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Promising applications of the anisotropic quantum Rabi model (AQRM) in broad parameter ranges are explored, which is realized with superconducting flux qubits simultaneously driven by two-tone time-dependent magnetic fields. Regarding the quantum phase transitions (QPTs), with assistance of fidelity susceptibility, we extract the scaling functions and the critical exponents, with which the universal scaling of the cumulant ratio is captured by rescaling the parameters related to the anisotropy. Moreover, a fixed point of the cumulant ratio is predicted at the critical point of the AQRM with finite anisotropy. In respect of quantum information tasks, the generation of the macroscopic Schrödinger cat states and quantum controlled phase gates are investigated in the degenerate case of the AQRM, whose performance is also investigated by numerical calculation with practical parameters. Therefore, our results pave the way to explore distinct features of the AQRM in circuit QED systems for QPTs, quantum simulations and quantum information processing.

Topological photonics has attracted extensive attention, since it allows for a platform to explore and exploit versatile nano-optics systems. In particular, the ideal Weyl metamaterials have recently been demonstrated with fascinating phenomena such as chiral zero mode and negative refraction. In this work, we apply the photonic Weyl metamateirals into the optical tweezers. Based on the effective medium approach, the optical force generated by the body state of the Weyl metamaterial is systematically investigated. Interestingly, theoretical results show that for oblique incidence, the optical force spectra present a valley around Weyl frequency with zero magnitude exactly at the Weyl frequency, and the forces show strong optical circular dichroism. In addition, due to the bi-anisotropic properties, transmissions through the Weyl metamaterial exhibit a significant linear-to-circular polarization conversion and the transmitted wavefront acquires spin momenta of photons, which induces abnormal force on chiral particles. Our study may provide potential applications in the optical manipulations, polarization conversions, and wavefront engineering optics.

We present a mean photon number dependent variational method, which works well in the whole coupling regime if the photon energy is dominant over the spin-flipping, to evaluate the properties of the Rabi model for both the ground state and excited states. For the ground state, it is shown that the previous approximate methods, the generalized rotating-wave approximation (only working well in the strong coupling limit) and the generalized variational method (only working well in the weak coupling limit), can be recovered in the corresponding coupling limits. The key point of our method is to tailor the merits of these two existing methods by introducing a mean photon number dependent variational parameter. For the excited states, our method yields considerable improvements over the generalized rotating-wave approximation. The variational method proposed could be readily applied to more complex models, for which it is difficult to formulate an analytic formula.

Peroxisomes are present ubiquitously and make important contributions to cellular metabolism in eukaryotes. They play crucial roles in pathogenicity of plant fungal pathogens. The peroxisomal matrix proteins and peroxisomal membrane proteins (PMPs) are synthesized in the cytosol and imported post-translationally. Although the peroxisomal import machineries are generally conserved, some species-specific features were found in different types of organisms. In phytopathogenic fungi, the pathways of the matrix proteins have been elucidated, while the import machinery of PMPs remains obscure. Here, we report that MoPEX19, an ortholog of ScPEX19, was required for PMPs import and peroxisomal maintenance, and played crucial roles in metabolism and pathogenicity of the rice blast fungus Magnaporthe oryzae. MoPEX19 was expressed in a low level and Mopex19p was distributed in the cytoplasm and newly formed peroxisomes. MoPEX19 deletion led to mislocalization of peroxisomal membrane proteins (PMPs), as well peroxisomal matrix proteins. Peroxisomal structures were totally absent in Δmopex19 mutants and woronin bodies also vanished. Δmopex19 exhibited metabolic deficiency typical in peroxisomal disorders and also abnormality in glyoxylate cycle which was undetected in the known mopex mutants. The Δmopex19 mutants performed multiple disorders in fungal development and pathogenicity-related morphogenesis, and lost completely the pathogenicity on its hosts. These data demonstrate that MoPEX19 plays crucial roles in maintenance of peroxisomal and peroxisome-derived structures and makes more contributions to fungal development and pathogenicity than the known MoPEX genes in the rice blast fungus.

The formation of giant clusters, namely the percolation phase transition, is one of the most widely studied critical phenom- ena on networks. The critical behaviors of percolation in one- and two-dimensional lattices have been given in the book [1]. For d-dimensional lattices, the critical exponents of percolation change with d until the upper critical dimension du = 6, above which they are independent of d and become meanfield like. It is also well known that the critical behaviors of percolation on Erdos-Renyi （ER） networks are also meanfield like [2, 3].

Herein, percolation phase transitions on a two-dimensional lattice were studied using machine learning techniques. Results reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks (NNs), whereas phase transitions of different universality classes require different NNs. Based on this finding, we proposed the universality class of machine learning for critical phenomena. Furthermore, we investigated and discussed the NNs of different universality classes. Our research contributes to machine learning by relating the NNs with the universality class.

In a statistical ensemble with M microstates, we introduce an M×M correlation matrix with correlations among microstates as its elements. Eigen microstates of ensemble can be defined using eigenvectors of the correlation matrix. The eigenvalue normalized by M represents weight factor in the ensemble of the corresponding eigen microstate. In the limit M → ∞, weight factors drop to zero in the ensemble without localization of the microstate. The finite limit of the weight factor when M → ∞ indicates a condensation of the corresponding eigen microstate. This finding indicates a transition into a new phase characterized by the condensed eigen microstate. We propose a finite-size scaling relation of weight factors near critical point, which can be used to identify the phase transition and its universality class of general complex systems. The condensation of eigen microstate and the finite-size scaling relation of weight factors are confirmed using Monte Carlo data of one-dimensional and two-dimensional Ising models.

We investigate the effect of counter-rotating-wave terms on the non-Markovianity in quantum open systems by employing the hierarchical equations of motion in the framework of the non-Markovian quantum state diffusion approach. As illustrative examples, the non-Markovian memory effect of a qubit embedded in a bosonic and a fermionic environment at zero temperature are analyzed. It is found that the counter-rotating-wave terms are able to enhance the observed non-Markovianity no matter the environment is composed of bosons or fermions. This result suggests that the rotating-wave approximation may inevitably reduce the non-Markovianity in quantum open systems. Moreover, we find that the modification of the non-Markovianity due to the different statistical properties of environmental modes becomes larger with the increase of the system-environment coupling strength.

Peroxisomes are present ubiquitously and make important contributions to cellular metabolism in eukaryotes. They play crucial roles in pathogenicity of plant fungal pathogens. The peroxisomal matrix proteins and peroxisomal membrane proteins (PMPs) are synthesized in the cytosol and imported post-translationally. Although the peroxisomal import machineries are generally conserved, some species-specific features were found in different types of organisms. In phytopathogenic fungi, the pathways of the matrix proteins have been elucidated, while the import machinery of PMPs remains obscure. Here, we report that MoPEX19, an ortholog of ScPEX19, was required for PMPs import and peroxisomal maintenance, and played crucial roles in metabolism and pathogenicity of the rice blast fungus Magnaporthe oryzae. MoPEX19 was expressed in a low level and Mopex19p was distributed in the cytoplasm and newly formed peroxisomes. MoPEX19 deletion led to mislocalization of peroxisomal membrane proteins (PMPs), as well peroxisomal matrix proteins. Peroxisomal structures were totally absent in Delta mopex19 mutants and woronin bodies also vanished. Delta mopex19 exhibited metabolic deficiency typical in peroxisomal disorders and also abnormality in glyoxylate cycle which was undetected in the known mopex mutants. The Delta mopex19 mutants performed multiple disorders in fungal development and pathogenicity-related morphogenesis, and lost completely the pathogenicity on its hosts. These data demonstrate that MoPEX19 plays crucial roles in maintenance of peroxisomal and peroxisome-derived structures and makes more contributions to fungal development and pathogenicity than the known MoPEX genes in the rice blast fungus.

In this study, we explore an approach aimed at enhancing the transmission or reflection coefficients of absorbing materials through the utilization of joint measurements of entangled photon states. On the one hand, through the implementation of photon catalysis in the reflected channel, we can effectively modify the state of the transmission channel, leading to a notable improvement in the transmission ratio. Similarly, this approach holds potential for significantly amplifying the reflection ratio of absorbing materials, which is useful for detecting cooperative targets. On the other hand, employing statistical counting methods based on the technique of heralding on zero photons, we evaluate the influence of our reflection enhancement protocol for detecting noncooperative targets, which is validated through Monte Carlo simulations of a quantum radar setup affected by Gaussian white noise. Our results demonstrate a remarkable enhancement in the signal-to-noise ratio of imaging, albeit with an increase in mean-square error. These findings highlight the potential practical applications of our approach in the implementation of quantum radar.