Results 41 to 50 of about 1,786,533 (325)

The CP-PACS Project and Lattice QCD Results [PDF]

, 2000
The aim of the CP-PACS project was to develop a massively parallel computer for performing numerical research in computational physics with primary emphasis on lattice QCD.
Kiyoyuki Terakura, Zhong Fang
core   +3 more sources

Molecular determinants of signal transduction in tropomyosin receptor kinases

FEBS Open Bio, EarlyView.
Tropomyosin receptor kinases control critical neuronal functions, but how do the same receptors produce diverse cellular responses? This review explores the structural mechanisms behind Trk signaling diversity, focusing on allosteric modulation and ligand bias.
Giray Enkavi
wiley   +1 more source

Computation across the curriculum: What skills are needed?

, 2015
Computation, the use of a computer to solve, simulate, or visualize a physical problem, has revolutionized how physics research is done. Computation is used widely to model systems, to simulate experiments, and to analyze data. Yet, in most undergraduate
Caballero, Marcos D.
core   +1 more source

Special Issue On Physics-Driven Machine Learning for Computational Imaging [PDF]

, 2021

openalex   +1 more source

Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications

FEBS Open Bio, EarlyView.
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley   +1 more source

Computability and Physical Theories [PDF]

Foundations of Physics, 1986
The familiar theories of physics have the feature that the application of the theory to make predictions in specific circumstances can be done by means of an algorithm. We propose a more precise formulation of this feature --- one based on the issue of whether or not the physically measurable numbers predicted by the theory are computable in the ...
Geroch, Robert, Hartle, James B.
openaire   +2 more sources

Numerical methods for computing Casimir interactions

, 2010
We review several different approaches for computing Casimir forces and related fluctuation-induced interactions between bodies of arbitrary shapes and materials.
da Rosa, Felipe, Dalvit, Diego, Milonni, Peter, Roberts, David   +3 more
core   +1 more source

Understanding bio‐based polymers: A study of origins, properties, biodegradation and their impact on health and the environment

FEBS Open Bio, EarlyView.
This review provides an overview of bio‐based polymer sources, their unique functional properties and their environmental impact, and addresses their role as sustainable alternatives. It discusses end‐of‐life options, including composting and anaerobic digestion for renewable energy.
Sabina Kolbl Repinc, Blaž Stres, Mirica Karlovits, Igor Karlovits, Petra Jerič, Ondrej Panák, Anja Verbič, Blaž Likozar, Uroš Novak   +8 more
wiley   +1 more source

Les Houches 2015: Physics at TeV colliders - new physics working group report [PDF]

, 2016
We present the activities of the 'New Physics' working group for the 'Physics at TeV Colliders' workshop (Les Houches, France, 1-19 June, 2015). Our report includes new physics studies connected with the Higgs boson and its properties, direct search ...
Barducci, D., Bernon, J., Bharucha, A., Brehmer, J., Brivio, I., Brooijmans, G., Buckley, A., Burns, D., Cacciapaglia, G., Cai, H., Carmona, A., Carvalho, A., Chalons, G., Chen, Y., Chivukula, R. S., Conte, E., De Filippis, N., Deandrea, A., Delaunay, C., Delgado, A., Desai, N., Englert, C., Falkowski, A., Flacke, T., Frigerio, M., Fuks, B., Garcia-Pepin, M., Gleyzer, S., Goertz, F., Goudelis, A., Gras, P., Henrot-Versillé, S., Hewett, J. L., Ittisamai, P., Katz, A., Kopp, J., Kraml, S., Krauss, M. E., Kulkarni, S., Laa, U., Lacroix, S., Lane, K., Majumder, D., Martin, A., Mawatari, K., Mimasu, K., Mohan, K., Morse, D. M., Mühlleitner, M., Nardecchia, M., Nikitenko, S., No, J. M., Orlando, R. D., Pani, P., Papucci, M., Polesello, G., Pollard, C., Porod, W., Prosper, H. B., Quirós, M., Rizzo, T., Sakurai, K., Santiago, J., Sanz, V., Schmeier, D., Schmidt, T., Sekmen, S., Sengupta, D., Shao, H. -S., Simmons, E. H., Sonneveld, J., Spieker, T., Spira, M., Tattersall, J., Unel, G., Vega-Morales, R., Waltenberger, W., Weiler, A., You, T., Zapata, O. A., Zerwas, D.   +80 more
core   +3 more sources

Deep Learning and Computational Physics (Lecture Notes) [PDF]

, 2023
Deep Ray, Orazio Pinti, Assad A. Oberai
openalex   +1 more source