The single-mode Dicke model is well known to undergo a quantum phase transition from the so-called normal phase to the superradiant phase (hereinafter called the 'superradiant quantum phase transition'). Normally, quantum phase transitions can be identified by the critical behavior of quantities such as entanglement, quantum fluctuations, and fidelity. In this paper, we study the role of the quantum Fisher information (QFI) of both the field mode and the atoms in the ground state of the Dicke Hamiltonian. For a finite but large number of atoms, our numerical results show that near the critical atom-field coupling, the QFI of the atomic and the field subsystems can surpass their classical limits, due to the appearance of nonclassical quadrature squeezing. As the coupling increases far beyond the critical point, each subsystem becomes a highly mixed state, which degrades the QFI and hence the ultimate phase sensitivity. In the thermodynamic limit, we present the analytical results of the QFI and their relationship with the reduced variances of the field mode and the atoms. For each subsystem, we find that there is a singularity in the derivative of the QFI at the critical point, a clear signature of the quantum criticality in the Dicke model.Quantum phase transitions in many-body systems are of fundamental interest [1] and have potential applications in quantum information [2][3][4][5][6][7] and quantum metrology [8][9][10][11][12][13][14][15]. Consider, for instance, a collection of N two-level atoms interacting with a single-mode bosonic field, described by the Dicke model (with = 1) [16]:z 0 whereb andˆ † b are annihilation and creation operators of the bosonic field with oscillation frequency ω, which is nearly resonant with the atomic energy splitting ω 0 . The collective spin operators σ ≡ˆ±ˆ= ∑± ± J J iJ x y k k and σ = ∑Ĵ 2 z k k z obey the SU(2) Lie algebra, where σ ± k and σ k z are Pauli operators of the kth atom. The atom-field coupling strength λ ∝ N V depends on the atomic density N V . For a finite number of atoms N (= j 2 ), the Hamiltonian (1) commutes with the parity, where Tr A (Tr B ) is the partial trace of the ground state |g over the atomic (bosonic field) degrees of freedom. The QFI is one of the central quantities used to qualify the utility of an input state [35,36], especially in Mach-Zehnder (or, equivalently, Ramsey) interferometer-based phase or parameter estimation. The achievable phase sensitivity is well known to be limited by the quantum Cramér-Rao bound δφ ρ ∝ˆF G 1 ( , ) min in , where the QFI ρF G ( , ) in depends on the input state ρ in and the New J. Phys. 16 (2014) 063039 T-L Wang et al B 2 . Therefore, the ultimate sensitivity is limited by δφ =n 1/(2 ) min cl , known as New J. Phys. 16 (2014) 063039 T-L Wang et al
Recent experiments have uncovered a fundamental information scale for cellular signaling networks: the correlation between input and output concentrations of molecules in a signaling pathway corresponds to at most 1-3 bits of mutual information. Our understanding of the physical constraints and evolutionary pressures that determine this scale remains incomplete. By focusing on a basic element of signaling pathways, the kinase-phosphatase enzymatic push-pull loop, we highlight the pivotal role played by energy resources available for signaling and their expenditure: the chemical potential energy of ATP hydrolysis, and the rate of ATP consumption. Scanning a broad range of reaction parameters based on enzymatic databases, we find that ATP chemical potentials in modern organisms are just above the threshold necessary to achieve empirical mutual information values. We also derive an analytical relation for the minimum ATP consumption required to maintain a certain signal fidelity across a range of input frequencies. Attempting to increase signal fidelity beyond a few bits lowers the bandwidth, the maximum characteristic signal frequency that the network can handle at a given energy cost. The observed information scale thus represents a balancing act between fidelity and the ability to process fast-changing environmental signals. Our analytical relation defines a performance limit for kinase-phosphatase networks, and we find evidence that a component of the yeast osmotic shock pathway may be close to the optimality line. By quantifying the evolutionary pressures that operate on these networks, we argue that this is not a coincidence: natural selection on energy expenditures is capable of pushing signaling systems toward optimality, particularly in unicellular organisms. Our theoretical framework is directly verifiable using existing experimental techniques, and predicts that more examples of such optimality should exist in nature.
The genus Psoralea, which belongs to the family Fabaceae, comprises ca. 130 species distributed all over the world, and some of the plants are used as folk medicine to treat various diseases. Psoralea corylifolia is a typical example, whose seeds have been widely used in many traditional Chinese medicine formulas for the treatment of various diseases such as leucoderma and other skin diseases, cardiovascular diseases, nephritis, osteoporosis, and cancer. So, the chemical and pharmacological studies on this genus were performed in the past decades. Here, we give a mini review on this genus about its phytochemical and pharmacological studies from 1910 to 2015.
This paper introduces the method of 3D modeling and visualization of ArcGIS combined with SketchUp, and describes the pipeline modeling process in SketchUp. And a drain-pipes network 3D GIS system is established with the actual drain-pipes data, which can fulfill the functions of three-dimensional display of drain-pipes network, pipeline locating, roaming and other functions.
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