Search Results for author:
Found 9 papers, 2 papers with code
Anomaly Detection in Aeronautics Data with Quantum-compatible Discrete Deep Generative Model
Moreover, the DVAE model with RBM prior can be easily integrated with quantum sampling by outsourcing its generative process to measurements of quantum states obtained from a quantum annealer or gate-model device.
Character randomized benchmarking for non-multiplicity-free groups with applications to subspace, leakage, and matchgate randomized benchmarking
Finally, we derive a scalable RB protocol for the matchgate group, a group that like the Clifford group is non-universal but becomes universal with the addition of one additional gate.
Quantum Physics
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder
Quantum machine learning is touted as a potential approach to demonstrate quantum advantage within both the gate-model and the adiabatic schemes.
Planning for Compilation of a Quantum Algorithm for Graph Coloring
Previous work demonstrated that temporal planning is an attractive approach for part of this compilationtask, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to the MaxCut problem on a quantum processor architecture.
Optimizing quantum heuristics with meta-learning
Variational quantum algorithms, a class of quantum heuristics, are promising candidates for the demonstration of useful quantum computation.
Quantum-assisted associative adversarial network: Applying quantum annealing in deep learning
We present an algorithm for learning a latent variable generative model via generative adversarial learning where the canonical uniform noise input is replaced by samples from a graphical model.
A flexible high-performance simulator for verifying and benchmarking quantum circuits implemented on real hardware
Here we present qFlex, a flexible tensor network based quantum circuit simulator.
Quantum Physics
Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation
Our hybrid methods use solutions found by temporal planning to warm start CP, leveraging the ability of the former to find satisficing solutions to problems with a high degree of task optionality, an area that CP typically struggles with.
Compiling quantum circuits to realistic hardware architectures using temporal planners
We investigate the application of temporal planners to the problem of compiling quantum circuits to newly emerging quantum hardware.
