Science China Physics, Mechanics & Astronomy

Any unitary transformation can be decomposed into a product of a group of near-trivial transformations. We investigate in detail the construction of universal quantum circuit of near trivial transformations. We first construct two universal quantum circuits which can implement any single-qubit rotation R y (θ) and R z (θ) within any given precision, and then we construct universal quantum circuit implementing any single-qubit transformation within any given precision. Finally, a universal quantum circuit implementing any n-qubit near-trivial transformation is constructed using the universal quantum circuits of R y (θ) and R z (θ). In the universal quantum circuit presented, each quantum transformation is encoded to a bit string which is used as ancillary inputs. The output of the circuit consists of the related bit string and the result of near-trivial transformation. Our result may be useful for the design of universal quantum computer in the future.

The nonlinear evolution process of new vortex structures at the late-stage of the transition, including the 3-D spatial structure of barrel-shaped vortex and “dark spots”structure observed by experiment research, has been confirmed by our computational results. The formation mechanisms of these structures have been explored. It is revealed that the new vortex structures, the ring-like vortex chain and induced disturbance velocities play a dominant role in the generation of turbulent spots.

With its tremendous success in many machine learning and pattern recognition tasks, deep learning, as one type of data-driven models, has also led to many breakthroughs in other disciplines including physics, chemistry and material science. Nevertheless, the supremacy of deep learning over conventional optimization approaches heavily depends on the huge amount of data collected in advance to train the model, which is a common bottleneck of such a data-driven technique. In this work, we present a comprehensive deep learning model for the design and characterization of nanophotonic structures, where a self-supervised learning mechanism is introduced to alleviate the burden of data acquisition. Taking reflective metasurfaces as an example, we demonstrate that the self-supervised deep learning model can effectively utilize randomly generated unlabeled data during training, with the total test loss and prediction accuracy improved by about 15% compared with the fully supervised counterpart. The proposed self-supervised learning scheme provides an efficient solution for deep learning models in some physics-related tasks where labeled data are limited or expensive to collect.

Bài báo này nhằm mục đích sử dụng phương trình động lực học bọt thống nhất để nghiên cứu hành vi của bọt trong các kịch bản phức tạp liên quan đến biên bề mặt tự do/hàn và sự tương tác giữa nhiều bọt. Tác động của sự di chuyển của điểm kỳ dị lên dạng của phương trình thống nhất được phân tích sau khi suy diễn phương trình dao động bọt bằng cách sử dụng nguồn điểm chuyển động và một cặp cực, tiếp theo là thảo luận về ảnh hưởng của các thuật ngữ liên quan đến tính nén trong quá trình di chuyển lên động lực học bọt. Ngoài ra, nghiên cứu hiện tại xem xét tác động của các biên hỗn hợp, bao gồm biên chéo và biên song song, bằng cách giới thiệu một số bọt phản chiếu hữu hạn cho biên chéo và một số bọt phản chiếu vô hạn cho biên song song. Các thí nghiệm bọt tia lửa và mô phỏng số được thực hiện để kiểm chứng lý thuyết hiện tại. Việc áp dụng phương trình thống nhất trong các tương tác đa bọt được minh họa thông qua việc tính toán một mảng bọt hình cầu chứa hơn 100 bọt khí hóa phân bố đồng đều dưới các điều kiện biên khác nhau. Đỉnh áp suất do cụm bọt gây ra có thể đạt gần gấp hai hoặc thậm chí cao hơn áp suất của một bọt đơn lẻ, làm nổi bật tiềm năng gây hại của cụm bọt khí hóa.

The first Chinese lunar orbiter Chang’E-1 is a successful mission with many fruitful results obtained in various disciplines. The scientific data acquired by the Chang’E-1 payloads can benefit studies of the lunar origin and evolution, as well as other relevant research areas, after careful validation of the data. Among the new results, the Chang’E-1 selenodetic products are continually uncovering characteristics of the lunar surface, undersurface and inner structure. Successful lunar orbiters such as the Clementine, Lunar Prospector, KAGUYA/SELENE, Chang’E-1, Lunar Reconnaissance Orbiter and GRAIL have been revealing, with increasing clarity, global selenodetic characteristics with state-of-the-art fine resolution and high precision. In particular, the Chang’E-1 plays an important distinctive role in selenodetic exploration through enhancing lunar topography and gravity models. The gravity model has been successfully improved with a factor of two after applying the Chang’E-1 long-wavelength tracking data. Using the new models, some medium-scale lunar surface characteristics such as basins and volcanoes have been identified. Furthermore, the old mascon basins of Bouguer, gravity anomaly and craters have been discovered with the Chang’E-1 selenodetic data.

In a superconducting topological insulator, a superconducting vortex line can trap a one-dimensional topological band with localized Majorana zero modes at the ends. Here, we study the effect of hexagonal warping and its corresponding symmetry-breaking effect on vortex phase transition. We perform both analytical calculations based on a semiclassical formula and numerical calculations based on full quantum mechanics using the Bogoliubov-de Gennes equation. We find that the hexagonal warping term extends the topological region of the vortex line as the chemical potential changes and leads to MZMs, even in the absence of topological surface states.

Electromagnetic levitation technique was used to undercool bulk samples of Co-20% Cu and Co-60% Cu alloys and high undercoolings up to 303 and 110 K were achieved, respectively. The dendritic growth velocities were measured as a function of undercooling. The dendrite growth velocity of the Co-20% Cu alloy was much higher than that of the Co-60% Cu alloy. The experimental data were analyzed on the basis of the LKT/BCT dendritic growth model by taking into account non-equilibrium interface kinetics. It has been revealed that a transition from solute diffusion controlled dendritic growth to thermal diffusion controlled dendritic growth occurs at an undercooling of about 66 K for the Co-20% Cu alloy, whereas the dendrite growth in Co-60% Cu alloy proceeds in a solute diffusion controlled mode within a large solidification temperature range, and the solutal undercooling plays a dominant role. It is thus deduced that certain distinct solidification temperature ranges may be responsible for the different solidification modes for the two alloys.

We investigate the effects of high pressure and physical aging on the boson peak and thermal expansion of a typical metallic glass. Specifically, the thermal expansion coefficient and boson peak intensity monotonically decrease during physical aging. With the increase of high pressure, the boson peak intensity and the thermal expansion coefficient coincidently experience an incipient decrease and then a subsequent increase. The boson peak intensity shows an approximately linear relationship with the thermal expansion coefficient. The thermal expansion can be affected by structural relaxation or rejuvenation, which can reflect the flow units variation and atomic packing of a metallic glass. Our results indicate a direct link between structural relaxation or rejuvenation and fast boson peak dynamics, providing insights into the boson peak behavior and structural heterogeneity of metallic glasses.