Efficient single-photon-assisted entanglement concentration for partially entangled photon pairs

We present two realistic entanglement concentration protocols (ECPs) for pure partially entangled photons. A partially entangled photon pair can be concentrated to a maximally entangled pair with only an ancillary single photon in a certain probability, while the conventional ones require two copies of partially entangled pairs at least. Our first protocol is implemented with linear optics and the second one is implemented with cross-Kerr nonlinearities. Compared with other ECPs, they do not need to know the accurate coefficients of the initial state. With linear optics, it is feasible with current experiment. With cross-Kerr nonlinearities, it does not require the sophisticated single-photon detectors and can be repeated to get a higher success probability. Moreover, the second protocol can get the higher entanglement transformation efficiency and it maybe the most economical one by far. Meanwhile, both of protocols are more suitable for multi-photon system concentration, because they need less operations and classical communications. All these advantages make two protocols be useful in current long-distance quantum communications

Electronic, mechanical, and thermodynamic properties of americium dioxide

By performing density functional theory (DFT) +$U$ calculations, we systematically study the electronic, mechanical, tensile, and thermodynamic properties of AmO$_{2}$. The experimentally observed antiferromagnetic insulating feature [J. Chem. Phys. 63, 3174 (1975)] is successfully reproduced. It is found that the chemical bonding character in AmO$_{2}$ is similar to that in PuO$_{2}$, with smaller charge transfer and stronger covalent interactions between americium and oxygen atoms. The valence band maximum and conduction band minimum are contributed by 2$p-5f$ hybridized and 5$f$ electronic states respectively. The elastic constants and various moduli are calculated, which show that AmO$_{2}$ is less stable against shear forces than PuO$_{2}$. The stress-strain relationship of AmO$_{2}$ is examined along the three low-index directions by employing the first-principles computational tensile test method. It is found that similar to PuO$_{2}$, the [100] and [111] directions are the strongest and weakest tensile directions, respectively, but the theoretical tensile strengths of AmO$_{2}$ are smaller than those of PuO$_{2}$. The phonon dispersion curves of AmO$_{2}$ are calculated and the heat capacities as well as lattice expansion curve are subsequently determined. The lattice thermal conductance of AmO$_{2}$ is further evaluated and compared with attainable experiments. Our present work integrally reveals various physical properties of AmO$_{2}$ and can be referenced for technological applications of AmO$_{2}$ based materials.Comment: 23 pages, 8 figure

2-(2-{[2-(2-Pyridylcarbon­yl)hydrazono]meth­yl}phen­oxy)acetic acid

In the title compound, C15H13N3O4, the pyridine and benzene rings are nearly coplanar [dihedral angle = 4.92 (12)°]. The maximum deviation from the best least-squares plane calculated for the main mol­ecular skeleton is 0.1722 (1) Å for the carbonyl O atom. In the crystal, inter­molecular O—H⋯O hydrogen bonds connect the mol­ecules into a chain, while π–π stacking inter­actions between the pyridine and benzene rings [centroid–centroid distance = 3.9162 (8) Å and offset angle = 27.20°] complete a two-dimensional network

Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning

The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models. Despite their potential, it remains elusive whether diffusion language models can solve general language tasks comparable to their autoregressive counterparts. This paper demonstrates that scaling diffusion models w.r.t. data, sizes, and tasks can effectively make them strong language learners. We build competent diffusion language models at scale by first acquiring knowledge from massive data via masked language modeling pretraining thanks to their intrinsic connections. We then reprogram pretrained masked language models into diffusion language models via diffusive adaptation, wherein task-specific finetuning and instruction finetuning are explored to unlock their versatility in solving general language tasks. Experiments show that scaling diffusion language models consistently improves performance across downstream language tasks. We further discover that instruction finetuning can elicit zero-shot and few-shot in-context learning abilities that help tackle many unseen tasks by following natural language instructions, and show promise in advanced and challenging abilities such as reasoning.Comment: added reference

Straight-line path following for asymmetric unmanned platform with disturbance estimation

The problem of straight-line path following for asymmetric unmanned platform exposed to unknown disturbances was addressed in this paper. The mathematical model of asymmetric unmanned platform was established and the inputs in sway and yaw directions were decoupled, which facilitated the establishment of control strategy of path following. The guidance law and the cross-track error were derived from the classical line-of-sight (LOS) guidance principle. And the equilibrium point of the cross-track error was proven to be uniformly semiglobally exponentially stable (USGES), which guaranteed the exponential convergence to zero. A new disturbance estimation law was developed by adding a linear item of the estimation error into the classical one, which improved the principle’s precision and sensitivity dramatically. The control strategy was developed based on the integrator backstepping technique and the new disturbance estimation law, which made the equilibrium system to be uniformly globally asymptotically stable (UGAS). Computer simulations were conducted to verify the effectiveness of the estimation and control laws during straight-line path following for asymmetric unmanned platform in the presence of unknown disturbances

Implementing Genuine Multi-Qubit Entanglement of Two-Level-System Inside a Superconducting Phase Qubit

The interaction between a superconducting phase qubit and the two-level systems locating inside the Josephson tunnel barrier is shown to be described by the XY model, which is naturally used to implement the iSWAP gate. With this gate, we propose a scheme to efficiently generate genuine multi-qubit entangled states of such two-level systems, including multipartite W state and cluster states. In particularly, we show that, with the help of the phase qubit, the entanglement witness can be used to efficiently detect the produced genuine multi-qubit entangled states. Furthermore, we analyze that the proposed approach for generating multi-qubit entangled states can be used in a wide class of candidates for quantum computation.Comment: 6 page

Linear Stability of f(R,ϕ,X)f(R,\phi,X) Thick Branes: Tensor Perturbations

We explore thick branes in $f(R,\phi,X)$ gravity. We obtain the linear tensor perturbation equation of $f(R,\phi,X)$ branes and show that the branes are stable against the tensor perturbations under the condition of $\frac{\partial f(R,\phi,X)}{\partial R}>0$. In order to obtain thick brane solutions of the fourth-order field equations in this theory, we employ the reconstruction technique. We get exact solutions of the specific $f(R,\phi,X)$ thick brane generated by a non-canonical scalar field. It is shown that the zero mode of the graviton for the thick brane is localized under certain conditions. This implies that the four-dimensional Newtonian potential is recovered on the brane. The effects of the Kaluza-Klein modes of the graviton for the $f(R,\phi,X)$ thick brane are also discussed.Comment: 23 pages, 5 figure