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Week of November 12, 2006

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Monday, November 13
4:00 pm - 5:00 pm
Lauritsen 469
Top Flavor Violation: From the B Factories to the LHC
  • Michele Papucci, postdoc in particle physics, UC Berkeley,
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4:15 pm - 5:00 pm
Guggenheim 133 (Lees-Kubota Lecture Hall)
Optical Tomography
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Tuesday, November 14
3:00 pm - 4:00 pm
Jorgensen 74
What's Entanglement Good For?
  • Steve Flammia, research assistant, University of New Mexico,
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3:30 pm - 5:00 pm
Carnegie Observatories, 813 Santa Barbara St., William T. Golden Auditorium
Connecting Galaxy Evolution, Star Formation and the X-ray Background
  • David Ballantyne, department of physics, University of Arizona,
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4:00 pm - 5:00 pm
Lauritsen 248
Top Quark Mass
  • Florencia Canelli, Wilson Fellow, Fermilab,
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4:00 pm - 5:00 pm
East Bridge 114
A Revolution in Numerical Simulations of Binary Black Holes
  • Mark Scheel, senior research fellow in theoretical astrophysics, Caltech,
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Wednesday, November 15
12:00 pm - 1:00 pm
On the Spectral Theory of 1-D Continuous Schrödinger Operator with Unbounded Potential
  • Stanislav Molchanov, professor of mathematics, University of North Carolina, Charlotte,
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4:00 pm - 5:00 pm
Arms 155 (Robert P. Sharp Lecture Hall)
The Ends of Stellar Lives at the Galactic Center
  • Michael Muno, postdoctoral researcher in astronomy, Caltech,
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Thursday, November 16
4:00 pm - 5:00 pm
East Bridge 201 (Richard P. Feynman Lecture Hall)
Symmetries of the Early Universe and the Origin of Matter
  • Michael Ramsey-Musolf, senior research associate in physics, Caltech,
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Friday, November 17
11:00 am - 12:00 pm
Lauritsen Library
Parity and Time Reversal Violation in Atoms and Nuclei, and Test of Unification Theories
  • Victor Flambaum, University of New South Wales and Argonne National Laboratory,
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11:00 am - 12:00 pm
Lauritsen 469
Topic to be announced.
  • Albion Lawrence, assistant professor of physics, Brandeis University,
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1:00 pm - 2:00 pm
Lauritsen 469
SLE for String Theorists
  • Paul Wiegmann, professor of physics, University of Chicago,
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2:30 pm - 4:00 pm
Moore 239
Statistical Learning II: Representation, Generalization, and Examples.
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