Money and Goldstone modes

Why is ``worthless'' fiat money generally accepted as payment for goods and services? In equilibrium theory, the value of money is generally not determined: the number of equations is one less than the number of unknowns, so only relative prices are determined. In the language of mathematics, the equations are ``homogeneous of order one''. Using the language of physics, this represents a continuous ``Goldstone'' symmetry. However, the continuous symmetry is often broken by the dynamics of the system, thus fixing the value of the otherwise undetermined variable. In economics, the value of money is a strategic variable which each agent must determine at each transaction by estimating the effect of future interactions with other agents. This idea is illustrated by a simple network model of monopolistic vendors and buyers, with bounded rationality. We submit that dynamical, spontaneous symmetry breaking is the fundamental principle for fixing the value of money. Perhaps the continuous symmetry representing the lack of restoring force is also the fundamental reason for large fluctuations in stock markets.Comment: 7 pages, 3 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

Polarisation vision: overcoming challenges of working with a property of light we barely see.

In recent years, the study of polarisation vision in animals has seen numerous breakthroughs, not just in terms of what is known about the function of this sensory ability, but also in the experimental methods by which polarisation can be controlled, presented and measured. Once thought to be limited to only a few animal species, polarisation sensitivity is now known to be widespread across many taxonomic groups, and advances in experimental techniques are, in part, responsible for these discoveries. Nevertheless, its study remains challenging, perhaps because of our own poor sensitivity to the polarisation of light, but equally as a result of the slow spread of new practices and methodological innovations within the field. In this review, we introduce the most important steps in designing and calibrating polarised stimuli, within the broader context of areas of current research and the applications of new techniques to key questions. Our aim is to provide a constructive guide to help researchers, particularly those with no background in the physics of polarisation, to design robust experiments that are free from confounding factors

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

Titania-doped tantala/silica coatings for gravitational-wave detection

Reducing thermal noise from optical coatings is crucial to reaching the required sensitivity in next generation interferometric gravitational-wave detectors. Here we show that adding TiO2 to Ta2O5 in Ta2O5/SiO2 coatings reduces the internal friction and in addition present data confirming it reduces thermal noise. We also show that TiO2-doped Ta2O5/SiO2 coatings are close to satisfying the optical absorption requirements of second generation gravitational-wave detectors

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

Droplets I: Pressure-Dominated Sub-0.1 pc Coherent Structures in L1688 and B18

We present the observation and analysis of newly discovered coherent structures in the L1688 region of Ophiuchus and the B18 region of Taurus. Using data from the Green Bank Ammonia Survey (GAS), we identify regions of high density and near-constant, almost-thermal, velocity dispersion. Eighteen coherent structures are revealed, twelve in L1688 and six in B18, each of which shows a sharp "transition to coherence" in velocity dispersion around its periphery. The identification of these structures provides a chance to study the coherent structures in molecular clouds statistically. The identified coherent structures have a typical radius of 0.04 pc and a typical mass of 0.4 Msun, generally smaller than previously known coherent cores identified by Goodman et al. (1998), Caselli et al. (2002), and Pineda et al. (2010). We call these structures "droplets." We find that unlike previously known coherent cores, these structures are not virially bound by self-gravity and are instead predominantly confined by ambient pressure. The droplets have density profiles shallower than a critical Bonnor-Ebert sphere, and they have a velocity (VLSR) distribution consistent with the dense gas motions traced by NH3 emission. These results point to a potential formation mechanism through pressure compression and turbulent processes in the dense gas. We present a comparison with a magnetohydrodynamic simulation of a star-forming region, and we speculate on the relationship of droplets with larger, gravitationally bound coherent cores, as well as on the role that droplets and other coherent structures play in the star formation process.Comment: Accepted by ApJ in April, 201

Women After War: Weaving Nostos in Homeric Epic and in the Twenty-First Century

While women play a circumscribed role in ancient epic, Homer\u27s Odyssey depicts both Helen and Penelope as undergoing their own forms of homecoming, or nostos, after the Trojan War: Helen returns to her husband Menelaus after experiencing the war firsthand at Troy and a ten-year separation; Penelope stays home, but Odysseus\u27 return is in many ways as much a challenge for her as it is for him and the Odyssey portrays her domestic ordeal as a form of heroic nostos. In this essay, I explore female ways of homecoming in the Odyssey and draw connections between Homeric heroines and members of Team Lioness returning home from Afghanistan and Iraq in the twenty-first century. The 2008 documentary Lioness gives voice to some of these women, the country\u27s first generation of female combat veterans, as they struggle to reconcile their experience of war in Iraq with their lives at home. While the ancient Greeks could not have conceived of women experiencing battle in the way the members of Team Lioness did, Helen\u27s and Penelope\u27s marginalized roles in the Odyssey open a window into the contemporary experience of women soldiers and veterans and provide ways of understanding the challenges of the trauma of war and female homecoming in the twenty-first century