1,896 research outputs found
An Analytical Solution in Detuned Two Level Systems
Finding the evolution of two level Hamiltonian is of great importance in
quantum computation and quantum precision manipulation due to the requirement
of quantum experiment control. However, the Schr\"odinger equation of an
arbitrary time-dependent two level Hamiltonian is hardly solvable due to its
non-commutativity Hamiltonian in different times. In this article, we expand
and demonstrate an exact solution of Schr\"odinger equation respect to general
two level systems with a few limitations. This analytical solution has lots of
manipulative parameters and a few boundary restrictions, which could drive many
applications. Furthermore, we show the adaptive capacity of our scheme, which
demonstrated the widely use of our scheme, and make it suitable for most of
experiment Hamiltonian directly
Improving Anomaly Segmentation with Multi-Granularity Cross-Domain Alignment
Anomaly segmentation plays a crucial role in identifying anomalous objects
within images, which facilitates the detection of road anomalies for autonomous
driving. Although existing methods have shown impressive results in anomaly
segmentation using synthetic training data, the domain discrepancies between
synthetic training data and real test data are often neglected. To address this
issue, the Multi-Granularity Cross-Domain Alignment (MGCDA) framework is
proposed for anomaly segmentation in complex driving environments. It uniquely
combines a new Multi-source Domain Adversarial Training (MDAT) module and a
novel Cross-domain Anomaly-aware Contrastive Learning (CACL) method to boost
the generality of the model, seamlessly integrating multi-domain data at both
scene and sample levels. Multi-source domain adversarial loss and a dynamic
label smoothing strategy are integrated into the MDAT module to facilitate the
acquisition of domain-invariant features at the scene level, through
adversarial training across multiple stages. CACL aligns sample-level
representations with contrastive loss on cross-domain data, which utilizes an
anomaly-aware sampling strategy to efficiently sample hard samples and anchors.
The proposed framework has decent properties of parameter-free during the
inference stage and is compatible with other anomaly segmentation networks.
Experimental conducted on Fishyscapes and RoadAnomaly datasets demonstrate that
the proposed framework achieves state-of-the-art performance.Comment: Accepted to ACM Multimedia 202
Angular Reconstruction of a Lead Scintillating-Fiber Sandwiched Electromagnetic Calorimeter
A new method called Neighbor Cell Deposited Energy Ratio (NCDER) is proposed
to reconstruct incidence position in a single layer for a 3-dimensional imaging
electromagnetic calorimeter (ECAL).This method was applied to reconstruct the
ECAL test beam data for the Alpha Magnetic Spectrometer-02 (AMS-02). The
results show that this method can achieve an angular resolution of 7.36\pm 0.08
/ \sqrt(E) \oplus 0.28 \pm 0.02 degree in the determination of the photons
direction, which is much more precise than that obtained with the
commonly-adopted Center of Gravity(COG) method (8.4 \pm 0.1 /sqrt(E) \oplus
0.8\pm0.3 degree). Furthermore, since it uses only the properties of
electromagnetic showers, this new method could also be used for other type of
fine grain sampling calorimeters.Comment: 6 pages, 8 figure
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