Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Zheng, Huihuo"'
We introduce spatiotemporal-graph models that concurrently process data from the twin advanced LIGO detectors and the advanced Virgo detector. We trained these AI classifiers with 2.4 million IMRPhenomXPHM waveforms that describe quasi-circular, spin
Externí odkaz:
http://arxiv.org/abs/2310.00052
Publikováno v:
Mach. Learn.: Sci. Technol. 5 (2024) 025056
We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes $(l, |m|)=\{(2, 2), (2, 1), (3, 3), (3, 2), (4, 4)\}$, and m
Externí odkaz:
http://arxiv.org/abs/2306.15728
Autor:
Schwartz, Jonathan, Di, Zichao Wendy, Jiang, Yi, Manassa, Jason, Pietryga, Jacob, Qian, Yiwen, Cho, Min Gee, Rowell, Jonathan L., Zheng, Huihuo, Robinson, Richard D., Gu, Junsi, Kirilin, Alexey, Rozeveld, Steve, Ercius, Peter, Fessler, Jeffrey A., Xu, Ting, Scott, Mary, Hovden, Robert
Publikováno v:
Nat Commun 15, 3555 (2024)
Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that
Externí odkaz:
http://arxiv.org/abs/2304.12259
Publikováno v:
Front. Artif. Intell. 5:828672 (2022)
We introduce an ensemble of artificial intelligence models for gravitational wave detection that we trained in the Summit supercomputer using 32 nodes, equivalent to 192 NVIDIA V100 GPUs, within 2 hours. Once fully trained, we optimized these models
Externí odkaz:
http://arxiv.org/abs/2201.11133
Publikováno v:
Phys. Rev. D 105, 024024 (2022)
We present a deep-learning artificial intelligence model that is capable of learning and forecasting the late-inspiral, merger and ringdown of numerical relativity waveforms that describe quasi-circular, spinning, non-precessing binary black hole mer
Externí odkaz:
http://arxiv.org/abs/2110.06968
Publikováno v:
Microsc Microanal 26 (2020) 2462-2465
Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D)
Externí odkaz:
http://arxiv.org/abs/2005.01662
Publikováno v:
Phys. Rev. Materials 3, 073803 (2019)
We derive a dielectric-dependent hybrid functional which accurately describes the electronic properties of heterogeneous interfaces and surfaces, as well as those of three- and two-dimensional bulk solids. The functional, which does not contain any a
Externí odkaz:
http://arxiv.org/abs/1901.00824
Publikováno v:
Physics Letters B 795 (2019) 248-258
The scale of ongoing and future electromagnetic surveys pose formidable challenges to classify astronomical objects. Pioneering efforts on this front include citizen science campaigns adopted by the Sloan Digital Sky Survey (SDSS). SDSS datasets have
Externí odkaz:
http://arxiv.org/abs/1812.02183
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Frontiers in Physics 6:43 (2018)
Due to advances in computer hardware and new algorithms, it is now possible to perform highly accurate many-body simulations of realistic materials with all their intrinsic complications. The success of these simulations leaves us with a conundrum: h
Externí odkaz:
http://arxiv.org/abs/1712.00477