9,313 research outputs found
Higher molecular pentaquarks arising from the interactions
The discoveries of the and as the potential molecules have sparked
our curiosity in exploring a novel class of molecular pentaquarks. In this study, we carry out an investigation
into the higher molecular pentaquarks, specifically focusing on the states arising from the interactions. Our approach employs the
one-boson-exchange model, incorporating both the - wave mixing effect and
the coupled channel effect. Our numerical results suggest that the states with , the
states with , the
states with , the
states with , the states
with , and the states with
can be recommended as the most promising molecular
pentaquark candidates, and there may exist the potential molecular pentaquark candidates for several isovector states. With the higher statistical data
accumulation at the LHCb's Run II and Run III status, there is the possibility
that our predicted states can be detected through
the weak decay of the baryon, especially in hunting for the predicted
states.Comment: 22 pages, 6 figures, and 10 table
New type of doubly charmed molecular pentaquarks containing most strange quarks: Mass spectra, radiative decays, and magnetic moments
In this work, we first predict the mass spectra of the
-type doubly charmed molecular pentaquark
candidates, where the one-boson-exchange model is adopted by considering both
the - wave mixing effect and the coupled channel effect. Our findings
indicate that the state with , the
state with , and the
state with can be considered as the
most promising doubly charmed molecular pentaquark candidates, and the
state with , the state
with , and the state with
are the possible doubly charmed molecular pentaquark
candidates. Furthermore, we further explore the radiative decays and the
magnetic moments of the most promising doubly charmed molecular pentaquark
candidates in the constituent quark model. As a crucial aspect of spectroscopy,
the information of the radiative decays and the magnetic moments can provide
the valuable clues to reflect their inner structures. With the accumulation of
higher statistical data at the Large Hadron Collider, we propose that the LHCb
Collaboration should focus on the problem of searching for these predicted
doubly charmed molecular pentaquark candidates containing most strange quarks
in the coming years.Comment: 16 pages, 1 figure, and 7 table
Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning
Domain adaptation problems arise in a variety of applications, where a
training dataset from the \textit{source} domain and a test dataset from the
\textit{target} domain typically follow different distributions. The primary
difficulty in designing effective learning models to solve such problems lies
in how to bridge the gap between the source and target distributions. In this
paper, we provide comprehensive analysis of feature learning algorithms used in
conjunction with linear classifiers for domain adaptation. Our analysis shows
that in order to achieve good adaptation performance, the second moments of the
source domain distribution and target domain distribution should be similar.
Based on our new analysis, a novel extremely easy feature learning algorithm
for domain adaptation is proposed. Furthermore, our algorithm is extended by
leveraging multiple layers, leading to a deep linear model. We evaluate the
effectiveness of the proposed algorithms in terms of domain adaptation tasks on
the Amazon review dataset and the spam dataset from the ECML/PKDD 2006
discovery challenge.Comment: ijca
Radiative decays and magnetic moments of the predicted -like molecules
In this work, we first perform a systematic study of the transition magnetic
moments and the corresponding radiative decay behaviors of the -like
molecular states associated with their mass spectra, where the constituent
quark model is adopted by considering the - wave mixing effect. Our
numerical results show that the radiative decay properties can be considered as
the effective physical observable to reflect the inner structures of these
-like molecular states. Meanwhile, we also discuss the magnetic moments of
the -like molecular states, and we find that the magnetic moment
properties can be used to distinguish the -like molecular states from the
conventional mesonic states, which have the same quantum numbers and
similar masses. We expect that the present study can inspire the interest of
experimentalist in exploring the electromagnetic properties of the -like
molecular states, especially the radiative decay properties.Comment: 13 pages, 8 tables, 1 figur
Timestamps as Prompts for Geography-Aware Location Recommendation
Location recommendation plays a vital role in improving users' travel
experience. The timestamp of the POI to be predicted is of great significance,
since a user will go to different places at different times. However, most
existing methods either do not use this kind of temporal information, or just
implicitly fuse it with other contextual information. In this paper, we revisit
the problem of location recommendation and point out that explicitly modeling
temporal information is a great help when the model needs to predict not only
the next location but also further locations. In addition, state-of-the-art
methods do not make effective use of geographic information and suffer from the
hard boundary problem when encoding geographic information by gridding. To this
end, a Temporal Prompt-based and Geography-aware (TPG) framework is proposed.
The temporal prompt is firstly designed to incorporate temporal information of
any further check-in. A shifted window mechanism is then devised to augment
geographic data for addressing the hard boundary problem. Via extensive
comparisons with existing methods and ablation studies on five real-world
datasets, we demonstrate the effectiveness and superiority of the proposed
method under various settings. Most importantly, our proposed model has the
superior ability of interval prediction. In particular, the model can predict
the location that a user wants to go to at a certain time while the most recent
check-in behavioral data is masked, or it can predict specific future check-in
(not just the next one) at a given timestamp
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