Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematic analyses

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

To constrain cosmological models beyond ACDM, the development of the Euclid analysis pipeline requires simulations that capture the non-linear phenomenology of such models. We present an overview of numerical methods and N-body simulation codes developed t ...

This paper investigates the fundamental regression task of learning k neurons (a.k.a. teachers) from Gaussian input, using two-layer ReLU neural networks with width m (a.k.a. students) and m, k = O(1), trained via gradient descent under proper initializati ...

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1 < z < 2.1. Divided by tracer type, we utilize 300,017 galaxies from the magnitude-limited ...

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

We present a reinforcement learning framework for constructing assemblies composed of rigid parts, which are commonly seen in many historical masonry buildings and bridges. Traditional construction methods for such structures often depend on dense scaffold ...

Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion control, ...

Deploying energy-efficient deep neural networks on energy-constrained edge devices is an important research topic in both machine learning and circuit design communities. Both artificial neural networks (ANNs) and spiking neural networks (SNNs) have been p ...

When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorit ...

Now is an exciting time for the domain of Earth observation (EO), with a multitude of diverse sensors looking at the planet from satellites, airplanes or drones. The volume of imagery acquired is massive, and hold great potential for a variety of applicati ...

The ability to train ever-larger neural networks brings artificial intelligence to the forefront of scientific and technical discoveries. However, their exponentially increasing size creates a proportionally greater demand for energy and computational hard ...

The JWST discovery of "little red dots" (LRDs) is reshaping our picture of the early Universe, yet the physical mechanisms driving their compact size and UV-optical colors remain elusive. Here, we report an unusually bright LRD (zspec = 3.1) observed as pa ...

This paper presents the specification, design, and development of the Visible Camera (VIS) on the European Space Agency’s Euclid mission. VIS is a large optical-band imager with a field of view of 0.54 deg2 sampled at 000 . 1 with an array of 609 Megapixel ...

In recent years, neural quantum states have emerged as a powerful variational approach, achieving state-of-the-art accuracy when representing the ground-state wave function of a great variety of quantum many-body systems, including spin lattices, interacti ...

We present a sample of over 100 highly X-ray luminous galaxy clusters (L-X,L-0.1-2.4keV similar to 10(45 )erg s(-1)) at z similar to 0.5-0.9, discovered by the extended Massive Cluster Survey (eMACS) in ROSAT All-Sky Survey (RASS) data. Follow-up observati ...

As one of the major threats to women's health worldwide, breast cancer requires early diagnosis and accurate classification, since they are key to optimizing therapeutic interventions and ensuring precise prognosis. Recently, deep learning has demonstrated ...

We present the Cosmic Evolution Early Release Science (CEERS) Survey, a 77.2 hr Director’s Discretionary Early Release Science Program. CEERS demonstrates, tests, and validates efficient extragalactic surveys using coordinated, overlapping parallel observa ...

The discovery of the Cosmic Microwave Background marked a pivotal moment in Physical Cosmology, propelling the field into an era of unprecedented precision in describing the Universe. Over the past two decades, rapid advancements in spectroscopic surveys h ...

Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematic analyses

Chattez avec Graph Search

Euclid preparation: LXII. Simulations and non-linearities beyond Lambda cold dark matter. 1. Numerical methods and validation

How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks

DESI 2024 III: baryon acoustic oscillations from galaxies and quasars

Improving the accuracy and interpretability of neural networks for wind power forecasting

Learning to Assemble with Alternative Plans

Using deep reinforcement learning to investigate stretch feedback during swimming of the lamprey

Eflop: a Sparsity-aware Metric for Evaluating Computational Cost in Spiking and Non-spiking Neural Networks

Fiducial-cosmology-dependent systematics for the DESI 2024 BAO analysis

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

Training hybrid neural networks with multimode optical nonlinearities using digital twins

Rubies: Jwst/nirspec Confirmation of an Infrared-luminous, Broad-line Little Red Dot with an Ionized Outflow

Euclid II. The VIS instrument

Accurate neural quantum states for interacting lattice bosons

Beyond MACS: physical properties of extremely X-ray luminous clusters at z > 0.5

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

The Cosmic Evolution Early Release Science Survey (CEERS)

Advancements in Spectroscopic Surveys and Simulation Techniques in Physical Cosmology