Sloan Digital Sky Survey III Photometric Quasar Clustering:Probing the Initial Conditions of the Universe Shirley Ho
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Quantum Detection of Wormholes Carlos Sabín
www.nature.com/scientificreports OPEN Quantum detection of wormholes Carlos Sabín We show how to use quantum metrology to detect a wormhole. A coherent state of the electromagnetic field experiences a phase shift with a slight dependence on the throat radius of a possible distant wormhole. We show that this tiny correction is, in principle, detectable by homodyne measurements Received: 16 February 2017 after long propagation lengths for a wide range of throat radii and distances to the wormhole, even if the detection takes place very far away from the throat, where the spacetime is very close to a flat Accepted: 15 March 2017 geometry. We use realistic parameters from state-of-the-art long-baseline laser interferometry, both Published: xx xx xxxx Earth-based and space-borne. The scheme is, in principle, robust to optical losses and initial mixedness. We have not observed any wormhole in our Universe, although observational-based bounds on their abundance have been established1. The motivation of the search of these objects is twofold. On one hand, the theoretical implications of the existence of topological spacetime shortcuts would entail a challenge to our understanding of deep physical principles such as causality2–5. On the other hand, typical phenomena attributed to black holes can be mimicked by wormholes. Therefore, if wormholes exist the identity of the objects in the center of the galaxies might be questioned6 as well as the origin of the already observed gravitational waves7, 8. For these reasons, there is a renewed interest in the characterization of wormholes9–11 and in their detection by classical means such as gravitational lensing12, 13, among others14. -
Active Galactic Nuclei: a Brief Introduction
Active Galactic Nuclei: a brief introduction Manel Errando Washington University in St. Louis The discovery of quasars 3C 273: The first AGN z=0.158 2 <latexit sha1_base64="4D0JDPO4VKf1BWj0/SwyHGTHSAM=">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</latexit> <latexit sha1_base64="H7Rv+ZHksM7/70841dw/vasasCQ=">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</latexit> The power source of quasars • The luminosity (L) of quasars, i.e. how bright they are, can be as high as Lquasar ~ 1012 Lsun ~ 1040 W. • The energy source of quasars is accretion power: - Nuclear fusion: 2 11 1 ∆E =0.007 mc =6 10 W s g− -
Mcwilliams Center for Cosmology
McWilliams Center for Cosmology McWilliams Center for Cosmology McWilliams Center for Cosmology McWilliams Center for Cosmology ,CODQTGG Rachel Mandelbaum (+Optimus Prime) Observational cosmology: • how can we make the best use of large datasets? (+stats, ML connection) • dark energy • the galaxy-dark matter connection I measure this: for tens of millions of galaxies to (statistically) map dark matter and answer these questions Data I use now: Future surveys I’m involved in: Hung-Jin Huang 0.2 0.090 0.118 0.062 0.047 0.118 0.088 0.044 0.036 0.186 0.016 70 0.011 0.011 − 0.011 − 0.011 − 0.011 − 0.011 − 0.011 0.011 − 0.011 0.011 ± ± ± ± ± ± ± ± ± ± 50 η 0.1 30 ∆ Fraction 10 1 24 23 22 21 0.40.81.2 0.20.61.0 0.6 0.2 0.20.6 0.30.50.70.9 1.41.61.82.02.2 0.15 0.25 0.10.30.5 0.4 0.00.4 − − 0−.1 − − − − . 0.090 ∆log(cen. R )[kpc/h] P ∆ 0.011 0.3 cen. Mr cen. color cen. e eff cen log(richness) z cluster e R ± dom 1 0.2 . − cen 0.1 3 Fraction − 21 Research: − 0.118 0.622 0.3 0.011 0.009 Mr 22 1 . ± ± 0.2 0 − . 23 − 0.1 Fraction cen intrinsic alignments in 24 − 0.8 0.062 0.062 0.084 0.7 1.2 0.011 0.011 0.011 0.6 redMaPPer clusters − ± − ± − ± 0.5 color . 0.4 0.8 0.3 Fraction cen 0.2 0.4 0.1 1.0 0.047 0.048 0.052 0.111 0.3 Advisor : 0.011 0.011 0.011 0.011 e − ± − ± − ± − ± . -
A Multimessenger View of Galaxies and Quasars from Now to Mid-Century M
A multimessenger view of galaxies and quasars from now to mid-century M. D’Onofrio 1;∗, P. Marziani 2;∗ 1 Department of Physics & Astronomy, University of Padova, Padova, Italia 2 National Institute for Astrophysics (INAF), Padua Astronomical Observatory, Italy Correspondence*: Mauro D’Onofrio [email protected] ABSTRACT In the next 30 years, a new generation of space and ground-based telescopes will permit to obtain multi-frequency observations of faint sources and, for the first time in human history, to achieve a deep, almost synoptical monitoring of the whole sky. Gravitational wave observatories will detect a Universe of unseen black holes in the merging process over a broad spectrum of mass. Computing facilities will permit new high-resolution simulations with a deeper physical analysis of the main phenomena occurring at different scales. Given these development lines, we first sketch a panorama of the main instrumental developments expected in the next thirty years, dealing not only with electromagnetic radiation, but also from a multi-messenger perspective that includes gravitational waves, neutrinos, and cosmic rays. We then present how the new instrumentation will make it possible to foster advances in our present understanding of galaxies and quasars. We focus on selected scientific themes that are hotly debated today, in some cases advancing conjectures on the solution of major problems that may become solved in the next 30 years. Keywords: galaxy evolution – quasars – cosmology – supermassive black holes – black hole physics 1 INTRODUCTION: TOWARD MULTIMESSENGER ASTRONOMY The development of astronomy in the second half of the XXth century followed two major lines of improvement: the increase in light gathering power (i.e., the ability to detect fainter objects), and the extension of the frequency domain in the electromagnetic spectrum beyond the traditional optical domain. -
A Supernova Origin for Dust in a High-Redshift Quasar
A SUPERNOVA ORIGIN FOR DUST IN A HIGH-REDSHIFT QUASAR R. Maiolino ∗, R. Schneider †∗, E. Oliva ‡∗, S. Bianchi §, A. Ferrara ¶, F. Mannucci§, M. Pedani‡, M. Roca Sogorb k ∗ INAF - Osservatorio Astrofisico di Arcetri, Largo Enrico Fermi 5, 50125 Firenze, Italy † “Enrico Fermi” Center, Via Panisperna 89/A, 00184 Roma, Italy ‡ Telescopio Nazionale Galileo, C. Alvarez de Abreu, 70, 38700 S.ta Cruz de La Palma, Spain § CNR-IRA, Sezione di Firenze, Largo Enrico Fermi 5, 50125 Firenze, Italy ¶ SISSA/International School for Advanced Studies, Via Beirut 4, 34100 Trieste, Italy k Astrofisico Fco. S`anchez, Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain Interstellar dust plays a crucial role in the evolution of the Universe by assisting the formation of molecules1, by triggering the formation of the first low-mass stars2, and by absorbing stellar ultraviolet-optical light and subsequently re-emitting it at infrared/millimetre wavelengths. Dust is thought to be produced predominantly in the envelopes of evolved (age >1 Gyr), low-mass stars3. This picture has, however, recently been brought into question by the discovery of large masses of dust in the host galaxies of quasars4,5 at redshift z > 6, when the age of the Universe was less than 1 Gyr. Theoretical studies6,7,8, corroborated by observations of nearby supernova remnants9,10,11, have suggested that supernovae provide a fast and efficient dust formation environment in the early Universe. Here we report infrared observations of a quasar at redshift 6.2, which are used to obtain directly its dust extinction curve. We then show that such a curve is in excellent agreement with supernova dust models. -
Dm2gal: Mapping Dark Matter to Galaxies with Neural Networks
dm2gal: Mapping Dark Matter to Galaxies with Neural Networks Noah Kasmanoff Francisco Villaescusa-Navarro Center for Data Science Department of Astrophysical Sciences New York University Princeton University New York, NY 10011 Princeton NJ 08544 [email protected] [email protected] Jeremy Tinker Shirley Ho Center for Cosmology and Particle Physics Center for Computational Astrophysics New York University Flatiron Institute New York, NY 10011 New York, NY 10010 [email protected] [email protected] Abstract Maps of cosmic structure produced by galaxy surveys are one of the key tools for answering fundamental questions about the Universe. Accurate theoretical predictions for these quantities are needed to maximize the scientific return of these programs. Simulating the Universe by including gravity and hydrodynamics is one of the most powerful techniques to accomplish this; unfortunately, these simulations are very expensive computationally. Alternatively, gravity-only simulations are cheaper, but do not predict the locations and properties of galaxies in the cosmic web. In this work, we use convolutional neural networks to paint galaxy stellar masses on top of the dark matter field generated by gravity-only simulations. Stellar mass of galaxies are important for galaxy selection in surveys and thus an important quantity that needs to be predicted. Our model outperforms the state-of-the-art benchmark model and allows the generation of fast and accurate models of the observed galaxy distribution. 1 Introduction Galaxies are not randomly distributed in the sky, but follow a particular pattern known as the cosmic web. Galaxies concentrate in high-density regions composed of dark matter halos, and galaxy clusters usually lie within these dark matter halos and they are connected via thin and long filaments. -
How to Learn to Love the BOSS Baryon Oscillations Spectroscopic Survey
How to learn to Love the BOSS Baryon Oscillations Spectroscopic Survey Shirley Ho Anthony Pullen, Shadab Alam, Mariana Vargas, Yen-Chi Chen + Sloan Digital Sky Survey III-BOSS collaboration Carnegie Mellon University SpaceTime Odyssey 2015 Stockholm, 2015 What is BOSS ? Shirley Ho, Sapetime Odyssey, Stockholm 2015 What is BOSS ? Shirley Ho, Sapetime Odyssey, Stockholm 2015 BOSS may be … Shirley Ho, Sapetime Odyssey, Stockholm 2015 SDSS III - BOSS Sloan Digital Sky Survey III - Baryon Oscillations Spectroscopic Survey What is it ? What does it do ? What is SDSS III - BOSS ? • A 2.5m telescope in New Mexico • Collected • 1 million spectra of galaxies , • 400,000 spectra of supermassive blackholes (quasars), • 400,000 spectra of stars • images of 20 millions of stars, galaxies and quasars. Shirley Ho, Sapetime Odyssey, Stockholm 2015 What is SDSS III - BOSS ? • A 2.5m telescope in New Mexico • Collected • 1 million spectra of galaxies , • 400,000 spectra of supermassive blackholes (quasars), • 400,000 spectra of stars • images of 20 millions of stars, galaxies and quasars. Shirley Ho, Sapetime Odyssey, Stockholm 2015 SDSS III - BOSS Sloan Digital Sky Survey III - Baryon Oscillations Spectroscopic Survey What is it ? What does it do ? SDSS III - BOSS Sloan Digital Sky Survey III - Baryon Oscillations Spectroscopic Survey BAO: Baryon Acoustic Oscillations AND Many others! What can we do with BOSS? • Probing Modified gravity with Growth of Structures • Probing initial conditions, neutrino masses using full shape of the correlation function • -
Deep21: a Deep Learning Method for 21Cm Foreground Removal
Prepared for submission to JCAP deep21: a Deep Learning Method for 21cm Foreground Removal T. Lucas Makinen, ID a;b;c;1 Lachlan Lancaster, ID a Francisco Villaescusa-Navarro, ID a Peter Melchior, ID a;d Shirley Ho,e Laurence Perreault-Levasseur, ID e;f;g and David N. Spergele;a aDepartment of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ, 08544, USA bInstitut d’Astrophysique de Paris, Sorbonne Université, 98 bis Boulevard Arago, 75014 Paris, France cCenter for Statistics and Machine Learning, Princeton University, Princeton, NJ 08544, USA dCenter for Computational Astrophysics, Flatiron Institute, 162 5th Avenue, New York, NY, 10010, USA eDepartment of Physics, Univesité de Montréal, CP 6128 Succ. Centre-ville, Montréal, H3C 3J7, Canada f Mila - Quebec Artificial Intelligence Institute, Montréal, Canada E-mail: [email protected], [email protected], fvillaescusa-visitor@flatironinstitute.org, [email protected], shirleyho@flatironinstitute.org, dspergel@flatironinstitute.org Abstract. We seek to remove foreground contaminants from 21cm intensity mapping ob- servations. We demonstrate that a deep convolutional neural network (CNN) with a UNet architecture and three-dimensional convolutions, trained on simulated observations, can effec- tively separate frequency and spatial patterns of the cosmic neutral hydrogen (HI) signal from foregrounds in the presence of noise. Cleaned maps recover cosmological clustering amplitude and phase within 20% at all relevant angular scales and frequencies. This amounts to a reduc- tion in prediction variance of over an order of magnitude across angular scales, and improved −1 accuracy for intermediate radial scales (0:025 < kk < 0:075 h Mpc ) compared to standard Principal Component Analysis (PCA) methods. -
Correspondence
Correspondence A global coalition to [email protected] in money-based laboratory convincingly, even though the sustain core data *On behalf of the Global experiments (see Nature 541, flatness of their outer parts might Life Science Data Resources 294–295; 2017). The assumption convey that impression. As members of an international Working Group (see go.nature. in interpreting such results seems At that time, I and several working group to support the com/2miobmk for full list). to be that consumers aim to other astronomers used the rapidly growing core-data ‘optimize’ the products they buy. 21-centimetre radio wavelength resources in the life sciences, we But unless an optimal product of neutral hydrogen to determine aim to create a sustainable and Zealandia is not a is defined, this hypothesis is rotation curves that often went accessible data infrastructure that continent untestable because it is subjective. well beyond the optical image, will benefit scientists worldwide. Apart from perishable produce, thereby probing the dark matter Although researchers have Now recognized in international I for one do not care about regime more effectively. relied on international resources law, Zealandia — the continental optimality. I care only about Such observations from such as the Protein Data Bank shelf and margin surrounding adequacy: whether an item meets several galaxies, coupled with and Flybase for decades, the New Zealand — is vast and my needs and is available and optical surface photometry, current system is unsustainable worthy of inquiry. However, affordable. Once these criteria are permitted the calculation of local because it is largely funded by we disagree with attempts to satisfied, I need never look again. -
Stellar Death: White Dwarfs, Neutron Stars, and Black Holes
Stellar death: White dwarfs, Neutron stars & Black Holes Content Expectaions What happens when fusion stops? Stars are in balance (hydrostatic equilibrium) by radiation pushing outwards and gravity pulling in What will happen once fusion stops? The core of the star collapses spectacularly, leaving behind a dead star (compact object) What is left depends on the mass of the original star: <8 M⦿: white dwarf 8 M⦿ < M < 20 M⦿: neutron star > 20 M⦿: black hole Forming a white dwarf Powerful wind pushes ejects outer layers of star forming a planetary nebula, and exposing the small, dense core (white dwarf) The core is about the radius of Earth Very hot when formed, but no source of energy – will slowly fade away Prevented from collapsing by degenerate electron gas (stiff as a solid) Planetary nebulae (nothing to do with planets!) THE RING NEBULA Planetary nebulae (nothing to do with planets!) THE CAT’S EYE NEBULA Death of massive stars When the core of a massive star collapses, it can overcome electron degeneracy Huge amount of energy BAADE ZWICKY released - big supernova explosion Neutron star: collapse halted by neutron degeneracy (1934: Baade & Zwicky) Black Hole: star so massive, collapse cannot be halted SN1006 1967: Pulsars discovered! Jocelyn Bell and her supervisor Antony Hewish studying radio signals from quasars Discovered recurrent signal every 1.337 seconds! Nicknamed LGM-1 now called PSR B1919+21 BRIGHTNESS TIME NATURE, FEBRUARY 1968 1967: Pulsars discovered! Beams of radiation from spinning neutron star Like a lighthouse Neutron -
Recent Developments in Neutrino Cosmology for the Layperson
Recent developments in neutrino cosmology for the layperson Sunny Vagnozzi The Oskar Klein Centre for Cosmoparticle Physics, Stockholm University [email protected] PhD thesis discussion Stockholm, 10 June 2019 1 / 27 D'o`uvenons-nous? Que sommes-nous ? O`uallons-nous? Courtesy of Paul Gauguin 2 / 27 The oldest questions... Where do we come from? What are we made of ? Where are we going? 3 / 27 ...and the modern versions of these questions What were the Universe's initial conditions? Where do we come from? −! What is the Universe What are we made of ? −! made of ? Where are we going? −! How will the Universe evolve? 4 / 27 Where do we come from? Cosmic inflation aka (Hot) Big Bang? 5 / 27 What are we made of? Mostly dark stuff (and a bit of neutrinos) 6 / 27 Where are we going? Depends on what dark energy is? 7 / 27 Lots of astrophysical and cosmological data to test theories for the origin/composition/fate of the Universe: 8 / 27 Neutrinos 9 / 27 Neutrino masses 10 / 27 Neutrino mass ordering 11 / 27 Paper I Sunny Vagnozzi, Elena Giusarma, Olga Mena, Katie Freese, Martina Gerbino, Shirley Ho, Massimiliano Lattanzi, Phys. Rev. D 96 (2017) 123503 [arXiv:1701.08172] What does current data tell us about the neutrino mass scale and mass ordering? How to quantify how much the normal ordering is favoured? 12 / 27 Paper I Even a small amount of massive neutrinos leaves a huge trace in the distribution of galaxies on the largest observables scales 13 / 27 Paper I 1 M < kg ν 10000000000000000000000000000000000000 14 / 27 Paper II Elena Giusarma, Sunny Vagnozzi, Shirley Ho, Simone Ferraro, Katie Freese, Rocky Kamen-Rubio, Kam-Biu Luk, Phys. -
From Dark Matter to Galaxies with Convolutional Networks
From Dark Matter to Galaxies with Convolutional Networks Xinyue Zhang*, Yanfang Wang*, Wei Zhang*, Siyu He Yueqiu Sun*∗ Department of Physics, Carnegie Mellon University Center for Data Science, New York University Center for Computational Astrophysics, Flatiron Institute xz2139,yw1007,wz1218,[email protected] [email protected] Gabriella Contardo, Francisco Shirley Ho Villaescusa-Navarro Center for Computational Astrophysics, Flatiron Institute Center for Computational Astrophysics, Flatiron Institute Department of Astrophysical Sciences, Princeton gcontardo,[email protected] University Department of Physics, Carnegie Mellon University [email protected] ABSTRACT 1 INTRODUCTION Cosmological surveys aim at answering fundamental questions Cosmology focuses on studying the origin and evolution of our about our Universe, including the nature of dark matter or the rea- Universe, from the Big Bang to today and its future. One of the holy son of unexpected accelerated expansion of the Universe. In order grails of cosmology is to understand and define the physical rules to answer these questions, two important ingredients are needed: and parameters that led to our actual Universe. Astronomers survey 1) data from observations and 2) a theoretical model that allows fast large volumes of the Universe [10, 12, 17, 32] and employ a large comparison between observation and theory. Most of the cosmolog- ensemble of computer simulations to compare with the observed ical surveys observe galaxies, which are very difficult to model theo- data in order to extract the full information of our own Universe. retically due to the complicated physics involved in their formation The constant improvement of computational power has allowed and evolution; modeling realistic galaxies over cosmological vol- cosmologists to pursue elucidating the fundamental parameters umes requires running computationally expensive hydrodynamic and laws of the Universe by relying on simulations as their theory simulations that can cost millions of CPU hours.