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CMS measures suppression in oxygen and neon collisions

CMS has captured the first suppression signal in oxygen and neon collisions, and the excited states fell harder than the ground state.

Jamie Taylor··1 min read
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CMS measures suppression in oxygen and neon collisions
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CMS has measured mesons in oxygen-oxygen and neon-neon collisions for the first time, using 2025 light-ion data at 5.36 TeV and comparing the yields with proton-proton collisions at the same energy. The collaboration presented the result as EXO-25-021 on June 24, 2026, during Hard Probes 2026 in Nashville, Tennessee.

The new measurement covers all three S-wave bottomonium states, (1S), (2S) and (3S), and shows a sequential suppression pattern. The excited (2S) and (3S) states were suppressed more strongly than the ground-state (1S), exactly the hierarchy physicists look for when a hot, dense medium is strong enough to break apart weakly bound quark-antiquark states. CMS quantified the effect with double ratios of ion-ion yields relative to proton-proton yields.

The oxygen and neon runs give CMS another calibration point for how suppression changes as the initial nuclear geometry shrinks, and how small a collision system can be while still showing partonic energy loss and quarkonium dissociation.

The new data also land on top of an earlier CMS light-ion result that already showed medium effects in the same 2025 campaign. At the Initial Stages 2025 conference, CMS found about 70% suppression of charged particles around transverse momentum of 6 GeV in oxygen-oxygen and neon-neon collisions, with no suppression at the highest pT near 100 GeV. CMS also found the suppression slightly stronger in neon-neon than in oxygen-oxygen, a comparison that fits the neon nucleus's bowling-pin shape.

CERN’s 2025 light-ion cycle included the first-ever oxygen-oxygen and neon-neon collisions at the LHC, along with proton-oxygen running over several days in late June and early July. The program had been in feasibility studies since 2019, and the 2025 LHC delivered a record amount of data.

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