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X-WR-CALDESC:Events for INPA
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DTSTART:20170312T100000
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DTSTART;TZID=America/Los_Angeles:20171006T120000
DTEND;TZID=America/Los_Angeles:20171006T130000
DTSTAMP:20260527T172000
CREATED:20170908T175303Z
LAST-MODIFIED:20171002T160637Z
UID:263-1507291200-1507294800@inpa.lbl.gov
SUMMARY:Marie Lau (UC Santa Cruz) - Quasars Probing Quasars: the Circumgalactic Medium Surrounding z ~ 2 Quasars
DESCRIPTION:Understanding the circumgalactic medium–the gaseous halo surrounding a galaxy\, is an integral part to understanding galaxy evolution. The z ~ 2-3 universe is interesting as this is when the star formation rate and AGN activity peak. My work concludes the decade-long Quasars Probing Quasars survey designed for studying massive galaxy formation and quasar feedback. I use background quasar sightlines that pass close to foreground quasars to study the circumgalactic medium of quasar-host galaxies in absorption. My sample of 149 quasar pairs involve spectra taken with 17 different optical and near IR instruments. I present results on the statistical and physical properties of the quasar circumgalactic medium. My results pose challenges for cosmological hydrodynamic simulations to produce a substantial cool gas reservoir surrounding quasars\, that is also enriched and exhibits extreme kinematics.\n\n\nI will discuss other science goals that can be facilitated using the spectral databases and absorption-line analysis tools built. If there is interest\, I will show preliminary results on a peculiar tidal disruption event and evidence for deep internal mixing in red giants.
URL:https://inpa.lbl.gov/event/marie-lau-uc-santa-cruz/
LOCATION:50A-5132- Sessler\, 50A-5132 Sessler Conference Room\, CA
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DTSTART;TZID=America/Los_Angeles:20171013T120000
DTEND;TZID=America/Los_Angeles:20171013T130000
DTSTAMP:20260527T172000
CREATED:20171010T231405Z
LAST-MODIFIED:20171019T173539Z
UID:277-1507896000-1507899600@inpa.lbl.gov
SUMMARY:Michael Walther (UCSB) - New Constraints on Thermal Evolution in the IGM from the Small Scale Lyα Forest Power Spectrum
DESCRIPTION:The line-of-sight power spectrum (P_F(k)) of the Ly-α forest has proven to be a valuable tool for doing cosmological observations. It also not only allows to constrain cosmological parameters\, but enables us to measure the thermal state of the IGM at redshifts z>1.8. While at large scales (k<0.02 s/km) P_F(k) has been accurately measured using the large number (10^3-10^5) of quasar sightlines from SDSS and BOSS\, there are much less spectra available at smaller scales (larger k). Prior power spectrum measurements from high-resolution data only used several times less (QSO) spectra in our redshift range about 15 years ago whereas a few hundred became available in the meantime. We therefore performed a new measurement using 74 quasar sightlines with 1.8<z<3.4 significantly improving the precision of the small-scale P_F(k). Using this additional precision on small scales combined with the BOSS measurements on large scales enables us to accurately constrain the thermal cutoff scale of the IGM set by a combination of temperature broadening of Ly-α forest lines\, and ‘Jeans’ smoothing due to baryonic pressure support. We perform an MCMC analysis based on Gaussian process based techniques for interpolation between a grid of high-resolution hydrodynamical simulations and using our new high-resolution dataset\, the BOSS data\, a recent X-SHOOTER analysis\, and a previous HIRES/MIKE analysis at higher redshifts. This allows us to measure thermal evolution in the IGM from z=5.4 to z=1.8 showing a suggestive peak at z~3.3 that might be attributed to He reionization. These constraints will help solving the existing discrepancies in the IGM thermal evolution between different works using different techniques as existing degeneracies between different thermal parameters in the existing measurements can be broken in our analysis.and can be used to place limits on possible exotic sources of heating. Additionally a better knowledge of thermal evolution will also lead to better constraints of e.g. the nature of dark matter or neutrino masses by breaking degeneracies in those measurements and thereby improve our knowledge of the underlying cosmology.
URL:https://inpa.lbl.gov/event/michael-walther-ucsb-new-constraints-on-thermal-evolution-in-the-igm-from-the-small-scale-ly%ce%b1-forest-power-spectrum/
LOCATION:50A-5132- Sessler\, 50A-5132 Sessler Conference Room\, CA
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20171020T120000
DTEND;TZID=America/Los_Angeles:20171020T130000
DTSTAMP:20260527T172000
CREATED:20171019T173727Z
LAST-MODIFIED:20171019T173801Z
UID:281-1508500800-1508504400@inpa.lbl.gov
SUMMARY:Prabhat (NERSC at LBL) - Deep Learning for Science
DESCRIPTION:Deep Learning has revolutionized the fields of computer vision\, speech recognition and control systems. Can Deep Learning (DL) work for scientific problems? This talk will explore a variety of DOE/LBL applications that are currently benefiting from Deep Learning. We will review classification and regression problems in astronomy\, cosmology\, neuroscience\, genomics and high-energy physics. We will outline several short and long-term challenges at the frontier of DL research\, and speculate about the future of DL for data-intensive science.
URL:https://inpa.lbl.gov/event/prabhat-nersc-at-lbl-deep-learning-for-science/
LOCATION:50A-5132- Sessler\, 50A-5132 Sessler Conference Room\, CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20171027T120000
DTEND;TZID=America/Los_Angeles:20171027T130000
DTSTAMP:20260527T172000
CREATED:20171024T173237Z
LAST-MODIFIED:20171024T173314Z
UID:297-1509105600-1509109200@inpa.lbl.gov
SUMMARY:Xavier Prochaska (UCSD) - Deep Learning of Quasar Spectra
DESCRIPTION:I will describe our development of a convolutional neural network (CNN) to learn to search for and characterize absorption lines in quasar spectra. Specifically\, the algorithm discovers and measures the redshift and Hydrogen column density of damped Lya systems (DLAs). These systems dominate the neutral hydrogen gas of the universe\, trace the interstellar medium of distant galaxies\, and offer cosmological constraints on the build up of gas and heavy elements across cosmic time. I will discuss the lessons learned employing CNN techniques on large spectral datasets and the prospects for future analysis.
URL:https://inpa.lbl.gov/event/xavier-prochaska-ucsd-deep-learning-of-quasar-spectra/
LOCATION:50A-5132- Sessler\, 50A-5132 Sessler Conference Room\, CA
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