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The core Python language is not particularly powerful or fast for numerical computing.  Fortunately, there is a large "numerical python" library, "numpy", that is a standard part of any Python-using scientist's toolkit.  I will present numpy, the associated "scientific python" library, "scipy", and the popular "matplotlib" plotting library.

Hypermassive neutron stars (HMNS) can be briefly formed after a binary neutron star merger and are likely to be highly deformed and strongly oscillating. These oscillations may be seen as modulation of the associated short gamma-ray burst and could provide observational evidence for the HMNS phase. I will discuss the prospects for their detection and the important physical information that can be gained by their observation.

 Python is a widely used programming language for scientific
computing, data analysis, and machine learning. This tutorial will
feature an introduction for those with little or no background.

In this talk I review some of what we have learned from string theory about the criteria one needs for a quantum theory to be able to consistently couple to quantum gravity (the landscape) as opposed to one that looks consistent but cannot be consistently coupled to gravity (the swampland).  Moreover, I review some of the cosmological implications of these conditions for our universe.

Topology illuminates properties of geometric spaces which are independent of scale.  Scale-independent features of physical systems play an important role, for example when deducing the large-scale behavior from a small-scale description.  After an introduction to basic topological ideas, I will discuss two joint results with Mike Hopkins, one an application to string theory and the other an application to condensed matter theory.

Julia is a modern programming language that is (so they say) as easy to use as Python and as fast as Fortran, combined with the expressive power of Lisp. I will introduce the language via examples taken from linear algebra, differential equations, and scientific visualization.

In quantum error correcting codes, there is a distinction
between coherent and incoherent noise. Coherent noise can cause the
average infidelity to accumulate quadratically when a fixed channel is
applied many times in succession, rather than linearly as in the case
of incoherent noise. I will present a proof that unitary single qubit
noise in the 2D toric code with minimum weight decoding is mapped to
less coherent logical noise, and as the code size grows, the coherence
of the logical noise channel is suppressed. In the process, I will
describe how to characterize the coherence of noise using either the
growth of infidelity or the relation between the diamond distance from
identity and the average infidelity. I will explain how coherence in
the noise on physical qubits is transformed by error correction in
stabilizer codes. Then, I will sketch the proof that coherence is
suppressed for the 2D toric code. The result holds even when the
single qubit unitary rotation are allowed to have arbitrary directions
and angles, so long as the angles are below a threshold, and even when
the rotations are correlated. Joint work with John Preskill.