Results 271 to 280 of about 5,472,881 (330)

Comparative analysis of ERA5 and Raman lidar‐derived moisture profiles in the framework of the WaLiNeAs field campaigns

Quarterly Journal of the Royal Meteorological Society, EarlyView.
In this paper, we compare atmospheric water vapour data acquired with lidars during the WaLiNeAs programme with data from the ECMWF ERA5 reanalysis. The WaLiNeAs field measurement campaigns took place in autumn/winter 2022/2023 over the French Mediterranean basin and in summer 2023 near Toulouse.
Frédéric Laly, Patrick Chazette
wiley   +1 more source

Ion Spectroscopy in the Context of the Diffuse Interstellar Bands: A Case Study with the Phenylacetylene Cation. [PDF]

ACS Earth Space Chem
Douglas-Walker TE, Campbell EK, Daly FC, Douin S, Gans B, Jacovella U, Maurice C, Odant R, Palotás J.   +8 more
europepmc   +1 more source

Effects of the urban land use on a severe convective windstorm

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Numerical simulations with the Weather Research and Forecasting model coupled with the Building Effect Parametrization–Building Energy Model multilayer canopy model were conducted to investigate the impact of urban land use on a severe convective windstorm in Milan, northern Italy, on July 25, 2023.
Francesco De Martin, Andrea Zonato, Silvana Di Sabatino   +2 more
wiley   +1 more source

Battle of the CH motions: aliphatic versus aromatic contributions to astronomical PAH emission and exploration of the aliphatic, aromatic, and ethynyl CH stretches. [PDF]

Mon Not R Astron Soc
Esposito VJ, Bejaoui S, Billinghurst BE, Boersma C, Fortenberry RC, Salama F.   +5 more
europepmc   +1 more source

Statistical Complexity of Quantum Learning

Advanced Quantum Technologies, EarlyView.
The statistical performance of quantum learning is investigated as a function of the number of training data N$N$, and of the number of copies available for each quantum state in the training and testing data sets, respectively S$S$ and V$V$. Indeed, the biggest difference in quantum learning comes from the destructive nature of quantum measurements ...
Leonardo Banchi, Jason Luke Pereira, Sharu Theresa Jose, Osvaldo Simeone   +3 more
wiley   +1 more source

Fast ground irradiance computations for agrivoltaics via physics-informed deep learning models. [PDF]

Commun Eng
Kurumundayil L, Burkhardt D, Gfüllner L, Rupitsch SJ, Preu R, Berwind M, Demant M.   +6 more
europepmc   +1 more source

Quantum‐Noise‐Driven Generative Diffusion Models

Advanced Quantum Technologies, EarlyView.
Diffusion Models (DMs) are today a very popular class of generative models for Machine Learning (ML), using a noisy dynamics to learn an unknown density probability of a finite set of samples in order to generate new synthetic data. This study proposes a method to generalize them into the quantum domain by introducing and investigating what are termed ...
Marco Parigi, Stefano Martina, Filippo Caruso   +2 more
wiley   +1 more source

Potential impact of the Sagittarius dwarf galaxy on the formation of young O-rich stars. [PDF]

Nat Commun
Sun T, Bi S, Chen X, Chen Y, Lu YL, Liu C, Buck T, Zhang X, Li T, Li Y, Wu Y, Ge Z, Ye L.   +12 more
europepmc   +1 more source

Additive Manufacturing for Advanced Quantum Technologies

Advanced Quantum Technologies, EarlyView.
Additive manufacturing has disruptive potential to enable quantum technology to be widely used in real‐world applications. In this review, we summarize the most important AM techniques that enable practical advance and fascinating opportunities for quantum technologies.
F. Wang, N. Cooper, D. Johnson, B. Hopton, A. Murray, R. McMullen, T. M. Fromhold, R. Hague, L. Turyanska, L. Hackermüller   +9 more
wiley   +1 more source

Chondrule formation by collisions of planetesimals containing volatiles triggered by Jupiter's formation. [PDF]

Sci Rep
Sirono SI, Turrini D.
europepmc   +1 more source