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
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 email@example.com
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
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
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)
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.
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
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.)
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
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.
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.
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
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
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
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
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]
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
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)
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
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
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.
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)
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?
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?
• 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)
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.)
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)