Materials Research Laboratory

Abstract: A central promise of quantum computing is the prospect of solving certain problems exponentially faster than any classical machine. As we develop the practical components of quantum algorithms—state preparation, algorithmic primitives, and measurement protocols—it becomes increasingly important to understand when quantum resources are truly indispensable and when classical computation can absorb part of the workload.

 A common intuition is that quantum advantage arises from generating enough entanglement or quantum magic. Surprisingly, however, many quantum states require circuit depths far exceeding what their entanglement structure alone would suggest. In the first part of this talk, I will show that in some cases substantial portions of this excess circuit depth can in fact be off‑loaded onto classical processors by replacing deep quantum circuits for state preparation with shallower classically-assisted adaptive circuits.  Here the quantum circuit’s core advantage then is building up the entanglement. 

In contrast, the second part of the talk reveals the opposite phenomenon: we develop an algorithm where numerous quantum circuits exhibiting both high entanglement and significant quantum magic nevertheless admit efficient classical simulation.  These results provide a sharper map of the quantum–classical border, revealing unexpected room for both classical assistance and classical simulation.

Bio: Bryan Clark is a condensed matter theorist specializing in quantum computing and computational condensed matter.  He did his graduate work at University of Illinois.  He did postdoctoral research at the Princeton Center for Theoretical Science,  KITP, and Microsoft Research - Station Q.  Bryan is currently an associate professor in the UIUC Physics department. 

To watch online, go to the IQUIST YouTube channel:   https://www.youtube.com/channel/UCCzAySwQXF8J4kRolUzg2ww