Determination of the cosmic far-infrared background level with the ISOPHOT instrument

The cosmic infrared background (CIRB) consists mainly of the integrated light of distant galaxies. In the far-infrared the current estimates of its surface brightness are based on the measurements of the COBE satellite. Independent confirmation of these results is still needed from other instruments. In this paper we derive estimates of the far-infrared CIRB using measurements made with the ISOPHOT instrument aboard the ISO satellite. The results are used to seek further confirmation of the CIRB levels that have been derived by various groups using the COBE data. We study three regions of very low cirrus emission. The surface brightness observed with the ISOPHOT instrument at 90, 150, and 180 um is correlated with hydrogen 21 cm line data from the Effelsberg radio telescope. Extrapolation to zero hydrogen column density gives an estimate for the sum of extragalactic signal plus zodiacal light. The zodiacal light is subtracted using ISOPHOT data at shorter wavelengths. Thus, the resulting estimate of the far-infrared CIRB is based on ISO measurements alone. In the range 150 to 180 um, we obtain a CIRB value of 1.08+-0.32+-0.30 MJy/sr quoting statistical and systematic errors separately. In the 90 um band, we obtain a 2-sigma upper limit of 2.3 MJy/sr. The estimates derived from ISOPHOT far-infrared maps are consistent with the earlier COBE results.Comment: Accepted for publication in A&A, 17 page

Foreground removal from WMAP 7yr polarization maps using an MLP neural network

One of the fundamental problems in extracting the cosmic microwave background signal (CMB) from millimeter/submillimeter observations is the pollution by emission from the Milky Way: synchrotron, free-free, and thermal dust emission. To extract the fundamental cosmological parameters from CMB signal, it is mandatory to minimize this pollution since it will create systematic errors in the CMB power spectra. In previous investigations, it has been demonstrated that the neural network method provide high quality CMB maps from temperature data. Here the analysis is extended to polarization maps. As a concrete example, the WMAP 7-year polarization data, the most reliable determination of the polarization properties of the CMB, has been analysed. The analysis has adopted the frequency maps, noise models, window functions and the foreground models as provided by the WMAP Team, and no auxiliary data is included. Within this framework it is demonstrated that the network can extract the CMB polarization signal with no sign of pollution by the polarized foregrounds. The errors in the derived polarization power spectra are improved compared to the errors derived by the WMAP Team.Comment: Accepted for publication in Astrophysics & Space Scienc

The Flexibility of Nonconsciously Deployed Cognitive Processes: Evidence from Masked Congruence Priming

Background: It is well accepted in the subliminal priming literature that task-level properties modulate nonconscious processes. For example, in tasks with a limited number of targets, subliminal priming effects are limited to primes that are physically similar to the targets. In contrast, when a large number of targets are used, subliminal priming effects are observed for primes that share a semantic (but not necessarily physical) relationship with the target. Findings such as these have led researchers to conclude that task-level properties can direct nonconscious processes to be deployed exclusively over central (semantic) or peripheral (physically specified) representations. Principal Findings: We find distinct patterns of masked priming for "novel" and "repeated" primes within a single task context. Novel primes never appear as targets and thus are not seen consciously in the experiment. Repeated primes do appear as targets, thereby lending themselves to the establishment of peripheral stimulus-response mappings. If the source of the masked priming effect were exclusively central or peripheral, then both novel and repeated primes should yield similar patterns of priming. In contrast, we find that both novel and repeated primes produce robust, yet distinct, patterns of priming. Conclusions: Our findings indicate that nonconsciously elicited cognitive processes can be flexibly deployed over both central and peripheral representations within a single task context. While we agree that task-level properties can influence nonconscious processes, our findings sharply constrain the extent of this influence. Specifically, our findings are inconsistent with extant accounts which hold that the influence of task-level properties is strong enough to restrict the deployment of nonconsciously elicited cognitive processes to a single type of representation (i.e. central or peripheral).13 page(s

Deep Learning for Temporal Logics

Temporal logics are a well established formal specification paradigm to specify the behavior of systems, and serve as inputs to industrial-strength verification tools. We report on current advances in applying deep learning to temporal logical reasoning tasks, showing that models can even solve instances where competitive classical algorithms timed out

Teaching Temporal Logics to Neural Networks

We study two fundamental questions in neuro-symbolic computing: can deep learning tackle challenging problems in logics end-to-end, and can neural networks learn the semantics of logics. In this work we focus on linear-time temporal logic (LTL), as it is widely used in verification. We train a Transformer on the problem to directly predict a solution, i.e. a trace, to a given LTL formula. The training data is generated with classical solvers, which, however, only provide one of many possible solutions to each formula. We demonstrate that it is sufficient to train on those particular solutions to formulas, and that Transformers can predict solutions even to formulas from benchmarks from the literature on which the classical solver timed out. Transformers also generalize to the semantics of the logics: while they often deviate from the solutions found by the classical solvers, they still predict correct solutions to most formulas

Foreground removal from CMB temperature maps using an MLP neural network

One of the main obstacles in extracting the Cosmic Microwave Background (CMB) signal from observations in the mm-submm range is the foreground contamination by emission from galactic components: mainly synchrotron, free-free and thermal dust emission. Due to the statistical nature of the intrinsic CMB signal it is essential to minimize the systematic errors in the CMB temperature determinations. Following the available knowledge of the spectral behavior of the galactic foregrounds simple, power law-like spectra have been assumed. The feasibility of using a simple neural network for extracting the CMB temperature signal from the combined CMB and foreground signals has been investigated. As a specific example, we have analysed simulated data, like that expected from the ESA Planck Surveyor mission. A simple multilayer perceptron neural network with 2 hidden layers can provide temperature estimates, over more than 80 percent of the sky, that are to a high degree uncorrelated with the foreground signals. A single network will be able to cover the dynamic range of the Planck noise level over the entire sky.Comment: Accepted for publication in Astrophysics and Space Scienc

Serological Studies Confirm the Novel Astrovirus HMOAstV-C as a Highly Prevalent Human Infectious Agent

Molecular identification of a microbe is the first step in determining its prevalence of infection and pathogenic potential. Detection of specific adaptive immune responses can provide insights into whether a microbe is a human infectious agent and its epidemiology. Here we characterized human anti-IgG antibody responses by luciferase immunoprecipitation systems (LIPS) against two protein fragments derived from the capsid protein of the novel HMOAstV-C astrovirus. While antibodies to the N-terminal fragment were not informative, the C-terminal capsid fragment of HMOAstV-C showed a high frequency of immunoreactivity with serum from healthy blood donors. In contrast, a similar C-terminal capsid fragment from the related HMOAstV-A astrovirus failed to show immunoreactivity. Detailed analysis of adult serum from the United Sates using a standardized threshold demonstrated HMOAstV-C seropositivity in approximately 65% of the samples. Evaluation of serum samples from different pediatric age groups revealed that the prevalence of antibodies in 6–12 month, 1–2 year, 2–5 year and 5–10 year olds was 20%, 23%, 32% and 36%, respectively, indicating rising seroprevalence with age. Additionally, 50% (11/22) of the 0–6 month old children showed anti-HMOAstV-C antibody responses, likely reflecting maternal antibodies. Together these results document human humoral responses to HMOAstV-C and validate LIPS as a facile and effective approach for identifying humoral responses to novel infectious agents

Sky Confusion Noise in the Far-Infrared: Cirrus, Galaxies and the Cosmic Far-Infrared Background

We examined the sky confusion noise in 40 sky regions by analysing 175 far-infrared (90--200 $\mu$m) maps obtained with ISOPHOT, the photometer on-board the Infrared Space Observatory. For cirrus fields with $\rm > 5$ MJysr$^{-1}$ the formula based on IRAS data (Helou & Beichman, \cite{Helou+Beichman_90}) predicts confusion noise values within a factor of 2 to our measurements. The dependence of the sky confusion noise on the surface brightness was determined for the wavelength range 90 $\le \lambda \le$ 200 $\mu$m. We verified that the confusion noise scales as N ~ ^{1.5}, independent of the wavelength and confirmed N ~ lambda^{2.5}$for lambda >= 100$um. The scaling of the noise value at different separations between target and reference positions was investigated for the first time, providing a practical formula. Since our results confirm the applicability of the Helou & Beichman (1990) formula, the cirrus confusion noise predictions made for future space missions with telescopes of a similar size can be trusted. At 90 and 170um a noise term with a Poissonian spatial distribution was detected in the faintest fields ( <= 3-5 MJysr^{-1}), which we interpret as fluctuations in the Cosmic Far-Infrared Background (CFIRB). Applying ratios of the fluctuation amplitude to the absolute level of 10% and 7% at 90 and 170um, respectively, as supported by model calculations, we achieved a new simultaneous determination of the fluctuation amplitudes and the surface brightness of the CFIRB. The fluctuation amplitudes are 7(+/-)2 mJy and 15(+/-)4 mJy at 90 and 170um, respectively. We obtained a CFIRB surface brightness of B(0)=0.8(+/-)0.2 MJysr^{-1} (nuI_nu=14(+/-)3nWm^-2sr^-1) at 170um and an upper limit of 1.1 MJysr^{-1} (nuI_nu=37 nWm^-2sr^-1) at 90um.Comment: A&A accepted, 9 pages in A&A style, including 7 figure

Estimating the tensor-to-scalar ratio and the effect of residual foreground contamination

We consider future balloon-borne and ground-based suborbital experiments designed to search for inflationary gravitational waves, and investigate the impact of residual foregrounds that remain in the estimated cosmic microwave background maps. This is achieved by propagating foreground modelling uncertainties from the component separation, under the assumption of a spatially uniform foreground frequency scaling, through to the power spectrum estimates, and up to measurement of the tensor to scalar ratio in the parameter estimation step. We characterize the error covariance due to subtracted foregrounds, and find it to be subdominant compared to instrumental noise and sample variance in our simulated data analysis. We model the unsubtracted residual foreground contribution using a two-parameter power law and show that marginalization over these foreground parameters is effective in accounting for a bias due to excess foreground power at low $\ell$. We conclude that, at least in the suborbital experimental setups we have simulated, foreground errors may be modeled and propagated up to parameter estimation with only a slight degradation of the target sensitivity of these experiments derived neglecting the presence of the foregrounds.Comment: 19 pages, 12 figures, accepted for publication in JCA

Singlet Portal to the Hidden Sector

Ultraviolet physics typically induces a kinetic mixing between gauge singlets which is marginal and hence non-decoupling in the infrared. In singlet extensions of the minimal supersymmetric standard model, e.g. the next-to-minimal supersymmetric standard model, this furnishes a well motivated and distinctive portal connecting the visible sector to any hidden sector which contains a singlet chiral superfield. In the presence of singlet kinetic mixing, the hidden sector automatically acquires a light mass scale in the range 0.1 - 100 GeV induced by electroweak symmetry breaking. In theories with R-parity conservation, superparticles produced at the LHC invariably cascade decay into hidden sector particles. Since the hidden sector singlet couples to the visible sector via the Higgs sector, these cascades necessarily produce a Higgs boson in an order 0.01 - 1 fraction of events. Furthermore, supersymmetric cascades typically produce highly boosted, low-mass hidden sector singlets decaying visibly, albeit with displacement, into the heaviest standard model particles which are kinematically accessible. We study experimental constraints on this broad class of theories, as well as the role of singlet kinetic mixing in direct detection of hidden sector dark matter. We also present related theories in which a hidden sector singlet interacts with the visible sector through kinetic mixing with right-handed neutrinos.Comment: 12 pages, 5 figure