Quantum hydrogen-bond symmetrization in the superconducting hydrogen sulfide system.

The quantum nature of the proton can crucially affect the structural and physical properties of hydrogen compounds. For example, in the high-pressure phases of H2O, quantum proton fluctuations lead to symmetrization of the hydrogen bond and reduce the boundary between asymmetric and symmetric structures in the phase diagram by 30 gigapascals (ref. 3). Here we show that an analogous quantum symmetrization occurs in the recently discovered sulfur hydride superconductor with a superconducting transition temperature Tc of 203 kelvin at 155 gigapascals--the highest Tc reported for any superconductor so far. Superconductivity occurs via the formation of a compound with chemical formula H3S (sulfur trihydride) with sulfur atoms arranged on a body-centred cubic lattice. If the hydrogen atoms are treated as classical particles, then for pressures greater than about 175 gigapascals they are predicted to sit exactly halfway between two sulfur atoms in a structure with Im3m symmetry. At lower pressures, the hydrogen atoms move to an off-centre position, forming a short H-S covalent bond and a longer H···S hydrogen bond in a structure with R3m symmetry. X-ray diffraction experiments confirm the H3S stoichiometry and the sulfur lattice sites, but were unable to discriminate between the two phases. Ab initio density-functional-theory calculations show that quantum nuclear motion lowers the symmetrization pressure by 72 gigapascals for H3S and by 60 gigapascals for D3S. Consequently, we predict that the Im3m phase dominates the pressure range within which the high Tc was measured. The observed pressure dependence of Tc is accurately reproduced in our calculations for the phase, but not for the R3m phase. Therefore, the quantum nature of the proton fundamentally changes the superconducting phase diagram of H3S.We acknowledge financial support from the Spanish Ministry of Economy and Competitiveness (FIS2013- 48286-C2-2-P), French Agence Nationale de la Recherche (Grant No. ANR-13-IS10-0003- 392 01), EPSRC (UK) (Grant No. EP/J017639/1), Cambridge Commonwealth Trust, National Natural Science Foundation of China (Grants No. 11204111, 11404148, and 11274136), and 2012 Changjiang Scholars Program of China. Work at Carnegie was supported by EFree, an Energy Frontier Research Center funded by the DOE, Office of Science, Basic Energy Sciences under Award No. DE-SC-0001057. Computer facilities were provided by the PRACE project AESFT and the Donostia International Physics Center (DIPC).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nature1717

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Phase transitions in random circuit sampling.

Undesired coupling to the surrounding environment destroys long-range correlations in quantum processors and hinders coherent evolution in the nominally available computational space. This noise is an outstanding challenge when leveraging the computation power of near-term quantum processors1. It has been shown that benchmarking random circuit sampling with cross-entropy benchmarking can provide an estimate of the effective size of the Hilbert space coherently available2-8. Nevertheless, quantum algorithms' outputs can be trivialized by noise, making them susceptible to classical computation spoofing. Here, by implementing an algorithm for random circuit sampling, we demonstrate experimentally that two phase transitions are observable with cross-entropy benchmarking, which we explain theoretically with a statistical model. The first is a dynamical transition as a function of the number of cycles and is the continuation of the anti-concentration point in the noiseless case. The second is a quantum phase transition controlled by the error per cycle; to identify it analytically and experimentally, we create a weak-link model, which allows us to vary the strength of the noise versus coherent evolution. Furthermore, by presenting a random circuit sampling experiment in the weak-noise phase with 67 qubits at 32 cycles, we demonstrate that the computational cost of our experiment is beyond the capabilities of existing classical supercomputers. Our experimental and theoretical work establishes the existence of transitions to a stable, computationally complex phase that is reachable with current quantum processors

Modeling dielectric permittivity of polymer composites filled with transition metal dichalcogenide nanoparticles

A model is developed for the dielectric permittivity of polymer nanocomposites reinforced with transition metal dichalcogenide fillers at microwave frequencies. The model takes into account aggregation of nanoparticles into clusters (that involve both filler and matrix components) and the aspect ratio of aggregates. The governing equations involve four material parameters that are found by matching observations on the real and imaginary parts of the dielectric permittivity of polymers reinforced with MoS2 and WS2 micro- and nanospheres, MoS2 nanosheets and nanoflowers, and composite heterostructures formed by MoS2 and MoS2-CoS2 nanoparticles with graphene and reduced graphene oxide. Good agreement is demonstrated between results of simulation and the experimental data at frequencies in the S, X, and Ku bands of the electromagnetic spectrum. It is shown that composite heterostructures have superior dielectric properties compared with those of neat transition metal dichalcogenide nanoparticles. </jats:p