{% raw %} Title: Create a Markdown Blog Post Integrating Research Details and a Featured Paper ==================================================================================== This task involves generating a Markdown file (ready for a GitHub-served Jekyll site) that integrates our research details with a featured research paper. The output must follow the exact format and conventions described below. ==================================================================================== Output Format (Markdown): ------------------------------------------------------------------------------------ --- layout: post title: "DAMA/LIBRA and dark matter: decisive tension or contrived cancellation" date: 2025-10-06 categories: papers --- ![AI generated image](/assets/images/posts/2025-10-06-2510.05216.png) Will Handley Content generated by [gemini-2.5-pro](https://deepmind.google/technologies/gemini/) using [this prompt](/prompts/content/2025-10-06-2510.05216.txt). Image generated by [imagen-4.0-generate-001](https://deepmind.google/technologies/gemini/) using [this prompt](/prompts/images/2025-10-06-2510.05216.txt). ------------------------------------------------------------------------------------ ==================================================================================== Please adhere strictly to the following instructions: ==================================================================================== Section 1: Content Creation Instructions ==================================================================================== 1. **Generate the Page Body:** - Write a well-composed, engaging narrative that is suitable for a scholarly audience interested in advanced AI and astrophysics. - Ensure the narrative is original and reflective of the tone and style and content in the "Homepage Content" block (provided below), but do not reuse its content. - Use bullet points, subheadings, or other formatting to enhance readability. 2. **Highlight Key Research Details:** - Emphasize the contributions and impact of the paper, focusing on its methodology, significance, and context within current research. - Specifically highlight the lead author ({'name': 'Giorgio Busoni'}). When referencing any author, use Markdown links from the Author Information block (choose academic or GitHub links over social media). 3. **Integrate Data from Multiple Sources:** - Seamlessly weave information from the following: - **Paper Metadata (YAML):** Essential details including the title and authors. - **Paper Source (TeX):** Technical content from the paper. - **Bibliographic Information (bbl):** Extract bibliographic references. - **Author Information (YAML):** Profile details for constructing Markdown links. - Merge insights from the Paper Metadata, TeX source, Bibliographic Information, and Author Information blocks into a coherent narrative—do not treat these as separate or isolated pieces. - Insert the generated narrative between the HTML comments: and 4. **Generate Bibliographic References:** - Review the Bibliographic Information block carefully. - For each reference that includes a DOI or arXiv identifier: - For DOIs, generate a link formatted as: [10.1234/xyz](https://doi.org/10.1234/xyz) - For arXiv entries, generate a link formatted as: [2103.12345](https://arxiv.org/abs/2103.12345) - **Important:** Do not use any LaTeX citation commands (e.g., `\cite{...}`). Every reference must be rendered directly as a Markdown link. For example, instead of `\cite{mycitation}`, output `[mycitation](https://doi.org/mycitation)` - **Incorrect:** `\cite{10.1234/xyz}` - **Correct:** `[10.1234/xyz](https://doi.org/10.1234/xyz)` - Ensure that at least three (3) of the most relevant references are naturally integrated into the narrative. - Ensure that the link to the Featured paper [2510.05216](https://arxiv.org/abs/2510.05216) is included in the first sentence. 5. **Final Formatting Requirements:** - The output must be plain Markdown; do not wrap it in Markdown code fences. - Preserve the YAML front matter exactly as provided. ==================================================================================== Section 2: Provided Data for Integration ==================================================================================== 1. **Homepage Content (Tone and Style Reference):** ```markdown --- layout: home --- ![AI generated image](/assets/images/index.png) The Handley Research Group stands at the forefront of cosmological exploration, pioneering novel approaches that fuse fundamental physics with the transformative power of artificial intelligence. We are a dynamic team of researchers, including PhD students, postdoctoral fellows, and project students, based at the University of Cambridge. Our mission is to unravel the mysteries of the Universe, from its earliest moments to its present-day structure and ultimate fate. We tackle fundamental questions in cosmology and astrophysics, with a particular focus on leveraging advanced Bayesian statistical methods and AI to push the frontiers of scientific discovery. Our research spans a wide array of topics, including the [primordial Universe](https://arxiv.org/abs/1907.08524), [inflation](https://arxiv.org/abs/1807.06211), the nature of [dark energy](https://arxiv.org/abs/2503.08658) and [dark matter](https://arxiv.org/abs/2405.17548), [21-cm cosmology](https://arxiv.org/abs/2210.07409), the [Cosmic Microwave Background (CMB)](https://arxiv.org/abs/1807.06209), and [gravitational wave astrophysics](https://arxiv.org/abs/2411.17663). ### Our Research Approach: Innovation at the Intersection of Physics and AI At The Handley Research Group, we develop and apply cutting-edge computational techniques to analyze complex astronomical datasets. Our work is characterized by a deep commitment to principled [Bayesian inference](https://arxiv.org/abs/2205.15570) and the innovative application of [artificial intelligence (AI) and machine learning (ML)](https://arxiv.org/abs/2504.10230). **Key Research Themes:** * **Cosmology:** We investigate the early Universe, including [quantum initial conditions for inflation](https://arxiv.org/abs/2002.07042) and the generation of [primordial power spectra](https://arxiv.org/abs/2112.07547). We explore the enigmatic nature of [dark energy, using methods like non-parametric reconstructions](https://arxiv.org/abs/2503.08658), and search for new insights into [dark matter](https://arxiv.org/abs/2405.17548). A significant portion of our efforts is dedicated to [21-cm cosmology](https://arxiv.org/abs/2104.04336), aiming to detect faint signals from the Cosmic Dawn and the Epoch of Reionization. * **Gravitational Wave Astrophysics:** We develop methods for [analyzing gravitational wave signals](https://arxiv.org/abs/2411.17663), extracting information about extreme astrophysical events and fundamental physics. * **Bayesian Methods & AI for Physical Sciences:** A core component of our research is the development of novel statistical and AI-driven methodologies. This includes advancing [nested sampling techniques](https://arxiv.org/abs/1506.00171) (e.g., [PolyChord](https://arxiv.org/abs/1506.00171), [dynamic nested sampling](https://arxiv.org/abs/1704.03459), and [accelerated nested sampling with $\beta$-flows](https://arxiv.org/abs/2411.17663)), creating powerful [simulation-based inference (SBI) frameworks](https://arxiv.org/abs/2504.10230), and employing [machine learning for tasks such as radiometer calibration](https://arxiv.org/abs/2504.16791), [cosmological emulation](https://arxiv.org/abs/2503.13263), and [mitigating radio frequency interference](https://arxiv.org/abs/2211.15448). We also explore the potential of [foundation models for scientific discovery](https://arxiv.org/abs/2401.00096). **Technical Contributions:** Our group has a strong track record of developing widely-used scientific software. Notable examples include: * [**PolyChord**](https://arxiv.org/abs/1506.00171): A next-generation nested sampling algorithm for Bayesian computation. * [**anesthetic**](https://arxiv.org/abs/1905.04768): A Python package for processing and visualizing nested sampling runs. * [**GLOBALEMU**](https://arxiv.org/abs/2104.04336): An emulator for the sky-averaged 21-cm signal. * [**maxsmooth**](https://arxiv.org/abs/2007.14970): A tool for rapid maximally smooth function fitting. * [**margarine**](https://arxiv.org/abs/2205.12841): For marginal Bayesian statistics using normalizing flows and KDEs. * [**fgivenx**](https://arxiv.org/abs/1908.01711): A package for functional posterior plotting. * [**nestcheck**](https://arxiv.org/abs/1804.06406): Diagnostic tests for nested sampling calculations. ### Impact and Discoveries Our research has led to significant advancements in cosmological data analysis and yielded new insights into the Universe. Key achievements include: * Pioneering the development and application of advanced Bayesian inference tools, such as [PolyChord](https://arxiv.org/abs/1506.00171), which has become a cornerstone for cosmological parameter estimation and model comparison globally. * Making significant contributions to the analysis of major cosmological datasets, including the [Planck mission](https://arxiv.org/abs/1807.06209), providing some of the tightest constraints on cosmological parameters and models of [inflation](https://arxiv.org/abs/1807.06211). * Developing novel AI-driven approaches for astrophysical challenges, such as using [machine learning for radiometer calibration in 21-cm experiments](https://arxiv.org/abs/2504.16791) and [simulation-based inference for extracting cosmological information from galaxy clusters](https://arxiv.org/abs/2504.10230). * Probing the nature of dark energy through innovative [non-parametric reconstructions of its equation of state](https://arxiv.org/abs/2503.08658) from combined datasets. * Advancing our understanding of the early Universe through detailed studies of [21-cm signals from the Cosmic Dawn and Epoch of Reionization](https://arxiv.org/abs/2301.03298), including the development of sophisticated foreground modelling techniques and emulators like [GLOBALEMU](https://arxiv.org/abs/2104.04336). * Developing new statistical methods for quantifying tensions between cosmological datasets ([Quantifying tensions in cosmological parameters: Interpreting the DES evidence ratio](https://arxiv.org/abs/1902.04029)) and for robust Bayesian model selection ([Bayesian model selection without evidences: application to the dark energy equation-of-state](https://arxiv.org/abs/1506.09024)). * Exploring fundamental physics questions such as potential [parity violation in the Large-Scale Structure using machine learning](https://arxiv.org/abs/2410.16030). ### Charting the Future: AI-Powered Cosmological Discovery The Handley Research Group is poised to lead a new era of cosmological analysis, driven by the explosive growth in data from next-generation observatories and transformative advances in artificial intelligence. Our future ambitions are centred on harnessing these capabilities to address the most pressing questions in fundamental physics. **Strategic Research Pillars:** * **Next-Generation Simulation-Based Inference (SBI):** We are developing advanced SBI frameworks to move beyond traditional likelihood-based analyses. This involves creating sophisticated codes for simulating [Cosmic Microwave Background (CMB)](https://arxiv.org/abs/1908.00906) and [Baryon Acoustic Oscillation (BAO)](https://arxiv.org/abs/1607.00270) datasets from surveys like DESI and 4MOST, incorporating realistic astrophysical effects and systematic uncertainties. Our AI initiatives in this area focus on developing and implementing cutting-edge SBI algorithms, particularly [neural ratio estimation (NRE) methods](https://arxiv.org/abs/2407.15478), to enable robust and scalable inference from these complex simulations. * **Probing Fundamental Physics:** Our enhanced analytical toolkit will be deployed to test the standard cosmological model ($\Lambda$CDM) with unprecedented precision and to explore [extensions to Einstein's General Relativity](https://arxiv.org/abs/2006.03581). We aim to constrain a wide range of theoretical models, from modified gravity to the nature of [dark matter](https://arxiv.org/abs/2106.02056) and [dark energy](https://arxiv.org/abs/1701.08165). This includes leveraging data from upcoming [gravitational wave observatories](https://arxiv.org/abs/1803.10210) like LISA, alongside CMB and large-scale structure surveys from facilities such as Euclid and JWST. * **Synergies with Particle Physics:** We will continue to strengthen the connection between cosmology and particle physics by expanding the [GAMBIT framework](https://arxiv.org/abs/2009.03286) to interface with our new SBI tools. This will facilitate joint analyses of cosmological and particle physics data, providing a holistic approach to understanding the Universe's fundamental constituents. * **AI-Driven Theoretical Exploration:** We are pioneering the use of AI, including [large language models and symbolic computation](https://arxiv.org/abs/2401.00096), to automate and accelerate the process of theoretical model building and testing. This innovative approach will allow us to explore a broader landscape of physical theories and derive new constraints from diverse astrophysical datasets, such as those from GAIA. Our overarching goal is to remain at the forefront of scientific discovery by integrating the latest AI advancements into every stage of our research, from theoretical modeling to data analysis and interpretation. We are excited by the prospect of using these powerful new tools to unlock the secrets of the cosmos. Content generated by [gemini-2.5-pro-preview-05-06](https://deepmind.google/technologies/gemini/) using [this prompt](/prompts/content/index.txt). Image generated by [imagen-3.0-generate-002](https://deepmind.google/technologies/gemini/) using [this prompt](/prompts/images/index.txt). ``` 2. **Paper Metadata:** ```yaml !!python/object/new:feedparser.util.FeedParserDict dictitems: id: http://arxiv.org/abs/2510.05216v1 guidislink: true link: https://arxiv.org/abs/2510.05216v1 title: 'DAMA/LIBRA and dark matter: decisive tension or contrived cancellation' title_detail: !!python/object/new:feedparser.util.FeedParserDict dictitems: type: text/plain language: null base: '' value: 'DAMA/LIBRA and dark matter: decisive tension or contrived cancellation' updated: '2025-10-06T18:00:45Z' updated_parsed: !!python/object/apply:time.struct_time - !!python/tuple - 2025 - 10 - 6 - 18 - 0 - 45 - 0 - 279 - 0 - tm_zone: null tm_gmtoff: null links: - !!python/object/new:feedparser.util.FeedParserDict dictitems: href: https://arxiv.org/abs/2510.05216v1 rel: alternate type: text/html - !!python/object/new:feedparser.util.FeedParserDict dictitems: href: https://arxiv.org/pdf/2510.05216v1 rel: related type: application/pdf title: pdf summary: "We assess the tension between DAMA/LIBRA and the latest dark matter annual\ \ modulation results from the ANAIS-112 and COSINE-100 NaI experiments, under\ \ a range of hypotheses ranging from physical to general parameterisations. We\ \ find that, in the most physically-motivated cases, the tension between DAMA\ \ and these other NaI experiments exceeds 5$\u03C3$. Lowering the tension to reasonable\ \ values requires significant tuning, such as overfitting with large numbers of\ \ free parameters, and opposite-sign modulation between recoil signals on sodium\ \ versus iodine." summary_detail: !!python/object/new:feedparser.util.FeedParserDict dictitems: type: text/plain language: null base: '' value: "We assess the tension between DAMA/LIBRA and the latest dark matter\ \ annual modulation results from the ANAIS-112 and COSINE-100 NaI experiments,\ \ under a range of hypotheses ranging from physical to general parameterisations.\ \ We find that, in the most physically-motivated cases, the tension between\ \ DAMA and these other NaI experiments exceeds 5$\u03C3$. Lowering the tension\ \ to reasonable values requires significant tuning, such as overfitting with\ \ large numbers of free parameters, and opposite-sign modulation between recoil\ \ signals on sodium versus iodine." tags: - !!python/object/new:feedparser.util.FeedParserDict dictitems: term: hep-ph scheme: http://arxiv.org/schemas/atom label: null published: '2025-10-06T18:00:45Z' published_parsed: !!python/object/apply:time.struct_time - !!python/tuple - 2025 - 10 - 6 - 18 - 0 - 45 - 0 - 279 - 0 - tm_zone: null tm_gmtoff: null arxiv_comment: 8 pages, 2 figures arxiv_primary_category: term: hep-ph authors: - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Giorgio Busoni - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Jonathan M. Cornell - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Will Handley - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Felix Kahlhoefer - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Anders Kvellestad - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Masen Pitts - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Lauren Street - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Aaron C. Vincent - !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Martin White author_detail: !!python/object/new:feedparser.util.FeedParserDict dictitems: name: Martin White author: Martin White ``` 3. **Paper Source (TeX):** ```tex % Bibliography and bibfile \def\ppnp{Prog.\ Part.\ Nuc.\ Phys.} % Progress in Particle and Nuclear Physics \def\pdu{Phys.\ Dark Univ.} % Physics of the Dark Universe \def\astropacific{Astron.\ Soc.\ Pacific Conf.\ Ser.} % Astronomical Society of the Pacific Conference Series \def\lnp{Lec.\ Notes in Physics} % Lecture Notes in Physics \def\cpc{Comp.\ Phys.\ Comm.} % Computer Physics Communications \def\jpg{J. Phys. G} % Journal of Physics G Nuclear Physics \def\ijmpa{Int.\ J.\ Mod.\ Phys.\ A} % International Journal of Modern Physics A \def\ijmpd{Int.\ J.\ Mod.\ Phys.\ D} % International Journal of Modern Physics D \def\epjc{Eur.\ Phys.\ J.\ C} % European Physical Journal C \def\nima{Nuc.\ Inst.\ Methods A} % Nuclear Instruments and Methods A \def\nimb{Nuc.\ Inst.\ Methods B} % Nuclear Instruments and Methods B \def\njp{New J.\ Phys.} % New Journal of Physics \def\rmp{Rev.\ Mod.\ Phys.} % Reviews of Modern Physics \def\app{Astropart.\ Phys.} % Astroparticle Physics \def\aj{AJ}% % Astronomical Journal \def\actaa{Acta Astron.}% % Acta Astronomica \def\araa{ARA\&A}% % Annual Review of Astron and Astrophys \def\arnps{Ann.~Rev.~Nucl.~\& Part.~Sci.}% % Annual Review of Astron and Astrophys \def\apj{ApJ}% % Astrophysical Journal \def\apjl{ApJ}% % Astrophysical Journal, Letters \def\apjs{ApJS}% % Astrophysical Journal, Supplement \def\ao{Appl.\ Opt.}% % Applied Optics \def\apss{Ap\&SS}% % Astrophysics and Space Science \def\aap{A\&A}% % Astronomy and Astrophysics \def\aapr{A\&A~Rev.}% % Astronomy and Astrophysics Reviews \def\aaps{A\&AS}% % Astronomy and Astrophysics, Supplement \def\azh{AZh}% % Astronomicheskii Zhurnal \def\pos{PoS}% % Proceedings of Science \def\baas{BAAS}% % Bulletin of the AAS \def\bac{Bull.\ Astr.\ Inst.\ Czechosl.}% % Bulletin of the Astronomical Institutes of Czechoslovakia \def\caa{Chinese Astron.\ Astrophys.}% % Chinese Astronomy and Astrophysics \def\cjaa{Chinese J.\ Astron.\ Astrophys.}% % Chinese Journal of Astronomy and Astrophysics \def\icarus{Icarus}% % Icarus \def\jhep{JHEP}% % Journal of High Energy Physics \def\jcap{JCAP}% % Journal of Cosmology and Astroparticle Physics \def\jpsj{J.\ Phys.\ Soc.\ Japan}% % Journal of the Physical Society of Japan \def\jrasc{JRASC}% % Journal of the RAS of Canada \def\canjphys{Can.~J.~Phys.} %Canadian Journal of Physics \def\apphys{Astropart.~Phys.} %Astroparticle Physics \def\mnras{MNRAS}% % Monthly Notices of the RAS \def\memras{MmRAS}% % Memoirs of the RAS \def\na{New A}% % New Astronomy \def\nar{New A Rev.}% % New Astronomy Review \def\pasa{PASA}% % Publications of the Astron. Soc. of Australia \def\pra{Phys.\ Rev.\ A}% % Physical Review A: General Physics \def\prb{Phys.\ Rev.\ B}% % Physical Review B: Solid State \def\prc{Phys.\ Rev.\ C}% % Physical Review C \def\prd{Phys.\ Rev.\ D}% % Physical Review D \def\pre{Phys.\ Rev.\ E}% % Physical Review E \def\prl{Phys.\ Rev.\ Lett.}% % Physical Review Letters \def\pasp{PASP}% % Publications of the ASP \def\pasj{PASJ}% % Publications of the ASJ \def\qjras{QJRAS}% % Quarterly Journal of the RAS \def\rmxaa{Rev. Mexicana Astron. Astrofis.}% % Revista Mexicana de Astronomia y Astrofisica \def\skytel{S\&T}% % Sky and Telescope \def\solphys{Sol.\ Phys.}% % Solar Physics \def\sovast{Soviet~Ast.}% % Soviet Astronomy \def\ssr{Space~Sci.\ Rev.}% % Space Science Reviews \def\zap{ZAp}% % Zeitschrift fuer Astrophysik \def\nat{Nature}% % Nature \def\science{Science}% \def\sci{\science}% % Science \def\iaucirc{IAU~Circ.}% % IAU Cirulars \def\aplett{Astrophys.\ Lett.}% % Astrophysics Letters \def\apspr{Astrophys.\ Space~Phys.\ Res.}% % Astrophysics Space Physics Research \def\bain{Bull.\ Astron.\ Inst.\ Netherlands}% % Bulletin Astronomical Institute of the Netherlands \def\fcp{Fund.\ Cosmic~Phys.}% % Fundamental Cosmic Physics \def\gca{Geochim.\ Cosmochim.\ Acta}% % Geochimica Cosmochimica Acta \def\grl{Geophys.\ Res.\ Lett.}% % Geophysics Research Letters \def\jcp{J.\ Chem.\ Phys.}% % Journal of Chemical Physics \def\jgr{J.\ Geophys.\ Res.}% % Journal of Geophysics Research \def\jqsrt{J.\ Quant.\ Spec.\ Radiat.\ Transf.}% % Journal of Quantitiative Spectroscopy and Radiative Trasfer \def\memsai{Mem.\ Soc.\ Astron.\ Italiana}% % Mem. Societa Astronomica Italiana \def\nphysa{Nucl.\ Phys.\ A}% % Nuclear Physics A \def\nphysb{Nucl.\ Phys.\ B}% % Nuclear Physics B \def\physrep{Phys.\ Rep.}% % Physics Reports \def\physscr{Phys.\ Scr}% % Physica Scripta \def\planss{Planet.\ Space~Sci.}% % Planetary Space Science \def\procspie{Proc.\ SPIE}% % Proceedings of the SPIE \def\repprogphys{Rep.\ Prog.\ Phys.}% % Reports of Progress in Physics \def\jpcrd{J. Phys. Chem. Ref. Data}% %Journal of Physical and Chemical Reference Data \def\jphysb{J. Phys. B}% %Journal of Physics B Atomic Molecular Physics \def\jphysd{J. Phys. D}% %Journal of Physics D \def\jphysconfseries{J. Phys. Conf. Series}% %Journal of Physics: Conference Series \def\physrev{\pr} \def\pr{Phys. Rev.}% %Physical Review \def\josa{J. Opt. Soc. Amer. (1917-1983)}% %Journal of the Optical Society of America (1917-1983) \def\josab{J. Opt. Soc. Amer. B}% %Journal of the Optical Society of America B Optical Physics \def\pla{Phys. Lett. A}% %Physics Letters A \def\plb{Phys. Lett. B}% %Physics Letters B \def\os{Opt. Spectrosc. (Russ.)}% %Optics and Spectroscopy (Russ. / USSR) \def\jas{J. Appl. Spectrosc.}% %Journal of Applied Spectroscopy (Russ. / USSR) \def\annp{Ann. Phys.}% %Annalen der Physik \def\sa{Spectrochim. Acta}% %Spectrochimica Acta \def\prsoca{Proc. R. Soc. London Ser. A}% %Proceedings of the Royal Society of London, Series A \def\zphysa{Z. Phys. A}% %Zeitschrift fur Physik A \def\zphysb{Z. Phys. B}% %Zeitschrift fur Physik B \def\zphysc{Z. Phys. C}% %Zeitschrift fur Physik C \def\zphysd{Z. Phys. D}% %Zeitschrift fur Physik D \def\zphyse{Z. Phys. E}% %Zeitschrift fur Physik E \def\zphys{Z. Phys.}% %Zeitschrift fur Physik \def\adndt{Atom. Data Nuc. Data Tables}% %Atomic Data and Nuclear Data Tables \def\jmolspec{J. Mol. Spectrosc.}% %Journal of Molecular Spectroscopy \def\aphysb{Appl. Phys. B}% %Applied Physics B: Lasers and Optics \def\nim{Nuc. Inst. Meth.}% %Nuclear Instruments and Methods \def\jphysique{J. Phys. (Paris)}% %Journal de Physique \def\epjp{Eur.~Phys.~J.~Plus}% %European Physical Journal Plus \def\epjc{Eur.~Phys.~J.~C}% %European Physical Journal C \def\epl{Europhys.~Lett}% %Europhysics Letters \def\njp{New J.~Phys.} %New Journal of Physics \def\pdu{Phys.~Dark.~Univ.} %Physics of the Dark Universe \let\astap=\aap \let\apjlett=\apjl \let\apjsupp=\apjs \let\applopt=\ao % \documentclass[% reprint, notitlepage, % preprint, superscriptaddress, %groupedaddress, %unsortedaddress, %runinaddress, %frontmatterverbose, %preprint, preprintnumbers, nofootinbib, %nobibnotes, %bibnotes, amsmath,amssymb, aps, %pra, %prb, %rmp, %prstab, %prstper, %floatfix, %onecolumn, twocolumn, ]{revtex4-2} \include{jdefs} \usepackage{tikz} \usepackage{verbatim} \usepackage{graphicx}% Include figure files \usepackage{dcolumn}% Align table columns on decimal point \usepackage{bm}% bold math \usepackage{booktabs} \usepackage{xcolor} \usepackage{tabularx} \usepackage[colorlinks]{hyperref} \hypersetup{ colorlinks, linkcolor={red!50!black}, citecolor={blue!50!black}, urlcolor={blue!80!black} } \usepackage[normalem]{ulem} \usepackage{physics} \usepackage{comment} \usepackage{multirow} \usepackage{subfigure} \usepackage{xspace} \usepackage{slashed} \usepackage{enumitem} \newcommand{\La}{{\rm \Lambda}} \newcommand\ddcalc{\textsf{DDCalc}\xspace} \newcommand\directdm{\textsf{DirectDM}\xspace} \newcommand\darkbit{\textsf{DarkBit}\xspace} \newcommand\ddcalcthree{\textsf{DDCalc 3.0}\xspace} \newcommand{\xmark}{\ding{55}} \newcommand\Tstrut{\rule{0pt}{2.6ex}} % = `top' strut \newcommand\Bstrut{\rule[-0.9ex]{0pt}{0pt}} % = `bottom' strut \newcommand{\ie}{{\it i.e.}} \newcommand{\Ie}{{\it I.e.}} \newcommand{\eg}{{\it e.g.}} \newcommand{\Eg}{{\it E.g.}} \newcommand{\cf}{{\it cf.}} \newcommand{\etc}{{\it etc.}} \newcommand{\eq}{Eq.} \newcommand{\eqs}{Eqs.} \newcommand{\Def}{Definition} \newcommand{\fig}{Fig.} \newcommand{\Fig}{Fig.} \newcommand{\figs}{Figures} \newcommand{\Figs}{Figures} \newcommand{\Refe}{Ref.} \newcommand{\Refes}{Refs.} \newcommand{\equ}[1]{\eq~(\ref{equ:#1})} \newcommand{\figu}[1]{\fig~\ref{fig:#1}} \newcommand{\mtr}{\mathrm{tr}} \newcommand{\msh}{\mathrm{sh}} \newcommand{\mdb}{\mathrm{db}} \newcommand{\mdbl}{\mathrm{dbl}} \newcommand{\mesc}{\mathrm{esc}} \newcommand{\Emin}{E_\mathrm{min}} \newcommand{\Emax}{E_\mathrm{max}} \newcommand{\ai}{\{\alpha_{i,\oplus}\}} \newcommand{\Ntr}{N_\mathrm{tr}} \newcommand{\Nsh}{N_\mathrm{sh}} \newcommand{\Ndb}{N_\mathrm{db}} \newcommand{\dcp}{\delta_{\rm CP}} \newcommand{\ytilde}{\tilde{y}} \newcommand{\gambit}{\textsf{GAMBIT}\xspace} \newcommand{\gambitlight}{\textsf{GAMBIT-light}\xspace} \newcommand{\GB}{\gambit} \newcommand{\diver}{\textsf{Diver}\xspace} %units? \newcommand{\GeV}{{\rm \,GeV}} \newcommand{\TeV}{{\rm \,TeV}} \newcommand{\MeV}{{\rm \,MeV}} \newcommand{\keV}{{\rm \,keV}} \newcommand{\eV}{{\rm \,eV}} \newcommand{\keVee}{{\rm \,keV_{\rm ee}}} \newcommand{\Q}[2]{ \if\relax\detokenize{#2}\relax \mathcal{Q}_{#1} \else \mathcal{Q}_{#1}^{(#2)} \fi } \newcommand{\C}[2]{ \if\relax\detokenize{#2}\relax \mathcal{C}_{#1} \else \mathcal{C}_{#1}^{(#2)} \fi } \newcommand{\AK}[1]{\textcolor{purple}{{ [AK: \bf #1]}}} \newcommand{\FK}[1]{\textcolor{magenta}{{ [FK: \bf #1]}}} \newcommand{\QL}[1]{\textcolor{orange}{{ [QL: \bf #1]}}} \newcommand{\AV}[1]{\textcolor{blue}{{ [AV: \bf #1]}}} \newcommand{\WH}[1]{\textcolor{violet}{{ [WH: \bf #1]}}} \newcommand{\Gb}[1]{\textcolor{red}{{ [GB: \bf #1]}}} \newcommand{\JC}[1]{\textcolor{green}{{ [JC: \bf #1]}}} \newcommand{\revAdd}[1]{\textcolor{cyan}{#1}} \newcommand{\sixflav}[6]{(\{{#1},{#2}\}:\{#3,#4\}:\{#5,#6\})} \newcommand{\sixflavor}[6]{\{{#1},{#2}\}:\{#3,#4\}:\{#5,#6\}} \newcolumntype{Y}{>{\centering\arraybackslash}X} \newcolumntype{Z}[1]{>{\centering\arraybackslash}m{#1}} \usepackage{cellspace} \setlength{\cellspacetoplimit}{8pt} \setlength{\cellspacebottomlimit}{8pt} \graphicspath{{figures/}} \begin{document} \preprint{ADP-25-32/T1294,TTP25-033} \title{DAMA/LIBRA and dark matter: decisive tension or contrived cancellation} \author{Giorgio Busoni} \email{giorgio.busoni@adelaide.edu.au} \affiliation{ARC Centre of Excellence for Dark Matter Particle Physics \& CSSM, Department of Physics, University of Adelaide, Adelaide, SA 5005} \author{Jonathan M. Cornell} \email{jonathancornell@weber.edu} \affiliation{Department of Physics and Astronomy, Weber State University, 1415 Edvalson St., Dept. 2508, Ogden, UT 84408, USA} \author{Will Handley} \email{wh260@cam.ac.uk} \affiliation{Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge, CB3 0HE, UK} \author{Felix Kahlhoefer} \email{kahlhoefer@kit.edu} \affiliation{Institute for Astroparticle Physics (IAP), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen, Germany} \author{Anders Kvellestad} \email{anders.kvellestad@fys.uio.no} \affiliation{Department of Physics, University of Oslo, N-0316 Oslo, Norway} \author{Masen Pitts} \affiliation{Department of Physics and Astronomy, Weber State University, 1415 Edvalson St., Dept. 2508, Ogden, UT 84408, USA} \author{Lauren Street} \affiliation{Department of Physics, University of Cincinnati, Cincinnati, OH 45221, USA} \author{Aaron C. Vincent} \email{aaron.vincent@queensu.ca} \affiliation{ Department of Physics, Engineering Physics and Astronomy,\\ Queen’s University, Kingston ON K7L 3N6, Canada } \affiliation{% Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Kingston ON K7L 3N6, Canada } \affiliation{Perimeter Institute for Theoretical Physics, Waterloo ON N2L 2Y5, Canada} \author{Martin White} \email{martin.white@adelaide.edu.au} \affiliation{ARC Centre of Excellence for Dark Matter Particle Physics \& CSSM, Department of Physics, University of Adelaide, Adelaide, SA 5005} %\date{\today} \begin{abstract} We assess the tension between DAMA/LIBRA and the latest dark matter annual modulation results from the ANAIS-112 and COSINE-100 NaI experiments, under a range of hypotheses ranging from physical to general parameterisations. We find that, in the most physically-motivated cases, the tension between DAMA and these other NaI experiments exceeds 5$\sigma$. Lowering the tension to reasonable values requires significant tuning, such as overfitting with large numbers of free parameters, and opposite-sign modulation between recoil signals on sodium versus iodine. \end{abstract} \maketitle \noindent \textbf{\textit{Introduction---}}It has been over two decades since the DAMA/LIBRA NaI experiment claimed the discovery of an annual modulation signal of dark matter (DM) at 6.3$\sigma$ \cite{Bernabei:2003za}. In combination with DAMA/LIBRA and DAMA/LIBRA phase2, 2.86 ton-yr of exposure over 22 annual cycles have now yielded a claimed signal over 13$\sigma$ \cite{Bernabei:2022ath}. Multiple analyses have shown that the energy dependence of this signal leads to a preference for a particle with a mass around 10 or 50 GeV, depending on whether it scatters primarily off sodium or iodine (e.g. \cite{Kelso:2013gda, Baum:2018ekm}). In parallel, however, advances in large direct detection experiments such as SuperCDMS, PICO-60, LZ and XENON1T have left very little room for a DM interpretation, with the current sensitivity being a full six orders of magnitude below DAMA/LIBRA's region of interest \cite{PhysRevLett.120.061802,PhysRevLett.121.051301,PhysRevLett.121.081307,PhysRevD.100.022001,PhysRevLett.131.041002,PhysRevLett.131.041003}. Nonetheless, the DAMA/LIBRA DM interpretation has persisted on the premise that no experiment to date has formally excluded it by searching for an annual modulation signature with the same technology, namely extremely pure NaI scintillator crystals, leaving the door open to DM particles with some inscrutable affinity towards sodium or iodine. While some exploratory efforts occurred starting from the early 2000s \cite{Ahmed:2003su,Kim:2012rza,DM-Ice:2016snk}, none of these experiments were able to completely exclude DAMA/LIBRA in a model-agnostic way. In recent years, a new generation of NaI experiments has been releasing data: the ANAIS-112 detector \cite{Amare:2019jul,Amare:2021yyu,Coarasa:2024xec,Amare:2025dfq}, located in Canfranc and COSINE-100 \cite{Adhikari:2018ljm,COSINE-100:2021xqn,COSINE-100:2019lgn,COSINE-100:2021zqh,Carlin:2024maf}, at Yangyang. Neither of these experiments alone has quite reached the 5$\sigma$ sensitivity to conclusively rule out the NaI-philic DM hypothesis of DAMA/LIBRA. A recent joint analysis \cite{COSINE-100:2025eyc} combining these datasets into two single-energy bins has excluded a modulation signal compatible with DAMA's at the level of 4.68$\sigma$ (3.53$\sigma$) in the 1-6 (2-6) keV range. In addition, the two experiments have separately determined modulation amplitudes for events binned in energy \cite{Carlin:2024maf, Amare:2025dfq}, assuming the expected phase for DM scattering, a useful result for model discrimination. These can be directly compared to similar results previously reported by DAMA \cite{Bernabei:2021kdo}. Performing such a comparison will be the goal of this letter. We use the full spectral information reported by the different experiments and determine how well we can reconcile the spectra reported by DAMA/LIBRA and COSINE-100/ANAIS-112 if we assume the modulation is due to DM-nucleon scattering. This comparison is not as trivial as it may seem: given a common \textit{nuclear recoil spectrum}, the differences in binning and energy resolution can lead to substantially different predictions for the \textit{measured} modulation spectrum between the various experiments. To remain as general as possible, we adopt two different model-independent approaches: a DM effective field theory in which the nuclear recoil spectrum is calculable and a more general scenario where the nuclear recoil spectrum is parameterized with various functional forms. We undertake fits to the experimental data sets to determine the best-fit parameters of these models, and based on these results we quantify the tension between the experiments. \noindent \textbf{\textit{Background---}} The scattering rate of weakly-interacting DM particles from a nuclear target is given in terms of the differential cross section $d\sigma/dE_R$ by \begin{equation} \label{eq:recoil} \frac{dR}{dE_R}=\frac{\rho_0}{m_\chi m_N}\int^{v_{\text{max}}}_{v_{\text{min}}}d^3v v \tilde{f}(\mathbf{v},t)\frac{d\sigma}{dE_R} \end{equation} where $\rho_0$ is the local DM mass density, $m_\chi$ is the DM particle mass, $m_N$ is the mass of the recoiling nucleus, $v_{\max}$ is the escape velocity and $v_{\min}$ is the minimum velocity needed to cause a nucleus to recoil with energy $E_R$. $\tilde{f}(\mathbf{v},t)$ is the DM velocity distribution in the lab frame. The lab-frame distribution is related to the Galactic frame distribution $f(\mathbf{v})$ by a Galilean boost: $\tilde{f}(\mathbf{v})=f(\mathbf{v}+\mathbf{v}_{\text{obs}}(t))$, where $\mathbf{v}_{\text{obs}}(t)=\mathbf{v}_{\odot}+\mathbf{V}_\oplus(t)$, $\mathbf{v}_{\odot}$ is the velocity of the Sun relative to the DM reference frame and $\mathbf{V}_{\oplus}$ is the velocity of the Earth about the Sun. In Boreal summer, the addition of the Earth's orbital velocity with that of the Sun boosts the ``wind'' of DM in our rest frame, whilst the wind is slower during the Austral summer. This changes the number of particles above the minimum speed required to create an observable nuclear recoil. The resulting annual modulation~\cite{Drukier:1986tm,Spergel:1987kx,Freese:1987wu} is parameterised as \begin{equation} \frac{dR}{dE_R}=A_0+A_1\cos\left[\omega(t-t_0)\right]+... \label{eq:parametrisation} \end{equation} Experimental results are reported not in terms of the nuclear recoil energy $E_R$ but in terms of the measured electron-equivalent energy $E_{ee}$, which is related to the former by a quenching factor $Q_T(E_R)$ that depends on both the target $T$ and the recoil energy. For a NaI detector with two potential nuclear targets $T=\{$Na,I$\}$, the total number of events in a given experimental bin $i$ is given by \begin{align} N_i &= \int_{E_{i,\text{min}}}^{E_{i,\text{max}}} dE_{ee} \epsilon(E_{ee}) \times\\ &\int_0^\infty dE_R \sum_T \xi_T\frac{1}{\sqrt{2\pi}\sigma(E_{ee})}e^{-\frac{(E_{ee}-Q_T(E_R)E_R)^2}{2\sigma(E_{ee})}} \frac{dR_T}{dE_R},\nonumber\label{eq:detectorresp} \end{align} where $\xi_T$ indicates the mass fraction of the target $T$, $dR_T/dE_R$ is the predicted recoil energy spectrum for that target, $E_{i,\text{min}},E_{i,\text{max}}$ define the bin energy range, $\epsilon$ is the detector efficiency and $\sigma$ is the detector resolution. %and $Q_T$ are the quenching factors on the target $T$. As all collaborations report efficiency-corrected results, we will set $\epsilon=1$ for all detectors. DAMA/LIBRA phases 1 and 2 \cite{Bernabei:2021kdo, Bernabei:2022xgg} have reported results compatible with a DM annual modulation signature in the energy range $1-6 \keVee$. However, they have presented results over a larger energy range, with DAMA/LIBRA-phase2 releasing data in the energy range $0.75-20 \keVee$ with a total exposure over 8 annual cycles of 1.53 t$\times$yr. This is in addition to data from DAMA/NaI and DAMA/LIBRA-phase1, which bring the total exposure in the range $2-20 \keVee$ to 2.86 t$\times$yr. In this work we fit to all of the available modulation data as presented in \cite{Bernabei:2021kdo}. The DAMA/LIBRA detector resolution is taken to be $ \sigma(E_{ee}) = a \sqrt{E_{ee}} + b E_{ee}$ with $a=0.488\sqrt{\keVee}$ and $b=0.0091$~\cite{DAMA:2008bis}. COSINE-100 recently released results with $6.4 \mathrm{yr}$ of exposure \cite{Carlin:2024maf}, where they find no evidence of an annual modulation signal and a greater than $3\sigma$ tension with DAMA/LIBRA in the energy range $1-6 \keVee$. In our fits, we include their reported modulations in the range $0.75-20 \keVee$ and make use of the detector resolution presented in \cite{Kang:2019uuj}: $ \sigma(E_{ee}) = \sqrt{a E_{ee} + b E_{ee}^2}$ with $a = 0.081483 \keVee$, $b = 0.001885$. ANAIS-112 recently presented binned modulation amplitude data from their 6-year exposure dataset \cite{Amare:2025dfq}. This data is incompatible with the DAMA/LIBRA modulation signal in the $1-6 \keVee$ range at nearly $4 \sigma$ confidence level. We fit to their reported modulation amplitudes over the range $1-20 \keVee$, and take the detector resolution to be $ \sigma(E_{ee}) = a + b \sqrt{E_{ee}} $ with $a = -0.08 \keVee$, $b = 0.378 \sqrt{\keVee}$~\cite{Amare:2018sxx}. Equally important is the nuclear recoil quenching factor $Q_T(E_R)$, defined as the ratio of scintillation light yield produced by nuclear recoil to that of electron recoil at the same energy. We take recently-measured energy-dependent quenching factors for sodium from Ref.~\cite{Carlin:2024maf} and iodine from Ref.~\cite{Lee:2024unz}, for all experiments. We will, however, examine the impact of alternative quenching factors. \textbf{\textit{Quantifying the tension between the datasets---}} We follow the approach from \cite{Maltoni:2003cu} to quantify the tension between the datasets of different experiments. Consider two experiments, $A$ and $B$, that measure a number of observables $m_A$ and $m_B$, respectively, and a model that describes the signal using $n$ parameters $c_i$. We define $\chi_X^2(c_i)$ as the $\chi^2$ obtained from the data of experiment $X=A,B$. We denote the best-fit point obtained by fitting the data of experiment $X$ alone as $c_i^X$, so that $\chi_X^2(c_i)$ has a minimum at $c_i=c_i^X$. Similarly, $c_i^{A+B}$ is the best-fit point obtained by fitting the data of both experiments simultaneously. In this case, the function \begin{equation} \chi_{A+B}^2(c_i) = \chi_A^2(c_i) + \chi_B^2(c_i) \end{equation} has a minimum at $c_i = c_i^{A+B}$, and the quantity \begin{equation} \delta\chi^2 = \chi_{A+B}^2(c_i^{A+B}) - \chi_A^2(c_i^{A}) - \chi_B^2(c_i^{B}) \label{eq:tensionstat} \end{equation} follows a $\chi^2$ distribution with $n$ degrees of freedom. This can be used to determine the level of statistical inconsistency of the two datasets, under the assumption that the chosen model describes the signals with the right level of precision to reproduce the data of the experiments. We will use this statistical test to assess the compatibility between DAMA/LIBRA and the combination of COSINE-100 and ANAIS-112. We will employ two qualitatively different approaches to derive the tension between the DAMA/LIBRA and combined COSINE-100 and ANAIS-112 datasets. \textbf{\textit{Detailed particle astrophysics test---}} The first is to use concrete assumptions for the astrophysics and particle physics defined in Eq.~\eqref{eq:recoil}. The DM distribution $f(\mathbf{v})$, is well-described by a Maxwellian velocity distribution in the halo frame, with a peak velocity $v_{0} = 240\, \pm \,8$\,km\,s$^{-1}$ \cite{Reid:2014boa}, cut off at the escape velocity $v_{\rm{\text{esc}}} = 528 \pm 25$\,km\,s$^{-1}$, based on \emph{Gaia} data \cite{Deason:2019kgj}. The halo parameters are fixed to their central values, as varying these parameters is expected to affect all experiments in the same way. The potential impact of varying the velocity distribution will be implicitly captured by the more-model-independent parametrization discussed later. On the particle physics side, we consider elastic scattering of DM on nuclei. However, instead of simply considering spin-independent and spin-dependent scattering, we adopt a more model-agnostic approach by considering an effective field theory (EFT) allowing for different types of interactions between DM and Standard Model particles. This approach avoids the need to specify the detailed microphysics of DM interactions, as long as the relevant energy scale is below the cutoff scale $\La$. For elastic scattering, we can simply set $\La$ equal to the hadronic scale, i.e.\ $\Lambda=2$~GeV without loss of generality. To construct the EFT, we further assume that the DM particle is a Dirac fermion and a singlet under the Standard Model gauge group. Following the notation of Refs.~\cite{Bishara:2017nnn,Brod:2017bsw}, we write the interaction Lagrangian for the theory as % \begin{equation} \mathcal{L}_{\rm{int}} = \sum_{a,d} \dfrac{\C{a}{d}}{\La^{d-4}} \Q{a}{d}\,, \end{equation} % where $\Q{a}{d}$ is a particular effective operator involving DM and Standard Model fields, $d\geq 5$ is the mass dimension of the operator and $\C{a}{d}$ is the dimensionless Wilson coefficient associated to $\Q{a}{d}$. The full Lagrangian density for the theory is then $ \mathcal{L} = \mathcal{L}_{\rm{SM}} + \mathcal{L}_{\rm{int}} + \overline{\chi}\left(i\slashed{\partial}-m_\chi\right)\chi\,, $ such that the free parameters of the theory are the DM mass $m_\chi$, and the set of dimensionless Wilson coefficients $\{ \C{a}{d} \}$. The phenomenology of DM in this model will be dominated by the lowest dimension operators. We thus limit ourselves to operators with $d\le 6$. At dimension 5, there are the two dipole operators \begin{align} \Q{1}{5} &= \frac{e}{8\pi^2} (\overline\chi \sigma_{\mu\nu} \chi) F^{\mu\nu} \,, \\ \Q{2}{5} &= \frac{e}{8\pi^2} (\overline\chi i \sigma_{\mu\nu} \gamma_5 \chi) F^{\mu\nu} \, , \end{align} where $F_{\mu\nu}$ is the electromagnetic field strength tensor and $e$ is the electromagnetic charge. These operators give rise to long-range interactions, i.e.\ steeply-falling recoil spectra. At dimension six, we consider the operators \begin{align} \label{dim6efts} \Q{1,q}{6} &= (\overline\chi \gamma_\mu \chi)(\overline{q} \gamma^\mu q)\,, \\ \Q{2,q}{6} &= (\overline\chi \gamma_\mu \gamma_5 \chi)(\overline{q} \gamma^\mu q)\,, \\ \Q{3,q}{6} &= (\overline\chi \gamma_\mu \chi)(\overline{q} \gamma^\mu \gamma_5 q)\,, \\ \Q{4,q}{6} &= (\overline\chi \gamma_\mu \gamma_5 \chi)(\overline{q} \gamma^\mu \gamma_5 q)\,. \label{dim6efts:end} \end{align} The first two operators give rise to spin-independent interactions, while the last two give rise to spin-dependent interactions. Moreover, $\Q{1,q}{6}$ and $\Q{4,q}{6}$ are independent of the momentum transfer and the DM velocity, while $\Q{2,q}{6}$ and $\Q{3,q}{6}$ vanish in the non-relativistic limit. Together these operators therefore capure a wide range of different possibilities for elastic scattering. The effective operators are defined at the scale $\La=2$~GeV, where the Higgs, $W$ and $Z$ bosons as well as the top, bottom and charm quarks have been integrated out. We do not consider interactions with leptons, which do not give rise to nuclear scattering at tree-level. Following the assumption of Minimal Flavour Violation, we take the Wilson coefficients for operators involving the down and strange quarks to be equal, but we allow the Wilson coefficients for operators involving up quarks to differ. We parameterize the relative couplings between the $u$ and $d$-type quarks by angles $\theta^{(6)}_a$, in the following form: \begin{align} C^{(6)}_{a,d} &= C^{(6)}_a \sin \theta^{(6)}_a = C^{(6)}_{a,s}\,, \\ C^{(6)}_{a,u} &= C^{(6)}_a \cos \theta^{(6)}_a \; . \end{align} In the EFT setup, we therefore have 11 model parameters to consider. The fits are performed with \gambit \cite{gambit, gambit_addendum} and its \darkbit~\cite{GAMBITDarkMatterWorkgroup:2017fax} module, using \diver 1.3\footnote{\url{https://github.com/diveropt/Diver/releases/tag/v1.3.0}}~\cite{ScannerBit} to explore the parameter space, \directdm~\cite{Bishara:2016hek, Bishara:2017pfq, Bishara:2017nnn} to match the effective operators introduced above onto the non-relativistic operators relevant for nuclear scattering, and \ddcalc\footnote{The rate calculations and likelihoods for the modulation experiments included in this paper will be part of the the upcoming \ddcalcthree public release.}~\cite{GAMBIT:2018eea} to evaluate nuclear form factors, calculate the differential event rate, and evaluate the experimental likelihoods. The best-fit values for all parameters for each scan to the modulation spectrum from DAMA/LIBRA, both ANAIS-112 and COSINE-100, or all three experiments combined, are shown in Table \ref{tab:EFTparams}. The corresponding $\chi^2$ values and resulting tension is shown in Table \ref{tab:EFTchi2}. The combination of ANAIS-112 and COSINE-100 is found to rule out the DM nuclear recoil interpretation of the DAMA signal with a significance of $5.1\sigma$. Our best fit to the DAMA data alone prefers interactions via the $C^{(6)}_{3}$ operator, which induces spin- and momentum-dependent interactions, with a DM mass of 184 GeV. We find an almost equally good fit at a mass of approximately 40 GeV. Fitting to ANAIS+COSINE, as well as to all three experiments, yields small couplings to all operators, i.e. no DM signal. Restricting the nuclear recoil energy range in DAMA below 7 keV$_{\mathrm ee}$ provides a best fit mass of 36 GeV. However, this restriction does not change the qualitative conclusions regarding the tension between DAMA and other experiments, which remains above 5$\sigma$, hence we choose to present the fit over the full range for completeness. It has been speculated that quenching factors may be specific to individual crystals, rather than to the material itself. Since DAMA has never measured the energy dependence of its crystal's quenching factor, they assume a constant value of $0.3$ for sodium and $0.09$ for iodine~\cite{Bernabei:1996vj}. Measurements from other groups have consistently shown a strong energy-dependence, with sodium quenching factors never being higher than $\sim 0.2$, and going as low as $0.1$ below 5 keV~\cite{Carlin:2024maf}. Nonetheless, we have repeated all scans using the DAMA quenching factors for the DAMA response modeling, and still find that this only modestly reduces the tension to 4.63$\sigma$. The final column of table \ref{tab:EFTchi2} shows the resulting $\chi^2$ values. Fig.~\ref{fig:bestfits} shows the expected spectrum seen at DAMA/LIBRA (left), ANAIS-112 (centre) and COSINE-100 (right), if the signal is fit to that experiment only (orange), or to all three simultaneously (red). The large discrepancy between the data points (black) and the red curves for all three experiments illustrates the tension---in this EFT model, the strong preference of DAMA for modulation at low energies leads to similar predictions for the other experiments, a scenario which the data do not support. \begin{figure*}[t!] \includegraphics[width=\textwidth]{figures/predicted_rates_3.pdf} \caption{Comparison of experimental data to the predicted rates at the best-fit points of selected fits. \label{fig:bestfits}} \end{figure*} \begin{figure} \centering \includegraphics[width=1\linewidth]{figures/A1NR.pdf} \caption{Best-fit nuclear recoil spectra necessary to produce ``only'' a 3$\sigma$ tension between DAMA/LIBRA and COSINE+ANAIS, using the polynomial-exponential parametrisation \eqref{eq:polyexp} (solid lines), and binned (2$\sigma$ tension, dashed lines) with 10 times 2 bins. The pathological opposite-sign recoil between Na and I is generic of models that improve the overall fit.} \label{fig:NRbestfit} \end{figure} \begin{table} \caption{EFT Parameter values that maximize individual experimental likelihoods and the likelihood for all experiments combined. \label{tab:EFTparams}} \begin{tabular}{lcccc} \toprule & \bf All && \bf DAMA & \bf ANAIS+COSINE\\ \midrule $m_\chi$ [GeV] & 17.1 && 184 & 102 \\ $C^{(5)}_1$ & $1.41 \times 10^{-4}$ && $1.47 \times 10^{-6}$ & $2.44 \times 10^{-5}$ \\ $C^{(5)}_2$ & $1.00 \times 10^{-8}$ && $1.04 \times 10^{-8}$ & $1.22 \times 10^{-8}$ \\ $C^{(6)}_{1}$ & $6.12 \times 10^{-5}$ && $9.08 \times 10^{-7}$ & $1.51 \times 10^{-6}$ \\ $C^{(6)}_{2}$ & $1.19 \times 10^{-7}$ && $8.18 \times 10^{-4}$ & $2.82 \times 10^{-8}$ \\ $C^{(6)}_{3}$ & $1.47 \times 10^{-7}$ && 0.436 & $4.77 \times 10^{-7}$ \\ $C^{(6)}_{4}$ & $3.75 \times 10^{-7}$ && $1.13 \times 10^{-8}$ & $5.37 \times 10^{-8}$ \\ $\theta^{(6)}_1$ & $1.77\pi$ && $0.0353\pi$ & $0.676\pi$ \\ $\theta^{(6)}_2$ & $1.61\pi$ && $0.482\pi$ & $0.489\pi$ \\ $\theta^{(6)}_3$ & $1.89\pi$ && $1.30\pi$ & $1.27\pi$ \\ $\theta^{(6)}_4$ & $1.65\pi$ && $0.367\pi$ & $1.21\pi$ \\ \bottomrule \end{tabular} \end{table} \begin{table}[h] \caption{Best fit $\chi^2$ values for individual and combined experiments, as well as tension parameters. The first column shows the tension when all three experiments assume measured quenching factors for I and Na. The second column allows DAMA to use constant quenching factors.\label{tab:EFTchi2}} \centering % \begin{tabular}{l r r} %\begin{tabularx}{\linewidth}{p{2.8cm} p{2.2cm} p{3.2cm}} %\toprule % & \textbf{Common } & \textbf{Different quenching} \\ % & \textbf{quenching} & \textbf{for DAMA} \\ %\midrule % %All & 181.36 & 173.37 \\ %DAMA/LIBRA & 74.02 & 71.83 \\ %ANAIS+COSINE & 55.85 & 55.85 \\ %\midrule %$\delta \chi^2$ & 51.49 & 45.69 \\ %p-value & $3.37\times 10^{-7}$ & $3.66\times 10^{-6}$ \\ %Tension & $5.10 \sigma$ & $4.63 \sigma$ \\ %\bottomrule %\end{tabularx} \begin{tabularx}{\linewidth}{l c c } \toprule & \textbf{Common } & \textbf{Different quenching} \\ & \textbf{quenching} & \textbf{for DAMA} \\ \midrule All & 181.36 & 173.37 \\ DAMA/LIBRA & 74.02 & 71.83 \\ ANAIS+COSINE & 55.85 & 55.85 \\ \midrule $\delta \chi^2$ & 51.49 & 45.69 \\ p-value & $3.37\times 10^{-7}$ & $3.66\times 10^{-6}$ \\ Tension & $5.10 \sigma$ & $4.63 \sigma$ \\ \bottomrule \end{tabularx} \end{table} \textbf{\textit{How generic is the tension?---}} The use of specific particle physics and astrophysics assumptions means that any derived tension between DAMA/LIBRA and other experiments is necessarily model-dependent. We therefore also adopt a second approach which simply replaces the right-hand side of Equation~\ref{eq:recoil} by a generic functional form that is not constrained by any known particle, nuclear or astrophysics. We consider two sets of model-independent parameterisations: 1) A modulated nuclear recoil signal injected in $2N$ uniform $E_R$ bins between 1 and 80 keV\footnote{This range in nuclear recoil energy ensures that for quenching factors ranging from 5\% to 30\%, we cover the signal range in electron-equivalent energy.} allowing independent bin amplitudes between recoils with sodium and iodine, and 2) a polynomial $\times$ exponential parameterisation, inspired by the expected DM signal, but leaving coefficients completely free: \begin{eqnarray} A_1 &=& \sum_{T = \mathrm{Na,I}} \left(c^T_0 + c^T_1 E_R + c^T_2E_R^2 + ...\right)e^{-d_T E_R} , \label{eq:polyexp} \end{eqnarray} where $d_T$ and the $c_i^T$ are free parameters. We use \diver 1.3 embedded in \gambitlight\footnote{\gambitlight is a lightweight version of \gambit, available at \url{github.com/GambitBSM/gambit_light_1.0}.} to maximise the likelihoods of the resulting spectra with respect to the DAMA/LIBRA data, combined ANAIS-112 and COSINE-100 datasets, and the combination of all three experiments, and compute the tension statistic as in Eq.~\eqref{eq:tensionstat}. Demanding that the spect ra be produced ony by scattering with Na or I further worsens the tension in all cases. Resulting best fit $\chi^2$ values, p-values, and tension statistics are presented in the appendix. Using the tension statistic defined above, more than 12 bins (6 Na, 6 I) are required for the tension between DAMA/LIBRA and ANAIS-112 and COSINE-100 to fall below 5$\sigma$. With 20 bins, the tension reduces to 2$\sigma$. If we only allow for a signal in Na or I, the tension does not fall below 5$\sigma$ for 10 or fewer bins. Indeed, we find that the tension is only reduced when the contributions from Na and I in each bin have opposite signs (such that the one contribution peaks in summer, while the other peaks in winter), allowing for delicate cancellations to simultaneously fit the overall signal shape in all experiments thanks to their different binning, and therefore different mapping from nuclear to electronic recoil. The DM-inspired parameterisation from Eq.~\eqref{eq:polyexp} also leads to a reduced tension as the number of parameters is increased. When including only 4 free parameters (i.e. $c^{T}_0 e^{-d_T E_R}$ for both sodium and iodine), the tension is above the 5$\sigma$ level, but it drops modestly to 4.5, 4.1 and 3.2$\sigma$ as linear, quadratic and cubic terms in energy are added, respectively. As in the binned case, the best-fit points to the combined data tend to be pathological, preferring a signal with a positive modulation amplitude for Na, and negative for I. In other words, while recoils off sodium peak in the summer, nuclear recoils on iodine would need to peak in winter, or vice-versa. Fig.~\ref{fig:bestfits} shows the resulting signals in all three experiments in the case of the 10-parameter fit. The NR signal that leads to these results is in Fig.~\ref{fig:NRbestfit}. It is worth noting that this solution implies that the individual modulation amplitudes $A_1^T$ in both sodium and iodine must be much larger than the actually observed modulation amplitude $A_1 = \sum_T A_1^T$. However, the positivity of the time-dependent event rate in Eq.~\eqref{eq:parametrisation} implies that the average rate $A^T_0$ in each target must satisfy $A^T_0 \gtrsim |A^T_1|$. If $A_1^T$ has opposite sign for sodium and iodine, it follows that the total rate $A_0$ must be much larger than the observed modulation amplitude $|A_1|$. The total rate, on the other hand, can be constrained using independent measurements, such as the one presented by COSINE-100 in Ref.~\cite{COSINE-100:2021xqn}. While our goal here is to remain as agnostic as possible about the total rates, this self-consistency requirement would place these scenarios under further strain. \textbf{\textit{Conclusion---}} We have revisited the tension between the DAMA/LIBRA, ANAIS-112 and COSINE-100 DM annual modulation datasets. For a Dirac fermion interacting with Standard Model particles through dimension-five and dimension-six operators, DAMA/LIBRA is in a 5.10 $\sigma$ tension with the other two experiments. This conclusion is now independent of the fact that direct search DM experiments with other target nuclei would exclude the DAMA/LIBRA excess. If instead a generic parameterisation of the modulation amplitude vs nuclear recoil energy is used, the tension is still greater than 5$\sigma$ unless there is a significant degree of fine-tuning, resulting in a cancellation of the contributions from sodium and iodine. It remains interesting to consider a Southern hemisphere NaI experiment, such as the forthcoming SABRE South experiment~\cite{SABRE:2022twu}, which may shed further light on the mystery, in particular because it is expected to place a world-leading limit on the total rate of DM scattering in NaI detectors. \begin{acknowledgements} We thank Ankit Beniwal, Torsten Bringmann, Joachim Brod, Jan Conrad, Andrew Fowlie, Hyun Su Lee, Seung Mok, Pat Scott, Sebastian Wild, Anthony Williams and Jure Zupan for useful input, along with the full GAMBIT collaboration. This work was performed using the Cambridge Service for Data Driven Discovery (CSD3), part of which is operated by the University of Cambridge Research Computing on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The DiRAC component of CSD3 was funded by BEIS capital funding via STFC capital grants ST/P002307/1 and ST/R002452/1 and STFC operations grant ST/R00689X/1. DiRAC is part of the National e-Infrastructure. Additional support and computing resources from the Center for High Performance Computing at the University of Utah are gratefully acknowledged. GB is supported by the Australian Research Council grant CE200100008. JMC acknowledges support from the Weber State University College of Science and Academic Resources and Computing Committee. In addition, he is grateful to the Mainz Institute of Theoretical Physics (MITP) of the Cluster of Excellence PRISMA$^+$ (Project ID 39083149), for its hospitality and partial support during the completion of this work. FK acknowledges support from the DFG via Emmy Noether Grant No.\ KA 4662/1--2. AK is supported by the Research Council of Norway (RCN) through the FRIPRO grant 323985 PLUMBIN'. MP was supported by the Jim S. Bateman Research Fund at Weber State University. ACV was supported by Arthur B. McDonald Canadian Astroparticle Physics Research Institute, NSERC the Canada Foundation for Innovation and the Province of Ontario. Research at Perimeter Institute is supported by the Government of Canada through the Department of Innovation, Science, and Economic Development, and by the Province of Ontario. MJW is supported by the Australian Research Council grants CE200100008 and DP220100007. \end{acknowledgements} \bibliographystyle{JHEP_pat} \bibliography{R2,modrefs} \appendix \section*{Appendix} We present additional details on the results of our fits in table~\ref{tab:bigtab}. \onecolumngrid \begin{table*} \caption{$\chi^2$ values, p-values and tension statistics obtained by maximizing individual experimental likelihoods and the likelihood for all experiments combined for the generic functional form recoil spectra. \label{tab:bigtab}} \begin{tabular}{lcrrclr} \toprule Model & Parameters & $\chi^2$: All & DAMA & COSINE+ANAIS & p-value & Tension ($\sigma$) \\ \midrule \textbf{polyxexp} & 4 & 168.44 & 76.81 & 53.81 & $1.22 \times 10^{-7}$ & 5.16 \\ (independent & 6 & 162.43 & 73.67 & 52.81 & $2.82 \times 10^{-6}$ & 4.54 \\ Na+I) & 8 & 160.72 & 72.91 & 52.51 & $2.35 \times 10^{-5}$ & 4.07 \\ & 10 & 156.06 & 73.08 & 52.52 & $7.19 \times 10^{-4}$ & 3.19 \\ \hline {Na only} & 2 & 181.91 & 92.33 & 57.76 & $1.23 \times 10^{-7}$ & 5.16 \\ & 3 & 168.10 & 76.90 & 57.60 & $2.41 \times 10^{-7}$ & 5.03 \\ \hline {I only} & 2 & 188.31 & 86.25 & 57.83 & $2.49 \times 10^{-10}$ & 6.22 \\ & 3 & 177.83 & 75.81 & 57.81 & $1.36 \times 10^{-9}$ & 5.95 \\ \hline \hline \textbf{bins} & 2 & 204.77 & 103.65 & 58.02 & $4.36 \times 10^{-10}$ & 6.13 \\ (independent & 4 & 194.57 & 75.94 & 56.54 & $1.05 \times 10^{-12}$ & 7.03 \\ Na + I) & 6 & 176.70 & 74.02 & 51.30 & $2.49 \times 10^{-9}$ & 5.85 \\ & 10 & 159.90 & 59.66 & 45.60 & $3.69 \times 10^{-8}$ & 5.38 \\ & 12 & 156.98 & 56.99 & 44.74 & $1.63 \times 10^{-7}$ & 5.11 \\ & 16 & 139.75 & 52.38 & 39.54 & $5.07 \times 10^{-5}$ & 3.89 \\ &20 & 121.59 & 46.60 & 40.52& $2.31 \times 10^{-2}$ &1.99 \\ \hline Na only & 1 & 236.01 & 143.34 & 58.60 & $5.32 \times 10^{-9}$ & 5.72 \\ & 2 & 186.08 & 78.28 & 58.53 & $2.00 \times 10^{-11}$ & 6.60 \\ & 5 & 178.33 & 74.71 & 51.92 & $6.22 \times 10^{-10}$ & 6.07 \\ & 10 & 170.68 & 67.47 & 49.24 & $4.93 \times 10^{-8}$ & 5.33 \\ \hline I only & 1 & 204.78 & 103.66 & 58.61 & $7.02 \times 10^{-11}$ & 6.42 \\ & 2 & 195.03 & 76.64 & 58.27 & $8.81 \times 10^{-14}$ & 7.37 \\ & 5 & 191.22 & 75.10 & 51.84 & $1.58 \times 10^{-12}$ & 6.97 \\ & 10 & 172.06 & 72.06 & 47.69 & $9.97 \times 10^{-8}$ & 5.20 \\ \bottomrule \end{tabular} \end{table*} \end{document} ``` 4. **Bibliographic Information:** ```bbl \providecommand{\href}[2]{#2}\begingroup\raggedright\begin{thebibliography}{10} \bibitem{Bernabei:2003za} R.~Bernabei {\em et.~al.}, {\it {Dark matter search}}, {\em Riv. 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Phys. J. C} {\bf 79} (2019) 38, [\href{http://arxiv.org/abs/1808.10465}{{\tt arXiv:1808.10465}}]. \bibitem{Bernabei:1996vj} R.~Bernabei {\em et.~al.}, {\it {New limits on WIMP search with large-mass low-radioactivity NaI(Tl) set-up at Gran Sasso}}, {\em Phys. Lett. B} {\bf 389} (1996) 757--766. \bibitem{SABRE:2022twu} SABRE: E.~Barberio {\em et.~al.}, {\it {Simulation and background characterisation of the SABRE South experiment: SABRE South Collaboration}}, {\em Eur. Phys. J. C} {\bf 83} (2023) 878, [\href{http://arxiv.org/abs/2205.13849}{{\tt arXiv:2205.13849}}]. \end{thebibliography}\endgroup ``` 5. **Author Information:** - Lead Author: {'name': 'Giorgio Busoni'} - Full Authors List: ```yaml Giorgio Busoni: {} Jonathan M. Cornell: {} Will Handley: pi: start: 2020-10-01 thesis: null postdoc: start: 2016-10-01 end: 2020-10-01 thesis: null phd: start: 2012-10-01 end: 2016-09-30 supervisors: - Anthony Lasenby - Mike Hobson thesis: 'Kinetic initial conditions for inflation: theory, observation and methods' original_image: images/originals/will_handley.jpeg image: /assets/group/images/will_handley.jpg links: Webpage: https://willhandley.co.uk Felix Kahlhoefer: {} Anders Kvellestad: {} Masen Pitts: {} Lauren Street: {} Aaron C. Vincent: {} Martin White: {} ``` This YAML file provides a concise snapshot of an academic research group. It lists members by name along with their academic roles—ranging from Part III and summer projects to MPhil, PhD, and postdoctoral positions—with corresponding dates, thesis topics, and supervisor details. Supplementary metadata includes image paths and links to personal or departmental webpages. A dedicated "coi" section profiles senior researchers, highlighting the group’s collaborative mentoring network and career trajectories in cosmology, astrophysics, and Bayesian data analysis. ==================================================================================== Final Output Instructions ==================================================================================== - Combine all data sources to create a seamless, engaging narrative. - Follow the exact Markdown output format provided at the top. - Do not include any extra explanation, commentary, or wrapping beyond the specified Markdown. - Validate that every bibliographic reference with a DOI or arXiv identifier is converted into a Markdown link as per the examples. - Validate that every Markdown author link corresponds to a link in the author information block. - Before finalizing, confirm that no LaTeX citation commands or other undesired formatting remain. - Before finalizing, confirm that the link to the paper itself [2510.05216](https://arxiv.org/abs/2510.05216) is featured in the first sentence. Generate only the final Markdown output that meets all these requirements. {% endraw %}