@article{15018, abstract = {The epitaxial growth of a strained Ge layer, which is a promising candidate for the channel material of a hole spin qubit, has been demonstrated on 300 mm Si wafers using commercially available Si0.3Ge0.7 strain relaxed buffer (SRB) layers. The assessment of the layer and the interface qualities for a buried strained Ge layer embedded in Si0.3Ge0.7 layers is reported. The XRD reciprocal space mapping confirmed that the reduction of the growth temperature enables the 2-dimensional growth of the Ge layer fully strained with respect to the Si0.3Ge0.7. Nevertheless, dislocations at the top and/or bottom interface of the Ge layer were observed by means of electron channeling contrast imaging, suggesting the importance of the careful dislocation assessment. The interface abruptness does not depend on the selection of the precursor gases, but it is strongly influenced by the growth temperature which affects the coverage of the surface H-passivation. The mobility of 2.7 × 105 cm2/Vs is promising, while the low percolation density of 3 × 1010 /cm2 measured with a Hall-bar device at 7 K illustrates the high quality of the heterostructure thanks to the high Si0.3Ge0.7 SRB quality.}, author = {Shimura, Yosuke and Godfrin, Clement and Hikavyy, Andriy and Li, Roy and Aguilera Servin, Juan L and Katsaros, Georgios and Favia, Paola and Han, Han and Wan, Danny and de Greve, Kristiaan and Loo, Roger}, issn = {1369-8001}, journal = {Materials Science in Semiconductor Processing}, keywords = {Mechanical Engineering, Mechanics of Materials, Condensed Matter Physics, General Materials Science}, number = {5}, publisher = {Elsevier}, title = {{Compressively strained epitaxial Ge layers for quantum computing applications}}, doi = {10.1016/j.mssp.2024.108231}, volume = {174}, year = {2024}, } @inproceedings{15011, abstract = {Pruning large language models (LLMs) from the BERT family has emerged as a standard compression benchmark, and several pruning methods have been proposed for this task. The recent “Sparsity May Cry” (SMC) benchmark put into question the validity of all existing methods, exhibiting a more complex setup where many known pruning methods appear to fail. We revisit the question of accurate BERT-pruning during fine-tuning on downstream datasets, and propose a set of general guidelines for successful pruning, even on the challenging SMC benchmark. First, we perform a cost-vs-benefits analysis of pruning model components, such as the embeddings and the classification head; second, we provide a simple-yet-general way of scaling training, sparsification and learning rate schedules relative to the desired target sparsity; finally, we investigate the importance of proper parametrization for Knowledge Distillation in the context of LLMs. Our simple insights lead to state-of-the-art results, both on classic BERT-pruning benchmarks, as well as on the SMC benchmark, showing that even classic gradual magnitude pruning (GMP) can yield competitive results, with the right approach.}, author = {Kurtic, Eldar and Hoefler, Torsten and Alistarh, Dan-Adrian}, booktitle = {Proceedings of Machine Learning Research}, issn = {2640-3498}, location = {Hongkong, China}, pages = {542--553}, publisher = {ML Research Press}, title = {{How to prune your language model: Recovering accuracy on the "Sparsity May Cry" benchmark}}, volume = {234}, year = {2024}, } @article{15024, abstract = {Electrostatic correlations between ions dissolved in water are known to impact their transport properties in numerous ways, from conductivity to ion selectivity. The effects of these correlations on the solvent itself remain, however, much less clear. In particular, the addition of salt has been consistently reported to affect the solution’s viscosity, but most modeling attempts fail to reproduce experimental data even at moderate salt concentrations. Here, we use an approach based on stochastic density functional theory, which accurately captures charge fluctuations and correlations. We derive a simple analytical expression for the viscosity correction in concentrated electrolytes, by directly linking it to the liquid’s structure factor. Our prediction compares quantitatively to experimental data at all temperatures and all salt concentrations up to the saturation limit. This universal link between the microscopic structure and viscosity allows us to shed light on the nanoscale dynamics of water and ions under highly concentrated and correlated conditions.}, author = {Robin, Paul}, issn = {1089-7690}, journal = {Journal of Chemical Physics}, number = {6}, publisher = {AIP Publishing}, title = {{Correlation-induced viscous dissipation in concentrated electrolytes}}, doi = {10.1063/5.0188215}, volume = {160}, year = {2024}, } @article{15025, abstract = {We consider quadratic forms of deterministic matrices A evaluated at the random eigenvectors of a large N×N GOE or GUE matrix, or equivalently evaluated at the columns of a Haar-orthogonal or Haar-unitary random matrix. We prove that, as long as the deterministic matrix has rank much smaller than √N, the distributions of the extrema of these quadratic forms are asymptotically the same as if the eigenvectors were independent Gaussians. This reduces the problem to Gaussian computations, which we carry out in several cases to illustrate our result, finding Gumbel or Weibull limiting distributions depending on the signature of A. Our result also naturally applies to the eigenvectors of any invariant ensemble.}, author = {Erdös, László and McKenna, Benjamin}, issn = {1050-5164}, journal = {Annals of Applied Probability}, number = {1B}, pages = {1623--1662}, publisher = {Institute of Mathematical Statistics}, title = {{Extremal statistics of quadratic forms of GOE/GUE eigenvectors}}, doi = {10.1214/23-AAP2000}, volume = {34}, year = {2024}, } @article{15033, abstract = {The GNOM (GN) Guanine nucleotide Exchange Factor for ARF small GTPases (ARF-GEF) is among the best studied trafficking regulators in plants, playing crucial and unique developmental roles in patterning and polarity. The current models place GN at the Golgi apparatus (GA), where it mediates secretion/recycling, and at the plasma membrane (PM) presumably contributing to clathrin-mediated endocytosis (CME). The mechanistic basis of the developmental function of GN, distinct from the other ARF-GEFs including its closest homologue GNOM-LIKE1 (GNL1), remains elusive. Insights from this study largely extend the current notions of GN function. We show that GN, but not GNL1, localizes to the cell periphery at long-lived structures distinct from clathrin-coated pits, while CME and secretion proceed normally in gn knockouts. The functional GN mutant variant GNfewerroots, absent from the GA, suggests that the cell periphery is the major site of GN action responsible for its developmental function. Following inhibition by Brefeldin A, GN, but not GNL1, relocates to the PM likely on exocytic vesicles, suggesting selective molecular associations en route to the cell periphery. A study of GN-GNL1 chimeric ARF-GEFs indicates that all GN domains contribute to the specific GN function in a partially redundant manner. Together, this study offers significant steps toward the elucidation of the mechanism underlying unique cellular and development functions of GNOM.}, author = {Adamowski, Maciek and Matijevic, Ivana and Friml, Jiří}, issn = {2050-084X}, journal = {eLife}, keywords = {General Immunology and Microbiology, General Biochemistry, Genetics and Molecular Biology, General Medicine, General Neuroscience}, publisher = {eLife Sciences Publications}, title = {{Developmental patterning function of GNOM ARF-GEF mediated from the cell periphery}}, doi = {10.7554/elife.68993}, volume = {13}, year = {2024}, }