Hybrid Tractable Classes of Binary Quantified Constraint Satisfaction Problems

In this paper, we investigate the hybrid tractability of binary Quantified Constraint Satisfaction Problems (QCSPs). First, a basic tractable class of binary QCSPs is identified by using the broken-triangle property. In this class, the variable ordering for the broken-triangle property must be same as that in the prefix of the QCSP. Second, we break this restriction to allow that existentially quantified variables can be shifted within or out of their blocks, and thus identify some novel tractable classes by introducing the broken-angle property. Finally, we identify a more generalized tractable class, i.e., the min-of-max extendable class for QCSPs

General Proof of the Tolman law

Tolman proposed that the proper temper $T$ of a static self-gravitating fluid in thermodynamic equilibrium satisfies the relation $\chi T=constant$, where $\chi$ is the redshift factor of the spacetime. The Tolman law has been proven for radiation in stationary spacetimes and for perfect fluids in stationary, asymototically flat and axisymmetric spacetimes. It is unclear whether the proof can be extended to more general cases. In this paper, we prove that under some reasonable conditions, the Tolman law always holds for a perfect fluid in a stationary spacetime. The key assumption in our proof is that the particle number density $n$ can not be determined by the energy density $\rho$ and pressure $p$ via the equations of state. This is true for many known fluids with the equation of state $p=p(\rho)$. Then, by requiring that the total entropy of the fluid is an extremum for the variation of $n$ with a fixed metric, we prove the Tolman law. In our proof, only the conservations of stress energy and the total particle number are used, and no field equations are involved. Our work suggests that the Tolman law holds for a generic perfect fluid in a stationary spacetime, even beyond general relativity.Comment: 4 pages, no figur

Linear Depth QFT over IBM Heavy-hex Architecture

Compiling a given quantum algorithm into a target hardware architecture is a challenging optimization problem. The compiler must take into consideration the coupling graph of physical qubits and the gate operation dependencies. The existing noise in hardware architectures requires the compilation to use as few running cycles as possible. Existing approaches include using SAT solver or heuristics to complete the mapping but these may cause the issue of either long compilation time (e.g., timeout after hours) or suboptimal compilation results in terms of running cycles (e.g., exponentially increasing number of total cycles). In this paper, we propose an efficient mapping approach for Quantum Fourier Transformation (QFT) circuits over the existing IBM heavy-hex architecture. Such proposal first of all turns the architecture into a structure consisting of a straight line with dangling qubits, and then do the mapping over this generated structure recursively. The calculation shows that there is a linear depth upper bound for the time complexity of these structures and for a special case where there is 1 dangling qubit in every 5 qubits, the time complexity is 5N+O(1). All these results are better than state of the art methods

A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation

Unsupervised domain adaptation (UDA) methods facilitate the transfer of models to target domains without labels. However, these methods necessitate a labeled target validation set for hyper-parameter tuning and model selection. In this paper, we aim to find an evaluation metric capable of assessing the quality of a transferred model without access to target validation labels. We begin with the metric based on mutual information of the model prediction. Through empirical analysis, we identify three prevalent issues with this metric: 1) It does not account for the source structure. 2) It can be easily attacked. 3) It fails to detect negative transfer caused by the over-alignment of source and target features. To address the first two issues, we incorporate source accuracy into the metric and employ a new MLP classifier that is held out during training, significantly improving the result. To tackle the final issue, we integrate this enhanced metric with data augmentation, resulting in a novel unsupervised UDA metric called the Augmentation Consistency Metric (ACM). Additionally, we empirically demonstrate the shortcomings of previous experiment settings and conduct large-scale experiments to validate the effectiveness of our proposed metric. Furthermore, we employ our metric to automatically search for the optimal hyper-parameter set, achieving superior performance compared to manually tuned sets across four common benchmarks. Codes will be available soon

Preservation of Topological Surface States in Millimeter-Scale Transferred Membranes

Ultrathin topological insulator membranes are building blocks of exotic quantum matter. However, traditional epitaxy of these materials does not facilitate stacking in arbitrary orders, while mechanical exfoliation from bulk crystals is also challenging due to the non-negligible interlayer coupling therein. Here we liberate millimeter-scale films of the topological insulator Bi2Se3, grown by molecular beam epitaxy, down to 3 quintuple layers. We characterize the preservation of the topological surface states and quantum well states in transferred Bi2Se3 films using angle-resolved photoemission spectroscopy. Leveraging the photon-energy-dependent surface sensitivity, the photoemission spectra taken with 6 and 21.2 eV photons reveal a transfer-induced migration of the topological surface states from the top to the inner layers. By establishing clear electronic structures of the transferred films and unveiling the wave function relocation of the topological surface states, our work lays the physics foundation crucial for the future fabrication of artificially stacked topological materials with single-layer precision

16S rRNA gene sequencing reveals the correlation between the gut microbiota and the susceptibility to pathological scars

The gut microbiome profile in patients with pathological scars remains rarely known, especially those patients who are susceptible to pathological scars. Previous studies demonstrated that gut microbial dysbiosis can promote the development of a series of diseases via the interaction between gut microbiota and host. The current study aimed to explore the gut microbiota of patients who are prone to suffer from pathological scars. 35 patients with pathological scars (PS group) and 40 patients with normal scars (NS group) were recruited for collection of fecal samples to sequence the 16S ribosomal RNA (16S rRNA) V3-V4 region of gut microbiota. Alpha diversity of gut microbiota showed a significant difference between NS group and PS group, and beta diversity indicated that the composition of gut microbiota in NS and PS participants was different, which implied that dysbiosis exhibits in patients who are susceptible to pathological scars. Based on phylum, genus, species levels, we demonstrated that the changing in some gut microbiota (Firmicutes; Bacteroides; Escherichia coli, etc.) may contribute to the occurrence or development of pathological scars. Moreover, the interaction network of gut microbiota in NS and PS group clearly revealed the different interaction model of each group. Our study has preliminary confirmed that dysbiosis exhibits in patients who are susceptible to pathological scars, and provide a new insight regarding the role of the gut microbiome in PS development and progression

Build your own hybrid thermal/EO camera for autonomous vehicle

to appear in the Proc. of the IEEE International Conference on Robotics and Automation, 2019International audienceIn this work, we propose a novel paradigm to design a hybrid thermal/EO (Electro-Optical or visible-light) camera, whose thermal and RGB frames are pixel-wisely aligned and temporally synchronized. Compared with the existing schemes, we innovate in three ways in order to make it more compact in dimension, and thus more practical and extendable for real-world applications. The first is a redesign of the structure layout of the thermal and EO cameras. The second is on obtaining a pixel-wise spatial registration of the thermal and RGB frames by a coarse mechanical adjustment and a fine alignment through a constant homography warping. The third innovation is on extending one single hybrid camera to a hybrid camera array, through which we can obtain wide-view spatially aligned thermal, RGB and disparity images simultaneously. The experimental results show that the average error of spatial-alignment of two image modalities can be less than one pixel