PhasePack: A Phase Retrieval Library

Phase retrieval deals with the estimation of complex-valued signals solely from the magnitudes of linear measurements. While there has been a recent explosion in the development of phase retrieval algorithms, the lack of a common interface has made it difficult to compare new methods against the state-of-the-art. The purpose of PhasePack is to create a common software interface for a wide range of phase retrieval algorithms and to provide a common testbed using both synthetic data and empirical imaging datasets. PhasePack is able to benchmark a large number of recent phase retrieval methods against one another to generate comparisons using a range of different performance metrics. The software package handles single method testing as well as multiple method comparisons. The algorithm implementations in PhasePack differ slightly from their original descriptions in the literature in order to achieve faster speed and improved robustness. In particular, PhasePack uses adaptive stepsizes, line-search methods, and fast eigensolvers to speed up and automate convergence

Language-Guided Traffic Simulation via Scene-Level Diffusion

Realistic and controllable traffic simulation is a core capability that is necessary to accelerate autonomous vehicle (AV) development. However, current approaches for controlling learning-based traffic models require significant domain expertise and are difficult for practitioners to use. To remedy this, we present CTG++, a scene-level conditional diffusion model that can be guided by language instructions. Developing this requires tackling two challenges: the need for a realistic and controllable traffic model backbone, and an effective method to interface with a traffic model using language. To address these challenges, we first propose a scene-level diffusion model equipped with a spatio-temporal transformer backbone, which generates realistic and controllable traffic. We then harness a large language model (LLM) to convert a user's query into a loss function, guiding the diffusion model towards query-compliant generation. Through comprehensive evaluation, we demonstrate the effectiveness of our proposed method in generating realistic, query-compliant traffic simulations

Dynamical Controls of the Eastward Transport of Overwintering Calanus finmarchicus From the Lofoten Basin to the Continental Slope

Diapausing populations of Calanus finmarchicus at depth in the Lofoten Basin (LB) return to the continental shelf and slope off the Lofoten-Vesterålen Islands during the phytoplankton spring bloom to feed and spawn, forming surface swarms with a great abundance. To study how overwintering populations of C. finmarchicus move with the deep currents and return to the shelf, Lagrangian transport characteristics of particles in deep water between 2008 and 2019 were analyzed using Global Ocean Reanalysis and Simulation re-analysis data and Lagrangian Coherent Structures (LCSs). Our analyses revealed that persistent eastward transport of diapausing C. finmarchicus between LB and continental slope occurred mainly between 600 and 1,100 m in the Arctic Intermediate Water. The consistency of the vertical distributions of C. finmarchicus abundance and salinity further suggests that physical factors control the horizontal distribution of the species. Hovmöller diagrams of kinetic energy indicate that there is an eastward advection of mean current at depth. The co-occurrence between the eastward transport of LCSs and the eastward advection of the mean current provides direct evidence that the life history of C. finmarchicus is subjected to physical control in the Norwegian Sea

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve