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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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SLAC microresonator RF(SMuRF) electronics: A tone-tracking readout system for superconducting microwave resonator arrays

Here, we describe the newest generation of the SLAC Microresonator RF (SMuRF) electronics, a warm digital control and readout system for microwave-frequency resonator-based cryogenic detector and multiplexer systems, such as microwave superconducting quantum interference device multiplexers (μmux) or microwave kinetic inductance detectors. Ultra-sensitive measurements in particle physics and astronomy increasingly rely on large arrays of cryogenic sensors, which in turn necessitate highly multiplexed readout and accompanying room-temperature electronics. Microwave-frequency resonators are a popular tool for cryogenic multiplexing, with the potential to multiplex thousands of detector channels on one readout line. The SMuRF system provides the capability for reading out up to 3328 channels across a 4–8 GHz bandwidth. Notably, the SMuRF system is unique in its implementation of a closed-loop tone-tracking algorithm that minimizes RF power transmitted to the cold amplifier, substantially relaxing system linearity requirements and effective noise from intermodulation products. Here, we present a description of the hardware, firmware, and software systems of the SMuRF electronics, comparing achieved performance with science-driven design requirements. In particular, we focus on the case of large-channel-count, low-bandwidth applications, but the system has been easily reconfigured for high-bandwidth applications. The system described here has been successfully deployed in lab settings and field sites around the world and is baselined for use on upcoming large-scale observatories.

47 OTHER INSTRUMENTATION↗

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Abstract Motivation Multiple sequence alignments (MSAs) of homologous sequences contain information on structural and functional constraints and their evolutionary histories. Despite their importance for many downstream tasks, such as structure prediction, MSA generation is often treated as a separate pre-processing step, without any guidance from the application it will be used for. Results Here, we implement a smooth and differentiable version of the Smith–Waterman pairwise alignment algorithm that enables jointly learning an MSA and a downstream machine learning system in an end-to-end fashion. To demonstrate its utility, we introduce SMURF (Smooth Markov Unaligned Random Field), a new method that jointly learns an alignment and the parameters of a Markov Random Field for unsupervised contact prediction. We find that SMURF learns MSAs that mildly improve contact prediction on a diverse set of protein and RNA families. As a proof of concept, we demonstrate that by connecting our differentiable alignment module to AlphaFold2 and maximizing predicted confidence, we can learn MSAs that improve structure predictions over the initial MSAs. Interestingly, the alignments that improve AlphaFold predictions are self-inconsistent and can be viewed as adversarial. This work highlights the potential of differentiable dynamic programming to improve neural network pipelines that rely on an alignment and the potential dangers of optimizing predictions of protein sequences with methods that are not fully understood. Availability and implementation Our code and examples are available at: https://github.com/spetti/SMURF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

Bandwidth and Aliasing in the Microwave SQUID Multiplexer

The microwave SQUID multiplexer (μmux) has enabled higher bandwidth or higher channel counts across a wide range of experiments in particle physics, astronomy, and spectroscopy. The large multiplexing factor coupled with recent commercial availability of microwave components and warm electronics readout systems make it an attractive candidate for systems requiring large cryogenic detector counts. Since the multiplexer is considered for both bolometric and calorimetric applications across several orders of magnitude of signal frequencies, understanding the bandwidth of the device and its interaction with readout electronics is key to appropriately designing and engineering systems. Here we discuss several important factors contributing to the bandwidth properties of μmux systems, including the intrinsic device bandwidth, interactions with warm electronics readout systems, and aliasing. Further, we present simulations and measurements of μmux devices coupled with SLAC Microresonator RF (SMuRF) tone-tracking electronics and discuss several implications for future experimental design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

slaclab/pysmurf-stable-docker

Docker image with pysmurf and firmware files for the SMuRF project. This docker image, named pysmurf-server contains pysmurf, firmware files (mcs and pyrogue's zip) and default configuration files (yml) for stable firmware versions.

Vasquez, Jesus↗

Microwave Multiplexing on the Keck Array

In this paper, we describe an on-sky demonstration of a microwave-multiplexing readout system in one of the receivers of the Keck Array, a polarimetry experiment observing the cosmic microwave background at the South Pole. During the austral summer of 2018–2019, we replaced the time-division multiplexing readout system with microwave-multiplexing components including superconducting microwave resonators coupled to radio frequency superconducting quantum interference devices at the sub-Kelvin focal plane, coaxial-cable plumbing and amplification between room temperature and the cold stages, and a SLAC Microresonator Radio Frequency system for the warm electronics. In the range 5–6 GHz, a single coaxial cable reads out 528 channels. The readout system is coupled to transition-edge sensors, which are in turn coupled to 150-GHz slot-dipole phased-array antennas. Observations began in April 2019, and we report here on an initial characterization of the system performance.

79 ASTRONOMY AND ASTROPHYSICS↗