S-matrix approach to quantum gases in the unitary limit II: the three-dimensional case

A new analytic treatment of three-dimensional homogeneous Bose and Fermi gases in the unitary limit of negative infinite scattering length is presented, based on the S-matrix approach to statistical mechanics we recently developed. The unitary limit occurs at a fixed point of the renormalization group with dynamical exponent z=2 where the S-matrix equals -1. For fermions we find T_c /T_F is approximately 0.1. For bosons we present evidence that the gas does not collapse, but rather has a critical point that is a strongly interacting form of Bose-Einstein condensation. This bosonic critical point occurs at n lambda^3 approximately 1.3 where n is the density and lambda the thermal wavelength, which is lower than the ideal gas value of 2.61.Comment: 26 pages, 16 figure

Virial expansion coefficients in the harmonic approximation

The virial expansion method is applied within a harmonic approximation to an interacting N-body system of identical fermions. We compute the canonical partition functions for two and three particles to get the two lowest orders in the expansion. The energy spectrum is carefully interpolated to reproduce ground state properties at low temperature and the non-interacting large temperature limit of constant virial coefficients. This resembles the smearing of shell effects in finite systems with increasing temperature. Numerical results are discussed for the second and third virial coefficients as function of dimension, temperature, interaction, and the transition temperature between low and high energy limits.Comment: 11 pages, 7 figures, published versio

In vitro bioactivities and phytochemicals content of vegetables from Sabah, Malaysia

This study aims to investigate potential of vegetables from Sabah with value-added benefits in nutraceuticals. Fifty-five samples of vegetables were collected from local market and tested for antioxidant activity using DPPH• assay. Four species with high DPPH• scavenging activity (>80%) which are Cosmos caudatus, Eryngium foetidum, Ipomoea batatas and Manihot esculenta Crantz were selected and subjected to different solvents extraction and tested to different scavenging assays (DPPH•, O2• and NO•), protein kinase phosphatase assay (GSK-3β, MKK1, and MSG5) and antibacterial tests. Ethanol extract of I. batatas (90.56%), boiled water extract of M. esculenta Crantz (62.77%) and extractable polyphenol extract of E. foetidum (50.93%) exhibits comparable scavenging activities to catechin for DPPH•, O2• and NO•, respectively. Polyphenols, phenolic acids, flavonoids and proanthocynidins are detected in all extracts at concentration between 0.001 mg/g to 0.52 mg/g. The highest total polyphenols content (0.40±0.01 mg GAE/g), total phenolics content (0.52±0.01 mg GAE/g), total flavonoids content (0.13±0.01 mg CE/g) and total proanthocyanidins content (0.12±0 mg CE/g) were obtained in extractable polyphenols of Cosmos caudatus. No extracts were observed as inhibitor for GSK-3β, MKK1 and MSG5. Inhibition of Pseudomonas aeruginosa (8.0 mm to 12.3 mm) was only obtained in extractable polyphenols and ethanol extracts. Extractable polyphenols of E. foetidum exhibit the largest inhibition of Pseudomonas aeruginosa (12.3 mm)

A GCSS model intercomparison for a tropical squall line observed during toga-coare. II: Intercomparison of single-column models and a cloud-resolving model

This paper presents single-column model (SCM) simulations of a tropical squall-line case observed during the Coupled Ocean-Atmosphere Response Experiment of the Tropical Ocean/Global Atmosphere Programme. This case-study was part of an international model intercomparison project organized by Working Group 4 ‘Precipitating Convective Cloud Systems’ of the GEWEX (Global Energy and Water-cycle Experiment) Cloud System Study. Eight SCM groups using different deep-convection parametrizations participated in this project. The SCMs were forced by temperature and moisture tendencies that had been computed from a reference cloud-resolving model (CRM) simulation using open boundary conditions. The comparison of the SCM results with the reference CRM simulation provided insight into the ability of current convection and cloud schemes to represent organized convection. The CRM results enabled a detailed evaluation of the SCMs in terms of the thermodynamic structure and the convective mass flux of the system, the latter being closely related to the surface convective precipitation. It is shown that the SCMs could reproduce reasonably well the time evolution of the surface convective and stratiform precipitation, the convective mass flux, and the thermodynamic structure of the squall-line system. The thermodynamic structure simulated by the SCMs depended on how the models partitioned the precipitation between convective and stratiform. However, structural differences persisted in the thermodynamic profiles simulated by the SCMs and the CRM. These differences could be attributed to the fact that the total mass flux used to compute the SCM forcing differed from the convective mass flux. The SCMs could not adequately represent these organized mesoscale circulations and the microphysicallradiative forcing associated with the stratiform region. This issue is generally known as the ‘scale-interaction’ problem that can only be properly addressed in fully three-dimensional simulations. Sensitivity simulations run by several groups showed that the time evolution of the surface convective precipitation was considerably smoothed when the convective closure was based on convective available potential energy instead of moisture convergence. Finally, additional SCM simulations without using a convection parametrization indicated that the impact of a convection parametrization in forced SCM runs was more visible in the moisture profiles than in the temperature profiles because convective transport was particularly important in the moisture budget

Core Formation, Coherence and Collapse: A New Core Evolution Paradigm Revealed by Machine Learning

We study the formation, evolution and collapse of dense cores by tracking density structures in a magnetohydrodynamic (MHD) simulation. We identify cores using the dendrogram algorithm and utilize machine learning techniques, including principal component analysis (PCA) and the k-means clustering algorithm to analyze the full density and velocity dispersion profiles of these cores. We find that there exists an evolutionary sequence consisting of three distinct phases: i) the formation of turbulent density structures (Phase I), ii) the dissipation of turbulence and the formation of coherent cores (Phase II), and iii) the transition to protostellar cores through gravitational collapse (Phase III). In dynamically evolving molecular clouds, the existence of these three phases corresponds to the coexistence of three populations of cores with distinct physical properties. The prestellar and protostellar cores frequently analyzed in previous studies of observations and simulations belong to the last phase in this evolutionary picture. We derive typical lifetimes of 1.4$\pm$1.0$\times$10$^5$ yr, 3.3$\pm$1.4$\times$10$^5$ yr and 3.3$\pm$1.4$\times$10$^5$ yr, respectively for Phase I, II and III. We find that cores can form from both converging flows and filament fragmentation and that cores may form both inside and outside the filaments. We then compare our results to previous observations of coherent cores and provide suggestions for future observations to study cores belonging to the three phases.Comment: Submitted to Astrophysical Journal in June, 202

Simulation of a Machine Learning Based Controller for a Fixed-Wing UAV with Distributed Sensors

Recent research suggests that the information obtained from arrays of sensors distributed on the wing of a fixed-wing small unmanned aerial vehicle (UAV) can provide information not available to conventional sensor suites. These arrays of sensors are capable of sensing the flow around the aircraft and it has been indicated that they could be a potential tool to improve flight control and overall flight performance. However, more work needs to be carried out to fully exploit the potential of these sensors for flight control. This work presents a 3 degrees-of-freedom longitudinal flight dynamics and control simulation model of a small fixed-wing UAV. Experimental readings of an array of pressure and strain sensors distributed across the wing were integrated in the model. This study investigated the feasibility of using machine learning to control airspeed of the UAV using the readings from the sensing array, and looked into the sensor layout and its effect on the performance of the controller. It was found that an artificial neural network was able to learn to mimic a conventional airspeed controller using only distributed sensor signals, but showed better performance for controlling changes in airspeed for a constant altitude than holding airspeed during changes in altitude. The neural network could control airspeed using either pressure or strain sensor information, but having both improved robustness to increased levels of turbulence. Results showed that some strain sensors and many pressure sensors signals were not necessary to achieve good controller performance, but that the pressure sensors near the leading edge of the wing were required. Future work will focus on replacing other elements of the flight control system with machine learning elements and investigate the use of reinforcement learning in place of supervised learning.</p

The Green Bank Ammonia Survey (GAS): First Results of NH3 mapping the Gould Belt

We present an overview of the first data release (DR1) and first-look science from the Green Bank Ammonia Survey (GAS). GAS is a Large Program at the Green Bank Telescope to map all Gould Belt star-forming regions with $A_V \gtrsim 7$ mag visible from the northern hemisphere in emission from NH$_3$ and other key molecular tracers. This first release includes the data for four regions in Gould Belt clouds: B18 in Taurus, NGC 1333 in Perseus, L1688 in Ophiuchus, and Orion A North in Orion. We compare the NH$_3$ emission to dust continuum emission from Herschel, and find that the two tracers correspond closely. NH$_3$ is present in over 60\% of lines-of-sight with $A_V \gtrsim 7$ mag in three of the four DR1 regions, in agreement with expectations from previous observations. The sole exception is B18, where NH$_3$ is detected toward ~ 40\% of lines-of-sight with $A_V \gtrsim 7$ mag. Moreover, we find that the NH$_3$ emission is generally extended beyond the typical 0.1 pc length scales of dense cores. We produce maps of the gas kinematics, temperature, and NH$_3$ column densities through forward modeling of the hyperfine structure of the NH$_3$ (1,1) and (2,2) lines. We show that the NH$_3$ velocity dispersion, ${\sigma}_v$, and gas kinetic temperature, $T_K$, vary systematically between the regions included in this release, with an increase in both the mean value and spread of ${\sigma}_v$ and $T_K$ with increasing star formation activity. The data presented in this paper are publicly available.Comment: 33 pages, 27 figures, accepted to ApJS. Datasets are publicly available: https://dataverse.harvard.edu/dataverse/GAS_DR