Zobrazeno 1 - 10
of 153 905
pro vyhledávání: '"MARTIN, H."'
Autor:
LEVINSON, MARTIN H., Tywoniak, Edward
Publikováno v:
ETC: A Review of General Semantics, 2014 Apr 01. 71(2), 154-161.
Externí odkaz:
http://www.jstor.org/stable/24761925
We present a novel experimental approach to detect dark matter by probing Yukawa interactions, commonly referred to as a fifth force, between dark matter and baryonic matter. Our method involves optically levitating nanoparticles within a Bessel-Gaus
Externí odkaz:
http://arxiv.org/abs/2410.21718
Autor:
Pfander, James E.1
Publikováno v:
Northwestern University Law Review. Winter2013, Vol. 107 Issue 2, p443-445. 3p.
We propose a low energy model for simulating an analog black hole on an optical lattice using ultracold atoms. Assuming the validity of the holographic principle, we employ the Sachdev-Ye-Kitaev (SYK) model, which describes a system of randomly infin
Externí odkaz:
http://arxiv.org/abs/2409.16553
Autor:
Müser, Martin H.
The split-charge equilibration method is extended to describe dissipative charge transfer similarly as the Drude model, whereby the generic frequency-dependent dielectric permitivitties or conductivities of dielectrics and metals can be mimicked. To
Externí odkaz:
http://arxiv.org/abs/2408.08791
The effect of cooling on the brittleness of glasses in general, and bulk metallic glasses (BMGs) in particular, is usually studied with continuously varying cooling rates; slower cooling rates lead to stiffer, harder, and more brittle glasses than hi
Externí odkaz:
http://arxiv.org/abs/2408.00536
Using atomic force microscopy experiments and molecular dynamics simulations of gold nanoislands on graphite, we investigate why ultra-small friction commonly associated with structural lubricity can be observed even under ambient conditions. Measure
Externí odkaz:
http://arxiv.org/abs/2407.03360
Autor:
Baker, Samuel J., Hobley, Michael A., Scherl, Isabel, Fang, Xiaohang, Leach, Felix C. P., Davy, Martin H.
We present EngineBench, the first machine learning (ML) oriented database to use high quality experimental data for the study of turbulent flows inside combustion machinery. Prior datasets for ML in fluid mechanics are synthetic or use overly simplis
Externí odkaz:
http://arxiv.org/abs/2406.03325
Autor:
Moghaddam, Mahdi, Dzemidzic, Mario, Guerrero, Daniel, Liu, Mintao, Alessi, Jonathan, Plawecki, Martin H., Harezlak, Jaroslaw, Kareken, David, Goñi, Joaquín
Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are nevertheless scarce. Here we present a principled mathematical framework to quantify brain fu
Externí odkaz:
http://arxiv.org/abs/2405.15905