Resonant Control of Interaction Between Different Electronic States

We observe a magnetic Feshbach resonance in a collision between the ground and metastable states of two-electron atoms of ytterbium (Yb). We measure the on-site interaction of doubly-occupied sites of an atomic Mott insulator state in a three-dimensional optical lattice as a collisional frequency shift in a high-resolution laser spectroscopy. The observed spectra are well fitted by a simple theoretical formula, in which two particles with an s-wave contact interaction are confined in a harmonic trap. This analysis reveals a wide variation of the interaction with a resonance behavior around a magnetic field of about 1.1 Gauss for the energetically lowest magnetic sublevel of ${}^{170}$Yb, as well as around 360 mG for the energetically highest magnetic sublevel of ${}^{174}$Yb. The observed Feshbach resonance can only be induced by an anisotropic inter-atomic interaction. This novel scheme will open the door to a variety of study using two-electron atoms with tunable interaction.Comment: 5 pages, 5 figure

Unmanned aerial vehicles and deep learning for assessment of anthropogenic marine debris on beaches on an island in a semi-enclosed sea in Japan

The increasing prevalence of marine debris is a global problem, and urgent action for amelioration is needed. Identifying hotspots where marine debris accumulates will enable effective control; however, knowledge on the location of accumulation hotspots remains incomplete. In particular, marine debris accumulation on beaches is a concern. Surveys of beaches require intensive human effort, and survey methods are not standardized. If marine debris monitoring is conducted using a standardized method, data from different regions can be compared. With an unmanned aerial vehicle (UAV) and deep learning computational methods, monitoring a wide area at a low cost in a standardized way may be possible. In this study, we aimed to identify marine debris on beaches through deep learning using high-resolution UAV images by conducting a survey on Narugashima Island in the Seto Inland Sea of Japan. The flight altitude relative to the ground was set to 5 m, and images of a 0.81-ha area were obtained. Flight was conducted twice: before and after the beach cleaning. The combination of UAVs equipped with a zoom lens and operation at a low altitude allows for the acquisition of high resolution images of 1.1 mm/pixel. The training dataset (2970 images) was annotated by using VoTT, categorizing them into two classes: 'anthropogenic marine debris' and 'natural objects.' Using RetinaNet, marine debris was identified with an average sensitivity of 51% and a precision of 76%. In addition, the abundance and area of marine debris coverage were estimated. In this study, it was revealed that the combination of UAVs and deep learning enables the effective identification of marine debris. The effects of cleanup activities by citizens were able to be quantified. This method can widely be used to evaluate the effectiveness of citizen efforts toward beach cleaning and low-cost long-term monitoring

Multi-state interferometric measurement of nonlinear AC Stark shift

We demonstrate measurement of quadratic AC Stark shifts between Zeeman sublevels in an $^{87}$Rb Bose--Einstein condensate using a multi-state atomic interferometer. The interferometer can detect a quadratic shift without being affected by relatively large state-independent shifts, thereby improving the measurement precision. We measure quadratic shifts in the total spin $F = 2$ state due to the light being near-resonant to the D$_1$ line. The agreement between the measured and theoretical detuning dependences of the quadratic shifts confirms the validity of the measurement. We also present results on the suppression of nonlinear spin evolution using near-resonant dual-color light pulses with opposite quadratic shifts.Comment: 7 pages, 6 figure

Do Kepler superflare stars really include slowly-rotating Sun-like stars ? - Results using APO 3.5m telescope spectroscopic observations and Gaia-DR2 data -

We report the latest view of Kepler solar-type (G-type main-sequence) superflare stars, including recent updates with Apache Point Observatory (APO) 3.5m telescope spectroscopic observations and Gaia-DR2 data. First, we newly conducted APO3.5m spectroscopic observations of 18 superflare stars found from Kepler 1-min time cadence data. More than half (43 stars) are confirmed to be "single" stars, among 64 superflare stars in total that have been spectroscopically investigated so far in this APO3.5m and our previous Subaru/HDS observations. The measurements of $v\sin i$ (projected rotational velocity) and chromospheric lines (Ca II H\&K and Ca II 8542\AA) support the brightness variation of superflare stars is caused by the rotation of a star with large starspots. We then investigated the statistical properties of Kepler solar-type superflare stars by incorporating Gaia-DR2 stellar radius estimates. As a result, the maximum superflare energy continuously decreases as the rotation period $P_{\mathrm{rot}}$ increases. Superflares with energies $\lesssim 5\times10^{34}$ erg occur on old, slowly-rotating Sun-like stars ($P_{\mathrm{rot}}\sim$25 days) approximately once every 2000--3000 years, while young rapidly-rotating stars with $P_{\mathrm{rot}}\sim$ a few days have superflares up to $10^{36}$ erg. The maximum starspot area does not depend on the rotation period when the star is young, but as the rotation slows down, it starts to steeply decrease at $P_{\mathrm{rot}}\gtrsim$12 days for Sun-like stars. These two decreasing trends are consistent since the magnetic energy stored around starspots explains the flare energy, but other factors like spot magnetic structure should also be considered.Comment: 71 pages, 31 figures, 10 tables. Accepted for publication in The Astrophysical Journal (on March 29, 2019