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Related papers: Redshift determination through weighted phase corr…

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We present simulations of quasar colors, magnitudes, and numbers at redshifts 5<z<10 based on our discovery of ten new high-redshift quasars and the cloning of lower redshift Sloan Digital Sky Survey (SDSS) quasars. The ten quasars have…

Sequential quadratic optimization algorithms are proposed for solving smooth nonlinear optimization problems with equality constraints. The main focus is an algorithm proposed for the case when the constraint functions are deterministic,…

Optimization and Control · Mathematics 2020-07-22 Albert Berahas , Frank E. Curtis , Daniel P. Robinson , Baoyu Zhou

In the modern galaxy surveys photometric redshifts play a central role in a broad range of studies, from gravitational lensing and dark matter distribution to galaxy evolution. Using a dataset of about 25,000 galaxies from the second data…

Instrumentation and Methods for Astrophysics · Physics 2017-06-14 Stefano Cavuoti , Crescenzo Tortora , Massimo Brescia , Giuseppe Longo , Mario Radovich , Nicola R. Napolitano , Valeria Amaro , Civita Vellucci

Using multiple tracers of large-scale structure allows to evade the limitations imposed by sampling variance for some parameters of interest in cosmology. We demonstrate the optimal way of carrying out a multitracer analysis in a galaxy…

Cosmology and Nongalactic Astrophysics · Physics 2012-11-22 Nico Hamaus , Uroš Seljak , Vincent Desjacques

Spectroscopic redshift surveys are key tools to trace the large-scale structure (LSS) of the Universe and test the $\Lambda$CDM model. However, using redshifts as distance proxies introduces distortions in the 3D galaxy distribution. If…

Cosmology and Nongalactic Astrophysics · Physics 2026-02-09 Edoardo Maragliano , Punyakoti Ganeshaiah Veena , Giulia Degni , Enzo Franco Branchini

We present a new approach to capturing the broad diversity of emission line and continuum properties in quasar spectra. We identify populations of spectrally similar quasars through pixel-level clustering on 12,968 high signal-to-noise…

Astrophysics of Galaxies · Physics 2022-02-16 Allyson Brodzeller , Kyle Dawson

The weak lensing shear signal has been measured numerically in $N$-body simulations at 14 different redshifts ($z_s = 0.1$ to 3.6) and on angular scales of $\theta = 2'$ to 32'. In addition, the data have been validated by analytical…

Astrophysics · Physics 2009-11-07 Andrew J. Barber

Large-scale non-convex sparsity-constrained problems have recently gained extensive attention. Most existing deterministic optimization methods (e.g., GraSP) are not suitable for large-scale and high-dimensional problems, and thus…

Machine Learning · Computer Science 2019-12-03 Fanhua Shang , Bingkun Wei , Hongying Liu , Yuanyuan Liu , Jiacheng Zhuo

We introduce a new Bayesian HI spectral line fitting technique capable of obtaining spectroscopic redshifts for millions of galaxies in radio surveys with the Square Kilometere Array (SKA). This technique is especially well-suited to the…

Cosmology and Nongalactic Astrophysics · Physics 2017-04-28 Ian Harrison , Michelle Lochner , Michael L. Brown

We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…

Astrophysics of Galaxies · Physics 2020-10-14 Paula Tarrío , Stefano Zarattini

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first…

Optimization and Control · Mathematics 2016-02-25 Aymeric Dieuleveut , Nicolas Flammarion , Francis Bach

We consider a structured estimation problem where an observed matrix is assumed to be generated as an $s$-sparse linear combination of $N$ given $n\times n$ positive-semidefinite matrices. Recovering the unknown $N$-dimensional and…

Information Theory · Computer Science 2020-03-27 Fabian Jaensch , Peter Jung

The problem of time series approximation by series of finite rank is considered from the viewpoint of signal extraction. For signal estimation, a weighted least-squares method is applied to the trajectory matrix of the considered time…

Methodology · Statistics 2016-09-29 Nikita Zvonarev , Nina Golyandina

Compressed sensing is an important problem in many fields of science and engineering. It reconstructs signals by finding sparse solutions to underdetermined linear equations. In this work we propose a deterministic and non-parametric…

Signal Processing · Electrical Eng. & Systems 2017-12-19 Mutian Shen , Pan Zhang , Hai-Jun Zhou

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for…

Methodology · Statistics 2021-04-02 Arindam Fadikar , Stefan M. Wild , Jonas Chaves-Montero

The Kennedy-like receiver is a quasi-optimal receiver employed in binary phase-shift-keyed communication schemes with coherent states. It is based on the interference of the two signals encoding the message with a reference local oscillator…

Quantum Physics · Physics 2016-11-15 Matteo Bina , Alessia Allevi , Maria Bondani , Stefano Olivares

Based on the Sloan Digital Sky Survey Data Release 5 Galaxy Sample, we explore photometric morphology classification and redshift estimation of galaxies using photometric data and known spectroscopic redshifts. An unsupervised method,…

Astrophysics · Physics 2009-11-13 Yanxia Zhang , Lili Li , Yongheng Zhao

The power spectrum estimated from a galaxy redshift survey is the real spectrum convolved with a window function, so when estimating the power on very large scales (for small k), it is important that this window function be as narrow as…

Astrophysics · Physics 2009-10-07 Max Tegmark

We conducted an extensive computational experiment, lasting multiple CPU-years, to optimally select parameters for two important classes of algorithms for finding sparse solutions of underdetermined systems of linear equations. We make the…

Numerical Analysis · Computer Science 2015-05-14 Arian Maleki , David L. Donoho

In this paper we tackle the problem of recovering the phase of complex linear measurements when only magnitude information is available and we control the input. We are motivated by the recent development of dedicated optics-based hardware…

Machine Learning · Computer Science 2020-02-17 Sidharth Gupta , Rémi Gribonval , Laurent Daudet , Ivan Dokmanić