Hasil untuk "q-bio.CB"

L. Biedenharn

A. Macfarlane

Hansuek Lee, Tong Chen, Jiang Li et al.

Bahare Kiumarsi-Khomartash, F. Lewis, H. Modares et al.

Ripal Nathuji, A. Kansal, Alireza Ghaffarkhah

A. Aral, Vijay Gupta, R. Agarwal

Bohua Chen, Xiaoyan Zhang, Kan Wu et al.

In this paper, we report 4 different saturable absorbers based on 4 transition metal dichalcogenides (MoS(2), MoSe(2), WS(2), WSe(2)) and utilize them to Q-switch a ring-cavity fiber laser with identical cavity configuration. It is found that MoSe(2) exhibits highest modulation depth with similar preparation process among four saturable absorbers. Q-switching operation performance is compared from the aspects of RF spectrum, optical spectrum, repetition rate and pulse duration. WS(2) Q-switched fiber laser generates the most stable pulse trains compared to other 3 fiber lasers. These results demonstrate the feasibility of TMDs to Q-switch fiber laser effectively and provide a meaningful reference for further research in nonlinear fiber optics with these TMDs materials.

L. Accardo, M. Aguilar, D. Aisa et al.

Christopher Potter, Bosiljka Tasic, Emilie V Russler et al.

B. J. Barros, T. Barreiro, T. Koivisto et al.

A Bayesian statistical analysis using redshift space distortions data is performed to test a model of Symmetric Teleparallel Gravity where gravity is non-metrical. The cosmological background mimics a $\Lambda$CDM evolution but differences arise in the perturbations. The linear matter fluctuations are numerically evolved and the study of the growth rate of structures is analysed in this cosmological setting. The best fit parameters reveal that the $\sigma_8$ tension between Planck and Large Scale Structure data can be alleviated within this framework.

M. Aguilar, D. Aisa, B. Alpat et al.

Knowledge of the precise rigidity dependence of the helium flux is important in understanding the origin, acceleration, and propagation of cosmic rays. A precise measurement of the helium flux in primary cosmic rays with rigidity (momentum/charge) from 1.9 GV to 3 TV based on 50 million events is presented and compared to the proton flux. The detailed variation with rigidity of the helium flux spectral index is presented for the first time. The spectral index progressively hardens at rigidities larger than 100 GV. The rigidity dependence of the helium flux spectral index is similar to that of the proton spectral index though the magnitudes are different. Remarkably, the spectral index of the proton to helium flux ratio increases with rigidity up to 45 GV and then becomes constant; the flux ratio above 45 GV is well described by a single power law.

F. Bajardi, D. Vernieri, S. Capozziello

We consider f(Q) extended symmetric teleparallel cosmologies, where Q is the non-metricity scalar, and constrain its functional form through the order reduction method. By using this technique, we are able to reduce and integrate the field equations and thus to select the corresponding models giving rise to bouncing cosmology. The selected Lagrangian is then used to develop the Hamiltonian formalism and to obtain the Wave Function of the Universe which suggests that classical observable universes can be recovered according to the Hartle Criterion.

C. Kelstrup, Dorte B. Bekker-Jensen, T. Arrey et al.

R. Aaij, C. Abellan Beteta, T. Ackernley et al.

An angular analysis of the B^{0}→K^{*0}(→K^{+}π^{-})μ^{+}μ^{-} decay is presented using a dataset corresponding to an integrated luminosity of 4.7  fb^{-1} of pp collision data collected with the LHCb experiment. The full set of CP-averaged observables are determined in bins of the invariant mass squared of the dimuon system. Contamination from decays with the K^{+}π^{-} system in an S-wave configuration is taken into account. The tension seen between the previous LHCb results and the standard model predictions persists with the new data. The precise value of the significance of this tension depends on the choice of theory nuisance parameters.

N. Frusciante

We investigate the impact on cosmological observables of $f(Q)$-gravity, a specific class of modified gravity models in which gravity is described by the nonmetricity scalar, $Q$. In particular we focus on a specific model which is indistinguishable from the $\mathrm{\ensuremath{\Lambda}}$-cold-dark-matter ($\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$) model at the background level, while showing peculiar and measurable signatures at linear perturbation level. These are attributed to a time-dependent Planck mass and are regulated by a single dimensionless parameter, $\ensuremath{\alpha}$. In comparison to the $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model, we find for positive values of $\ensuremath{\alpha}$ a suppressed matter power spectrum and lensing effect on the cosmic microwave background radiation (CMB) angular power spectrum and an enhanced integrated-Sachs-Wolfe tail of CMB temperature anisotropies. The opposite behaviors are present when the $\ensuremath{\alpha}$ parameter is negative. We also investigate the modified gravitational waves (GWs) propagation and show the prediction of the GWs luminosity distance compared to the standard electromagnetic one. Finally, we infer the accuracy on the free parameter of the model with standard sirens at future GWs detectors.

A. K. Srinivasa, Dagmar Mithöfer

Solar- powered irrigation systems (SPIS) are instruments for sustainable energy transition in agriculture. Despite the government of India's efforts, the adoption of SPIS has remained low. This paper uses the Q method to examine shared stakeholder views on the challenges of increasing SPIS adoption. The aim is to understand barriers to and drivers for SPIS adoption, and the necessary institutional setting to scale up adoption. To capture the discourse on challenges to SPIS adoption, a Q sample of 20 statements was extracted after stakeholder interviews and expert ratings. The statements were Q sorted by 22 respondents across SPIS stakeholder groups. Factor analysis identifies two distinct perspectives on constraints to expanding SPIS: (1) economic and financial barriers; and (2) institutional and governance challenges. This calls for re-framing SPIS from the incentive side of things and convergence across concerned implementing agencies.

Rasool Fakoor, P. Chaudhari, Stefano Soatto et al.

This paper introduces Meta-Q-Learning (MQL), a new off-policy algorithm for meta-Reinforcement Learning (meta-RL). MQL builds upon three simple ideas. First, we show that Q-learning is competitive with state-of-the-art meta-RL algorithms if given access to a context variable that is a representation of the past trajectory. Second, a multi-task objective to maximize the average reward across the training tasks is an effective method to meta-train RL policies. Third, past data from the meta-training replay buffer can be recycled to adapt the policy on a new task using off-policy updates. MQL draws upon ideas in propensity estimation to do so and thereby amplifies the amount of available data for adaptation. Experiments on standard continuous-control benchmarks suggest that MQL compares favorably with the state of the art in meta-RL.

A. Sirunyan, A. Tumasyan, W. Adam et al.

A bstractResults are reported from a search for supersymmetric particles in the final state with multiple jets and large missing transverse momentum. The search uses a sample of proton-proton collisions at s$$ \sqrt{s} $$ = 13 TeV collected with the CMS detector in 2016–2018, corresponding to an integrated luminosity of 137 fb−1, representing essentially the full LHC Run 2 data sample. The analysis is performed in a four-dimensional search region defined in terms of the number of jets, the number of tagged bottom quark jets, the scalar sum of jet transverse momenta, and the magnitude of the vector sum of jet transverse momenta. No significant excess in the event yield is observed relative to the expected background contributions from standard model processes. Limits on the pair production of gluinos and squarks are obtained in the framework of simplified models for supersymmetric particle production and decay processes. Assuming the lightest supersymmetric particle to be a neutralino, lower limits on the gluino mass as large as 2000 to 2310 GeV are obtained at 95% confidence level, while lower limits on the squark mass as large as 1190 to 1630 GeV are obtained, depending on the production scenario.

C. Schulze, B. Matzdorf

Agri-environmental climate measures (AECM) are considered a promising tool to achieve environmental policy goals. Not only farmers but also policy administrators and intermediaries are important actors whose attitudes and actions drive the success of these measures. To follow the idea of better stakeholder participation in the design of policy instruments, we analyse stakeholder viewpoints on the contract design of AECM. We apply Q methodology with 25 individuals from Brandenburg, Germany, who are from the farmer, policy administrator and intermediary domains. We identify three distinct attitudinal profiles, the “planners”, the “cooperators” and the “individualists”, which do not correspond to the three individual stakeholder groups. The results provide evidence that general differences in the viewpoints of policy designers and implementers on the one hand and farmers on the other hand are not a source of potential institutional mismatch. We further use the attitudinal profiles to develop three types of policy programmes with slightly different underlying rationalities. Policymakers could use such an approach to better develop target group-specific (sub)programmes in parallel. Our research strengthens the argument that multiple stakeholders should be involved in co-designing conservation measures. Moreover, behavioural factors should be considered in policy making processes.

Justin Fu, Aviral Kumar, Matthew Soh et al.

Q-learning methods represent a commonly used class of algorithms in reinforcement learning: they are generally efficient and simple, and can be combined readily with function approximators for deep reinforcement learning (RL). However, the behavior of Q-learning methods with function approximation is poorly understood, both theoretically and empirically. In this work, we aim to experimentally investigate potential issues in Q-learning, by means of a "unit testing" framework where we can utilize oracles to disentangle sources of error. Specifically, we investigate questions related to function approximation, sampling error and nonstationarity, and where available, verify if trends found in oracle settings hold true with modern deep RL methods. We find that large neural network architectures have many benefits with regards to learning stability; offer several practical compensations for overfitting; and develop a novel sampling method based on explicitly compensating for function approximation error that yields fair improvement on high-dimensional continuous control domains.