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  1. Free, publicly-accessible full text available December 10, 2025
  2. null (Ed.)
  3. Abstract A recent focus of quantum spin liquid (QSL) studies is how disorder/randomness in a QSL candidate affects its true magnetic ground state. The ultimate question is whether the QSL survives disorder or the disorder leads to a “spin-liquid-like” state, such as the proposed random-singlet (RS) state. Since disorder is a standard feature of most QSL candidates, this question represents a major challenge for QSL candidates. YbMgGaO 4 , a triangular lattice antiferromagnet with effective spin-1/2 Yb 3+ ions, is an ideal system to address this question, since it shows no long-range magnetic ordering with Mg/Ga site disorder. Despite the intensive study, it remains unresolved as to whether YbMgGaO 4 is a QSL or in the RS state. Here, through ultralow-temperature thermal conductivity and magnetic torque measurements, plus specific heat and DC magnetization data, we observed a residual κ 0 / T term and series of quantum spin state transitions in the zero temperature limit for YbMgGaO 4 . These observations strongly suggest that a QSL state with itinerant excitations and quantum spin fluctuations survives disorder in YbMgGaO 4 . 
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  4. Simulation-to-real domain adaptation for semantic segmentation has been actively studied for various applications such as autonomous driving. Existing methods mainly focus on a single-source setting, which cannot easily handle a more practical scenario of multiple sources with different distributions. In this paper, we propose to investigate multi-source domain adaptation for semantic segmentation. Specifically, we design a novel framework, termed Multi-source Adversarial Domain Aggregation Network (MADAN), which can be trained in an end-to-end manner. First, we generate an adapted domain for each source with dynamic semantic consistency while aligning at the pixel-level cycle-consistently towards the target. Second, we propose sub-domain aggregation discriminator and cross-domain cycle discriminator to make different adapted domains more closely aggregated. Finally, feature-level alignment is performed between the aggregated domain and target domain while training the segmentation network. Extensive experiments from synthetic GTA and SYNTHIA to real Cityscapes and BDDS datasets demonstrate that the proposed MADAN model outperforms state-of-the-art approaches. Our source code is released at: https://github.com/Luodian/MADAN. 
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  5. Abstract The occurrences and cycling of slab‐originated carbon and hydrogen are considered to be controlled by their reactions with metallic iron from mantle disproportionation and slab serpentinization, to form Fe alloys containing carbon and hydrogen. Here we show experimental results on the phase relations and melting of the Fe‐C‐H system using laser‐heated diamond anvil cell and X‐ray diffraction techniques up to 72 GPa. The incorporation of hydrogen was found to lower the eutectic melting temperatures of Fe‐C alloy by ∼50–178 K at 20–70 GPa, facilitating the formation of metallic liquids in the deep mantle and thus enhancing the mobility and deep cycling of subducted carbon and hydrogen. Hydrogen also substitutes with carbon in Fe‐C metal to form hydride and diamond at relatively high‐temperature conditions (e.g., 42.6 GPa, >1885 K and 71.8 GPa, >1798 K). The hydrogen‐carbon‐enriched metallic liquids provide the necessary fluid environment for superdeep diamond growth. 
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  6. Abstract A search for leptoquark pair production decaying into$$te^- \bar{t}e^+$$ t e - t ¯ e + or$$t\mu ^- \bar{t}\mu ^+$$ t μ - t ¯ μ + in final states with multiple leptons is presented. The search is based on a dataset ofppcollisions at$$\sqrt{s}=13~\text {TeV} $$ s = 13 TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$$^{-1}$$ - 1 . Four signal regions, with the requirement of at least three light leptons (electron or muon) and at least two jets out of which at least one jet is identified as coming from ab-hadron, are considered based on the number of leptons of a given flavour. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No excess above the Standard Model background prediction is observed and 95% confidence level limits on the production cross section times branching ratio are derived as a function of the leptoquark mass. Under the assumption of exclusive decays into$$te^{-}$$ t e - ($$t\mu ^{-}$$ t μ - ), the corresponding lower limit on the scalar mixed-generation leptoquark mass$$m_{\textrm{LQ}_{\textrm{mix}}^{\textrm{d}}}$$ m LQ mix d is at 1.58 (1.59) TeV and on the vector leptoquark mass$$m_{{\tilde{U}}_1}$$ m U ~ 1 at 1.67 (1.67) TeV in the minimal coupling scenario and at 1.95 (1.95) TeV in the Yang–Mills scenario. 
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  7. A search for high-mass resonances decaying into a τ -lepton and a neutrino using proton-proton collisions at a center-of-mass energy of s = 13 TeV is presented. The full run 2 data sample corresponding to an integrated luminosity of 139 fb 1 recorded by the ATLAS experiment in the years 2015–2018 is analyzed. The τ -lepton is reconstructed in its hadronic decay modes and the total transverse momentum carried out by neutrinos is inferred from the reconstructed missing transverse momentum. The search for new physics is performed on the transverse mass between the τ -lepton and the missing transverse momentum. No excess of events above the Standard Model expectation is observed and upper exclusion limits are set on the W τ ν production cross section. Heavy W vector bosons with masses up to 5.0 TeV are excluded at 95% confidence level, assuming that they have the same couplings as the Standard Model W boson. For nonuniversal couplings, W bosons are excluded for masses less than 3.5–5.0 TeV, depending on the model parameters. In addition, model-independent limits on the visible cross section times branching ratio are determined as a function of the lower threshold on the transverse mass of the τ -lepton and missing transverse momentum. © 2024 CERN, for the ATLAS Collaboration2024CERN 
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