NYU & AMNH & CUNY AstroExtravaganza

7feb7bbc3605d995c6099de0e25b4b99?s=47 David W Hogg
September 28, 2018

NYU & AMNH & CUNY AstroExtravaganza

A community-built slide deck for a series of lightning talks.

7feb7bbc3605d995c6099de0e25b4b99?s=128

David W Hogg

September 28, 2018
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Transcript

  1. NYU & AMNH & CUNY AstroFest 2018-09-28 at the CCPP

  2. 600 hours to conduct a variability study for cloud patterns

    on young brown dwarfs (see J. Vos talk) 60 hours to follow-up on new cold and close brown dwarf candidates Spitzer Projects ESA Gaia DR2 project 1 Yr project to determine the acceleration of stars in DR2 due to unseen companions. Looking for interested people! Kepler K2 project HST Project 1 Yr project to measure the rotation rate and flare rate for M dwarfs in K2 campaign fields. See R. Kiman and M. Popinchalk talks. 5 orbits of HST to obtain J band photometry on new cold and close brown dwarfs (Y dwarfs). Looking for interested people! (E. Gonzales is in the UK working on this! Also see C. Cleary) PI’s Jackie Faherty, Kelle Cruz, Emily Rice Team members: Vos, Bardalez-Gagliuffi, Cleary, Kiman, Popinchalk, Gonzales, Cid, Ventura, Godfrey-Giorla, Chan
  3. Benjamin Pope

  4. The Brightest Stars in Kepler

  5. Asteroseismology

  6. The Dead World of Aldebaran b

  7. Johanna Vos

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  13. Zachary Richards

  14. Teaching Astrobiology to Non-Science Majors: Challenges and Strategies Zachary Richards

    Department of Natural Sciences LaGuardia Community College, CUNY Painted by James Silva SCP 105 “Life in the Universe” Fall 2017
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  16. Hands-On Activities

  17. Creativity

  18. Engaging Students Through Demonstrations

  19. Contact Me Email - zrichards@lagcc.cuny.edu Phone - 1 (917) 763

    0495
  20. Richard Galvez

  21. Richard Galvez: Postdoc @NYU CDS and CCPP Research Interests: >>

    Data Science, Machine Learning (mostly deep learning) applied to astrophysics data sets >> Understanding Dark Matter through particle cosmology methods, mostly BBN (let’s bring it back!).
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  26. Relaxing Neff at CMB = Neff at BBN allows for

    four neutrinos.
  27. Richard Galvez: Postdoc @NYU CDS and CCPP Contact me for:

    >> Fun deep learning projects with astrophysics data / or any data really. >> Gaia data analysis, particularly using ML. richard.galvez@nyu.edu
  28. Joshua Tan

  29. WHAT CAN WE DO WITH A SIXTEEN INCH TELESCOPE? Joshua

    Tan LaGuardia Community College, CUNY ASTROFEST 28 September 2018
  30. SN 2014J OGLE-2006BLG109Lbc DY Peg DISCOVERIES and FOLLOW-UPS by small

    telescopes
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  32. Mark Popinchalk

  33. @markpopinchalk markpopinchalk@gmail.com Comparison of Model Spectra in NIR to Brown

    Dwarfs and Massive Exoplanets Mark Popinchalk
  34. Mark Popinchalk Comparison of Model Spectra in NIR to Brown

    Dwarfs and Massive Exoplanets @markpopinchalk markpopinchalk@gmail.com
  35. Mark Popinchalk Comparison of Model Spectra in NIR to Brown

    Dwarfs and Massive Exoplanets @markpopinchalk markpopinchalk@gmail.com
  36. Mark Popinchalk Comparison of Model Spectra in NIR to Brown

    Dwarfs and Massive Exoplanets Opportunity to share research and network! @markpopinchalk markpopinchalk@gmail.com
  37. Mark Popinchalk Comparison of Model Spectra in NIR to Brown

    Dwarfs and Massive Exoplanets Opportunity to share research and network! Drink Tickets! @markpopinchalk markpopinchalk@gmail.com
  38. Comparison of Model Spectra in NIR to Brown Dwarfs and

    Massive Exoplanets @markpopinchalk markpopinchalk@gmail.com Mark Popinchalk
  39. Comparison of Model Spectra in NIR to Brown Dwarfs and

    Massive Exoplanets @markpopinchalk markpopinchalk@gmail.com Mark Popinchalk and Cam Buzard
  40. Normalized Flux Wavelength • High Mass gaseous companions spectroscopically similar

    to young low mass brown dwarfs • Both luminous in NIR. • K band (1.97 - 2.40µm) has high resolution, high signal to noise @markpopinchalk markpopinchalk@gmail.com
  41. Normalized Flux Wavelength • High Mass gaseous companions spectroscopically similar

    to young low mass brown dwarfs • Both luminous in NIR. • K band (1.97 - 2.40µm) has high resolution, high signal to noise @markpopinchalk markpopinchalk@gmail.com
  42. Normalized Flux Wavelength @markpopinchalk markpopinchalk@gmail.com 169 Observed Objects - SpeX

    Prism • Low gravity and Field • Planetary Companions BT Settl 2013 Model Gird • Effective Temperature • Surface Gravity
  43. Steepness of Slope Effective Temperature • Blue slopes increase with

    decreasing T eff • Models don’t agree from 1600 K - 2000 K @markpopinchalk markpopinchalk@gmail.com
  44. Steepness of Slope Effective Temperature • Higher Surface gravity have

    steeper Red Slopes. • Models broadly agree. @markpopinchalk markpopinchalk@gmail.com
  45. Steepness of Slope Effective Temperature • Higher Surface gravity have

    steeper Red Slopes. • Models broadly agree. • Blue slopes increase with decreasing T eff • Models don’t agree from 1600 K - 2000 K K Band Structure may be an indicator for Brown Dwarf and Massive Exoplanet Effective Temperature and Surface Gravity @markpopinchalk markpopinchalk@gmail.com
  46. Tim Paglione

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  48. • • • • • • • → → π

    → γ
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  50. Rocio Kiman

  51. Age-Dating Low Mass Stars Using Galactic Kinematics Rocio Kiman City

    University of New York, American Museum of Natural History Advisor: Kelle Cruz Collaborators: Sarah Schmidt, Ruth Angus, Jackie Faherty & Emily Rice
  52. Rocio Kiman - @rociokiman Our project “Gaia-Cupid”: combining age relations

    to infer ages for low mass stars. 2/3
  53. Vertical Action vs Hα shows the age-velocity trend. Our catalog

    shows that old stars are kinematically heated and less active and the contrary for young stars. Kiman et al. in prep soon! Old Activity Strength Young Old Kinematic Heating Young Rocio Kiman - @rociokiman 3/3
  54. Suroor Seher Gandhi

  55. High and Low Alpha Stars are Dynamically Distinct at All

    Ages Suroor S Gandhi Research Mentor: Prof Melissa K Ness AstroFest September 28, 2018
  56. High- and Low-Alpha Sequences and their Dynamics ❖ Separation by

    approximation ➢ High-alpha stars mostly old ➢ Low-alpha stars mostly young ❖ Calculate actions J R , J z , L z using galpy (Bovy 2015) ➢ J R : Radial Action → eccentricity ➢ J z : Vertical Action → height above plane ➢ J ϕ (or L z ): Angular Momentum →orbital radius ~150,000 LAMOST Red Giants: ❖ Ages: Ho et al (2017) ❖ Distances & proper motions: Gaia DR2 Age
  57. Actions for High- and Low-Alpha Sequences ❖ Plots show running

    means and std dev.s ❖ High- and low-alpha sequences are dynamically distinct at all ages
  58. Old Low-Alpha Stars Stars which are: ❖ Metal-poor ❖ Old

    ❖ Halo might be the markers of another galaxy (“Gaia-Enceladus”) which merged with the MW Halo Debris
  59. Conclusions ❖ Used ages of the ~150,000 LAMOST stars from

    Ho et al (2017) and proper motions from Gaia DR2 to compute actions ❖ Separately calculated running means of actions for high- and low-alpha stars ❖ Found that high- and low-alpha stars are dynamically distinct at all ages ❖ We see old low-alpha stars which might coincide with the infall (“Gaia-Enceladus”) that is discussed in Helmi et al (2018)
  60. Maryam Modjaz

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  65. Marc Williamson

  66. A New Approach to Classifying Massive Stellar Explosions Marc Williamson

    NYU mew488@nyu.edu Maryam Modjaz NYU Federica Bianco CUSP
  67. Current Classification Techniques • Only focus on spectral features at

    specific wavelengths. • Have difficulty identifying new types or “transition” supernovae. Modjaz 2011 Pruzhinskaya 2016
  68. Motivations We want a classification method that... • Uses all

    of the information in each spectrum. • Could yield insight into progenitors or explosion mechanism. • Is data driven. • Can identify interesting supernovae (new types, outliers, transition objects). • Informs us when to follow-up LSST supernovae.
  69. Principal Component Analysis & Support Vector Machine (SVM) Classification •

    PCA4 captures H-alpha and H-beta absorption features. • PCA1 captures ejecta velocity information. • Linear SVM classifies 83% of sample correctly. • SNe close to decision boundaries are very interesting. Williamson, Modjaz, Bianco in prep
  70. K. E. Saavik Ford

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  74. Barry McKernan

  75. See posters by: Andrea Mejia, Freddy Caban, Jose Adorno, Syeda

    Nasim
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  77. χ Χ Θ Θ Χ

  78. Sjoert van Velzen

  79. Sjoert van Velzen (NYU)

  80. Sjoert van Velzen

  81. Things to ask me over coffee/lunch/drinks: - Can we measure

    the spin of quiescent supermassive black holes (yes) - Can we use tidal flares to infer how back holes formed at z=10? (yes) - Can you show me how to use ZTF data? (yes) sjoert@nyu.edu
  82. Nathan Leigh

  83. Gravity’s Garbage Nathan Leigh Stony Brook University American Museum of

    Natural History Universidad de Concepcion • Gravity in the collisional regime (strong deflections, direct collisions between particles, etc.) • Often most interested in the crud that gets tossed away (either thrown out or crushed) ◦ Fewbody dynamics (Three-Body Problem, Four-Body Problem, etc.) ◦ Stellar Exotica (Blue Stragglers, Stellar Collisions, Binary Evolution, etc.) ◦ Dense stellar systems (Globular Clusters, Nuclear Star Clusters, Open Clusters) ◦ Black Hole Dynamics (Hypervelocity Stars, Tidal Disruption Events, Compact Object Mergers, etc.)
  84. Black Hole Kicks in Star Clusters • 100 M Sun

    BH sits at r=0 in a rotating Plummer “sphere” (z-axis = axis of rotation) • At t=0, the BH receives a kick with v kick < v esc • The kick direction is oriented: ◦ along the x-axis (left panel) ◦ along the z-axis (middle panel) ◦ at an angle of 45 degrees between the x- and z-axes (right panel) • At first, the BH’s orbit decays like a damped simple harmonic oscillator • Due to the cluster’s rotation, the BH picks up angular momentum as its orbit decays Webb, Leigh, Serrano, et al., in prep
  85. A mechanism to enhance the rate of BH growth? Damped

    SHO regime Circular regime Brownian regime During the circular phase, the relative velocities between the BH and stars are very low → This increases the rate of tidal captures and/or disruptions by an order of magnitude.
  86. Andrew MacFadyen

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  96. Matt O’Dowd

  97. matt.odowd@gmail.com GothamFest 2018 How to Unbox a Quasar Matt O'Dowd

    (Lehman College, AMNH) Rachel Webster (Melbourne Uni) Nick Bate (Cambridge) Giorgos Vernados (Groningen) Kathleen Labrie (Gemini Obs.) Suk Yee Yong (Melbourne Uni) Anthea King (Melbourne Uni) Daniel Neri-Larios ( Melbourne Uni) Josh Rogers (CUNY, AMNH) Juan Guerras (Yale)
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  106. E+08: Eigenbrod et al. 2008a P+08: Poindexter et al. 2008

    A+08: Anguita et al. 2008 B+08: Bate et al. 2008 F+09: Floyd et al. 2009 B+11: Blackburne et al. 2011 B+13: Blackburne et al. 2013 J+14: Jiménez-Vicente et al. 2014 E+08 B+11 P+08 A+08 B+08 F+09 B+13 multi-source, single epoch single source, multi-epoch single source, single epoch Publication ζ Shakura-Sunyaev thin disk `slim’ disk magnetic coupling Agol Krolik 2008 J+14 Abramowicz 1988 Gaskell 2008 GothamFest 2018
  107. GothamFest 2018 Bate, Vernados, O’Dowd, et al. 2018

  108. E+08: Eigenbrod et al. 2008a P+08: Poindexter et al. 2008

    A+08: Anguita et al. 2008 B+08: Bate et al. 2008 F+09: Floyd et al. 2009 B+11: Blackburne et al. 2011 B+13: Blackburne et al. 2013 J+14: Jiménez-Vicente et al. 2014 E+08 B+11 P+08 A+08 B+08 F+09 B+13 multi-source, single epoch single source, multi-epoch single source, single epoch Publication ζ Shakura-Sunyaev thin disk `slim’ disk magnetic coupling Agol Krolik 2008 J+14 Abramowicz 1988 Gaskell 2008 GothamFest 2018
  109. GothamFest 2018 Rest Wavelength (Å)

  110. GothamFest 2018 5° 25° 45° 65°

  111. matt.odowd@gmail.com GothamFest 2018 How to Unbox a Quasar Matt O'Dowd

    (Lehman College, AMNH)
  112. Michael Shara

  113. GOAL: Use SALT’s High Resolution Spectrograph to measure vsini of

    O stars in WR + O Binaries
  114. à

  115. Glennys Farrar

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  117. Observed ratio: 5.3 Conventional DM models (axions, WIMPs) no prediction

    -- ratio could be a factor million. Why 5?
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  119. uds Dark Matter gives PERFECT fit to observed ratio Accident,

    or message from Nature?
  120. Quinn Minor

  121. Binary Population Modeling in Dwarf Galaxies

  122. Minor et al., in prep

  123. With a ridiculously nice dataset...

  124. David W Hogg

  125. David W Hogg (NYU) (MPIA) (Flatiron) • Cold stellar streams

    are like gravitational antennae. • They show us the potential of the Milky Way. ◦ Information theory approaches. • They encode some traces of time-dependence in the potential. ◦ Not fully understood. • They are very sensitive to gravitational substructure. • ESA Gaia DR2 has changed the world.
  126. Price-Whelan & Bonaca, arXiv:1805.00425

  127. Bonaca et al, in preparation

  128. Shengqi Yang

  129. Shengqi Yang (NYU) Calibrating magnification bias for the Eg statistic

    to test GR • Cosmic acceleration Dark energy model or modified GR? • Eg statistic: probe gravity + independent of clustering bias. • Lensing magnification effect brings higher order corrections to Eg bias dependence + scale dependence
  130. We propose a calibration method: use measured lensing convergence auto

    spectra to estimate the contribution from lensing effect. DESI ELG X Adv. ACTPol LSST X Adv. ACTPol Yang S., Pullen A. R., 2018, MNRAS, 481, 1441
  131. Andy Lawler

  132. Andy Lawler (Baylor University) Advisor: Dr. Viviana Acquaviva (NYC College

    of Technology) ❖ Spectral energy distribution (SED) fitting of z = 1, 2, 3 galaxies is used to understand their physical properties ➢ MCMC sampling techniques have been used historically for posterior inference ▪ Not great for high-dimensional parameter spaces, non-gaussian likelihoods, and multimodal, skewed posteriors ▪ Not great for comparing models in a Bayesian context with varying degrees of complexity Parameter posteriors created with BAGPIPES: Carnall arXiv:1712.04452
  133. ❖ Nested sampling and Bayesian evidence calculation have been used

    for cosmological model comparison (e.g. Trotta doi:10.1080/00107510802066753, Mukherjee & Parkinson, doi:10.1086/501068). ❖ The same principles can be applied to SED fitting to compare models with different star formation histories and different dust laws and help answer: ➢ How many major episodes of star formation do galaxies undergo throughout their lives? ➢ What is the dust attenuation law that is responsible for obscuration of the UV/optical emission from galaxies? ❖ We will also compare results at different redshifts to understand how these answers evolve along cosmic time ❖ CANDELS multi-wavelength data will be used
  134. Faraz Chahili

  135. Separation of Lyman Alpha Emitting galaxies from contaminants in the

    HETDEX survey using machine learning. Dr. Viviana Acquaviva - CUNY New York City College of Technology Faraz Chahili – CUNY City College of New York
  136. HETDEX & its Purpose ◈

  137. Lyman Alpha Emitting (LAEs) Galaxies ◈

  138. Machine Learning ◈ What is Machine Learning? Machine learning is

    a branch of Artificial Intelligence (AI), in which a machine is given the ability to learn and improve through experience, without being explicitly programmed. ◈ Supervised Machine Learning algorithms: ◈ Decision Trees & Random Forests ◈ Support Vector Machines
  139. Our Job Get data from HETDEX Separate genuine emission lines

    from all spectra Classify Lyman Alpha Emitters (LAEs)
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  141. Edmund (Ned) Douglass

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  149. Siddharth Mishra-Sharma

  150. Siddharth Mishra Sharma (NYU) 1. New astrophysical search targets for

    dark matter annihilation and decay [arXiv: 1804.04132] on Galactic halo (with Chang, Lisanti) [arXiv: 1708.09385] on extragalactic groups (with Lisanti, Rodd, Safdi) Targets other than dwarf galaxies can be sensitive targets to probe DM particle properties [1804.04132]
  151. Siddharth Mishra Sharma (NYU) 2. Sensitivity of future cosmological surveys

    to new physics LSST combined with CMB-S4 can break degeneracies in extended cosmological models and discover the minimal neutrino mass [arXiv: 1803.07561] (with Dunkley, Alonso)
  152. Siddharth Mishra Sharma (NYU) 3. Novel statistical methods for new

    physics searches [arXiv: 1612.03173] (with Rodd, Safdi) Code for characterization of different populations of unresolved point sources in any dataset
  153. Xingchen Xu

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  158. Marco Muzio

  159. A consistent multi-messenger picture for UHE cosmic ray and neutrino

    sources Marco Muzio (NYU) Glennys Farrar (NYU), Michael Unger (KIT) UHE cosmic ray source models must: 1. Explain observed UHE CR spectrum and composition 2. Respect gamma-ray (Fermi-LAT) and neutrino (IceCube) bounds 3. Bonus: Explain IceCube astrophysical neutrino flux
  160. UFA model explains spectrum and composition • Allows for injected

    nuclei to undergo photonuclear disintegration in the source environment • Explains the origin of ankle and light composition at EeV energies • Beautifully fits Auger spectrum and composition using escaping mixed-composition M. Unger, G.R. Farrar & L.A. Anchordoqui, Phys. Rev. D 92 (2015) 123001, arXiv:1505.02153
  161. UFA within secondary constraints & explains astrophysical neutrinos • Within

    gamma-ray & neutrino bounds • Adding minimal level of hadronic (pA) interactions can account for astrophysical IceCube flux
  162. Unofficial After Party Open invitation, all welcome Zum Schneider https://goo.gl/maps/pSZbgLiSGmL2

    5:00/6:00PM East Village (ABC city), so plenty options for more entertainment later in the evening
  163. Emily Rice

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  174. Michael Blanton

  175. Sloan Digital Sky Survey Sloan Foundation Telescope Apache Point Observatory

    eBOSS: Large scale structure to redshift z ~ 2.5 MaNGA: 10,000 integral field observations of galaxies Michael Blanton (NYU)
  176. Sloan Digital Sky Survey du Pont Telescope Las Campanas Observatory

    Sloan Foundation Telescope Apache Point Observatory APOGEE-2: stellar spectroscopy in all components of the Milky Way Michael Blanton (NYU)
  177. Sloan Digital Sky Survey Next generation is converting from spectroscopic

    plug-plates to robotic positions and a massive wide-field integral field system. New scientific questions. For a galaxy evolution person like myself, it is about ISM and stellar population questions that underlie our understanding of galaxy observers. New technical challenges: huge opportunity for students interested in learning how a large astronomical survey works. Milky Way Mapper Black Hole Mapper Local Volume Mapper Michael Blanton (NYU)
  178. Jeremy Tinker

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  182. Mehmet Alpaslan

  183. No galaxy is an island Galaxies are tightly linked to

    their environment - the presence of other galaxies has a strong impact on morphology and baryonic content. • How are galaxies influenced by their environments, both local and global? ◦ Specifically, how does the star formation activity in galaxies vary due to environment? • How do we even define ‘environment’? Mehmet Alpaslan NYU
  184. Mehmet Alpaslan NYU SF quenching as galaxies fall into filaments

  185. Groupfinding & halo masses Mehmet Alpaslan NYU Stay tuned for

    extremely accurate halo masses… (fully open source code!)
  186. Ariyeh Maller

  187. Secondary Bias The clustering of halos depends on halo mass.

    But there is additional clustering dependence on most other halo properties including age, concentration, shape and spin. While in the past this has been called assembly bias, it turns out that for high mass halos there is a bias for concentration, but not for age. So secondary bias is a better name for this phenomena
  188. Neighbor Bias When halos are near other massive halos, the

    value of their properties change. If you select halos by a property like age or cvir you are preferentially choosing halos that are near a massive neighbor. This is what causes secondary bias for most halo properties, but not for spin.
  189. Spin Bias Spin doesn’t correlate with neighbor distance, but it

    does with twin distance.
  190. Derek Inman

  191. Λ Λ • •

  192. • • •

  193. Digvijay (Jay) Wadekar

  194. • We have mock simulations for covariance; why an analytic

    method? ◦ Mocks become tougher to simulate as survey volume increases (LSST, Euclid, DESI) Analytic Power spectrum covariance Digvijay (Jay) Wadekar, Roman Scoccimarro (NYU) (within minutes!) • Analytic - Advantages: ◦ Massive speedup (takes a few minutes vs months for mocks) ◦ Cosmological parameter dependence of covariance matrix can be studied • Analytic method - Included effects: ◦ Highly non-trivial survey mask ◦ Redshift space distortions ◦ Bias, Shot Noise ◦ Non-linear structure growth Beat Coupling (also known as Super sample effect)
  195. • Leo-T galaxy Astrophysical constraints on dark matter Digvijay (Jay)

    Wadekar, Glennys Farrar (NYU) • Recent Interest- EDGES observations of first stars ◦ R. Barkana (Nature, 2018): Lower bound on DM-baryon interactions ◦ Gas rich dwarf galaxy 420 kpc away ◦ Observed by HST & (GMRT+WSRT)
  196. Yacine Ali-Haïmoud

  197. Dark matter... A new particle? Primordial black holes?

  198. Testing particle-dark matter with the CMB If DM scatters with

    standard model particles: => heat exchange, spectral distortions of the CMB blackbody => momentum exchange, affects CMB anisotropies/ LSS Detailed rates depend on degree of self-interaction of DM. Standard implicit assumption: DM self-interacts enough that it has a Maxwell-Boltzmann distribution of velocities. What if it doesn’t? How to accurately treat the fundamentally non-linear fluid equations when interactions depend on local relative velocity?
  199. Distortion from Maxwell-Boltzmann (difference in d f/d log(v)) Temperature evolution

    (T/T baryon ) Dashed: Maxwell-Boltzmann Solid: Fokker-Planck
  200. Primordial black holes: more than a DM candidate.

  201. Questions on primordial black holes: - How clustered are they

    born? - How clustered do they become? => Derek Inman
  202. Questions on primordial black holes: - How efficiently do they

    accrete gas in the early Universe, and how much does it affect the CMB? - How efficiently do they form binaries, how likely are these binaries to survive till the present day and be detectable by LIGO?
  203. Eve Armstrong

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  212. Anthony Pullen

  213. Anthony Pullen Center for Cosmology and Particle Physics New York

    University AstroFest New York University September 28, 2018 CII Intensity Mapping & EXCLAIM
  214. The CII Line • Fine structure line of ionized carbon

    • Emission due to CII ion spin transitions caused by collisional excitations with electrons in PDRs • Traces star-forming galaxies, interstellar medium • Typically brightest line in SF galaxies (0.1-1% of total FIR) λ CII = 157μm Gong et al. 2012, Silva et al. 2015, Yue et al. 2015 HI HI e- HI e- e- e- C+ C+ C+ C+ Photo-Dissociation Region (PDR)
  215. CII Measurements • We cross-correlate Planck high-ν maps with BOSS

    quasars and galaxies • Jointly constrain cosmic infrared background (CIB) and CII emission • Marginalizing over dust maps does not reduce foreground errors since dust and CIB have similar spectra • Higher spectral resolution maps will reduce errors by relegating foregrounds to large-scale, line-of-sight modes. Contaminated Switzer, Anderson, AP, Yang (2018) AP, Serra, Chang, Doré, Ho (2017) (95% c.l.)
  216. EXCLAIM - CO & CII Mapper • Instrument: high-altitude balloon

    spectrometer • Objective: Map CO and CII in late cosmic time • Method: Cross-correlate maps with eBOSS galaxy and quasar maps • Science Questions: star formation rate, CO-H 2 abundance, ISM phases, high-z LIM viability The EXperiment for Cryogenic Large-Aperture Intensity Mapping Frequency Range 420-540 GHz CO z-range 0 — 0.64 CII z-range 2.5 — 3.5 Survey Area 400 deg2 Aperture 0.74 m Angular Res. 3.5 arcmin Spectral Res. 512 Potential H 2 Constraints PI: Eric Switzer (NASA Goddard)
  217. My Research Group Shengqi Yang Yucheng Zhang Priyesh Chakraborty E

    G magnification bias calibration 21-cm weak lensing on full sky
  218. Unofficial After Party Open invitation, all welcome Zum Schneider 107

    Ave C, between 7 and 8 https://goo.gl/maps/pSZbgLiSGmL2 5PM East Village (ABC city), so plenty options for more entertainment later in the evening
  219. Thank you all!