Solar Magnetism and the Activity Telescope at HSOS

A new solar telescope system is described, which has been operating at Huairou Solar Observing Station （HSOS）, National Astronomical Observatories, Chinese Academy of Sciences （CAS）, since the end of 2005. This instrument, the Solar Magnetism and Activity Telescope （SMAT）, comprises two telescopes which respectively make measurements of full solar disk vector magnetic field and Ha observation. The core of the full solar disk video vector magnetograph is a birefringent filter with 0.1A bandpass, installed in the tele-centric optical system of the telescope. We present some preliminary observational results of the full solar disk vector magnetograms and Ha filtergrams obtained with this telescope system.

Learning Unitary Transformation by Quantum Machine Learning Model

Quantum machine learning(QML)is a rapidly rising research eld that incorporates ideas from quantum computing and machine learning to develop emerging tools for scientic research and improving data processing.How to efciently control or manipulate the quantum system is a fundamental and vexing problem in quantum computing.It can be described as learning or approximating a unitary operator.Since the success of the hybrid-based quantum machine learning model proposed in recent years,we investigate to apply the techniques from QML to tackle this problem.Based on the Choi–Jamiołkowski isomorphism in quantum computing,we transfer the original problem of learning a unitary operator to a min–max optimization problem which can also be viewed as a quantum generative adversarial network.Besides,we select the spectral norm between the target and generated unitary operators as the regularization term in the loss function.Inspired by the hybrid quantum-classical framework widely used in quantum machine learning,we employ the variational quantum circuit and gradient descent based optimizers to solve the min-max optimization problem.In our numerical experiments,the results imply that our proposed method can successfully approximate the desired unitary operator and dramatically reduce the number of quantum gates of the traditional approach.The average delity between the states that are produced by applying target and generated unitary on random input states is around 0.997.

Effect of Fe Content on the Interfacial Reliability of SnAgCu/Fe—Ni Solder Joints

Fe-Ni films with compositions of Fe-75Ni, Fe-50Ni, and Fe-30Ni were used as under bump metallization （UBM） to evaluate the interracial reliability of SnAgCu/Fe-Ni solder joints through ball shear test, high temperature storage, and temperature cycling. The shear strengths for Fe-75Ni, Fe-5ONi, and Fe-3ONi solder joints after reflow were 42.57, 53.94 and 53.98 MPa, respectively, which were all satisfied the requirement of industrialization （〉34.3 MPa）. High temperature storage was conducted at 150, 175 and 200 ℃. It was found that higher Fe content in Fe-Ni layer had the ability to inhibit the mutual diffusion at interface region below 150 ℃, and the growth speed of intermetallic compound （IMC） decreased with increasing Fe concentration. When stored at 200 ℃, the IMC thickness reached a limit for all three films after 4 days, and some cracks occurred at the interface between IMC and Fe-Ni layer. The activation energies for the growth of FeSn2 on Fe-30Ni, Fe-5ONi, and Fe-75Ni films were calculated as 246, 185, and 81 kJ/mol, respectively. Temperature cycling tests revealed that SnAgCu/Fe-5ONi solder joint had the lowest failure rate （less than 10%）, and had the best interfacial reliability among three compositions.