We present a search at the Jefferson Laboratory for new forces mediated by sub-GeV vector bosons with weak coupling α' to electrons. Such a particle A' can be produced in electron-nucleus fixed-target scattering and then decay to an e + e- pair, producing a narrow resonance in the QED trident spectrum. Using APEX test run data, we searched in the mass range 175-250 MeV, found no evidence for an A'→ e+ e- reaction, and set an upper limit of α'/α ~/= 10(-6). Our findings demonstrate that fixed-target searches can explore a new, wide, and important range of masses and couplings for sub-GeV forces.

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The angular correlation of radiation from positrons annihilating in lithium single crystals has been measured. The crystals were oriented in the [100], [110], and [111] directions, and the measurements yield information closely related to the areas of slices through the Fermi surface normal to these directions. The measurements show that the Fermi surface of lithium is anisotropic, the length of the radius vector &no being about 5% greater than km. The measurements also yield estimates of the energy gap at the boundary of the first Brillouin zone, and the amplitudes of the most important higher-momentum components of the electron wave function.

Experimental data from positron annihilation in sodium single crystals show (a) that the Fermi surface is spherical and (b) that the momentum dependence of the "enhancement factor" of the polarization of the electron sea by the positron agrees with calculations.

GENE solves the five-dimensional gyrokinetic equations to simulate the development and evolution of plasma microturbulence in magnetic fusion devices. The plasma model used is close to first principles and computationally very expensive to solve in the relevant physical regimes. In order to use the emerging computational capabilities to gain new physics insights, several new numerical and computational developments are required. Here, we focus on the fact that it is crucial to efficiently utilize GPUs (graphics processing units) that provide the vast majority of the computational power on such systems. In this paper, we describe the various porting approaches considered and given the constraints of the GENE code and its development model, justify the decisions made, and describe the path taken in porting GENE to GPUs. We introduce a novel library called gtensor that was developed along the way to support the process. Performance results are presented for the ported code, which in a single node of the Summit supercomputer achieves a speed-up of almost 15× compared to running on central processing unit (CPU) only. Typical GPU kernels are memory-bound, achieving about 90% of peak. Our analysis shows that there is still room for improvement if we can refactor/fuse kernels to achieve higher arithmetic intensity. We also performed a weak parallel scalability study, which shows that the code runs well on a massively parallel system, but communication costs start becoming a significant bottleneck.