1.3k citations
- Universidad Autónoma de MadridES24 papers
- Université de Bretagne SudFR21 papers
- Max Planck Institute for Gravitational PhysicsDE19 papers
- University of Wisconsin–MilwaukeeUS15 papers
- Centre National de la Recherche ScientifiqueFR14 papers
- Pennsylvania State UniversityUS14 papers
- Tsinghua UniversityCN14 papers
- The University of Texas at AustinUS13 papers
- University of MichiganUS13 papers
- California Institute of TechnologyUS12 papers
- Goddard Space Flight CenterUS12 papers
- Instituto de Física TeóricaES12 papers
47 papers · 1 filter
Energy-Efficient Beamforming and Cooperative Jamming in IRS-Assisted MISO Networks
Qun Wang, Fuhui Zhou, Rose Qingyang Hu +1
The energy-efficient (EE) design problem is very important to design a good performance network. Besides this, the security of communication is also important. Based on the new IRS…
Kummer sandwiches and Greene-Plesser construction
Noah Braeger, Andreas Malmendier, Yih Sung
In the context of K3 mirror symmetry, the Greene-Plesser orbifolding method constructs a family of K3 surfaces, the mirror of quartic hypersurfaces in , starting from…
The effects of simple density-dependent prey diffusion and refuge in a predator-prey system
Leoncio Rodriguez Quinones, Jia Zhao, Luis Gordillo
We study a spatial (two-dimensional) Rosenzweig-MacArthur model under the following assumptions: prey movement follows a nonlinear diffusion, preys have a refuge zone (…
Direct Numerical Simulation of Rotating Ellipsoidal Particles using Moving Nonconforming Schwarz-Spectral Element Method
Ketan Mittal, Som Dutta, Paul Fischer
We present application of a highly-scalable overlapping grid-based nonconforming Schwarz-spectral element method (Schwarz-SEM) to study the dynamics of rotating ellipsoidal particl…
3-Dimensional TQFTs From Non-Semisimple Modular Categories
Marco De Renzi, Azat M. Gainutdinov, Nathan Geer +2
We use modified traces to renormalize Lyubashenko's closed 3-manifold invariants coming from twist non-degenerate finite unimodular ribbon categories. Our construction produces new…
A Data Driven Approach to Learning The Hamiltonian Matrix in Quantum Mechanics
Jordan Burns, David Maughan, Yih Sung
We present a new machine learning technique which calculates a real-valued, time independent, finite dimensional Hamiltonian matrix from only experimental data. A novel cost functi…