Strong Lens Time Delay Challenge. Ii. Results Of Tdc1

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As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

Multiply lensed images of a same source experience a relative time delay in the arrival of photons due to the path length difference and the different gravitational potentials the photons travel through. This effect can be used to measure absolute distance ...

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Univ ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Performance-critical industrial applications, including large-scale program, network, and distributed system analyses, are increasingly reliant on recursive queries for data analysis. Yet traditional relational algebra-based query optimization techniques d ...

Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modelling in galaxy clusters is computationally expensive, ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Context. The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. Aims. We expand and adjust the mock Euclid likelihoods of t ...

This work considers which higher order modeling e ffects on the cosmic shear angular power spectra must be taken into account for Euclid. We identified the relevant terms and quantified their individual and cumulative impact on the cosmological parameter i ...

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI ...

The distribution of mass in galaxy-scale strong gravitational lenses is often modelled as an elliptical power-law plus 'external shear', which notionally accounts for neighbouring galaxies and cosmic shear along our line of sight. A small amount of externa ...

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point c ...

Superconducting qubits are among the most advanced candidates for achieving fault-tolerant quantum computing. Despite recent significant advancements in the qubit lifetimes, the origin of the loss mechanism for state-of-the-art qubits is still subject to i ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

Strong Lens Time Delay Challenge. Ii. Results Of Tdc1

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Extensions of Peer Prediction Incentive Mechanisms

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Time-Delay Cosmography: Measuring the Hubble Constant and Other Cosmological Parameters with Strong Gravitational Lensing

XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Room-temperature quantum optomechanics using an ultralow noise cavity

Adaptive Recursive Query Optimization

CURLING - I. The influence of point-like image approximation on the outcomes of cluster strong lens modelling

Stability: a search for structure

Data-driven statistical optimization of a groundwater monitoring network

Euclid: Validation of the MontePython forecasting tools

Euclid preparation XXXVI. Modelling the weak lensing angular power spectrum

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Strong gravitational lensing's 'external shear' is not shear

SUNBIRD : a simulation-based model for full-shape density-split clustering

Mechanically induced correlated errors on superconducting qubits with relaxation times exceeding 0.4 ms

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Dynamism in the context of views out: A literature review

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression