Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Ronagh, Pooya"'
Echoed conditional displacement (ECD) gates for bosonic systems have become the key element for real-time quantum error correction beyond the break-even point. These gates are characterized by a single complex parameter $\beta$, and can be constructe
Externí odkaz:
http://arxiv.org/abs/2408.05299
Autor:
Silva, Allyson, Zhang, Xiangyi, Webb, Zak, Kramer, Mia, Yang, Chan Woo, Liu, Xiao, Lemieux, Jessica, Chen, Ka-Wai, Scherer, Artur, Ronagh, Pooya
Publikováno v:
19th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2024). LIPIcs, Volume 310, pp. 1:1-1:22, 2024
Fault-tolerant quantum computation using two-dimensional topological quantum error correcting codes can benefit from multi-qubit long-range operations. By using simple commutation rules, a quantum circuit can be transpiled into a sequence of solely n
Externí odkaz:
http://arxiv.org/abs/2405.17688
We investigate the advantages of using autoregressive neural quantum states as ansatze for classical shadow tomography to improve its predictive power. We introduce a novel estimator for optimizing the cross-entropy loss function using classical shad
Externí odkaz:
http://arxiv.org/abs/2405.06864
In the traditional approach to controlling superconducting qubits using microwave pulses, the field of pulse shaping has emerged in order to assist in the removal of leakage and increase gate fidelity. However, the challenge of scaling microwave cont
Externí odkaz:
http://arxiv.org/abs/2309.04606
Autor:
Marcotte, Frédéric, Mouny, Pierre-Antoine, Yon, Victor, Dagnew, Gebremedhin A., Kulchytskyy, Bohdan, Rochette, Sophie, Beilliard, Yann, Drouin, Dominique, Ronagh, Pooya
Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors. Despite the good performance
Externí odkaz:
http://arxiv.org/abs/2307.09463
Autor:
Crum, Noah A., Sunny, Leanto, Ronagh, Pooya, Laflamme, Raymond, Balu, Radhakrishnan, Siopsis, George
We investigate whether long-run persistent chain Monte Carlo simulation of Langevin dynamics improves the quality of the representations achieved by energy-based models (EBM). We consider a scheme wherein Monte Carlo simulation of a diffusion process
Externí odkaz:
http://arxiv.org/abs/2305.07973
Publikováno v:
Phys. Rev. Research 6, 023250 (2024)
Quantum state tomography (QST) is the art of reconstructing an unknown quantum state through measurements. It is a key primitive for developing quantum technologies. Neural network quantum state tomography (NNQST), which aims to reconstruct the quant
Externí odkaz:
http://arxiv.org/abs/2305.01078
Autor:
Motamedi, Arsalan, Ronagh, Pooya
Publikováno v:
Proceedings of the 41st International Conference on Machine Learning, PMLR 235:36322-36371, 2024
Gibbs sampling from continuous real-valued functions is a challenging problem of interest in machine learning. Here we leverage quantum Fourier transforms to build a quantum algorithm for this task when the function is periodic. We use the quantum al
Externí odkaz:
http://arxiv.org/abs/2210.08104
We investigate the possibility of solving continuous non-convex optimization problems using a network of interacting quantum optical oscillators. We propose a native encoding of continuous variables in analog signals associated with the quadrature op
Externí odkaz:
http://arxiv.org/abs/2209.04415
Publikováno v:
2023 IEEE International Conference on Quantum Computing and Engineering (QCE), Bellevue, Washington, USA
We propose a scheme for solving mixed-integer programming problems in which the optimization problem is translated to a ground-state preparation problem on a set of bosonic quantum field modes (qumodes). We perform numerical demonstrations by simulat
Externí odkaz:
http://arxiv.org/abs/2112.13917