Large-scale bias in the Universe: bispectrum method

Evidence that the Universe may be close to the critical density, required for its expansion eventually to be halted, comes principally from dynamical studies of large-scale structure. These studies either use the observed peculiar velocity field of galaxies directly, or indirectly by quantifying its anisotropic effect on galaxy clustering in redshift surveys. A potential difficulty with both such approaches is that the density parameter $\Omega_0$ is obtained only in the combination $\beta = \Omega_0^{0.6}/b$, if linear perturbation theory is used. The determination of the density parameter $\Omega_0$ is therefore compromised by the lack of a good measurement of the bias parameter $b$, which relates the clustering of sample galaxies to the clustering of mass. In this paper, we develop an idea of Fry (1994), using second-order perturbation theory to investigate how to measure the bias parameter on large scales. The use of higher-order statistics allows the degeneracy between $b$ and $\Omega_0$ to be lifted, and an unambiguous determination of $\Omega_0$ then becomes possible. We apply a likelihood approach to the bispectrum, the three-point function in Fourier space. This paper is the first step in turning the idea into a practical proposition for redshift surveys, and is principally concerned with noise properties of the bispectrum, which are non-trivial. The calculation of the required bispectrum covariances involves the six-point function, including many noise terms, for which we have developed a generating functional approach which will be of value in calculating high-order statistics in general.Comment: 12 pages, latex, 7 postscript figures included. Accepted by MNRAS. (Minor numerical typesetting errors corrected: results unchanged

The nonlinear redshift-space power spectrum of galaxies

We study the power spectrum of galaxies in redshift space, with third order perturbation theory to include corrections that are absent in linear theory. We assume a local bias for the galaxies: i.e. the galaxy density is sampled from some local function of the underlying mass distribution. We find that the effect of the nonlinear bias in real space is to introduce two new features: first, there is a contribution to the power which is constant with wavenumber, whose nature we reveal as essentially a shot-noise term. In principle this contribution can mask the primordial power spectrum, and could limit the accuracy with which the latter might be measured on very large scales. Secondly, the effect of second- and third-order bias is to modify the effective bias (defined as the square root of the ratio of galaxy power spectrum to matter power spectrum). The effective bias is almost scale-independent over a wide range of scales. These general conclusions also hold in redshift space. In addition, we have investigated the distortion of the power spectrum by peculiar velocities, which may be used to constrain the density of the Universe. We look at the quadrupole-to-monopole ratio, and find that higher-order terms can mimic linear theory bias, but the bias implied is neither the linear bias, nor the effective bias referred to above. We test the theory with biased N-body simulations, and find excellent agreement in both real and redshift space, providing the local biasing is applied on a scale whose fractional r.m.s. density fluctuations are $< 0.5$.Comment: 13 pages, 7 figures. Accepted by MNRA

The Distributional Impact of a Carbon Tax in Ireland

We study the effects of carbon taxation and revenue recycling across the income distribution in Ireland. Price changes of fuels and all other final goods and services are taken into account. If applied only to the emissions not covered by the EU Emissions Trading Scheme, a carbon tax of €20/tCO2 would cost the poorest households around €3.5/week and the richest ones €5/week. The tax is regressive, therefore. However, if the revenue is used to increase social benefits and tax credits, households across the income distribution can be made better off without exhausting the total carbon tax revenue.

Tests for primordial non-Gaussianity

We investigate the relative sensitivities of several tests for deviations from Gaussianity in the primordial distribution of density perturbations. We consider models for non-Gaussianity that mimic that which comes from inflation as well as that which comes from topological defects. The tests we consider involve the cosmic microwave background (CMB), large-scale structure (LSS), high-redshift galaxies, and the abundances and properties of clusters. We find that the CMB is superior at finding non-Gaussianity in the primordial gravitational potential (as inflation would produce), while observations of high-redshift galaxies are much better suited to find non-Gaussianity that resembles that expected from topological defects. We derive a simple expression that relates the abundance of high-redshift objects in non-Gaussian models to the primordial skewness.Comment: 6 pages, 2 figures, MNRAS in press (minor changes to match the accepted version

The International Dimension of the EU Emissions Trading System: Bringing the Pieces Together

We analyse the international dimension of the EU Emissions Trading System (EU ETS) over the past two decades and in the foreseeable future by reviewing facts and economic theory. The facts mainly concern the international climate change regime and the EU’s relevant experience in international cooperation. Club theory shows how incentives can be created for cooperation on climate mitigation. The linkage of the EU ETS to the Kyoto fexible mechanisms had mixed results: it promoted emissions trading abroad, but the infow of credits into the EU ETS added to a large market surplus and the environmental integrity of certain credits was problematic. Looking ahead, the ability of the EU ETS to reduce foreign emissions may grow. Key will be whether competitiveness and distributional efects are successfully addressed. The Carbon Border Adjustment Mechanism might help the EU reduce the risk of carbon leakage while incentivising emission reductions in countries exporting to the EU. The EU’s focus on reducing domestic emissions only, suggests we will probably not see new international linkages this decade. However, it cannot be excluded that the EU will revisit its decision and relax the domestic constraint

Exploring the impact of data poisoning attacks on machine learning model reliability

Recent years have seen the widespread adoption of Artificial Intelligence techniques in several domains, including healthcare, justice, assisted driving and Natural Language Processing (NLP) based applications (e.g., the Fake News detection). Those mentioned are just a few examples of some domains that are particularly critical and sensitive to the reliability of the adopted machine learning systems. Therefore, several Artificial Intelligence approaches were adopted as support to realize easy and reliable solutions aimed at improving the early diagnosis, personalized treatment, remote patient monitoring and better decision-making with a consequent reduction of healthcare costs. Recent studies have shown that these techniques are venerable to attacks by adversaries at phases of artificial intelligence. Poisoned data set are the most common attack to the reliability of Artificial Intelligence approaches. Noise, for example, can have a significant impact on the overall performance of a machine learning model. This study discusses the strength of impact of noise on classification algorithms. In detail, the reliability of several machine learning techniques to distinguish correctly pathological and healthy voices by analysing poisoning data was evaluated. Voice samples selected by available database, widely used in research sector, the Saarbruecken Voice Database, were processed and analysed to evaluate the resilience and classification accuracy of these techniques. All analyses are evaluated in terms of accuracy, specificity, sensitivity, F1-score and ROC area

Hiponatremia no calazar

There are few reports linking hyponatremia and visceral leishmaniasis (kala-azar). This is a study of 55 consecutive kala-azar patients and 20 normal individuals as a control group. Hyponatremia and serum hypo-osmolality were detected in 100% of kala-azar patients. High first morning urine osmolality (750.0 ± 52.0 vs. 894.5 ± 30.0mOsm/kg H2O, p < 0.05), and high 24-hour urine osmolality (426.0 ± 167.0 vs. 514.6 ± 132.0 mOsm/kg H2O, p < 0.05) demonstrated persistent antidiuretic hormone secretion. Urinary sodium was high (82.3 ± 44.2 vs.110.3 ± 34.7 mEq/L, p < 0.05). Low seric uric acid occurred in 61.8% of patients and increased fractional urinary uric acid excretion was detected in 74.5% of them. Increased glomerular filtration rate was present in 25.4% of patients. There was no evidence of extracellular volume depletion. Normal plasma ADH levels were observed in kala-azar patients. No endocrine or renal dysfunction was detected. It is possible that most hyponatremic kala-azar patients present the syndrome of inappropriate antidiuretic hormone secretion.Existem poucos relatos relacionando hiponatremia com a leshmaniose visceral (calazar). Este é um estudo de 55 pacientes portadores de calazar e um grupo controle de 20 indivíduos normais. Hiponatremia e hipo-osmolalidade sérica foram detectados em 100% dos pacientes portadores de calazar. A presença de alta osmolalidade da primeira urina da manhã (750,0 ± 52,0 vs. 894,5 ± 30 mOsm/Kg H2O, p < 0,05) e da urina de 24h (426,0 ± 167,0 vs. 514,6 ± 132,0 mOsm/Kg H2O, p < 0,05), demonstraram a presença de persistente secreção de hormônio antidiurético. A concentração de sódio urinário foi elevada (82,3 ± 44,2 vs. 110,3 ± 34,7 mEq/L, p < 0,05). Hipouricemia ocorreu em 61,8% dos pacientes e aumento da fração de excreção urinária de ácido úrico foi detectada em 74,5% dos casos. Aumento da velocidade de filtração glomerular estava presente em 25,4% dos pacientes. Não havia evidência clínica de depleção de volume extracelular. Valores normais de ADH plasmático foram observados nos pacientes com calazar. Não foi detectada disfunção renal ou endócrina. É provável, que a maioria dos pacientes com calazar apresente uma síndrome de secreção inapropriada de hormônio antidiurético

The Bispectrum of IRAS Galaxies

We compute the bispectrum for the galaxy distribution in the IRAS QDOT, 2Jy, and 1.2Jy redshift catalogs for wavenumbers 0.05<k<0.2 h/Mpc and compare the results with predictions from gravitational instability in perturbation theory. Taking into account redshift space distortions, nonlinear evolution, the survey selection function, and discreteness and finite volume effects, all three catalogs show evidence for the dependence of the bispectrum on configuration shape predicted by gravitational instability. Assuming Gaussian initial conditions and local biasing parametrized by linear and non-linear bias parameters b_1 and b_2, a likelihood analysis yields 1/b_1 = 1.32^{+0.36}_{-0.58}, 1.15^{+0.39}_{-0.39} and b_2/b_1^2=-0.57^{+0.45}_{-0.30}, -0.50^{+0.31}_{-0.51}, for the for the 2Jy and 1.2Jy samples, respectively. This implies that IRAS galaxies trace dark matter increasingly weakly as the density contrast increases, consistent with their being under-represented in clusters. In a model with chi^2 non-Gaussian initial conditions, the bispectrum displays an amplitude and scale dependence different than that found in the Gaussian case; if IRAS galaxies do not have bias b_1> 1 at large scales, \chi^2 non-Gaussian initial conditions are ruled out at the 95% confidence level. The IRAS data do not distinguish between Lagrangian or Eulerian local bias.Comment: 30 pages, 11 figure