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Abstract The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments. 

Abstract Despite the f₀(980) hadron having been discovered half a century ago, the question about its quark content has not been settled: it might be an ordinary quark-antiquark ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$) meson, a tetraquark ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$) exotic state, a kaon-antikaon ($${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$) molecule, or a quark-antiquark-gluon ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$) hybrid. This paper reports strong evidence that the f₀(980) state is an ordinary$${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$meson, inferred from the scaling of elliptic anisotropies (v₂) with the number of constituent quarks (n_q), as empirically established using conventional hadrons in relativistic heavy ion collisions. The f₀(980) state is reconstructed via its dominant decay channel f₀(980) →π⁺π⁻, in proton-lead collisions recorded by the CMS experiment at the LHC, and itsv₂is measured as a function of transverse momentum (p_T). It is found that then_q= 2 ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$state) hypothesis is favored overn_q= 4 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$or$${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$states) by 7.7, 6.3, or 3.1 standard deviations in thep_T< 10, 8, or 6 GeV/cranges, respectively, and overn_q= 3 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$hybrid state) by 3.5 standard deviations in thep_T< 8 GeV/crange. This result represents the first determination of the quark content of the f₀(980) state, made possible by using a novel approach, and paves the way for similar studies of other exotic hadron candidates. 

Abstract A search is presented for the pair production of new heavy resonances, each decaying into a top quark (t) or antiquark and a gluon (g). The analysis uses data recorded with the CMS detector from proton–proton collisions at a center-of-mass energy of 13$$\,\text {Te}\hspace{-.08em}\text {V}$$ $\text{Te}\text{V}$at the LHC, corresponding to an integrated luminosity of 138$$\,\text {fb}^{-1}$$ ${\text{fb}}^{-1}$. Events with one muon or electron, multiple jets, and missing transverse momentum are selected. After using a deep neural network to enrich the data sample with signal-like events, distributions in the scalar sum of the transverse momenta of all reconstructed objects are analyzed in the search for a signal. No significant deviations from the standard model prediction are found. Upper limits at 95% confidence level are set on the product of cross section and branching fraction squared for the pair production of excited top quarks in the$$\text {t}^{*} \rightarrow {\text {t}} {\text {g}} $$ $\text{t}_{}^{\ast }\to \text{tg}$decay channel. The upper limits range from 120 to 0.8$$\,\text {fb}$$ $\text{fb}$for a$$\text {t}^{*} $$ $\text{t}_{}^{\ast }$with spin-1/2 and from 15 to 1.0$$\,\text {fb}$$ $\text{fb}$for a$$\text {t}^{*} $$ $\text{t}_{}^{\ast }$with spin-3/2. These correspond to mass exclusion limits up to 1050 and 1700$$\,\text {Ge}\hspace{-.08em}\text {V}$$ $\text{Ge}\text{V}$for spin-1/2 and spin-3/2$$\text {t}^{*} $$ $\text{t}_{}^{\ast }$particles, respectively. These are the most stringent limits to date on the existence of$$\text {t}^{*} \rightarrow {\text {t}} {\text {g}} $$ $\text{t}_{}^{\ast }\to \text{tg}$resonances. 

Abstract A measurement of the dijet production cross section is reported based on proton–proton collision data collected in 2016 at$$\sqrt{s}=13\,\text {Te}\hspace{-.08em}\text {V} $$ $\sqrt{s}=13\mathrm{Te}V$by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of up to 36.3$$\,\text {fb}^{-1}$$ ${\mathrm{fb}}^{-1}$. Jets are reconstructed with the anti-$$k_{\textrm{T}} $$ $k_{\text{T}}$algorithm for distance parameters of$$R=0.4$$ $R=0.4$and 0.8. Cross sections are measured double-differentially (2D) as a function of the largest absolute rapidity$$|y |_{\text {max}} $$ ${\left|y\right|}_{\max }$of the two jets with the highest transverse momenta$$p_{\textrm{T}}$$ $p_{\text{T}}$and their invariant mass$$m_{1,2} $$ $m_{1,2}$, and triple-differentially (3D) as a function of the rapidity separation$$y^{*} $$ $y^{\ast }$, the total boost$$y_{\text {b}} $$ $y_b$, and either$$m_{1,2} $$ $m_{1,2}$or the average$$p_{\textrm{T}}$$ $p_{\text{T}}$of the two jets. The cross sections are unfolded to correct for detector effects and are compared with fixed-order calculations derived at next-to-next-to-leading order in perturbative quantum chromodynamics. The impact of the measurements on the parton distribution functions and the strong coupling constant at the mass of the$${\text {Z}} $$ $Z$boson is investigated, yielding a value of$$\alpha _\textrm{S} (m_{{\text {Z}}}) =0.1179\pm 0.0019$$ ${\alpha }_{\text{S}}\left(m_Z\right)=0.1179\pm 0.0019$. 

Abstract Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors. 

Abstract This paper describes theCombinesoftware package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to runCombineand reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details ofCombine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide. 

Abstract A search is reported for charge-parity$$CP$$ $\mathrm{CP}$violation in$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$ ${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0$decays, using data collected in proton–proton collisions at$$\sqrt{s} = 13\,\text {Te}\hspace{-.08em}\text {V} $$ $\sqrt{s}=13\text{Te}\text{V}$recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6$$\,\text {fb}^{-1}$$ ${\text{fb}}^{-1}$, which consists of about 10 billion events containing a pair of b hadrons, nearly all of which decay to charm hadrons. The flavor of the neutral D meson is determined by the pion charge in the reconstructed decays$${{{\textrm{D}}}^{{*+}}} \rightarrow {{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} $$ $\text{D}_{}^{\ast +}\to {\text{D}}^0{\pi }^{+}$and$${{{\textrm{D}}}^{{*-}}} \rightarrow {\overline{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{-}}} $$ $\text{D}_{}^{\ast -}\to {\overline{\text{D}}}^0{\pi }^{-}$. The$$CP$$ $\mathrm{CP}$asymmetry in$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$ ${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0$is measured to be$$A_{CP} ({{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} ) = (6.2 \pm 3.0 \pm 0.2 \pm 0.8)\%$$ $A_{\mathrm{CP}}\left({\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0\right)=(6.2\pm 3.0\pm 0.2\pm 0.8)\%$, where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the$$CP$$ $\mathrm{CP}$asymmetry in the$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} {{{\mathrm{\uppi }}}^{{-}}} $$ ${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\pi }^{+}{\pi }^{-}$decay. This is the first$$CP$$ $\mathrm{CP}$asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state. 

Abstract Partons traversing the strongly interacting medium produced in heavy-ion collisions are expected to lose energy depending on their color charge and mass. We measure the nuclear modification factors for charm- and bottom-decay electrons, defined as the ratio of yields, divided by the number of binary nucleon–nucleon collisions, in $$\sqrt{s_{\textrm{NN}}}=200$$ s NN = 200 GeV Au+Au collisions to p + p collisions ( $$R_{\textrm{AA}}$$ R AA ), or in central to peripheral Au+Au collisions ( $$R_{\textrm{CP}}$$ R CP ). We find the bottom-decay electron $$R_{\textrm{AA}}$$ R AA and $$R_{\textrm{CP}}$$ R CP to be significantly higher than those of charm-decay electrons. Model calculations including mass-dependent parton energy loss in a strongly coupled medium are consistent with the measured data. These observations provide evidence of mass ordering of charm and bottom quark energy loss when traversing through the strongly coupled medium created in heavy-ion collisions. 

Abstract Using proton–proton collision data corresponding to an integrated luminosity of$$140\hbox { fb}^{-1}$$ $140{\text{fb}}^{-1}$collected by the CMS experiment at$$\sqrt{s}= 13\,\text {Te}\hspace{-.08em}\text {V} $$ $\sqrt{s}=13\text{Te}\text{V}$, the$${{{\Lambda }} _{\text {b}}^{{0}}} \rightarrow {{\text {J}/\uppsi }} {{{\Xi }} ^{{-}}} {{\text {K}} ^{{+}}} $$ ${\Lambda }_{\text{b}}^0\to \text{J}/\psi {\Xi }^{-}{\text{K}}^{+}$decay is observed for the first time, with a statistical significance exceeding 5 standard deviations. The relative branching fraction, with respect to the$${{{\Lambda }} _{\text {b}}^{{0}}} \rightarrow {{{\uppsi }} ({2\textrm{S}})} {{\Lambda }} $$ ${\Lambda }_{\text{b}}^0\to \psi \left(2\text{S}\right)\Lambda$decay, is measured to be$$\mathcal {B}({{{\Lambda }} _{\text {b}}^{{0}}} \rightarrow {{\text {J}/\uppsi }} {{{\Xi }} ^{{-}}} {{\text {K}} ^{{+}}} )/\mathcal {B}({{{\Lambda }} _{\text {b}}^{{0}}} \rightarrow {{{\uppsi }} ({2\textrm{S}})} {{\Lambda }} ) = [3.38\pm 1.02\pm 0.61\pm 0.03]\%$$ $B({\Lambda }_{\text{b}}^0\to \text{J}/\psi {\Xi }^{-}{\text{K}}^{+})/B({\Lambda }_{\text{b}}^0\to \psi \left(2\text{S}\right)\Lambda )=[3.38\pm 1.02\pm 0.61\pm 0.03]\%$, where the first uncertainty is statistical, the second is systematic, and the third is related to the uncertainties in$$\mathcal {B}({{{\uppsi }} ({2\textrm{S}})} \rightarrow {{\text {J}/\uppsi }} {{{\uppi }} ^{{+}}} {{{\uppi }} ^{{-}}} )$$ $B(\psi \left(2\text{S}\right)\to \text{J}/\psi {\pi }^{+}{\pi }^{-})$and$$\mathcal {B}({{{\Xi }} ^{{-}}} \rightarrow {{\Lambda }} {{{\uppi }} ^{{-}}} )$$ $B({\Xi }^{-}\to \Lambda {\pi }^{-})$.