Astronomy
At least one in a dozen stars shows evidence of planetary ingestion
Abstract: The chemical composition of stars can be changed by the ingestion of material from planets and/or the formation of planets, which removes refractory material from the protostellar disk. These "planet signatures" appear as correlations between differences in elemental abundance and the condensation temperature of dust. However, detecting these planet signatures is challenging due to unknown occurrence rates, small amplitudes, and heterogeneous samples of stars with large differences in age. Therefore, stars that are born together (i.e., co-natal) with identical compositions can facilitate the detection of planet signatures. Although previous spectroscopic studies have been limited to a small number of binary stars, the Gaia satellite offers opportunities to detect stellar chemical signatures of planets among pairs of stars confirmed to be co-natal. In this study, we report high-precision chemical abundances for a uniform sample of ninety-one co-natal pairs of stars with a well-defined selection function and identify at least seven instances of planetary ingestion, corresponding to an occurrence rate of eight percent. We deploy an independent Bayesian indicator, which can effectively separate planet signatures from other factors such as random abundance variation and atomic diffusion. Our study provides evidence of planet signatures and promotes a deeper understanding of the connection between stars, planets, and chemistry by providing observational constraints on the mechanisms of planet engulfment, formation, and evolution. Physics
Penning Micro-trap for Quantum Computing
Authors: Shreyans Jain, Tobias Sägesser, Pavel Hrmo, Celeste Torkzaban, Martin Stadler, Robin Oswald, et al.
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Abstract:
Trapping ions in radio-frequency (RF) traps stands as one of the primary methods for realizing quantum computers, thanks to high-fidelity quantum gates and extended coherence times. Nevertheless, employing RF poses various challenges for scalability, including the necessity for chip compatibility with high voltages, power management, and limitations on ion transport and placement.
The research group has achieved a microfabricated Penning ion trap that overcomes these hurdles by substituting the RF field with a 3T magnetic field. They demonstrate complete quantum control over ions in this configuration, along with the capability to transport ions arbitrarily within the trapping plane above the chip.
This distinctive feature of the Penning micro-trap approach enhances the architecture of quantum charge-coupled devices, improving connectivity and flexibility, thus facilitating the realization of large-scale trapped-ion quantum computing, quantum simulation, and quantum sensing.
Pattern Formation by Turbulent Cascades
Authors: Xander M. de Wit, Michel Fruchart, Tali Khain, Federico Toschi & Vincenzo Vitelli
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Abstract:
Fully developed turbulence represents a universal and scale-invariant chaotic state characterized by energy cascades from large to small scales, with the energy cascades ultimately dissipating.
The research group demonstrates how to utilize these seemingly unstructured turbulent cascades to generate patterns. Pattern formation necessitates a wavelength selection process, typically traceable to linear instabilities of a uniform state. Conversely, the mechanism proposed by the research group is entirely nonlinear. It is triggered by non-dissipative stagnation of turbulent cascades: energy accumulates at intermediate scales, which are neither system scales nor the smallest scales usually subject to energy dissipation. Utilizing a blend of theory and large-scale simulations, our research team demonstrates that the tunable wavelength of these cascading induced patterns can be established through a non-dissipative transport coefficient known as "odd viscosity," prevalent in chiral fluids spanning from bioactive to quantum systems. Odd viscosity acts akin to a scale-dependent Coriolis force, inducing a two-dimensionalization of flow at smaller scales, contrary to rotating fluids where such two-dimensionalization occurs at larger scales. In addition to fluids exhibiting odd viscosity, we explore the occurrence of cascade-induced patterns in natural systems, such as atmospheric flows, stellar plasma like the solar wind, or the fragmentation and consolidation of objects or droplets where mass rather than energy cascades.
Abstract: Fully developed turbulence is a universal and scale-invariant chaotic state characterized by an energy cascade from large to small scales at which the cascade is eventually arrested by dissipation. Here we show how to harness these seemingly structureless turbulent cascades to generate patterns. Pattern formation entails a process of wavelength selection, which can usually be traced to the linear instability of a homogeneous state. By contrast, the mechanism we propose here is fully nonlinear. It is triggered by the non-dissipative arrest of turbulent cascades: energy piles up at an intermediate scale, which is neither the system size nor the smallest scales at which energy is usually dissipated. Using a combination of theory and large-scale simulations, we show that the tunable wavelength of these cascade-induced patterns can be set by a non-dissipative transport coefficient called odd viscosity, ubiquitous in chiral fluids ranging from bioactive to quantum systems. Odd viscosity, which acts as a scale-dependent Coriolis-like force, leads to a two-dimensionalization of the flow at small scales, in contrast with rotating fluids in which a two-dimensionalization occurs at large scales. Apart from odd viscosity fluids, we discuss how cascade-induced patterns can arise in natural systems, including atmospheric flows, stellar plasma such as the solar wind, or the pulverization and coagulation of objects or droplets in which mass rather than energy cascades.
Photonic chip-based low-noise microwave oscillator 基于光子芯片的低噪声微波振荡器 Authors: Igor Kudelin, William Groman, Qing-Xin Ji, Joel Guo, Megan L. Kelleher, Dahyeon Lee, et al. Link: Article Link
Abstract: Many modern technologies rely on microwave signals with low-phase noise and precise timing stability. Significant progress has been made in microwave photonics, where low-noise microwave signals are generated by converting ultrastable optical references using a frequency comb. However, these systems are typically bulky or fiber-based, making it challenging to reduce their size and power consumption further. In this study, we address this challenge by leveraging advancements in integrated photonics to achieve low-noise microwave generation through two-point optical frequency division. We stabilize narrow-linewidth self-injection-locked integrated lasers within a miniature Fabry–Pérot cavity and divide the frequency gap between lasers using an efficient dark soliton frequency comb. The stabilized output of the microcomb is photodetected to produce a 20 GHz microwave signal with phase noise of -96 dBc Hz^(-1) at a 100 Hz offset frequency, decreasing to -135 dBc Hz^(-1) at a 10 kHz offset—values unprecedented for an integrated photonic system. All photonic components can be heterogeneously integrated on a single chip, marking a significant advancement for applying photonics to high-precision navigation, communication, and timing systems.
Field: Chemistry
Title: Oxidative cyclization reagents reveal tryptophan cation–π interactions Selective covalent modification methods for amino acids on proteins have a wide range of applications, from probing and modulating protein function to proteomics. Cysteine and lysine residues, due to their high nucleophilicity, are commonly targeted for protein bioconjugation through acid-base reactivity.
In this study, a redox-based strategy is introduced for the bioconjugation of tryptophan, the rarest amino acid, using oxaziridine reagents. These reagents mimic oxidative cyclization reactions found in indole-based alkaloid biosynthetic pathways, allowing for highly efficient and specific tryptophan labeling.
The method, termed Tryptophan Chemical Ligation by Cyclization (Trp-CLiC), is demonstrated to be broadly applicable for selectively attaching payloads to tryptophan residues on peptides and proteins. The reaction rates are comparable to traditional click reactions, enabling comprehensive profiling of highly reactive tryptophan sites across entire proteomes.
Importantly, these reagents also unveil a systematic map of tryptophan residues involved in cation-π interactions, which include functional sites capable of regulating protein-mediated phase-separation processes.
Abstract: Floods pose significant threats in developing countries where dense streamflow gauge networks are often lacking. Timely and accurate flood warnings are crucial for reducing risks associated with such disasters. However, traditional hydrological simulation models require extensive calibration with long-term data records for each watershed. In this study, we demonstrate the reliability of artificial intelligence-based forecasting in predicting extreme riverine events in ungauged watersheds with up to a five-day lead time. This reliability is comparable to or even better than the nowcasts provided by the current state-of-the-art global modeling system, the Copernicus Emergency Management Service Global Flood Awareness System, which operates with zero-day lead time. Furthermore, our model achieves accuracies for events with return periods of over five years that are similar to or better than those for events with return periods of just one year. This suggests that artificial intelligence can offer earlier flood warnings for larger and more impactful events in ungauged basins. The model developed in this study has been integrated into an operational early warning system that provides real-time forecasts publicly and freely in over 80 countries. This research underscores the importance of enhancing the availability of hydrological data to continually enhance global access to reliable flood warnings.
