5,450 research outputs found
Primordial Black Holes from Sound Speed Resonance during Inflation
We report on a novel phenomenon of the resonance effect of primordial density
perturbations arisen from a sound speed parameter with an oscillatory behavior,
which can generically lead to the formation of primordial black holes in the
early Universe. For a general inflaton field, it can seed primordial density
fluctuations and their propagation is governed by a parameter of sound speed
square. Once if this parameter achieves an oscillatory feature for a while
during inflation, a significant non-perturbative resonance effect on the
inflaton field fluctuations takes place around a critical length scale, which
results in significant peaks in the primordial power spectrum. By virtue of
this robust mechanism, primordial black holes with specific mass function can
be produced with a sufficient abundance for dark matter in sizable parameter
ranges.Comment: 6 pages, 4 figures; v2: figures replotted with corrections, analysis
extended, version accepted by Phys.Rev.Let
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
Feature pyramids are widely exploited by both the state-of-the-art one-stage
object detectors (e.g., DSSD, RetinaNet, RefineDet) and the two-stage object
detectors (e.g., Mask R-CNN, DetNet) to alleviate the problem arising from
scale variation across object instances. Although these object detectors with
feature pyramids achieve encouraging results, they have some limitations due to
that they only simply construct the feature pyramid according to the inherent
multi-scale, pyramidal architecture of the backbones which are actually
designed for object classification task. Newly, in this work, we present a
method called Multi-Level Feature Pyramid Network (MLFPN) to construct more
effective feature pyramids for detecting objects of different scales. First, we
fuse multi-level features (i.e. multiple layers) extracted by backbone as the
base feature. Second, we feed the base feature into a block of alternating
joint Thinned U-shape Modules and Feature Fusion Modules and exploit the
decoder layers of each u-shape module as the features for detecting objects.
Finally, we gather up the decoder layers with equivalent scales (sizes) to
develop a feature pyramid for object detection, in which every feature map
consists of the layers (features) from multiple levels. To evaluate the
effectiveness of the proposed MLFPN, we design and train a powerful end-to-end
one-stage object detector we call M2Det by integrating it into the architecture
of SSD, which gets better detection performance than state-of-the-art one-stage
detectors. Specifically, on MS-COCO benchmark, M2Det achieves AP of 41.0 at
speed of 11.8 FPS with single-scale inference strategy and AP of 44.2 with
multi-scale inference strategy, which is the new state-of-the-art results among
one-stage detectors. The code will be made available on
\url{https://github.com/qijiezhao/M2Det.Comment: AAAI1
Computational Design of Flexible Electride with Nontrivial Band Topology
Electrides, with their excess electrons distributed in crystal cavities playing the role of anions, exhibit a variety of unique electronic and magnetic properties. In this work, we employ the first-principles crystal structure prediction to identify a new prototype of A3B electride in which both interlayer spacings and intralayer vacancies provide channels to accommodate the excess electrons in the crystal. This A3B type of structure is calculated to be thermodynamically stable for two alkaline metals oxides (Rb3O and K3O). Remarkably, the unique feature of multiple types of cavities makes the spatial arrangement of anionic electrons highly flexible via elastic strain engineering and chemical substitution, in contrast to the previously reported electrides characterized by a single topology of interstitial electrons. More importantly, our first-principles calculations reveal that Rb3O is a topological Dirac nodal line semimetal, which is induced by the band inversion at the general electronic k momentums in the Brillouin zone associated with the intersitial electric charges. The discovery of flexible electride in combining with topological electronic properties opens an avenue for electride design and shows great promises in electronic device applications
BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction
Language models pre-trained on scientific literature corpora have
substantially advanced scientific discovery by offering high-quality feature
representations for downstream applications. However, these features are often
not interpretable, and thus can reveal limited insights to domain experts.
Instead of obtaining features from language models, we propose BLIAM, a
literature-based data synthesis approach to directly generate training data
points that are interpretable and model-agnostic to downstream applications.
The key idea of BLIAM is to create prompts using existing training data and
then use these prompts to synthesize new data points. BLIAM performs these two
steps iteratively as new data points will define more informative prompts and
new prompts will in turn synthesize more accurate data points. Notably,
literature-based data augmentation might introduce data leakage since labels of
test data points in downstream applications might have already been mentioned
in the language model corpus. To prevent such leakage, we introduce GDSC-combo,
a large-scale drug combination discovery dataset that was published after the
biomedical language model was trained. We found that BLIAM substantially
outperforms a non-augmented approach and manual prompting in this rigorous data
split setting. BLIAM can be further used to synthesize data points for novel
drugs and cell lines that were not even measured in biomedical experiments. In
addition to the promising prediction performance, the data points synthesized
by BLIAM are interpretable and model-agnostic, enabling in silico augmentation
for in vitro experiments
Nonleptonic two-body decays of charmed mesons
Nonleptonic decays of charmed mesons into two pseudoscalar mesons or one
pseudoscalar meson and one vector meson are studied on the basis of a
generalized factorization method considering the resonance effects in the pole
model for the annihilation contributions. Large strong phases between different
topological diagrams are considered in this work, simply taking the phase in
the coefficients . We find that the annihilation-type contributions
calculated in the pole model are large in both of the and modes,
which make our numerical results agree with the experimental data better than
those previous calculations.Comment: 18 pages, 2 figures;typos corrected;discussions and references adde
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