Talks

We study the problem of learning a Hamiltonian given copies of its Gibbs state at a known inverse temperature. Anshu et al. recently studied the sample complexity (number of copies of the Gibbs state needed) of this problem for geometrically local Hamiltonians. In the high-temperature regime, their algorithm has sample complexity polynomial in the system size, temperature, and accuracy. Their algorithm can also be implemented with polynomial, but suboptimal, time complexity. Here, we study the same question for a more general class of Hamiltonians and present an algorithm that solves this problem with improved sample complexity and time complexity linear in the sample size. Furthermore, we prove a matching lower bound showing that our algorithm's sample complexity is optimal, and hence our time complexity is also optimal. Joint work with Robin Kothari and Ewin Tang.

 

Academic science reflects the context in which science is conducted. Thus, the academic scientific enterprise struggles with privilege, racism, sexism, ableism, and homophobia, in Canada, as around the world. In this talk, I will address the uncomfortable and sometimes difficult conversations we must have in order to get to the real work of identifying and removing barriers that limit access and engagement in the scientific enterprise for the full diversity of humanity. We live within a myth of meritocracy in academia and are failing to achieve our full potential as a sector. Moving on from self-awareness as individuals or organizations, we can start to identify the tools and skill sets that individuals and collectives need in order to create cultures of care that achieve inclusive excellence and the very best scientific outputs.

Academic science reflects the context in which science is conducted.  Thus, the academic scientific enterprise struggles with privilege, racism, sexism, ableism, and homophobia, in Canada, as around the world.  In this talk, I will address the uncomfortable and sometimes difficult conversations we must have in order to get to the real work of identifying and removing barriers that limit access and engagement in the scientific enterprise for the full diversity of humanity.  We live within a myth of meritocracy in academia and are failing to achieve our full potential as a sector.  Moving on from self-awareness as individuals or organizations, we can start to identify the tools and skill sets that individuals and collectives need in order to create cultures of care that achieve inclusive excellence and the very best scientific outputs.  

Zoom Link: https://pitp.zoom.us/j/91715376839?pwd=TnBIM1NNek4zOFNyVWFnMHMySE02Zz09