Zobrazeno 1 - 10
of 12 328
pro vyhledávání: '"Redding AT"'
In this work, we introduce and experimentally demonstrate a photonic frequency-multiplexed next generation reservoir computer (FM-NGRC) capable of performing real-time inference at GHz speed. NGRCs apply a feed-forward architecture to produce a featu
Externí odkaz:
http://arxiv.org/abs/2411.09624
In this paper, we introduce a system based on transfer learning for detecting segment misalignment in multimirror satellites, such as future CubeSat designs and the James Webb Space Telescope (JWST), using image-based methods. When a mirror segment b
Externí odkaz:
http://arxiv.org/abs/2407.20582
This work investigates the unsteady behavior of unstart phenomena within a scramjet inlet using advanced computational techniques. Scramjets and ramjets, with their reliance on inlet compression, offer promising airbreathing propulsion for hypersonic
Externí odkaz:
http://arxiv.org/abs/2405.17671
The objective of this work is to assess the impact of parameter uncertainty on hypersonic aerothermal surface heating predictions in Reynolds-Averaged Navier-Stokes (RANS) simulations using non-intrusive uncertainty quantification (UQ) techniques. RA
Externí odkaz:
http://arxiv.org/abs/2405.15875
Autor:
Heintz, Tyler M., Hermes, J. J., Tremblay, P. -E., Rouis, Lou Baya Ould, Redding, Joshua S., Kaiser, B. C., van Saders, Jennifer L.
White dwarf stars have been used for decades as precise and accurate age indicators. This work presents a test of the reliability of white dwarf total ages when spectroscopic observations are available. We conduct follow-up spectroscopy of 148 indivi
Externí odkaz:
http://arxiv.org/abs/2405.02423
Reservoir computing (RC) is a machine learning paradigm that excels at dynamical systems analysis. Photonic RCs, which perform implicit computation through optical interactions, have attracted increasing attention due to their potential for low laten
Externí odkaz:
http://arxiv.org/abs/2404.07116
With more scientific fields relying on neural networks (NNs) to process data incoming at extreme throughputs and latencies, it is crucial to develop NNs with all their parameters stored on-chip. In many of these applications, there is not enough time
Externí odkaz:
http://arxiv.org/abs/2403.08980
Autor:
Redding, Brandon, Murray, Joseph B., Hart, Joseph D., Zhu, Zheyuan, Pang, Shuo S., Sarma, Raktim
The widespread adoption of machine learning and other matrix intensive computing algorithms has inspired renewed interest in analog optical computing, which has the potential to perform large-scale matrix multiplications with superior energy scaling
Externí odkaz:
http://arxiv.org/abs/2308.14504
Autor:
Wang, Xiao, Redding, Brandon, Karl, Nicholas, Long, Christopher, Zhu, Zheyuan, Pang, Shuo, Brady, David, Sarma, Raktim
Modern lens designs are capable of resolving >10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made Terapixel/s data acquisition a real possibility. The main bottlenecks preventing such high data-rate systems are powe
Externí odkaz:
http://arxiv.org/abs/2306.04554
Cryptographic random number generation is critical for any quantum safe encryption. Based on the natural uncertainty of some quantum processes, variety of quantum random number generators or QRNGs have been created with physical quantum processes. Th
Externí odkaz:
http://arxiv.org/abs/2303.01315