arXiv subjects

Duncan J. Watts

Publications and source records attributed to Duncan J. Watts.

53 records · Page 3Linked to original sources

arXiv2020

Empirica: a virtual lab for high-throughput macro-level experiments

Virtual labs allow researchers to design high-throughput and macro-level experiments that are not feasible in traditional in-person physical lab settings. Despite the increasing popularity of online research, researchers still face many technical and logistical barriers when designing and deploying virtual lab experiments. While several platforms exist to facilitate the development of virtual lab experiments, they typically present researchers with a stark trade-off between usability and functionality. We introduce Empirica: a modular virtual lab that offers a solution to the usability-functionality trade-off by employing a "flexible defaults" design strategy. This strategy enables us to maintain complete "build anything" flexibility while offering a development platform that is accessible to novice programmers. Empirica's architecture is designed to allow for parameterizable experimental designs, reusable protocols, and rapid development. These features will increase the accessibility of virtual lab experiments, remove barriers to innovation in experiment design, and enable rapid progress in the understanding of distributed human computation.

cs.HC↗

arXiv2020

Control and systems software for the Cosmology Large Angular Scale Surveyor (CLASS)

The Cosmology Large Angular Scale Surveyor (CLASS) is an array of polarization-sensitive millimeter wave telescopes that observes ~70% of the sky at frequency bands centered near 40GHz, 90GHz, 150GHz, and 220GHz from the Atacama desert of northern Chile. Here, we describe the architecture of the software used to control the telescopes, acquire data from the various instruments, schedule observations, monitor the status of the instruments and observations, create archival data packages, and transfer data packages to North America for analysis. The computer and network architecture of the CLASS observing site is also briefly discussed. This software and architecture has been in use since 2016, operating the telescopes day and night throughout the year, and has proven successful in fulfilling its design goals.

astro-ph.IM↗

arXiv2020

Two-year Cosmology Large Angular Scale Surveyor (CLASS) Observations: 40 GHz Telescope Pointing, Beam Profile, Window Function, and Polarization Performance

The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background (CMB) over 75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. CLASS measures the large angular scale ($1^\circ\lesssimθ\leqslant 90^\circ$) CMB polarization to constrain the tensor-to-scalar ratio at the $r\sim0.01$ level and the optical depth to last scattering to the sample variance limit. This paper presents the optical characterization of the 40 GHz telescope during its first observation era, from 2016 September to 2018 February. High signal-to-noise observations of the Moon establish the pointing and beam calibration. The telescope boresight pointing variation is $<0.023^\circ$ ($<1.6$% of the beam's full width at half maximum (FWHM)). We estimate beam parameters per detector and in aggregate, as in the CMB survey maps. The aggregate beam has an FWHM of $1.579^\circ\pm.001^\circ$ and a solid angle of $838 \pm 6\ μ{\rm sr}$, consistent with physical optics simulations. The corresponding beam window function has a sub-percent error per multipole at $\ell < 200$. An extended $90^\circ$ beam map reveals no significant far sidelobes. The observed Moon polarization shows that the instrument polarization angles are consistent with the optical model and that the temperature-to-polarization leakage fraction is $<10^{-4}$ (95% C.L.). We find that the Moon-based results are consistent with measurements of M42, RCW 38, and Tau A from CLASS's CMB survey data. In particular, Tau A measurements establish degree-level precision for instrument polarization angles.

astro-ph.IM↗

arXiv2020

Two-year Cosmology Large Angular Scale Surveyor (CLASS) Observations: A First Detection of Atmospheric Circular Polarization at Q Band

The Earth's magnetic field induces Zeeman splitting of the magnetic dipole transitions of molecular oxygen in the atmosphere, which produces polarized emission in the millimeter-wave regime. This polarized emission is primarily circularly polarized and manifests as a foreground with a dipole-shaped sky pattern for polarization-sensitive ground-based cosmic microwave background experiments, such as the Cosmology Large Angular Scale Surveyor (CLASS), which is capable of measuring large angular scale circular polarization. Using atmospheric emission theory and radiative transfer formalisms, we model the expected amplitude and spatial distribution of this signal and evaluate the model for the CLASS observing site in the Atacama Desert of northern Chile. Then, using two years of observations at 32.3 GHz to 43.7 GHz from the CLASS Q-band telescope, we present a detection of this signal and compare the observed signal to that predicted by the model. We recover an angle between magnetic north and true north of $(-5.5 \pm 0.6)^\circ$, which is consistent with the expectation of $-5.9^\circ$ for the CLASS observing site. When comparing dipole sky patterns fit to both simulated and data-derived sky maps, the dipole directions match to within a degree, and the measured amplitudes match to within ${\sim}20\%$.

astro-ph.IM↗

arXiv2019

Two-year Cosmology Large Angular Scale Surveyor (CLASS) Observations: A Measurement of Circular Polarization at 40 GHz

We report circular polarization measurements from the first two years of observation with the 40 GHz polarimeter of the Cosmology Large Angular Scale Surveyor (CLASS). CLASS is conducting a multi-frequency survey covering 75% of the sky from the Atacama Desert designed to measure the cosmic microwave background (CMB) linear E and B polarization on angular scales $1^\circ \lesssim θ\leq 90^\circ$, corresponding to a multipole range of $2 \leq \ell \lesssim 200$. The modulation technology enabling measurements of linear polarization at the largest angular scales from the ground, the Variable-delay Polarization Modulator, is uniquely designed to provide explicit sensitivity to circular polarization (Stokes $V$). We present a first detection of circularly polarized atmospheric emission at 40 GHz that is well described by a dipole with an amplitude of $124\pm4\,\mathrm{μK}$ when observed at an elevation of $45^\circ$, and discuss its potential impact as a foreground to CMB experiments. Filtering the atmospheric component, CLASS places a 95% C.L. upper limit of $0.4\,\mathrm{μK}^2$ to $13.5\,\mathrm{μK}^2$ on $\ell(\ell+1)C_\ell^{VV}/(2π)$ between $1 \leq \ell \leq 120$, representing a two-orders-of-magnitude improvement over previous limits.

astro-ph.CO↗

arXiv2019

Mid-Infrared Spectroscopic Evidence for AGN Heating Warm Molecular Gas

We analyse 2,015 mid-infrared (MIR) spectra of galaxies observed with Spitzer's Infrared Spectrograph, including objects with growing super-massive black holes and objects where most of the infrared emission originates from newly formed stars. We determine if and how accreting super-massive black holes at the centre of galaxies -- known as active galactic nuclei (AGN) -- heat and ionize their host galaxies' dust and molecular gas. We use four MIR diagnostics to estimate the contribution of the AGN to the total MIR emission. We refer to galaxies whose AGN contribute more than 50 per cent of the total MIR emission as AGN-dominated. We compare the relative strengths of PAH emission features and find that PAH grains in AGN-dominated sources have a wider range of sizes and fractional ionizations than PAH grains in non-AGN dominated sources. We measure rotational transitions of H_2 and estimate H_2 excitation temperatures and masses for individual targets, H_2 excitation temperatures for spectra stacked by their AGN contribution to the MIR, and the H_2 excitation temperature distributions via a hierarchical Bayesian model. We find an average 200 K difference between the excitation temperatures of the H_2 S(5) and H_2 S(7) pure rotational molecular hydrogen transition pair in AGN-dominated versus non-AGN dominated galaxies. Our findings suggest that AGN impact the interstellar medium of their host galaxies.

astro-ph.GA↗

arXiv2019

On-sky performance of the CLASS Q-band telescope

The Cosmology Large Angular Scale Surveyor (CLASS) is mapping the polarization of the Cosmic Microwave Background (CMB) at large angular scales ($2<\ell\lesssim200$) in search of a primordial gravitational wave B-mode signal down to a tensor-to-scalar ratio of $r \approx 0.01$. The same data set will provide a near sample-variance-limited measurement of the optical depth to reionization. Between June 2016 and March 2018, CLASS completed the largest ground-based Q-band CMB survey to date, covering over 31 000~square-degrees (75% of the sky), with an instantaneous array noise-equivalent temperature (NET) sensitivity of $32~μ\mbox{K}_{cmb}\sqrt{\mbox{s}}$. We demonstrate that the detector optical loading ($1.6~\mbox{pW}$) and noise-equivalent power ($19~\mbox{aW}\sqrt{\mbox{s}}$) match the expected noise model dominated by photon bunching noise. We derive a $13.1\pm0.3~\mbox{K/pW}$ calibration to antenna temperature based on Moon observations, which translates to an optical efficiency of $0.48\pm0.04$ and a $27~\mbox{K}$ system noise temperature. Finally, we report a Tau A flux density of $308\pm11~\mbox{Jy}$ at $38.4\pm0.2~\mbox{GHz}$, consistent with the WMAP Tau A time-dependent spectral flux density model.

astro-ph.IM↗

arXiv2018

A Projected Estimate of the Reionization Optical Depth Using the CLASS Experiment's Sample-Variance Limited E-Mode Measurement

We analyze simulated maps of the Cosmology Large Angular Scale Surveyor (CLASS) experiment and recover a nearly cosmic-variance limited estimate of the reionization optical depth $τ$. We use a power spectrum-based likelihood to simultaneously clean foregrounds and estimate cosmological parameters in multipole space. Using software specifically designed to constrain $τ$, the amplitude of scalar fluctuations $A_s$, and the tensor-to-scalar ratio $r$, we demonstrate that the CLASS experiment will be able to estimate $τ$ within a factor of two of the full-sky cosmic variance limit allowed by cosmic microwave background polarization measurements. Additionally, we discuss the role of CLASS's $τ$ constraint in conjunction with gravitational lensing of the CMB on obtaining a $\gtrsim4σ$ measurement of the sum of the neutrino masses.

astro-ph.CO↗

arXiv2018

Split-door criterion: Identification of causal effects through auxiliary outcomes

We present a method for estimating causal effects in time series data when fine-grained information about the outcome of interest is available. Specifically, we examine what we call the split-door setting, where the outcome variable can be split into two parts: one that is potentially affected by the cause being studied and another that is independent of it, with both parts sharing the same (unobserved) confounders. We show that under these conditions, the problem of identification reduces to that of testing for independence among observed variables, and present a method that uses this approach to automatically find subsets of the data that are causally identified. We demonstrate the method by estimating the causal impact of Amazon's recommender system on traffic to product pages, finding thousands of examples within the dataset that satisfy the split-door criterion. Unlike past studies based on natural experiments that were limited to a single product category, our method applies to a large and representative sample of products viewed on the site. In line with previous work, we find that the widely-used click-through rate (CTR) metric overestimates the causal impact of recommender systems; depending on the product category, we estimate that 50-80\% of the traffic attributed to recommender systems would have happened even without any recommendations. We conclude with guidelines for using the split-door criterion as well as a discussion of other contexts where the method can be applied.

stat.ME↗

arXiv2017

A generalized model of social and biological contagion

We present a model of contagion that unifies and generalizes existing models of the spread of social influences and micro-organismal infections. Our model incorporates individual memory of exposure to a contagious entity (e.g., a rumor or disease), variable magnitudes of exposure (dose sizes), and heterogeneity in the susceptibility of individuals. Through analysis and simulation, we examine in detail the case where individuals may recover from an infection and then immediately become susceptible again (analogous to the so-called SIS model). We identify three basic classes of contagion models which we call \textit{epidemic threshold}, \textit{vanishing critical mass}, and \textit{critical mass} classes, where each class of models corresponds to different strategies for prevention or facilitation. We find that the conditions for a particular contagion model to belong to one of the these three classes depend only on memory length and the probabilities of being infected by one and two exposures respectively. These parameters are in principle measurable for real contagious influences or entities, thus yielding empirical implications for our model. We also study the case where individuals attain permanent immunity once recovered, finding that epidemics inevitably die out but may be surprisingly persistent when individuals possess memory.

physics.soc-ph↗

arXiv2016

Robust Likelihoods for Inflationary Gravitational Waves from Maps of Cosmic Microwave Background Polarization

The B-mode polarization of the cosmic microwave background (CMB) provides a unique window into tensor perturbations from inflationary gravitational waves. Survey effects complicate the estimation and description of the power spectrum on the largest angular scales. The pixel-space likelihood yields parameter distributions without the power spectrum as an intermediate step, but it does not have the large suite of tests available to power spectral methods. Searches for primordial B-modes must rigorously reject and rule out contamination. Many forms of contamination vary or are uncorrelated across epochs, frequencies, surveys, or other data treatment subsets. The cross power and the power spectrum of the difference of subset maps provide approaches to reject and isolate excess variance. We develop an analogous joint pixel-space likelihood. Contamination not modeled in the likelihood produces parameter-dependent bias and complicates the interpretation of the difference map. We describe a null test that consistently weights the difference map. Excess variance should either be explicitly modeled in the covariance or be removed through reprocessing the data.

astro-ph.CO↗

arXiv2016

Exploring limits to prediction in complex social systems

How predictable is success in complex social systems? In spite of a recent profusion of prediction studies that exploit online social and information network data, this question remains unanswered, in part because it has not been adequately specified. In this paper we attempt to clarify the question by presenting a simple stylized model of success that attributes prediction error to one of two generic sources: insufficiency of available data and/or models on the one hand; and inherent unpredictability of complex social systems on the other. We then use this model to motivate an illustrative empirical study of information cascade size prediction on Twitter. Despite an unprecedented volume of information about users, content, and past performance, our best performing models can explain less than half of the variance in cascade sizes. In turn, this result suggests that even with unlimited data predictive performance would be bounded well below deterministic accuracy. Finally, we explore this potential bound theoretically using simulations of a diffusion process on a random scale free network similar to Twitter. We show that although higher predictive power is possible in theory, such performance requires a homogeneous system and perfect ex-ante knowledge of it: even a small degree of uncertainty in estimating product quality or slight variation in quality across products leads to substantially more restrictive bounds on predictability. We conclude that realistic bounds on predictive accuracy are not dissimilar from those we have obtained empirically, and that such bounds for other complex social systems for which data is more difficult to obtain are likely even lower.

cs.SI↗

arXiv2015

Measuring the Largest Angular Scale CMB B-mode Polarization with Galactic Foregrounds on a Cut Sky

We consider the effectiveness of foreground cleaning in the recovery of Cosmic Microwave Background (CMB) polarization sourced by gravitational waves for tensor-to-scalar ratios in the range $0<r<0.1$. Using the planned survey area, frequency bands, and sensitivity of the Cosmology Large Angular Scale Surveyor (CLASS), we simulate maps of Stokes $Q$ and $U$ parameters at 40, 90, 150, and 220 GHz, including realistic models of the CMB, diffuse Galactic thermal dust and synchrotron foregrounds, and Gaussian white noise. We use linear combinations (LCs) of the simulated multifrequency data to obtain maximum likelihood estimates of $r$, the relative scalar amplitude $s$, and LC coefficients. We find that for 10,000 simulations of a CLASS-like experiment using only measurements of the reionization peak ($\ell\leq23$), there is a 95% C.L. upper limit of $r<0.017$ in the case of no primordial gravitational waves. For simulations with $r=0.01$, we recover at 68% C.L. $r=0.012^{+0.011}_{-0.006}$. The reionization peak corresponds to a fraction of the multipole moments probed by CLASS, and simulations including $30\leq\ell\leq100$ further improve our upper limits to $r<0.008$ at 95% C.L. ($r=0.01^{+0.004}_{-0.004}$ for primordial gravitational waves with $r=0.01$). In addition to decreasing the current upper bound on $r$ by an order of magnitude, these foreground-cleaned low multipole data will achieve a cosmic variance limited measurement of the E-mode polarization's reionization peak.

astro-ph.CO↗

arXiv2015

Estimating the Causal Impact of Recommendation Systems from Observational Data

Recommendation systems are an increasingly prominent part of the web, accounting for up to a third of all traffic on several of the world's most popular sites. Nevertheless, little is known about how much activity such systems actually cause over and above activity that would have occurred via other means (e.g., search) if recommendations were absent. Although the ideal way to estimate the causal impact of recommendations is via randomized experiments, such experiments are costly and may inconvenience users. In this paper, therefore, we present a method for estimating causal effects from purely observational data. Specifically, we show that causal identification through an instrumental variable is possible when a product experiences an instantaneous shock in direct traffic and the products recommended next to it do not. We then apply our method to browsing logs containing anonymized activity for 2.1 million users on Amazon.com over a 9 month period and analyze over 4,000 unique products that experience such shocks. We find that although recommendation click-throughs do account for a large fraction of traffic among these products, at least 75% of this activity would likely occur in the absence of recommendations. We conclude with a discussion about the assumptions under which the method is appropriate and caveats around extrapolating results to other products, sites, or settings.

cs.SI↗

arXiv2014

Inside Money, Procyclical Leverage, and Banking Catastrophes

We explore a model of the interaction between banks and outside investors in which the ability of banks to issue inside money (short-term liabilities believed to be convertible into currency at par) can generate a collapse in asset prices and widespread bank insolvency. The banks and investors share a common belief about the future value of certain long-term assets, but they have different objective functions; changes to this common belief result in portfolio adjustments and trade. Positive belief shocks induce banks to buy risky assets from investors, and the banks finance those purchases by issuing new short-term liabilities. Negative belief shocks induce banks to sell assets in order to reduce their chance of insolvency to a tolerably low level, and they supply more assets at lower prices, which can result in multiple market-clearing prices. A sufficiently severe negative shock causes the set of equilibrium prices to contract (in a manner given by a cusp catastrophe), causing prices to plummet discontinuously and banks to become insolvent. Successive positive and negative shocks of equal magnitude do not cancel; rather, a banking catastrophe can occur even if beliefs simply return to their initial state. Capital requirements can prevent crises by curtailing the expansion of balance sheets when beliefs become more optimistic, but they can also force larger price declines. Emergency asset price supports can be understood as attempts by a central bank to coordinate expectations on an equilibrium with solvency.

q-fin.PR↗

arXiv2011

Cooperation and Contagion in Web-Based, Networked Public Goods Experiments

A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of web-based experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. This result implies either that individuals are not conditional cooperators, or else that cooperation does not benefit from positive reinforcement between connected neighbors. We then tested both of these possibilities in two subsequent series of experiments in which artificial seed players were introduced, making either full or zero contributions. First, we found that although players did generally behave like conditional cooperators, they were as likely to decrease their contributions in response to low contributing neighbors as they were to increase their contributions in response to high contributing neighbors. Second, we found that positive effects of cooperation were contagious only to direct neighbors in the network. In total we report on 113 human subjects experiments, highlighting the speed, flexibility, and cost-effectiveness of web-based experiments over those conducted in physical labs.

cs.GT↗

arXiv2009

Characterizing Individual Communication Patterns

The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for characterizing individual behavior and, by extension, identifying latent structure in human populations. Here, we propose a model of individual e-mail communication that is sufficiently rich to capture meaningful variability across individuals, while remaining simple enough to be interpretable. We show that the model, a cascading non-homogeneous Poisson process, can be formulated as a double-chain hidden Markov model, allowing us to use an efficient inference algorithm to estimate the model parameters from observed data. We then apply this model to two e-mail data sets consisting of 404 and 6,164 users, respectively, that were collected from two universities in different countries and years. We find that the resulting best-estimate parameter distributions for both data sets are surprisingly similar, indicating that at least some features of communication dynamics generalize beyond specific contexts. We also find that variability of individual behavior over time is significantly less than variability across the population, suggesting that individuals can be classified into persistent "types". We conclude that communication patterns may prove useful as an additional class of attribute data, complementing demographic and network data, for user classification and outlier detection--a point that we illustrate with an interpretable clustering of users based on their inferred model parameters.

physics.soc-ph↗