Zobrazeno 1 - 10
of 7 701
pro vyhledávání: '"Beckett P"'
Autor:
Karimi, Pantea, Pirelli, Solal, Kakarla, Siva Kesava Reddy, Beckett, Ryan, Segarra, Santiago, Li, Beibin, Namyar, Pooria, Arzani, Behnaz
Many problems that cloud operators solve are computationally expensive, and operators often use heuristic algorithms (that are faster and scale better than optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and
Externí odkaz:
http://arxiv.org/abs/2410.15086
We consider the periodic fractional nonlinear Schr\"{o}dinger equation $$ iu_t -(-\Delta)^{\frac{s}{2}} u + \mathcal{N}(|u|)u=0, \quad x\in \mathbb{T}^N,\, \, t \in \mathbb R, \, \, s>0, $$ where the nonlinearity term is expressed in two ways: the fi
Externí odkaz:
http://arxiv.org/abs/2410.08144
Autor:
Pensabene, A., Galbiati, M., Fumagalli, M., Fossati, M., Smail, I., Rafelski, M., Revalski, M., Arrigoni-Battaia, F., Beckett, A., Cantalupo, S., Dutta, R., Lusso, E., Lazeyras, T., Quadri, G., Tornotti, D.
We present new ALMA continuum and spectral observations of the MUSE Ultra Deep Field (MUDF), a $2\times 2$ arcmin$^2$ region with ultradeep multiwavelength imaging and spectroscopy hosting two bright $z\approx 3.22$ quasars used to study intervening
Externí odkaz:
http://arxiv.org/abs/2410.06249
Autor:
Beckett, Andrew D. K.
We provide some examples of Killing superalgebras on 2-dimensional pseudo-Riemannian manifolds within the theoretical framework established in arXiv:2409.11306. We compute the Spencer cohomology group $\mathsf{H}^{2,2}(\mathfrak{s}_-;\mathfrak{s})$ a
Externí odkaz:
http://arxiv.org/abs/2410.01765
Autor:
Beckett, Andrew D. K.
We generalise the notion of a Killing superalgebra which arises in the physics literature on supergravity to general dimension, signature and choice of spinor module and squaring map, and also allowing for Lie algebras as well as superalgebras, captu
Externí odkaz:
http://arxiv.org/abs/2409.11306
Autor:
Beckett, Alexander, Rafelski, Marc, Revalski, Mitchell, Fumagalli, Michele, Fossati, Matteo, Nedkova, Kalina, Dutta, Rajeshwari, Bielby, Rich, Cantalupo, Sebastiano, Dayal, Prakita, D'Odorico, Valentina, Galbiati, Marta, Péroux, Céline
We present intial results associating galaxies in the MUSE Ultra Deep Field (MUDF) with gas seen in absorption along the line-of-sight to two bright quasars in this field, to explore the dependence of metals in the circumgalactic medium (CGM) on gala
Externí odkaz:
http://arxiv.org/abs/2408.11914
Efficient and accurate prediction of physical systems is important even when the rules of those systems cannot be easily learned. Reservoir computing, a type of recurrent neural network with fixed nonlinear units, is one such prediction method and is
Externí odkaz:
http://arxiv.org/abs/2408.09223
Autor:
Volpe, Giorgio, Araújo, Nuno A. M., Guix, Maria, Miodownik, Mark, Martin, Nicolas, Alvarez, Laura, Simmchen, Juliane, Di Leonardo, Roberto, Pellicciotta, Nicola, Martinet, Quentin, Palacci, Jérémie, Ng, Wai Kit, Saxena, Dhruv, Sapienza, Riccardo, Nadine, Sara, Mano, João F., Mahdavi, Reza, Adiels, Caroline Beck, Forth, Joe, Santangelo, Christian, Palagi, Stefano, Seok, Ji Min, Webster-Wood, Victoria A., Wang, Shuhong, Yao, Lining, Aghakhani, Amirreza, Barois, Thomas, Kellay, Hamid, Coulais, Corentin, van Hecke, Martin, Pierce, Christopher J., Wang, Tianyu, Chong, Baxi, Goldman, Daniel I., Reina, Andreagiovanni, Trianni, Vito, Volpe, Giovanni, Beckett, Richard, Nair, Sean P., Armstrong, Rachel
Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, adaptability, and autonomy, emulate
Externí odkaz:
http://arxiv.org/abs/2407.10623
We present a Python package called Modular Petri Net Assembly Toolkit (MPAT) that empowers users to easily create large-scale, modular Petri Nets for various spatial configurations, including extensive spatial grids or those derived from shape files,
Externí odkaz:
http://arxiv.org/abs/2407.10372
Petri nets are a promising modeling framework for epidemiology, including the spread of disease across populations or within an individual. In particular, the Susceptible-Infectious-Recovered (SIR) compartment model is foundational for population epi
Externí odkaz:
http://arxiv.org/abs/2407.10019