33 citations · 124 across the 17 of their papers we have counts for
4 papers · 1 filter
Learning Equivariant Maps with Variational Quantum Circuits
Zachary P. Bradshaw, Ethan N. Evans, Matthew Cook +1
Geometric quantum machine learning uses the symmetries inherent in data to design tailored machine learning tasks with reduced search space dimension. The field has been well-studi…
Quantum Algorithms for Realizing Symmetric, Asymmetric, and Antisymmetric Projectors
Margarite L. LaBorde, Soorya Rethinasamy, Mark M. Wilde
In quantum computing, knowing the symmetries a given system or state obeys or disobeys is often useful. For example, Hamiltonian symmetries may limit allowed state transitions or s…
Logarithmic-Depth Quantum Circuits for Hamming Weight Projections
Soorya Rethinasamy, Margarite L. LaBorde, Mark M. Wilde
A pure state of fixed Hamming weight is a superposition of computational basis states such that each bitstring in the superposition has the same number of ones. Given a Hilbert spa…
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention
Ethan N. Evans, Matthew Cook, Zachary P. Bradshaw +1
The recent exploding growth in size of state-of-the-art machine learning models highlights a well-known issue where exponential parameter growth, which has grown to trillions as in…