scholarly journals High-fidelity, low-latency polarization quantum state transmissions over a hollow-core conjoined-tube fiber at around 800 nm

2021 ◽  
Author(s):  
Xinyu Chen ◽  
Wei Ding ◽  
Yingying Wang ◽  
Shoufei Gao ◽  
Feixiang Xu ◽  
...  
Keyword(s):  
Quantum State ◽  
Low Latency ◽  
High Fidelity ◽  
Hollow Core

scholarly journals A phononic interface between a superconducting quantum processor and quantum networked spin memories

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Tomáš Neuman ◽  
Matt Eichenfield ◽  
Matthew E. Trusheim ◽  
Lisa Hackett ◽  
Prineha Narang ◽  
...  
Keyword(s):  
Quantum State ◽  
Piezoelectric Transducers ◽  
High Fidelity ◽  
Hybrid Architecture ◽  
Quantum Networks ◽  
Superconducting Circuit ◽  
Artificial Atom ◽  
Experimental Parameters ◽  
Quantum Processor ◽  
State Spin

AbstractWe introduce a method for high-fidelity quantum state transduction between a superconducting microwave qubit and the ground state spin system of a solid-state artificial atom, mediated via an acoustic bus connected by piezoelectric transducers. Applied to present-day experimental parameters for superconducting circuit qubits and diamond silicon-vacancy centers in an optimized phononic cavity, we estimate quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of superconducting circuit quantum computing and artificial atoms, the hybrid architecture provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.

Reconstructing a quantum state with a variational autoencoder

2021 ◽  
Author(s):  
Chuangtao Chen ◽  
Zhimin He ◽  
Zhiming Huang ◽  
Haozhen Situ
Keyword(s):  
Quantum State ◽  
Circuit Simulation ◽  
Entanglement Entropy ◽  
Ghz State ◽  
High Fidelity ◽  
Training Samples ◽  
Variational Autoencoder ◽  
Minimum Number ◽  
Number Formula ◽  
State Tomography

Quantum state tomography (QST) is an important and challenging task in the field of quantum information, which has attracted a lot of attentions in recent years. Machine learning models can provide a classical representation of the quantum state after trained on the measurement outcomes, which are part of effective techniques to solve QST problem. In this work, we use a variational autoencoder (VAE) to learn the measurement distribution of two quantum states generated by MPS circuits. We first consider the Greenberger–Horne–Zeilinger (GHZ) state which can be generated by a simple MPS circuit. Simulation results show that a VAE can reconstruct 3- to 8-qubit GHZ states with a high fidelity, i.e., 0.99, and is robust to depolarizing noise. The minimum number ([Formula: see text]) of training samples required to reconstruct the GHZ state up to 0.99 fidelity scales approximately linearly with the number of qubits ([Formula: see text]). However, for the quantum state generated by a complex MPS circuit, [Formula: see text] increases exponentially with [Formula: see text], especially for the quantum state with high entanglement entropy.

Low latency transmission over 400 m Hollow-Core-Fiber Cable at 100G PAM-4 per wavelength

2021 ◽  
Author(s):  
Jose. M Castro ◽  
Bulent Kose ◽  
Rick Pimpinella ◽  
Paul Huang ◽  
Brett Lane ◽  
...  
Keyword(s):  
Low Latency ◽  
Hollow Core ◽  
Core Fiber

scholarly journals Hollow‐Core Fibers: Low‐Latency WDM Intensity‐Modulation and Direct‐Detection Transmission Over >100 km Distances in a Hollow Core Fiber (Laser Photonics Rev. 15(9)/2021)

2021 ◽  
Vol 15 (9) ◽  
pp. 2170048
Author(s):  
Yang Hong ◽  
Kyle R. H. Bottrill ◽  
Thomas D. Bradley ◽  
Hesham Sakr ◽  
Gregory T. Jasion ◽  
...  
Keyword(s):  
Fiber Laser ◽  
Direct Detection ◽  
Intensity Modulation ◽  
Low Latency ◽  
Hollow Core ◽  
Core Fiber
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