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1. Evidence of a liquid–liquid phase transition in H$$_2$$O and D$$_2$$O from path-integral molecular dynamics simulations

   https://doi.org/10.1038/s41598-022-09525-x  

   Eltareb, Ali ; Lopez, Gustavo E. ; Giovambattista, Nicolas ( April 2022 , Scientific Reports)

   We perform path-integral molecular dynamics (PIMD), ring-polymer MD (RPMD), and classical MD simulations of H$$_2$$${}_2$O and D$$_2$$${}_2$O using the q-TIP4P/F water model over a wide range of temperatures and pressures. The density$$\rho (T)$$$\rho \left(T\right)$, isothermal compressibility$$\kappa _T(T)$$${\kappa }_T\left(T\right)$, and self-diffusion coefficientsD(T) of H$$_2$$${}_2$O and D$$_2$$${}_2$O are in excellent agreement with available experimental data; the isobaric heat capacity$$C_P(T)$$$C_P\left(T\right)$obtained from PIMD and MD simulations agree qualitatively well with the experiments. Some of these thermodynamic properties exhibit anomalous maxima upon isobaric cooling, consistent with recent experiments and with the possibility that H$$_2$$${}_2$O and D$$_2$$${}_2$O exhibit a liquid-liquid critical point (LLCP) at low temperatures and positive pressures. The data from PIMD/MD for H$$_2$$${}_2$O and D$$_2$$${}_2$O can be fitted remarkably well using the Two-State-Equation-of-State (TSEOS). Using the TSEOS, we estimate that the LLCP for q-TIP4P/F H$$_2$$${}_2$O, from PIMD simulations, is located at$$P_c = 167 \pm 9$$$P_c=167\pm 9$ MPa,$$T_c = 159 \pm 6$$$T_c=159\pm 6$ K, and$$\rho _c = 1.02 \pm 0.01$$${\rho }_c=1.02\pm 0.01$ g/cm$$^3$$${}^3$. Isotope substitution effects are important; the LLCP location in q-TIP4P/F D$$_2$$${}_2$O is estimated to be$$P_c = 176 \pm 4$$$P_c=176\pm 4$ MPa,$$T_c = 177 \pm 2$$$T_c=177\pm 2$ K, and$$\rho _c = 1.13 \pm 0.01$$${\rho }_c=1.13\pm 0.01$ g/cm$$^3$$${}^3$. Interestingly, for the water model studied, differences in the LLCP location from PIMD and MD simulations suggest that nuclear quantum effects (i.e., atoms delocalization) play an important role in the thermodynamics of water around the LLCP (from the MD simulations of q-TIP4P/F water,$$P_c = 203 \pm 4$$$P_c=203\pm 4$ MPa,$$T_c = 175 \pm 2$$$T_c=175\pm 2$ K, and$$\rho _c = 1.03 \pm 0.01$$${\rho }_c=1.03\pm 0.01$ g/cm$$^3$$${}^3$). Overall, our results strongly support the LLPT scenario to explain water anomalous behavior, independently of the fundamental differences between classical MD and PIMD techniques. The reported values of$$T_c$$$T_c$for D$$_2$$${}_2$O and, particularly, H$$_2$$${}_2$O suggest that improved water models are needed for the study of supercooled water.

    

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2. Searching for a dark matter particle with anti-protonic atoms

   https://doi.org/10.1140/epjc/s10052-023-12319-8  

   Doser, Michael ; Farrar, Glennys ; Kornakov, Georgy ( December 2023 , The European Physical Journal C)

   A wide range of dark matter candidates have been proposed and are actively being searched for in a large number of experiments, both at high (TeV) and low (sub meV) energies. One dark matter candidate, a deeply bounduuddsssexaquark,$$S$$$S$, with mass$$\sim 2$$$\sim 2$GeV (having the same quark content as the hypothesized H-dibaryon, but long lived) is particularly difficult to explore experimentally. In this paper, we propose a scheme in which such a state could be produced at rest through the formation of$$\bar{p}$$$\overline{p}$–$$^3$$${}^3$He antiprotonic atoms and their annihilation into$$S$$$S$+$$K^+K^+\pi ^-$$$K^{+}{K}^{+}{\pi }^{-}$, identified both through the unique tag of a$$S=+2, Q=+1$$$S=+2,Q=+1$final state, as well as through full kinematic reconstruction of the final state recoiling against it.

    

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3. 3D Mirror Symmetry for Instanton Moduli Spaces

   https://doi.org/10.1007/s00220-023-04831-5  

   Koroteev, Peter ; Zeitlin, Anton M. ( September 2023 , Communications in Mathematical Physics)

   We prove that the Hilbert scheme ofkpoints on$${\mathbb {C}}^2$$$C^2$($$\hbox {Hilb}^k[{\mathbb {C}}^2]$$${\text{Hilb}}^k\left[C^2\right]$) is self-dual under three-dimensional mirror symmetry using methods of geometry and integrability. Namely, we demonstrate that the corresponding quantum equivariant K-theory is invariant upon interchanging its Kähler and equivariant parameters as well as inverting the weight of the$${\mathbb {C}}^\times _\hbar $$$C_{ħ}^{\times }$-action. First, we find a two-parameter family$$X_{k,l}$$$X_{k,l}$of self-mirror quiver varieties of type A and study their quantum K-theory algebras. The desired quantum K-theory of$$\hbox {Hilb}^k[{\mathbb {C}}^2]$$${\text{Hilb}}^k\left[C^2\right]$is obtained via direct limit$$l\longrightarrow \infty $$$l⟶\infty$and by imposing certain periodic boundary conditions on the quiver data. Throughout the proof, we employ the quantum/classical (q-Langlands) correspondence between XXZ Bethe Ansatz equations and spaces of twisted$$\hbar $$$ħ$-opers. In the end, we propose the 3d mirror dual for the moduli spaces of torsion-free rank-Nsheaves on$${\mathbb {P}}^2$$$P^2$with the help of a different (three-parametric) family of type A quiver varieties with known mirror dual.

    

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4. Search for supersymmetry in final states with missing transverse momentum and three or more b-jets in 139 fb$$^{-1}$$ of proton–proton collisions at $$\sqrt{s} = 13$$ TeV with the ATLAS detector

   https://doi.org/10.1140/epjc/s10052-023-11543-6  

   Aad, G. ; Abbott, B. ; Abbott, D. C. ; Abeling, K. ; Abidi, S. H. ; Aboulhorma, A. ; Abramowicz, H. ; Abreu, H. ; Abulaiti, Y. ; Abusleme Hoffman, A. C. ; et al ( July 2023 , The European Physical Journal C)

   A search for supersymmetry involving the pair production of gluinos decaying via off-shell third-generation squarks into the lightest neutralino$$(\tilde{\chi }^0_1)$$$\left({\tilde{\chi }}_1^0\right)$is reported. It exploits LHC proton–proton collision data at a centre-of-mass energy$$\sqrt{s} = 13$$$\sqrt{s}=13$TeV with an integrated luminosity of 139 fb$$^{-1}$$${}^{-1}$collected with the ATLAS detector from 2015 to 2018. The search uses events containing large missing transverse momentum, up to one electron or muon, and several energetic jets, at least three of which must be identified as containingb-hadrons. Both a simple kinematic event selection and an event selection based upon a deep neural-network are used. No significant excess above the predicted background is found. In simplified models involving the pair production of gluinos that decay via off-shell top (bottom) squarks, gluino masses less than 2.44 TeV (2.35 TeV) are excluded at 95% CL for a massless$$\tilde{\chi }^0_1.$$${\tilde{\chi }}_1^0.$Limits are also set on the gluino mass in models with variable branching ratios for gluino decays to$$b\bar{b}\tilde{\chi }^0_1,$$$b\overline{b}{\tilde{\chi }}_1^0,$$$t\bar{t}\tilde{\chi }^0_1$$$t\overline{t}{\tilde{\chi }}_1^0$and$$t\bar{b}\tilde{\chi }^-_1/\bar{t}b\tilde{\chi }^+_1.$$$t\overline{b}{\tilde{\chi }}_1^{-}/\overline{t}b{\tilde{\chi }}_1^{+}.$

    

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5. Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

   https://doi.org/10.1186/s13321-022-00660-1  

   Kenney, David H. ; Paffenroth, Randy C. ; Timko, Michael T. ; Teixeira, Andrew R. ( January 2023 , Journal of Cheminformatics)

   MF-LOGP, a new method for determining a single component octanol–water partition coefficients ($$LogP$$$\mathrm{LogP}$) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make$$LogP$$$\mathrm{LogP}$predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average$$RMSE$$$\mathrm{RMSE}$= 0.77 ± 0.007,$$MAE$$$\mathrm{MAE}$= 0.52 ± 0.003, and$${R}^{2}$$$R^2$= 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ($$RMSE$$$\mathrm{RMSE}$= 0.42–1.54,$$MAE$$$\mathrm{MAE}$= 0.09–1.07, and$${R}^{2}$$$R^2$= 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures.

   Graphical Abstract

    

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