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Found 6 papers, 1 papers with code
Symmetry breaking in geometric quantum machine learning in the presence of noise
This work studies the behavior of EQNN models in the presence of noise.
Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images
Quantum Neural Networks (QNNs) are suggested as one of the quantum algorithms which can be efficiently simulated with a low depth on near-term quantum hardware in the presence of noises.
Running the Dual-PQC GAN on noisy simulators and real quantum hardware
In an earlier work, we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of a quantum GAN.
Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics
Generative models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo simulations.
Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors
We introduce and analyze a new prototype of quantum GAN (qGAN) employed in continuous-variable (CV) quantum computing, which encodes quantum information in a continuous physical observable.
Bell Diagonal and Werner state generation: entanglement, non-locality, steering and discord on the IBM quantum computer
We propose the first correct special-purpose quantum circuits for preparation of Bell-diagonal states (BDS), and implement them on the IBM Quantum computer, characterizing and testing complex aspects of their quantum correlations in the full parameter space.
Quantum Physics Information Theory Information Theory
