Zobrazeno 1 - 10
of 1 715
pro vyhledávání: '"Cowan, P J"'
We consider a general class of translation-invariant systems with a specific category of output nonlinearities motivated by biological sensing. We show that no dynamic output feedback can stabilize this class of systems to an isolated equilibrium poi
Externí odkaz:
http://arxiv.org/abs/2411.06612
Autor:
Roederer, Ian U., Vassh, Nicole, Holmbeck, Erika M., Mumpower, Matthew R., Surman, Rebecca, Cowan, John J., Beers, Timothy C., Ezzeddine, Rana, Frebel, Anna, Hansen, Terese T., Placco, Vinicius M., Sakari, Charli M.
Publikováno v:
Science, 382, 1177-1180 (2023)
The heaviest chemical elements are naturally produced by the rapid neutron-capture process (r-process) during neutron star mergers or supernovae. The r-process production of elements heavier than uranium (transuranic nuclei) is poorly understood and
Externí odkaz:
http://arxiv.org/abs/2312.06844
Robotic adaptation to unanticipated operating conditions is crucial to achieving persistence and robustness in complex real world settings. For a wide range of cutting-edge robotic systems, such as micro- and nano-scale robots, soft robots, medical r
Externí odkaz:
http://arxiv.org/abs/2310.02141
Autor:
Deng, Siming, Liu, Junning, Datta, Bibekananda, Pantula, Aishwarya, Gracias, David H., Nguyen, Thao D., Bittner, Brian A., Cowan, Noah J.
It is challenging to perform system identification on soft robots due to their underactuated, high-dimensional dynamics. In this work, we present a data-driven modeling framework, based on geometric mechanics (also known as gauge theory) that can be
Externí odkaz:
http://arxiv.org/abs/2307.01062
Autor:
Sneden, Christopher, Boesgaard, Ann Merchant, Cowan, John J., Roederer, Ian U., Hartog, Elizabeth A. Den, Lawler, James E.
We have derived new detailed abundances of Mg, Ca, and the Fe-group elements Sc through Zn (Z = 21-30) for 37 main sequence turnoff very metal-poor stars ([Fe/H] <= -2.1). We analyzed Keck HIRES optical and near-UV high signal-to-noise spectra origin
Externí odkaz:
http://arxiv.org/abs/2304.06899
We report new measurements of branching fractions for 20 UV and blue lines in the spectrum of neutral silicon (Si I) originating in the 3$s^{2}$3$p$4$s$ $^{3}$P$^{\rm o}_{1,2}$, $^{1}$P$^{\rm o}_{1}$ and 3$s$3$p^{3}$ $^{1}$D$^{\rm o}_{1,2}$ upper lev
Externí odkaz:
http://arxiv.org/abs/2301.11391
Autor:
Roederer, Ian U., Cowan, John J., Pignatari, Marco, Beers, Timothy C., Hartog, Elizabeth A. Den, Ezzeddine, Rana, Frebel, Anna, Hansen, Terese T., Holmbeck, Erika M., Mumpower, Matthew R., Placco, Vinicius M., Sakari, Charli M., Surman, Rebecca, Vassh, Nicole
Publikováno v:
Astrophysical Journal Vol. 936, p. 84 (2022)
We present new observational benchmarks of rapid neutron-capture process (r-process) nucleosynthesis for elements at and between the first (A ~ 80) and second (A ~ 130) peaks. Our analysis is based on archival ultraviolet and optical spectroscopy of
Externí odkaz:
http://arxiv.org/abs/2210.15105
Given a plant subject to delayed sensor measurement, there are several approaches to compensate for the delay. An obvious approach is to address this problem in state space, where the $n$-dimensional plant state is augmented by an $N$-dimensional (Pa
Externí odkaz:
http://arxiv.org/abs/2210.12123
For a general class of translationally invariant systems with a specific category of nonlinearity in the output, this paper presents necessary and sufficient conditions for global observability. Critically, this class of systems cannot be stabilized
Externí odkaz:
http://arxiv.org/abs/2210.03848
Autor:
De Silva, Ashwin, Ramesh, Rahul, Ungar, Lyle, Shuler, Marshall Hussain, Cowan, Noah J., Platt, Michael, Li, Chen, Isik, Leyla, Roh, Seung-Eon, Charles, Adam, Venkataraman, Archana, Caffo, Brian, How, Javier J., Kebschull, Justus M, Krakauer, John W., Bichuch, Maxim, Kinfu, Kaleab Alemayehu, Yezerets, Eva, Jayaraman, Dinesh, Shin, Jong M., Villar, Soledad, Phillips, Ian, Priebe, Carey E., Hartung, Thomas, Miller, Michael I., Dey, Jayanta, Ningyuan, Huang, Eaton, Eric, Etienne-Cummings, Ralph, Ogburn, Elizabeth L., Burns, Randal, Osuagwu, Onyema, Mensh, Brett, Muotri, Alysson R., Brown, Julia, White, Chris, Yang, Weiwei, Rusu, Andrei A., Verstynen, Timothy, Kording, Konrad P., Chaudhari, Pratik, Vogelstein, Joshua T.
Learning is a process which can update decision rules, based on past experience, such that future performance improves. Traditionally, machine learning is often evaluated under the assumption that the future will be identical to the past in distribut
Externí odkaz:
http://arxiv.org/abs/2201.07372