High-responsivity vertical-illumination Si/Ge uni-traveling-carrier photodiodes based on silicon-on-insulator substrate

Si/Ge uni-traveling carrier photodiodes exhibit higher output current when space-charge effects are overcome and thermal effects are suppressed, which is highly beneficial for increasing the dynamic range of various microwave photonic systems and simplifying high-bit-rate digital receivers in different applications. From the point of view of packaging, detectors with vertical-illumination configuration can be easily handled by pick-and-place tools and are a popular choice for making photo-receiver modules. However, vertical-illumination Si/Ge uni-traveling carrier (UTC) devices suffer from inter-constraint between high speed and high responsivity. Here, we report a high responsivity vertical-illumination Si/Ge UTC photodiode based on a silicon-on-insulator substrate. The maximum absorption efficiency of the devices was 2.4 times greater than the silicon substrate owing to constructive interference. The Si/Ge UTC photodiode was successfully fabricated and had a dominant responsivity at 1550 nm of 0.18 A/W, a 50% improvement even with a 25% thinner Ge absorption layer.Comment: 5pages,2figure

Benzene-1,4-dicarboxylic acid–N,N-dimethyl­acetamide (1/2)

The asymmetric unit of title compound, C8H6O4·2C4H9NO, contains one half-mol­ecule (an inversion centre in P21/n generates the other half of the molecule) of terephthalic acid (TA) and one mol­ecule of N,N-dimethyl­acetamide (DMAC). The DMAC mol­ecules are linked to TA by strong O—H⋯O hydrogen bonds

CoLFI: Cosmological Likelihood-free Inference with Neural Density Estimators

In previous works, we proposed to estimate cosmological parameters with the artificial neural network (ANN) and the mixture density network (MDN). In this work, we propose an improved method called the mixture neural network (MNN) to achieve parameter estimation by combining ANN and MDN, which can overcome shortcomings of the ANN and MDN methods. Besides, we propose sampling parameters in a hyper-ellipsoid for the generation of the training set, which makes the parameter estimation more efficient. A high-fidelity posterior distribution can be obtained using $\mathcal{O}(10^2)$ forward simulation samples. In addition, we develop a code-named CoLFI for parameter estimation, which incorporates the advantages of MNN, ANN, and MDN, and is suitable for any parameter estimation of complicated models in a wide range of scientific fields. CoLFI provides a more efficient way for parameter estimation, especially for cases where the likelihood function is intractable or cosmological models are complex and resource-consuming. It can learn the conditional probability density $p(\boldsymbol\theta|\boldsymbol{d})$ using samples generated by models, and the posterior distribution $p(\boldsymbol\theta|\boldsymbol{d}_0)$ can be obtained for a given observational data $\boldsymbol{d}_0$. We tested the MNN using power spectra of the cosmic microwave background and Type Ia supernovae and obtained almost the same result as the Markov Chain Monte Carlo method. The numerical difference only exists at the level of $\mathcal{O}(10^{-2}\sigma)$. The method can be extended to higher-dimensional data.Comment: 24 pages, 8 tables, 17 figures, ApJS in press, corrected the ELU plot in Table 5. The code repository is available at https://github.com/Guo-Jian-Wang/colf

Entanglement control in one-dimensional s=1/2s=1/2 random XY spin chain

The entanglement in one-dimensional random XY spin systems where the impurities of exchange couplings and the external magnetic fields are considered as random variables is investigated by solving the different spin-spin correlation functions and the average magnetization per spin. The entanglement dynamics near particular locations of the system is also studied when the exchange couplings (or the external magnetic fields) satisfy three different distributions(the Gaussian distribution, double-Gaussian distribution, and bimodal distribution). We find that the entanglement can be controlled by varying the strength of external magnetic field and the different distributions of impurities. Moreover, the entanglement of some nearest-neighboring qubits can be increased for certain parameter values of the three different distributions.Comment: 13 pages, 4 figure

2-Cyclo­hexyl-4-[(3,5-dimethyl­piperidin-1-yl)meth­yl]-5-methyl­phenol

The title compound, C21H33NO, crystallizes with three independent mol­ecules in the asymmetric unit. The cyclo­hexane and piperidine rings adopt chair conformations. The crystal packing is stabilized by inter­molecular O—H⋯N and C—H⋯O hydrogen bonds, and by weak π–π stacking inter­actions [centroid–centroid distance = 3.876 (2) Å]

2,6-Dichloro-N-(4-chloro­phen­yl)benzamide

In the title compound, C13H8Cl3NO, the dihedral angle between the benzene rings is 63.2 (2)°. In the crystal, N—H⋯O hydrogen bonds link the mol­ecules into C(4) chains propagating in [001]. Weak aromatic π–π stacking also occurs [centroid–centroid separations = 3.759 (3) and 3.776 (3) Å]

2-(5-Amino-2H-tetra­zol-2-yl)acetic acid

In the title mol­ecule, C3H5N5O2, the tetra­zole ring and carboxyl group form a dihedral angle of 82.25 (14)°. In the crystal, adjacent mol­ecules are linked through O—H⋯N, N—H⋯O and N—H⋯N hydrogen bonds into layers parallel to the bc plane