JuliaCon 2023

Faster Simulation of Quantum Entanglement with BPGates.jl
07-27, 14:20–14:30 (US/Eastern), 32-082

BPGates.jl is a tool for extremely fast simulation of quantum circuits, as long as the circuit is limited to only performing entanglement purification over Bell pairs.


Quantum dynamics is famously infeasible to simulate efficiently by classical hardware. However, there are important classes of processes that can be simulated efficiently: Gaussian optics and Clifford circuits being the prototypical examples. In particular, the ease of simulating Clifford circuits was crucial for the development of quantum error correcting codes.

The purification of entangled Bell pairs can already be efficiently (polynomially) simulated by Clifford circuits. However, if we restrict ourselves to only purification circuits, not general Clifford circuits, the simulation can be even faster, both asymptotically and practically.

BPGates.jl implements this new simulation algorithm, providing for simulating bilateral quantum gates in 𝒪(1) assymptotic time (and ns wall time), instead of the typical 𝒪(n) complexity. We introduce the new algorithm, implementation, and discuss applications, including the immense effect it has had on simulating and optimizing entanglement purification circuits.

I am a researcher in Quantum Information Science. I obtained my PhD in quantum physics at the Yale Quantum Institute at 2019 and have worked as a postdoc and a research scientist at Harvard and MIT since then. Last year I started my own group as an assistant professor at UMass Amherst, in the College of Information & Computer Sciences.

My open source biography starts with my involvement in the SymPy project, developing its plotting module and differential geometry module in 2012. Since then I have counted myself as one of the scientific programming hackers in the python (and more recently julia) ecosystems, in particular with focus on quantum information science.

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