Fig. 6 shows a stable or fluctuating balance of talk labels, which is not equivalent to integration. Please either remove/rephrase the 'increasing integration' claim or replace it with a direct measure of theory-experiment collaboration (e.g., co-authorship patterns, joint theory/experiment sessions, or explicit collaboration indicators in the dataset).
  2. [§3.4, classification rule] The theory/experiment classification rests entirely on the rule that a talk is experimental if and only if its title contains detector or collaboration names such as ALICE, ATLAS, CMS, STAR, or PHENIX, and theoretical otherwise. This is an unvalidated and plausibly time-varying proxy. Many experimental talks are titled by phenomenon (e.g., 'Measurement of elliptic flow...') without naming a detector, while theory talks often mention detectors for comparison. If titling conventions changed between 2011 and 2025, the balance in Fig. 6 would be an artifact of naming practices rather than a measure of community composition. Please validate the classifier on a stratified random sample of titles (with manual labels), report agreement rates, and test sensitivity to the detector-name list. Without this, the interpretation of Fig. 6 cannot be sustained.
  3. [§3.3, Fig. 4 and Fig. 5] The topic-evolution analysis relies on keywords extracted from titles after stop-word removal, but the paper does not specify the keyword dictionaries, the handling of abbreviations (e.g., 'HF', 'UPC', 'QGP'), or the normalization procedure beyond 'relative frequency.' The claims that certain topics 'show clear temporal trends' and that the field shifted 'from facility-focused to phenomenon-focused' are not accompanied by any statistical trend test, confidence intervals, or sensitivity analysis with respect to keyword choice. Given that Fig. 4 appears to show non-monotonic curves, the reader cannot tell which rises/falls are meaningful. Please provide the keyword lists, the normalization formula, and at least simple trend tests (or bootstrap confidence bands).
  4. [§3.1–§3.7, general] Most temporal claims in the paper—e.g., 'Asian participation shows a gradual upward trend' (Fig. 7), 'female representation has shown a gradual increase' (Fig. 13), and 'HHI values show a declining trend' (Fig. 11)—are made without any statistical test, error bars, or uncertainty quantification. Since these are core descriptive findings, the absence of even basic trend tests (e.g., Kendall's tau or linear regression with confidence intervals) makes it difficult to distinguish signal from sampling fluctuation. This is particularly important for the gender analysis, where the 'unknown' category is acknowledged to be non-negligible.
  5. [§2; Appendix B] The paper acknowledges substantial data-quality issues: inconsistent JSON formats, incomplete participant information, manual review and correction, and a system that is 'not fully automated.' Appendix B specifically notes that conferences from 2011, 2012, 2015, and 2023 had inconsistent data and that some advisory-committee information came from no-longer-accessible websites. Given this manual intervention, the authors should make the cleaned dataset and analysis scripts publicly available, and they should quantify how many records were manually corrected or imputed. Without this, the reproducibility of the descriptive statistics cannot be assessed.
minor comments (7)
  1. [§3.6, Fig. 10 caption] The caption says 'only countries with at least 5 parallel talks are included to ensure statistical significance', but a minimum count threshold is not a statistical significance test. Please rephrase to 'to reduce small-sample instability' and, ideally, add confidence intervals for the representation ratios.
  2. [§3.4, text] The funding-program examples (JETSCAPE, Center of Excellence in Quark Matter, SFB 1225, CRC-TR 211) are external anecdotes, not measurements from the conference dataset. They are useful context, but they should be explicitly labeled as such and not used as evidence for trends inferred from Fig. 6.
  3. [Fig. 6] The text says experimental contributions 'typically comprise between 44% and 58%' while the figure labels include 42% (e.g., 2011 or 2012). Please reconcile the stated range with the plotted values.
  4. [§3.7, Fig. 13 caption] Typo: 'displayes' should be 'displays'.
  5. [Table 1] The column headers 'Y ear' and 'T alks' contain stray spaces; please correct.
  6. [§3.6, text] The phrase 'an measure of representational equity' should be 'a measure of representational equity'.
  7. [§4 Discussion] The Discussion repeats the 'growing interactions between theoretical and experimental groups' claim. This should be revised consistently with whatever conclusion is supported by the validated analysis, because the current wording overstates what Fig. 6 shows.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper is descriptive statistics; the theory/experiment split is an explicit operationalization, and the 'integration' inference is an interpretation, not a derivation from a fitted parameter or a self-citation chain.

full rationale

The paper's derivation chain is data collection from Indico, manual/rule-based affiliation resolution, keyword frequency counts, and a title-based theory/experiment classification (Section 3.4: 'if a presentation's title contains specific experiment or detector names... it is categorized as experimental; otherwise, it is classified as theoretical'). No parameters are fitted to a subset of the data and then used to 'predict' a closely related quantity; the paper reports descriptive statistics and trends. The main interpretive claim—'increasing integration between theoretical and experimental approaches'—is not a mathematical consequence of the measured quantities. Fig. 6 shows a roughly stable 45–55 split with fluctuations; calling this 'integration' is a construct-validity/overreach concern (the data do not show a monotonic increase, and title-keyword balance is not a direct measure of collaboration), but it is not circular because 'integration' is not defined as the balance nor is the balance derived from the integration claim. The keyword categories in Section 3.3 are hand-selected proxies; while this limits what the topic trends can establish, the trends are not defined in terms of the conclusions they are used to support. The self-citations in the Introduction (e.g., [23]–[25]) and the funding-program example [43] (the authors' own Center of Excellence) are background/illustrative evidence, not the load-bearing derivation of any result; removing them would not change the computed figures. The paper's own stated limitations (e.g., gender-guesser uncertainty, manual affiliation review) and the proxy nature of the title-based classification concern measurement validity, not circular reasoning. No step in the claimed derivation reduces by construction to its own inputs.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The analysis depends on unpublished data-cleaning choices (keyword dictionaries, manual affiliation mapping) and on several proxy assumptions about titles and names. No free physical parameters are fitted; the free parameters are analytical thresholds and dictionaries chosen by the authors.

free parameters (2)
  • minimum_parallel_talks_threshold = 5
    Countries with fewer than 5 parallel talks are excluded from the representation ratio in Section 3.6 to avoid small-sample anomalies; this choice affects the distributions shown.
  • topic_keyword_dictionaries = hand-selected keywords such as QGP, Flow, Small Systems, UPC, CME, Bayesian, Machine Learning
    Topic trends in Figure 4 depend on hand-selected keyword sets and stop-word lists; no dictionary is published, so the trend definitions are not auditable.
assumptions (5)
  • domain assumption Indico records for 2011-2025 are complete and representative of the conference contributions.
    All counts come from public Indico pages; Appendix B notes inconsistent JSON formats for 2011, 2012, 2015, 2023, so completeness is assumed but not verified.
  • domain assumption Presentation titles are a valid proxy for research content.
    Topic trends (Section 2, Figure 4) and theory/experiment labels (Section 3.4) are based solely on title text.
  • ad hoc to paper Experimental talks name their detector or collaboration in the title; otherwise the talk is theoretical.
    Section 3.4 classification rule; no validation of this rule against abstracts or proceedings is provided.
  • domain assumption Gender can be inferred from first names using the gender-guesser library.
    Section 3.7 uses name-based classification; authors note limitations for cultural variability and non-binary identities.
  • standard math The Herfindahl-Hirschman Index computed from country shares is a valid measure of diversity.
    Section 3.6 applies the standard HHI formula; no issue with the formula itself.

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Cite this review

Pith. "Pith review of The Evolution of Heavy-Ion Physics: A Data-Driven Analysis of Quark Matter Conferences." pith.science (2026). https://pith.science/paper/2UZBQ2M5

@misc{pith2026250900160,
  author       = {Pith},
  title        = {Pith review of: The Evolution of Heavy-Ion Physics: A Data-Driven Analysis of Quark Matter Conferences},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2UZBQ2M5}},
  note         = {Machine review of arXiv:2509.00160}
}
read the original abstract

This paper presents a data-driven analysis of Quark Matter conferences from 2011 to 2025, investigating trends in geographical representation, research emphasis, and methodological strategies. Using a dataset of over 10,000 presentations, the evolution of heavy-ion physics through its premier conference series is examined. The distribution of presentations across countries and institutions shows the global reach of the field while highlighting opportunities for broader international engagement. Research topics show clear temporal trends, with certain physics concepts rising and falling in prominence, and a gradual shift from facility-focused to phenomenon-focused research. The analysis reveals increasing integration between theoretical and experimental approaches over time, reflecting a maturing field where these complementary domains strengthen and enhance each other. These findings provide quantitative insights that the evolution of heavy-ion physics is strengthened by international collaboration at conferences. The analytical methods developed here could help other scientific communities understand their own patterns of knowledge sharing and development.

Figures

Figures reproduced from arXiv: 2509.00160 by the authors.

Figure 1
Figure 1. Historical timeline of Quark Matter conferences from 1980 to 2025. The top panel [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Geographical distribution of Quark Matter conference venues from 2011 to 2025. The [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Statistical overview of Quark Matter conferences from 2011 to 2025. The top panel [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figures from the paper (10 more)
Figure 4
Figure 4. Figure 4: Analysis of research topics in Quark Matter conferences from 2011 to 2025. The [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 5
Figure 5. Figure 5: Trends in experimental facilities mentions at Quark Matter conferences from 2011 [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Evolution of theory versus experimental contributions in Quark Matter conferences [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: Detailed view of regional representation at Quark Matter conferences from 2011 to [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]
Figure 8
Figure 8. Figure 8: Distribution of plenary talks by country across Quark Matter conferences from 2011 [PITH_FULL_IMAGE:figures/full_fig_p013_8.png]
Figure 9
Figure 9. Figure 9: Distribution of parallel talks by country across Quark Matter conferences from 2011 [PITH_FULL_IMAGE:figures/full_fig_p014_9.png]
Figure 10
Figure 10. Figure 10: Representation ratio between plenary and parallel talks by country. This chart com [PITH_FULL_IMAGE:figures/full_fig_p015_10.png]
Figure 11
Figure 11. Figure 11: Evolution of diversity metrics over time. The blue line shows the number of countries [PITH_FULL_IMAGE:figures/full_fig_p016_11.png]
Figure 12
Figure 12. Figure 12: Institute contributions across Quark Matter conferences from 2011 to 2025. This [PITH_FULL_IMAGE:figures/full_fig_p017_12.png]
Figure 13
Figure 13. Figure 13: Gender diversity in Quark Matter conferences. The left panel displays the gender [PITH_FULL_IMAGE:figures/full_fig_p018_13.png]

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Reference graph

Works this paper leans on

54 extracted references · 31 canonical work pages

  1. [1]

    Physics of Strongly coupled Quark-Gluon Plasma

    Edward Shuryak. Physics of Strongly coupled Quark-Gluon Plasma. Prog. Part. Nucl. Phys., 62:48–101, 2009. doi: 10.1016/j.ppnp.2008.09.001

    work page doi:10.1016/j.ppnp.2008.09.001 2009

  2. [2]

    Kovtun, Dan T

    P. Kovtun, Dan T. Son, and Andrei O. Starinets. Viscosity in strongly interacting quantum field theories from black hole physics. Phys. Rev. Lett., 94:111601, 2005. doi: 10.1103/ PhysRevLett.94.111601

    work page 2005

  3. [3]

    Experimental and theoretical challenges in the search for the quark gluon plasma: The STAR Collaboration’s critical assessment of the evidence from RHIC collisions

    John Adams et al. Experimental and theoretical challenges in the search for the quark gluon plasma: The STAR Collaboration’s critical assessment of the evidence from RHIC collisions. Nucl. Phys., A757:102–183, 2005. doi: 10.1016/j.nuclphysa.2005.03.085

    doi:10.1016/j.nuclphysa.2005.03.085 2005

  4. [4]

    Adcox et al

    K. Adcox et al. Formation of dense partonic matter in relativistic nucleus-nucleus collisions at RHIC: Experimental evaluation by the PHENIX collaboration. Nucl. Phys., A757:184– 283, 2005. doi: 10.1016/j.nuclphysa.2005.03.086

    doi:10.1016/j.nuclphysa.2005.03.086 2005

  5. [5]

    Arsene et al

    I. Arsene et al. Quark gluon plasma and color glass condensate at RHIC? The Perspective from the BRAHMS experiment. Nucl. Phys., A757:1–27, 2005. doi: 10.1016/j.nuclphysa. 2005.02.130

    doi:10.1016/j.nuclphysa 2005

  6. [6]

    B. B. Back et al. The PHOBOS perspective on discoveries at RHIC. Nucl. Phys., A757: 28–101, 2005. doi: 10.1016/j.nuclphysa.2005.03.084

    doi:10.1016/j.nuclphysa.2005.03.084 2005

  7. [7]

    The ALICE experiment: a journey through QCD

    Shreyasi Acharya et al. The ALICE experiment: a journey through QCD. Eur. Phys. J. C, 84(8):813, 2024. doi: 10.1140/epjc/s10052-024-12935-y

    doi:10.1140/epjc/s10052-024-12935-y 2024

  8. [8]

    Heavy Ion Collisions: The Big Picture and the Big Questions

    Wit Busza, Krishna Rajagopal, and Wilke van der Schee. Heavy Ion Collisions: The Big Picture and the Big Questions. Ann. Rev. Nucl. Part. Sci., 68:339–376, 2018. doi: 10.1146/annurev-nucl-101917-020852

    doi:10.1146/annurev-nucl-101917-020852 2018

Show all 54 references
  1. [9]

    Brambilla et al

    N. Brambilla et al. QCD and Strongly Coupled Gauge Theories: Challenges and Perspec- tives. Eur. Phys. J. C, 74(10):2981, 2014. doi: 10.1140/epjc/s10052-014-3026-9

    2014 doi

  2. [10]

    The phase diagram of dense QCD

    Kenji Fukushima and Tetsuo Hatsuda. The phase diagram of dense QCD. Rept. Prog. Phys., 74:014001, 2011. doi: 10.1088/0034-4885/74/1/014001

    2011 doi

  3. [11]

    The Hot QCD White Paper: Exploring the Phases of QCD at RHIC and the LHC

    Yasuyuki Akiba et al. The Hot QCD White Paper: Exploring the Phases of QCD at RHIC and the LHC. arXiv:1502.02730 [nucl-ex], 2 2015

    2015 arXiv

  4. [12]

    Bernhard, J

    Jonah E. Bernhard, J. Scott Moreland, Steffen A. Bass, Jia Liu, and Ulrich Heinz. Applying Bayesian parameter estimation to relativistic heavy-ion collisions: simultaneous character- ization of the initial state and quark-gluon plasma medium. Phys. Rev., C94(2):024907,

  5. [13]

    Everett et al

    D. Everett et al. Multisystem Bayesian constraints on the transport coefficients of QCD matter. Phys. Rev. C, 103(5):054904, 2021. doi: 10.1103/PhysRevC.103.054904

    2021 doi

  6. [14]

    Bayesian analysis of heavy ion collisions with the heavy ion computational framework Trajectum

    Govert Nijs, Wilke van der Schee, Umut G¨ ursoy, and Raimond Snellings. Bayesian analysis of heavy ion collisions with the heavy ion computational framework Trajectum. Phys. Rev. C, 103(5):054909, 2021. doi: 10.1103/PhysRevC.103.054909. 20

    2021 doi

  7. [15]

    Extraction of Heavy-Flavor Transport Coefficients in QCD Matter

    Ralf Rapp et al. Extraction of Heavy-Flavor Transport Coefficients in QCD Matter. Nucl. Phys. A, 979:21–86, 2018. doi: 10.1016/j.nuclphysa.2018.07.006

    2018 doi

  8. [16]

    Giuliano Giacalone, Chun Shen, and Fernando G. Gardim. Mapping the QCD phase diagram with relativistic nuclear collisions: Status and future directions. Prog. Part. Nucl. Phys., 132:104034, 2023. doi: 10.1016/j.ppnp.2023.104034

    2023

  9. [17]

    Bernhard, Peter W

    Jonah E. Bernhard, Peter W. Marcy, Christopher E. Coleman-Smith, Snehalata Huzur- bazar, Robert L. Wolpert, and Steffen A. Bass. Quantifying properties of hot and dense QCD matter through systematic model-to-data comparison. Phys. Rev. C, 91(5):054910,

  10. [18]

    Bernhard, J

    Jonah E. Bernhard, J. Scott Moreland, Steffen A. Bass, Jia Liu, and Ulrich Heinz. Ap- plying bayesian parameter estimation to relativistic heavy-ion collisions: Simultaneous characterization of the initial state and quark-gluon plasma medium. Phys. Rev. C, 94: 024907, Aug 2016...

    2016 doi

  11. [19]

    Bernhard

    Jonah E. Bernhard. Bayesian parameter estimation for relativistic heavy-ion collisions. PhD thesis, Duke U., 4 2018

    2018

  12. [20]

    Bernhard, J

    Jonah E. Bernhard, J. Scott Moreland, and Steffen A. Bass. Bayesian estimation of the specific shear and bulk viscosity of quark-gluon plasma. Nature Physics, 15:1113–1117,

  13. [21]

    Eskola, Pasi Huovinen, Harri Niemi, Risto Paatelainen, and Peter Petreczky

    Jussi Auvinen, Kari J. Eskola, Pasi Huovinen, Harri Niemi, Risto Paatelainen, and Peter Petreczky. Temperature dependence of η/s of strongly interacting matter: Effects of the equation of state and the parametric form of ( η/s)(T ). Phys. Rev. C, 102(4):044911, 2020. doi: 10.1...

    2020 doi

  14. [22]

    A transverse momentum differential global analysis of Heavy Ion Collisions

    Govert Nijs, Wilke van der Schee, Umut G¨ ursoy, and Raimond Snellings. A transverse momentum differential global analysis of Heavy Ion Collisions. Phys. Rev. Lett., 126(20): 202301, 2021. doi: 10.1103/PhysRevLett.126.202301

    2021 doi

  15. [23]

    J. E. Parkkila, A. Onnerstad, and D. J. Kim. Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma with additional flow harmonic observables. Phys. Rev. C, 104:054904, Nov 2021. doi: 10.1103/PhysRevC.104.054904. URL https: //link.aps.org/doi/10...

    2021 doi

  16. [24]

    J. E. Parkkila, A. Onnerstad, S. F. Taghavi, C. Mordasini, A. Bilandzic, M. Virta, and D. J. Kim. New constraints for QCD matter from improved Bayesian parameter estimation in heavy-ion collisions at LHC. Phys. Lett. B, 835:137485, 2022. doi: 10.1016/j.physletb. 2022.137485

    2022

  17. [25]

    Enhancing Bayesian parameter es- timation by adapting to multiple energy scales in RHIC and LHC heavy-ion collisions

    Maxim Virta, Jasper Parkkila, and Dong Jo Kim. Enhancing Bayesian parameter es- timation by adapting to multiple energy scales in RHIC and LHC heavy-ion collisions. arXiv:2411.01932 [hep-ph], 11 2024

    2024 arXiv

  18. [26]

    Citron et al

    Z. Citron et al. Report from Working Group 5: Future physics opportunities for high- density QCD at the LHC with heavy-ion and proton beams. CERN Yellow Rep. Monogr., 7:1159–1410, 2019. doi: 10.23731/CYRM-2019-007.1159

    2019 doi

  19. [27]

    Apollinari, I

    G. Apollinari, I. B´ ejar Alonso, O. Br¨ uning, M. Lamont, and L. Rossi. High-Luminosity Large Hadron Collider (HL-LHC): Technical Design Report V. 0.1. CERN Yellow Rep. Monogr., 4:1–516, 2017. doi: 10.23731/CYRM-2017-004. 21

    2017 doi

  20. [28]

    Bruce et al

    R. Bruce et al. HL-LHC operational scenarios for Pb-Pb and p-Pb operation. CERN Yellow Rep. Monogr., 7:293–318, 2022. doi: 10.23731/CYRM-2022-001.293

    2022 doi

  21. [29]

    ALICE 3: A next generation LHC heavy-ion experiment

    Dagmar Adamov´ a et al. ALICE 3: A next generation LHC heavy-ion experiment. Technical report, CERN, 11 2022

    2022

  22. [30]

    The Phase-2 Upgrade of the CMS Endcap Calorimeter

    CMS Collaboration. The Phase-2 Upgrade of the CMS Endcap Calorimeter. Technical design report, CERN, 11 2017. URL https://cds.cern.ch/record/2293646

    2017

  23. [31]

    ATLAS Phase-II Upgrade Scoping Document

    ATLAS Collaboration. ATLAS Phase-II Upgrade Scoping Document. Technical report, CERN, 9 2015. URL https://cds.cern.ch/record/2055248

    2015

  24. [32]

    Jasmine Brewer, Abhijit Majumder, and Matthew D. Sievert. Opportunities for jet mea- surements in heavy-ion collisions at the HL-LHC. Phys. Rev. C, 103(6):064908, 2021. doi: 10.1103/PhysRevC.103.064908

    2021 doi

  25. [33]

    Collective flow and viscosity in relativistic heavy- ion collisions

    Ulrich Heinz and Raimond Snellings. Collective flow and viscosity in relativistic heavy- ion collisions. Ann. Rev. Nucl. Part. Sci., 63:123–151, 2013. doi: 10.1146/annurev-nucl- 102212-170540

    2013 doi

  26. [34]

    Experimental overview on small collision systems at the LHC

    Constantin Loizides. Experimental overview on small collision systems at the LHC. Nucl. Phys. A, 956:200–207, 2016. doi: 10.1016/j.nuclphysa.2016.04.022

    2016 doi

  27. [35]

    Bertulani, Spencer R

    Carlos A. Bertulani, Spencer R. Klein, and Joakim Nystrand. Physics of ultra-peripheral nuclear collisions. Ann. Rev. Nucl. Part. Sci., 55:271–310, 2005. doi: 10.1146/annurev. nucl.55.090704.151526

    2005

  28. [36]

    Historical introduction to ultra peripheral collisions

    Carlos Bertulani. Historical introduction to ultra peripheral collisions. Phys. Proc. UPC, 1:1, 2024. doi: 10.17161/e6epmx12

    2024 doi

  29. [37]

    Medium Response and Jet–Hadron Correlations in Relativistic Heavy-Ion Collisions

    Shanshan Cao and Guang-You Qin. Medium Response and Jet–Hadron Correlations in Relativistic Heavy-Ion Collisions. Ann. Rev. Nucl. Part. Sci., 73:205–229, 2023. doi: 10.1146/annurev-nucl-112822-031317

    2023 doi

  30. [38]

    Flavor dependence of jet quenching in heavy-ion collisions from a Bayesian analysis

    Shan-Liang Zhang, Enke Wang, Hongxi Xing, and Ben-Wei Zhang. Flavor dependence of jet quenching in heavy-ion collisions from a Bayesian analysis. Phys. Lett. B, 850:138549,

  31. [39]

    Heavy and light flavor jet quenching in heavy-ion collisions in a perturbative QCD approach

    Wen-Jing Xing, Shanshan Cao, Guang-You Qin, and Hongxi Xing. Heavy and light flavor jet quenching in heavy-ion collisions in a perturbative QCD approach. Nucl. Phys. A, 1005: 121829, 2021. doi: 10.1016/j.nuclphysa.2020.121829

    2021

  32. [40]

    Flavor hierarchy of jet quenching in relativistic heavy-ion collisions

    Wen-Jing Xing, Shanshan Cao, Guang-You Qin, and Hongxi Xing. Flavor hierarchy of jet quenching in relativistic heavy-ion collisions. Phys. Lett. B, 805:135424, 2020. doi: 10.1016/j.physletb.2020.135424

    2020

  33. [41]

    Machine learning for high energy heavy ion collisions

    Long-Gang Pang. Machine learning for high energy heavy ion collisions. Nucl. Phys. A, 1005:121972, 2021. doi: 10.1016/j.nuclphysa.2020.121972

    2021

  34. [42]

    Kharzeev, Jinfeng Liao, Sergei A

    Dmitri E. Kharzeev, Jinfeng Liao, Sergei A. Voloshin, and Gang Wang. Chiral magnetic effect in high-energy nuclear collisions — a status report. Prog. Part. Nucl. Phys., 88:1–28,

  35. [43]

    Centre of excellence in quark matter

    Research Council of Finland. Centre of excellence in quark matter. Finnish Centres of Excellence Programme, Research Council of Finland, 2022. URL https://www.aka.fi/en/ research-funding/programmes-and-other-funding-schemes/finnish-centres-of-excellence/. 22

    2022

  36. [44]

    Burke et al

    Karen M. Burke et al. Extracting the jet transport coefficient from jet quenching in high- energy heavy-ion collisions. Phys. Rev. C, 90(1):014909, 2014. doi: 10.1103/PhysRevC. 90.014909. U.S. Department of Energy under Contract Nos.DE-AC02-05CH11231, DE- FG02-93ER40764, DE-AC...

    2014 doi

  37. [45]

    Exploring the Universe through Strong Interactions

    EUSTRONG ERC. Exploring the Universe through Strong Interactions. European Re- search Council (ERC) Grant, 2020. URL https://cordis.europa.eu/project/id/101020842. H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) (Grant agreement ID: 101020842)

    2020

  38. [46]

    Isolating - and Quantifying - Strange and Charm Quarks in the QCD Matter

    SFB 1225 ISOQUANT. Isolating - and Quantifying - Strange and Charm Quarks in the QCD Matter. Collaborative Research Center funded by the German Research Foundation (DFG), 2019. URL https://www.isoquant.uni-heidelberg.de. Funded by the German Re- search Foundation (DFG) under G...

    2019

  39. [47]

    doi: 10.1016/j.ppnp.2016.01.001

    2016 doi

  40. [48]

    Stephen A. Rhoades. The herfindahl-hirschman index. Federal Reserve Bulletin, 79:188– 189, 1993

    1993

  41. [49]

    Gender guesser: A python library for guessing gender from first names

    Marcos Vanetta. Gender guesser: A python library for guessing gender from first names. https://github.com/lead-ratings/gender-guesser, 2015. Accessed: 2023

    2015

  42. [50]

    Iupap policy statements - quark matter 2025

    IUPAP. Iupap policy statements - quark matter 2025. Website, 2025. URL https://indico. cern.ch/event/1334113/page/38092-iupap. Accessed April 2025. A Quark Matter Conference Proceedings This appendix provides a list of all Quark Matter conference proceedings from 1980 to 2025,...

    2025

  43. [52]

    Strong-Interaction Matter under Extreme Conditions

    CRC-TR 211 Collaboration. Strong-Interaction Matter under Extreme Conditions. Collaborative Research Center, 2020. URL https://www.rhein-main-universitaeten.de/ en/research/strong-interaction-matter-under-extreme-conditions. Project No. 315477589, funded by the Deutsche Forsch...

    2020

  44. [2015]

    doi: 10.1103/PhysRevC.91.054910

    doi

  45. [2019]

    doi: 10.1038/s41567-019-0611-8

    ISSN 1745-2481. doi: 10.1038/s41567-019-0611-8. URL https://doi.org/10.1038/ s41567-019-0611-8

    doi

  46. [2024]

    doi: 10.1016/j.physletb.2024.138549

    2024

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.