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Kriti Mahajan

Publications and source records attributed to Kriti Mahajan.

2 recordsLinked to original sources

A pathway towards decentralized studies of radioactive post-lead elements and their applications in beyond standard model physics

Molecules have proven to be sensitive tools for studying physics beyond the standard model, with heavy and deformed nuclei offering decisive sensitivity to parity- and time-reversal-violating effects. However, almost all elements beyond lead, occupying the 6p~to~5f atomic orbitals, lack stable isotopes, hence molecules containing them are referred to as radioactive molecules. Among those, radium monofluoride has seen particular interest, but to date, research on radioactive molecules has mainly been limited to large-scale nuclear facilities. Here, we present a scheme that allows efficient and fast harvest of radioactive ions (including short-lived Ra), and show ion gas-phase reaction studies of singly and doubly charged Ra, Po, and Pb ions with SF$_6$ gas inside an ion trap. Our results show that the chemical reaction rate of Ra$^+$ is in line with trends of other alkaline earth elements, further support by quantum chemical computations. The reaction Ra$^{2+}$ + SF$_6$ $\rightarrow$ RaF${^+}$ + SF$_5^{+}$ achieves an almost unity conversion efficiency, making it particularly suitable for the application for studies in physics beyond the standard model. The scheme enables future decentralized research avenues with short-lived radioactive molecules for fundamental physics research at laboratories without the need for local nuclear reactors or accelerators.

nucl-ex

FlowDB a large scale precipitation, river, and flash flood dataset

Flooding results in 8 billion dollars of damage annually in the US and causes the most deaths of any weather related event. Due to climate change scientists expect more heavy precipitation events in the future. However, no current datasets exist that contain both hourly precipitation and river flow data. We introduce a novel hourly river flow and precipitation dataset and a second subset of flash flood events with damage estimates and injury counts. Using these datasets we create two challenges (1) general stream flow forecasting and (2) flash flood damage estimation. We have created several publicly available benchmarks and an easy to use package. Additionally, in the future we aim to augment our dataset with snow pack data and soil index moisture data to improve predictions.

cs.AI