AGN-driven helium reionization and the incidence of extended HeIII regions at redshift z>3

We use hydrodynamic simulations post-processed with the radiative-transfer code RADAMESH to assess recent claims that the low HeII opacity observed in z>3 quasar spectra may be incompatible with models of HeII reionization driven by the observed population of active galactic nuclei (AGNs). In particular, building upon our previous work, we consider an early population of sources and start the radiative-transfer calculation at redshifts z>=5. Our model faithfully reproduces the emissivity of optically selected AGNs as inferred from measurements of their luminosity function. We find that HeII reionization is very extended in redshift ({\Delta} z>=2) and highly spatially inhomogeneous. In fact, mock spectra extracted from the simulations show a large variability in the evolution of the HeII effective optical depth within chunks of size {\Delta} z=0.04. Regions with low opacity ({\tau}^{eff}_{HeII}<3) can be found at high redshift, in agreement with the most recent observations of UV-transmitting quasars. At the highest redshift currently probed by observations (z~3.4), our updated model predicts a much lower HeII effective optical depth than previous simulations in the literature relieving most of the tension with the current data, that, however, still persists at about the (Gaussian) 1{\sigma} to 2{\sigma} level. Given the very small number of observed lines of sight, our analysis indicates that current data cannot rule out a purely AGN-driven scenario with high statistical significance.Comment: 12 pages, 8 figures. Matches version accepted for publication in MNRA

Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology's usefulness for optimization and sampling tasks. Here, we present a way to partially embed both Monte Carlo policy iteration for finding an optimal policy on random observations, as well as how to embed (n) sub-optimal state-value functions for approximating an improved state-value function given a policy for finite horizon games with discrete state spaces on a D-Wave 2000Q quantum processing unit (QPU). We explain how both problems can be expressed as a quadratic unconstrained binary optimization (QUBO) problem, and show that quantum-enhanced Monte Carlo policy evaluation allows for finding equivalent or better state-value functions for a given policy with the same number episodes compared to a purely classical Monte Carlo algorithm. Additionally, we describe a quantum-classical policy learning algorithm. Our first and foremost aim is to explain how to represent and solve parts of these problems with the help of the QPU, and not to prove supremacy over every existing classical policy evaluation algorithm.Comment: 17 pages, 7 figure

Generalized Costs of Travel by Solo and Pooled Ridesourcing vs. Privately Owned Vehicles, and Policy Implications

The emergence of “3 Revolutions” in transportation (automation, electrification and shared mobility) presents a range of questions regarding how consumers will travel in the future, and under what conditions there may be rapid adoption of various services. These include individual on-demand taxi-style services, shared mobility in pooled services, and use of public transit, all with or without drivers. There is now enough data and estimates on the costs of these service combinations, and in some cases ridership data, to consider how consumers are making choices and could do so in the future as things evolve. This project involved: (a) reviewing existing literature and data on consumer mode and vehicle choice; (b) developing new “generalized cost” estimates that combine monetary and non-monetary (e.g., hedonic) components of travel choice, notably incorporating value of time; and (c) conducting a comparison of monetary and generalized trip cost for a range of trip types across travel options in the near term (2020) and longer term (2030-35). Three main travel options were considered: privately owned vehicles, ridesourced solo trips, and ridesourced pooled trips. Consideration of internal combustion vs. battery electric and, in the longer term, automated technology was also core to the analysis. The trips considered include urban and suburban types in the San Francisco metro area, using actual trip characteristics. The results suggest that in the near-term, solo ridesourcing is likely to be perceived as significantly more expensive (in terms of monetary and time costs) than pooled ridesourcing or solo private vehicle trips except for those with a very high value of time. Solo ridesourcing does better in dense, slow, urban trips than in faster suburban trips. In the longer term, with automated driverless vehicles, solo ridesourcing could become the cheapest mode for many travelers in a range of situations. This report includes an initial consideration of the implications of these policies for affecting travel choices, presumably to push choices toward pooled ridesourcing as a sustainable option. VMT-based pricing, pricing that could be adjusted with vehicle occupancy, and parking-related approaches are described. A large price signal might be needed to shift travel, given some of the differences in generalized cost found in this analysis

Top quark properties at the Tevatron

Precise determination of the top quark properties allows for stringent tests of the Standard Model. In this paper we report the latest results from the CDF and DØ Collaborations on a data sample of p¯p collisions at 1.96TeV collected at the Fermilab Tevatron up to an integrated luminosity of 4.8 fb−1

Monitoring functional capacity in heart failure.

This document reflects the key points of a consensus meeting of the Heart Failure Association of European Society of Cardiology (ESC) held to provide an overview the role of physiological monitoring in the complex multimorbid heart failure (HF) patient. This article reviews assessments of the functional ability of patients with HF. The gold standard measurement of cardiovascular functional capacity is peak oxygen consumption obtained from a cardiopulmonary exercise test. The 6-min walk test provides an indirect measure of cardiovascular functional capacity. Muscular functional capacity is assessed using either a 1-repetition maximum test of the upper and lower body or other methods, such as handgrip measurement. The short physical performance battery may provide a helpful, indirect indication of muscular functional capacity

Language and perception. Investigating linear and hierarchical implicit statistical learning across the visual, auditory, and tactile sensory domains.

This thesis explored how humans process and form recursive hierarchical structures arising from temporally ordered sequences of stimuli, across the visual, auditory, and tactile sensory domains. As we will explain throughout this thesis, we posit that the ability to form recursive hierarchical abstract representations from temporally ordered stimuli is a cognitive ability involved in human syntax processing and acquisition. Language unfolds in a linear fashion. Words follow one another, creating sentences that, on the surface, appear as linear sequences of sounds or symbols. However, a purely sequential arrangement of words alone falls short in encompassing the complexities of human language syntax. It is evident that the syntax of human languages has a fundamental hierarchical dimension, where constituents are organized in a way that is intricately linked to their linear order. Among the various syntactic phenomena that depend on this hierarchical organization, recursion is one of the most fascinating and controversial in the study of language. Recursion in human syntax, understood as the characteristic of embedding constituents within constituents of the same kind, has long been considered a fundamental and distinctive feature of human language. Therefore, the cognitive ability to deal with recursion has been viewed as crucial for language capacity, possibly representing a uniquely human faculty at the core of language ability. However, this topic is highly controversial. Despite the importance attributed to recursion in linguistics, several questions remain open. What is the role of recursion in human language? Is the ability to handle recursion specifically tied to the human language faculty? What is the mechanism underlying the cognitive ability to form recursive abstract representations in language, considering both the linear and hierarchical nature of syntax? To analyze this topic, this thesis will delve into three critical issues at the core of theoretical and experimental linguistic debates. The first issue addresses the debated role of recursion in human language syntax. The second issue examines the contributions of recursive hierarchical abstract representation and statistical learning to the acquisition and processing of human syntax. The third issue, intimately connected to the second, examines the existence of domain-specific representational and learning constraints, alongside the influence of domain-general learning abilities on this process. Our research had two main objectives: Firstly, we aimed to determine whether sequential statistical learning and the formation of recursive hierarchical abstract representation operate independently as distinct levels of language analysis or if they work together synergistically as complementary learning mechanisms. If they complement each other, we sought to understand the cognitive processes involved in transitioning from linear to recursive hierarchical dimensions. Secondly, we investigated whether the ability to form recursive hierarchical abstract structures from sequential stimuli is a language-specific ability or a domain-general ability, shared across different modalities and whether there are domain-specific differences in this ability between sensory domains. To address these inquiries, we employed the Artificial Grammar Learning paradigm, conducting three Serial Reaction Time tasks. Three distinct groups of adult participants were presented with a sequence of stimuli featuring the rules of a non-canonical binary grammar belonging to the Lindenmayer systems: The Fibonacci grammar (Fib). The choice to use this grammar was driven by its exceptional suitability for thoroughly investigating this research topic in all its various facets. On one hand, it allows for the investigation of the application of recursive algorithms for predicting points in the string, while simultaneously examining the relationship between sequential statistical learning and the creation of recursive hierarchical representations. On the other hand, this paradigm permits the examination and direct comparison of these cognitive abilities across different sensory modalities. In the three tasks, the symbols of Fib were encoded onto auditory tones, vibrotactile impulses, or colorful visual shapes. Through analysis of reaction times and accuracy data in response to perceived stimuli, we explored whether participants implicitly learned the regularities of Fib across all three sensory domains and potentially domain-specific learning differences. Our findings suggested a close linkage between the ability to form recursive hierarchical representations and the capacity to grasp low-level transitional regularities. With this regard, we introduced a cognitive parsing algorithm hypothesizing the cognitive mechanisms involved in transitioning from sequence to hierarchy. Furthermore, we observed that the cognitive ability to process and learn these structures, which underpin human language, is a domain-general ability present across diverse sensory domains. However, we also identified domain-specific differences, with auditory and tactile modalities exhibiting a distinct advantage over the visual domain. In summary, our results indicated that sequential statistical learning and recursive hierarchical abstract representation synergize as complementary modes of learning, rather than operating as distinct levels of language analysis. Moreover, our findings suggest that the capability to from recursive hierarchical abstract structures arising from temporally ordered stimuli is not a language-specific ability but rather a domain-general capacity present across different sensory modalities, potentially interacting with language in specific ways

Combined search for the standard model Higgs boson decaying to a bb pair using the full CDF data set

We combine the results of searches for the standard model Higgs boson based on the full CDF Run II data set obtained from sqrt(s) = 1.96 TeV p-pbar collisions at the Fermilab Tevatron corresponding to an integrated luminosity of 9.45/fb. The searches are conducted for Higgs bosons that are produced in association with a W or Z boson, have masses in the range 90-150 GeV/c^2, and decay into bb pairs. An excess of data is present that is inconsistent with the background prediction at the level of 2.5 standard deviations (the most significant local excess is 2.7 standard deviations).Comment: To be published in Phys. Rev. Lett (v2 contains minor updates based on comments from PRL