Discourse, justification and critique: towards a legitimate digital copyright regime?

Digitization and the internet have posed an acute economic challenge to rights holders in the cultural industries. Faced with a threat to their form of capital accumulation from copyright infringement, rights holders have used discourse strategically in order to try and legitimate and strengthen their position in the digital copyright debate with governments and media users. In so doing, they have appealed to general justificatory principles – about what is good, right, and just – that provide some scope for opposition and critique, as other groups contest their interpretation of these principles and the evidence used to support them. In this article, we address the relative lack of academic attention paid to the role of discourse in copyright debates by analysing user-directed marketing campaigns and submissions to UK government policy consultations. We show how legitimacy claims are justified and critiqued, and conclude that amid these debates rests some hope of achieving a more legitimate policy resolution to the copyright wars – or at least the possibility of beginning a more constructive dialogue

Toward a More Complex Description of Chemical Profiles in Exoplanet Retrievals: A Two-layer Parameterization

State of the art spectral retrieval models of exoplanet atmospheres assume constant chemical profiles with altitude. This assumption is justified by the information content of current data sets which do not allow, in most cases, for the molecular abundances as a function of pressure to be constrained. In the context of the next generation of telescopes, a more accurate description of chemical profiles may become crucial to interpret observations and gain new insights into atmospheric physics. We explore here the possibility of retrieving pressure-dependent chemical profiles from transit spectra, without injecting any priors from theoretical chemical models in our retrievals. The "two-layer" parameterization presented here allows for the independent extraction of molecular abundances above and below a certain atmospheric pressure. By simulating various cases, we demonstrate that this evolution from constant chemical abundances is justified by the information content of spectra provided by future space instruments. Comparisons with traditional retrieval models show that assumptions made on chemical profiles may significantly impact retrieved parameters, such as the atmospheric temperature, and justify the attention we give here to this issue. We find that the two-layer retrieval accurately captures discontinuities in the vertical chemical profiles, which could be caused by disequilibrium processes—such as photochemistry—or the presence of clouds/hazes. The two-layer retrieval could also help to constrain the composition of clouds and hazes by exploring the correlation between the chemical changes in the gaseous phase and the pressure at which the condensed phase occurs. The two-layer retrieval presented here therefore represents an important step forward in our ability to constrain theoretical chemical models and cloud/haze composition from the analysis of future observations

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

An Exploration of Model Degeneracies with a Unified Phase Curve Retrieval Analysis: The Light and Dark Sides of WASP-43 b

The analysis of exoplanetary atmospheres often relies upon the observation of transit or eclipse events. While very powerful, these snapshots provide mainly one-dimensional information on the planet structure and do not easily allow precise latitude–longitude characterizations. The phase curve technique, which consists of measuring the planet emission throughout its entire orbit, can break this limitation and provide useful two-dimensional thermal and chemical constraints on the atmosphere. As of today, however, computing performances have limited our ability to perform unified retrieval studies on the full set of observed spectra from phase curve observations at the same time. Here, we present a new phase curve model that enables fast, unified retrieval capabilities. We apply our technique to the combined phase curve data from the Hubble and Spitzer space telescopes of the hot Jupiter WASP-43 b. We tested different scenarios and discussed the dependence of our solution on different assumptions in the model. Our more comprehensive approach suggests that multiple interpretations of this data set are possible, but our more complex model is consistent with the presence of thermal inversions and a metal-rich atmosphere, contrasting with previous data analyses, although this likely depends on the Spitzer data reduction. The detailed constraints extracted here demonstrate the importance of developing and understanding advanced phase curve techniques, which we believe will unlock access to a richer picture of exoplanet atmospheres

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Observation of the Ωc0\Omega_{c}^{0} Charmed Baryon at CLEO

The CLEO experiment at the CESR collider has used 13.7 fb$^{-1}$ of data to search for the production of the $\Omega_c^0$ (css-ground state) in $e^{+}e^{-}$ collisions at $\sqrt{s} \simeq 10.6$ {\rm GeV}. The modes used to study the $\Omega_c^0$ are $\Omega^- \pi^+$, $\Omega^- \pi^+ \pi^0$, $\Xi^- K^- pi^+ \pi^+$, $\Xi^0 K^- pi^+$, and $\Omega^- \pi^+ \pi^- \pi^+$. We observe a signal of 40.4$\pm$9.0(stat) events at a mass of 2694.6$\pm$2.6(stat)$\pm$1.9(syst) {\rm MeV/$c^2$}, for all modes combined.Comment: 10 pages postscript, also available through http://w4.lns.cornell.edu/public/CLN

Measurement of the Relative Branching Fraction of Υ(4S)\Upsilon(4S) to Charged and Neutral B-Meson Pairs

We analyze 9.7 x 10^6 B\bar{B}$ pairs recorded with the CLEO detector to determine the production ratio of charged to neutral B-meson pairs produced at the Y(4S) resonance. We measure the rates for B^0 -> J/psi K^{(*)0} and B^+ -> J/psi K^{(*)+} decays and use the world-average B-meson lifetime ratio to extract the relative widths f+-/f00 = Gamma(Y(4S) -> B+B-)/Gamma(Y(4S) -> B0\bar{B0}) = = 1.04 +/- 0.07(stat) +/- 0.04(syst). With the assumption that f+- + f00 = 1, we obtain f00 = 0.49 +/- 0.02(stat) +/- 0.01(syst) and f+- = 0.51 +/- 0.02(stat) +/- 0.01(syst). This production ratio and its uncertainty apply to all exclusive B-meson branching fractions measured at the Y(4S) resonance.Comment: 11 pages postscript, also available through http://w4.lns.cornell.edu/public/CLN

Disentangling atmospheric compositions of K2-18 b with next generation facilities

Recent analysis of the planet K2-18 b has shown the presence of water vapour in its atmosphere. While the H_{2}O detection is significant, the Hubble Space Telescope (HST) WFC3 spectrum suggests three possible solutions of very different nature which can equally match the data. The three solutions are a primary cloudy atmosphere with traces of water vapour (cloudy sub-Neptune), a secondary atmosphere with a substantial amount (up to 50% Volume Mixing Ratio) of H_{2}O (icy/water world) and/or an undetectable gas such as N2 (super-Earth). Additionally, the atmospheric pressure and the possible presence of a liquid/solid surface cannot be investigated with currently available observations. In this paper we used the best fit parameters from Tsiaras et al. (Nat. Astron. 3, 1086, 2019) to build James Webb Space Telescope (JWST) and Ariel simulations of the three scenarios. We have investigated 18 retrieval cases, which encompass the three scenarios and different observational strategies with the two observatories. Retrieval results show that twenty combined transits should be enough for the Ariel mission to disentangle the three scenarios, while JWST would require only two transits if combining NIRISS and NIRSpec data. This makes K2-18 b an ideal target for atmospheric follow-ups by both facilities and highlights the capabilities of the next generation of space-based infrared observatories to provide a complete picture of low mass planets

Peeking inside the Black Box: Interpreting Deep-learning Models for Exoplanet Atmospheric Retrievals

Deep-learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly nonlinear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast retrievals of atmospheric parameters with the use of machine-learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being "black boxes." It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong, and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us–among other things–of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that, for different molecules, the wavelength ranges to which the DNNs predictions are most sensitive do indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions

Peeking inside the Black Box: Interpreting Deep-learning Models for Exoplanet Atmospheric Retrievals

Deep-learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly nonlinear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast retrievals of atmospheric parameters with the use of machine-learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being "black boxes." It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong, and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us–among other things–of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that, for different molecules, the wavelength ranges to which the DNNs predictions are most sensitive do indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions