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We present the Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM). The LVM is an integral-field spectroscopic survey of the Milky Way, Magellanic Clouds, and of a sample of local volume galaxies, connecting resolved pc-scale individual sources of feedback to kpc-scale ionized interstellar medium (ISM) properties. The 4-year survey covers the southern Milky Way disk at spatial resolutions of 0.05 to 1 pc, the Magellanic Clouds at 10 pc resolution, and nearby large galaxies at larger scales totaling $>4300$ square degrees of sky, and more than 55M spectra. It utilizes a new facility of alt-alt mounted siderostats feeding 16 cm refractive telescopes, lenslet-coupled fiber-optics, and spectrographs covering 3600-9800A at R ~ 4000. The ultra-wide field IFU has a diameter of 0.5 degrees with 1801 hexagonally packed fibers of 35.3 arcsec apertures. The siderostats allow for a completely stationary fiber system, avoiding instability of the line spread function seen in traditional fiber feeds. Scientifically, LVM resolves the regions where energy, momentum, and chemical elements are injected into the ISM at the scale of gas clouds, while simultaneously charting where energy is being dissipated (via cooling, shocks, turbulence, bulk flows, etc.) to global scales. This combined local and global view enables us to constrain physical processes regulating how stellar feedback operates and couples to galactic kinematics and disk-scale structures, such as the bar and spiral arms, as well as gas in- and out-flows., Comment: 29 pages, 12 figures, accepted for publication in The Astronomical Journal

Craters are one of the most prominent features on planetary surfaces, used in applications such as age estimation, hazard detection, and spacecraft navigation. Crater detection is a challenging problem due to various aspects, including complex crater characteristics such as varying sizes and shapes, data resolution, and planetary data types. Similar to other computer vision tasks, deep learning-based approaches have significantly impacted research on crater detection in recent years. This survey aims to assist researchers in this field by examining the development of deep learning-based crater detection algorithms (CDAs). The review includes over 140 research works covering diverse crater detection approaches, including planetary data, craters database, and evaluation metrics. To be specific, we discuss the challenges in crater detection due to the complex properties of the craters and survey the DL-based CDAs by categorizing them into three parts: (a) semantic segmentation-based, (b) object detection-based, and (c) classification-based. Additionally, we have conducted training and testing of all the semantic segmentation-based CDAs on a common dataset to evaluate the effectiveness of each architecture for crater detection and its potential applications. Finally, we have provided recommendations for potential future works.

We present measurements and simulations of semiconductor-superconductor heterostructure devices that are consistent with the observation of topological superconductivity and Majorana zero modes. The devices are fabricated from high-mobility two-dimensional electron gases in which quasi-one-dimensional wires are defined by electrostatic gates. These devices enable measurements of local and non-local transport properties and have been optimized via extensive simulations to ensure robustness against non-uniformity and disorder. Our main result is that several devices, fabricated according to the design's engineering specifications, have passed the topological gap protocol defined in Pikulin et al. [arXiv:2103.12217]. This protocol is a stringent test composed of a sequence of three-terminal local and non-local transport measurements performed while varying the magnetic field, semiconductor electron density, and junction transparencies. Passing the protocol indicates a high probability of detection of a topological phase hosting Majorana zero modes as determined by large-scale disorder simulations. Our experimental results are consistent with a quantum phase transition into a topological superconducting phase that extends over several hundred millitesla in magnetic field and several millivolts in gate voltage, corresponding to approximately one hundred micro-electron-volts in Zeeman energy and chemical potential in the semiconducting wire. These regions feature a closing and re-opening of the bulk gap, with simultaneous zero-bias conductance peaks at both ends of the devices that withstand changes in the junction transparencies. The extracted maximum topological gaps in our devices are 20-60 $\mu$eV. This demonstration is a prerequisite for experiments involving fusion and braiding of Majorana zero modes., Comment: Final version

A novel technique to deposit metals on highly conjugated polyaniline films has been developed. In general, electrodeposition of metals, having low reduction potential, from aqueous solution, is difficult due to disruptive effect of hydrogen which evolves during the process. This difficulty is avoided using conducting polymers films with high surface mass density. The polymer chains of these films possess a high degree of conjugation. Such a polymer produces highly stable polarons and therefore has the ability to perform underpotential deposition. Our method involves reduction of polyaniline film with formic acid followed by dipping the coated electrode in the metal salt solution. Deposition of the metal is monitored by rise in the open circuit potential of the electrode. Deposition of metals with high surface mass density has been achieved. The metal is most likely present in the polymer as a coordination complex with amine nitrogen. Such form of metal is expected to have higher catalytic activity than the zero-valent metal. We have been able to deposit metals such as Mn and Cu. Among these, Mn cannot be deposited on polymer by any other method., Comment: 18 pages, 10 figures

Dispersive sensing is a powerful technique that enables scalable and high-fidelity readout of solid-state quantum bits. In particular, gate-based dispersive sensing has been proposed as the readout mechanism for future topological qubits, which can be measured by single electrons tunneling through zero-energy modes. The development of such a readout requires resolving the coherent charge tunneling amplitude from a quantum dot in a Majorana-zero-mode host system faithfully on short time scales. Here, we demonstrate rapid single-shot detection of a coherent single-electron tunneling amplitude between InAs nanowire quantum dots. We have realized a sensitive dispersive detection circuit by connecting a sub-GHz, lumped element microwave resonator to a high-lever arm gate on one of dots. The resulting large dot-resonator coupling leads to an observed dispersive shift that is of the order of the resonator linewidth at charge degeneracy. This shift enables us to differentiate between Coulomb blockade and resonance, corresponding to the scenarios expected for qubit state readout, with a signal to noise ratio exceeding 2 for an integration time of 1 microsecond. Our result paves the way for single shot measurements of fermion parity on microsecond timescales in topological qubits., Comment: 6 pages, 4 figures