Abstract: Normal operation of complementary metal-oxide semiconductor (CMOS) devices entails the emission of picosecond pulses of light, which can be used to diagnose circuit problems. The pulses that are observed from submicron sized field effect transistors (FETs) are synchronous with logic state switching. Picosecond Imaging Circuit Analysis (PICA), a new optical imaging technique combining imaging with timing, spatially resolves individual devices at the 0.5 micron level and switching events on a 10 picosecond timescale. PICA is used here for the diagnostics of failures on two VLSI microprocessors.

Abstract: Microcalorimeters and bolometers are noise-limited devices, therefore, a proper understanding of all noise sources is essential to predict and interpret their performance. In this paper, I review the fundamental noise processes contributing to Transition Edge Sensor (TES) microcalorimeters and bolometers and their effect on device performance. In particular, I will start with a simple, monolithic device model, moving to a more complex one involving discrete components, to finally move to today's more realistic, comprehensive model. In addition to the basic noise contribution (equilibrium Johnson noise and phonon noise), TES are significantly affected by extra noise, which is commonly referred to as excess noise. Different fundamental processes have been proposed and investigated to explain the origin of this excess noise, in particular near equilibrium non-linear Johnson noise, flux-flow noise, and internal thermal fluctuation noise. Experimental evidence shows that all three processes are real and contribute, at different levels, to the TES noise, although different processes become important at different regimes. It is therefore time to discard the term “excess noise” and consider these terms part of the “fundamental noise processes” instead.

Abstract: The current noise at the output of a microcalorimeter with a voltage biased superconducting transition edge thermometer is studied in detail. In addition to the two well-known noise sources: thermal fluctuation noise from the heat link to the bath and Johnson noise from the resistive thermometer, a third noise source strongly correlated with the steepness of the thermometer is required to fit the measured noise spectra. Thermal fluctuation noise, originating in the thermometer itself, fully explains the additional noise. A simple model provides quantitative agreement between the observed and calculated noise spectra for all bias points in the superconducting transition.