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Lang, Michael

Publications and source records attributed to Lang, Michael.

Characterization of the pressure coefficient of manganin and temperature evolution of pressure in piston-cylinder cells

Here, we report measurements of the temperature- and pressure-dependent resistance, R ( T , p ), of a manganin manometer in a 4 He-gas pressure setup from room temperature down to the solidification temperature of 4 He ( T solid ~ 50 K at 0.8 GPa) for pressures, p , between 0 GPa and ~0.8 GPa. The same manganin wire manometer was also measured in a piston-cylinder cell (PCC) from 300 K down to 1.8 K and for pressures between 0 GPa and ~2 GPa. From these data, we infer the temperature and pressure dependence of the pressure coefficient of manganin, α ( T , p ), defined by the equation R p = (1 + αp ) R 0 , where R 0 and R p are the resistances of manganin at ambient pressure and finite pressure, respectively. Our results indicate that upon cooling, α first decreases, then goes through a broad minimum at ~120 K, and increases again toward lower temperatures. In addition, we find that α is almost pressure-independent at T ≳ 60 K up to p ~ 2 GPa, but shows a pronounced p dependence at T ≲ 60 K. Using this manganin manometer, we demonstrate that p overall decreases with decreasing temperature in the PCC for the full pressure range and that the size of the pressure difference between room temperature and low temperatures ( T = 1.8 K), Δ p , decreases with increasing pressure. We also compare the pressure values inferred from the manganin manometer with the low-temperature pressure, determined from the superconducting transition temperature of elemental lead (Pb). As a result of these data and analysis, we propose a practical algorithm to infer the evolution of pressure with temperature in a PCC.

47 OTHER INSTRUMENTATION↗

Signatures for spinons in the quantum spin liquid candidate Ca 10 Cr 7 O 28

We present new experimental low-temperature heat capacity and detailed dynamical spin-structure factor data for the quantum spin-liquid candidate material Ca 10 Cr 7 O 28 . The measured heat capacity shows an almost-perfect linear temperature dependence in the range $0.1K ≲T≲ 0.5K$, reminiscent of fermionic spinon degrees of freedom. The spin-structure factor exhibits two energy regimes of strong signal which display rather different but solely diffuse scattering features. We theoretically describe these findings by an effective spinon-hopping model which crucially relies on the existence of strong ferromagnetically coupled triangles in the system. Our spinon theory is shown to naturally reproduce the overall weight distribution of the measured spin-structure factor. Particularly, we argue that various different observed characteristic properties of the spin-structure factor and the heat capacity consistently indicate the existence of a spinon Fermi surface. A closer analysis of the heat capacity at the lowest accessible temperatures hints toward the presence of weak f-wave spinon-pairing terms inducing a small partial gap along the Fermi surface (except for discrete nodal Dirac points) and suggesting an overall Z2 quantum spin-liquid scenario for Ca 10 Cr 7 O 28 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Modeling Universal Globally Adaptive Load-Balanced Routing

Universal globally adaptive load-balanced (UGAL) routing has been proposed for various interconnection networks and has been deployed in a number of current-generation supercomputers. Although UGAL-based schemes have been extensively studied, most existing results are based on either simulation or measurement. Without a theoretical understanding of UGAL, multiple questions remain: For which traffic patterns is UGAL most suited? Furthermore, what determines the performance of the UGAL-based scheme on a particular network configuration? Here, we develop a set of throughput models for UGALbased on linear programming. We show that the throughput models are valid across the torus, Dragonfly, and Slim Fly network topologies. Finally, we identify a robust model that can accurately and efficiently predict UGAL throughput for a set of representative traffic patterns across different topologies. Our models not only provide a mechanism to predict UGAL performance on large-scale interconnection networks but also reveal the inner working of UGAL and further our understanding of this type of routing.

97 MATHEMATICS AND COMPUTING↗