 |
Center for Nonlinear Studies |
This talk will argue that data loading can be an important bottleneck for quantum algorithms. The concept of block encodings, a popular data input model, is introduced, along with its use-cases like the quantum singular value transformation. I will show how our work can leverage structure present in the input matrices to construct low-cost block encoding circuits. I'll also explain how the circuits work and try to convey how I think about them.
Based on https://quantum-journal.org/papers/q-2024-01-11-1226/
Bio: Christoph discovered his passion for quantum theory in the second year of his university studies in Heidelberg, London, and St. Louis, MO. His PhD at the Max-Planck-Institute of Quantum Optics, Munich, focused on chaos in many-body quantum systems. Since 2021, he has been a researcher at Cambridge, UK based quantum computing startup Riverlane, where he thinks about quantum algorithms and applications for tomorrow’s fault-tolerant quantum computers. Among his hobbies is hiking, and he looks forward to exploring some of the trails in Los Alamos.
Host: Samuel Slezak (CCS-3)