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G. Khalsa

Publications and source records attributed to G. Khalsa.

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LLRF System Considerations for a Compact, Commercial C-band Accelerator using the AMD Xilinx RF-SoC

This work describes the LLRF and control system in use for a novel accelerator structure developed for a compact design operating in C-band developed by SLAC, with collaboration from RadiaBeam and RadiaSoft. This design is a pulsed RF/pulsed beam system that only provides minimal monitoring for control of each two-cavity pair. Available signals include only a forward and reflected signal for each pair; such a design requires careful consideration of calibration and power-on routines, as well an understanding of how to correct for disturbances caused by the entire RF signal chain, including a new SSA, klystron, and distribution system. An AMD Xilinx RF-SoC with a separate supervisory computer is the LLRF system core, with on-board pulse-to-pulse feedback corrections. This work presents the current status of the project, as well as obstacles and manufacturing plans from the viewpoint of developing for larger-volume manufacturing. This material is based upon work supported by the Defense Advanced Research Projects Agency under Contract Numbers 140D0423C0006 and 140D0423C0007. The views, opinions, and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.

physics.acc-ph

Neuromorphic Computing through Time-Multiplexing with a Spin-Torque Nano-Oscillator

Fabricating powerful neuromorphic chips the size of a thumb requires miniaturizing their basic units: synapses and neurons. The challenge for neurons is to scale them down to submicrometer diameters while maintaining the properties that allow for reliable information processing: high signal to noise ratio, endurance, stability, reproducibility. In this work, we show that compact spin-torque nano-oscillators can naturally implement such neurons, and quantify their ability to realize an actual cognitive task. In particular, we show that they can naturally implement reservoir computing with high performance and detail the recipes for this capability.

cs.ET

d0 Perovskite-Semiconductor Electronic Structure

We address the low-energy effective Hamiltonian of electron doped d0 perovskite semiconductors in cubic and tetragonal phases using the k*p method. The Hamiltonian depends on the spin-orbit interaction strength, on the temperature-dependent tetragonal distortion, and on a set of effective-mass parameters whose number is determined by the symmetry of the crystal. We explain how these parameters can be extracted from angle resolved photo-emission, Raman spectroscopy, and magneto-transport measurements and estimate their values in SrTiO3.

cond-mat.mtrl-sci