4,414 research outputs found
A critical analysis of self-supervision, or what we can learn from a single image
We look critically at popular self-supervision techniques for learning deep
convolutional neural networks without manual labels. We show that three
different and representative methods, BiGAN, RotNet and DeepCluster, can learn
the first few layers of a convolutional network from a single image as well as
using millions of images and manual labels, provided that strong data
augmentation is used. However, for deeper layers the gap with manual
supervision cannot be closed even if millions of unlabelled images are used for
training. We conclude that: (1) the weights of the early layers of deep
networks contain limited information about the statistics of natural images,
that (2) such low-level statistics can be learned through self-supervision just
as well as through strong supervision, and that (3) the low-level statistics
can be captured via synthetic transformations instead of using a large image
dataset.Comment: Accepted paper at the International Conference on Learning
Representations (ICLR) 202
NaI revisited: Theoretical investigation of predissociation via ultrafast XUV transient absorption spectroscopy.
Avoided crossings can trigger abrupt changes of electronic character and redirect the outcomes of photochemical reactions. Here, we report a theoretical investigation into core-level spectroscopic probing of predissociation dynamics of sodium iodide (NaI), a prototype system for studies of avoided-crossing dynamics. The elegant femtochemistry work of Zewail and co-workers pioneered the real-time dynamics of NaI, detecting the Na atoms bursting forth from the avoided crossing and the residual NaI molecules oscillating inside the quasibound potential. The simulated results show that core-level spectroscopy not only observes these integrated outcomes but also provides a direct measure of the abrupt switching of electronic character at the avoided crossing. The valence and core-excited electronic structures of NaI are computed by spin-orbit general multiconfigurational quasidegenerate perturbation theory, from which core-level absorption spectra of the predissociation dynamics are constructed. The wave-packet motion on the covalent potential is continuously mapped as shifts in the absorption energies, and the switching between the covalent and ionic character at the avoided crossing is characterized as the sharp rise and fall of the Na+ signal. The Na+ signal is found to be insensitive to the wave-packet motion in the asymptotic part of the ionic potential, which, in turn, enables a direct measure of the nonadiabatic crossing probability excluding the effect of wave-packet broadening
Bulk electronic structure of non-centrosymmetric EuTGe3 (T= Co, Ni, Rh, Ir) studied by hard x-ray photoelectron spectroscopy
Non-centrosymmetric EuTGe3 (T=Co, Ni, Rh, and Ir) possesses magnetic Eu2+
ions and antiferromagnetic ordering appears at low temperatures. Transition
metal substitution leads to changes of the unit cell volume and of the magnetic
ordering. However, the magnetic ordering temperature does not scale with the
volume change and the Eu valence is expected to remain divalent. Here we study
the bulk electronic structure of non-centrosymmetric EuTGe3 (T=Co, Ni, Rh, and
Ir) by hard x-ray photoelectron spectroscopy. The Eu 3d core level spectrum
confirms the robust Eu2+ valence state against the transition metal
substitution with a small contribution from Eu3+. The estimated Eu mean-valence
is around 2.1 in these compounds as confirmed by multiplet calculations. In
contrast, the Ge 2p spectrum shifts to higher binding energy upon changing the
transition metal from 3d to 4d to 5d elements, hinting of a change in the Ge-T
bonding strength. The valence bands of the different compounds are found to be
well reproduced by ab initio band structure calculations
Deuterium-deuterium nuclear cross-sections in insulator and metallic environments
The three-dimensional Thomas-Fermi (TF) model is used to simulate the
variation of the d+d to t + p cross-section at low impact energies, when the
target deuterium nucleus is embedded in metallic or insulator environments.
Comparison of the computational results to recent experiments demonstrates that
even though the TF model can explain some increase in the low energy cross
section for metallic host, a full explanation of the experimental results is
still lacking. Possible reasons for the disagreement are discussed.Comment: 6 pages;6 figures. Accepted for publication in Eur. Phys. Jour.
Particle Monte Carlo simulation of string-like colloidal assembly in 2 dimensions
We simulate structural phase behavior of polymer-grafted colloidal particles
by molecular Monte Carlo technique. Interparticle potential, which has a finite
repulsive square-step outside a rigid core of the colloid, was previously
confirmed via numerical self-consistent field calculation. This model potential
is purely repulsive. We simulate these model colloids in the canonical ensemble
in 2 dimensions and find that these particles containing no interparticle
attraction self-assemble and align in a string-like assembly, at low
temperature and high density. This string-like colloidal assembly is related to
percolation phenomena. Analyzing the cluster size distribution and the average
string length, we build phase diagrams and discover that the average string
length diverges around the region where the melting transition line and the
percolation transition line cross. This result is similar to Ising spin
systems, in which the percolation transition line and the order-disorder line
meet at a critical point.Comment: 11 pages, 14 figure
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