Entanglement distillation between solid-state quantum network nodes
By N. Kalb, A. Reiserer, Peter Conway Humphreys, Jacob J. W. Bakermans, Sten J. Kamerling, Naomi H. Nickerson, Simon C. Benjamin, Daniel J. Twitchen, M. Markham, Ronald Hanson. Science, 2017
453 citations recorded by the source corpus.
A distillation protocol is developed that enhances entanglement between distant nodes of a quantum network. Entangle, swap, purify, repeat The key to a successful quantum internet will be the ability to generate robust entanglement between distant quantum memories. Unavoidable interactions with the environment, however, generally result in the loss of entanglement. Kalb et al. describe an entanglement distillation protocol that could be used to enhance the purity and robustness of entanglement between quantum nodes of a primitive quantum network. Science, this issue p. 928 The impact of future quantum networks hinges on high-quality quantum entanglement shared between network nodes. Unavoidable imperfections necessitate a means to improve remote entanglement by local quantum operations. We realize entanglement distillation on a quantum network primitive of distant electron-nuclear two-qubit nodes. The heralded generation of two copies of a remote entangled state is demonstrated through single-photon–mediated entangling of the electrons and robust storage in the nuclear spins. After applying local two-qubit gates, single-shot measurements herald the distillation of an entangled state with increased fidelity that is available for further use. The key combination of generating, storing, and processing entangled states should enable the exploration of multiparticle entanglement on an extended quantum network.
Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics
View Paper: https://www.semanticscholar.org/paper/bd0845ceb450c33b7256843547b8b351afb1487a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Ronald Hanson
- Stephanie Wehner
- Nicolas Delfosse
- M. Markham
- Daniel J. Twitchen
- Naomi H. Nickerson
- Melissa Guidry
- David Elkouss
In Atomic and Molecular Physics, and Optics
- Ronald Hanson
- Daniel J. Twitchen
- M. Markham
- Stephanie Wehner
- Tim Taminiau
- David Elkouss
- Peter Conway Humphreys
- Nicolas Delfosse
Citations in the corpus
- Integrated Quantum Photonics with Silicon Carbide: Challenges and Prospects (2020, background): “9995) of a color-center spin state and memory-enhanced quantum communication [21]; nanophotonic quantum memories based on rare-earth ensembles [22]; entanglement distillation between distant electron-nuclear two-qubit nodes [23]; and a ten-qubit quantum register based on nuclear spins coupled to a s”
- A Ten-Qubit Solid-State Spin Register with Quantum Memory up to One Minute (2019, methodology): “, the detection of a photon [16,42] (see Supplemental Material for all readout parameters [53]).”
- Quantum internet: A vision for the road ahead (2018, background): “In a very recent experiment, such hybrid network nodes enabled the generation of two remote entangled states on which entanglement distillation could then be performed (85).”
- Deterministic delivery of remote entanglement on a quantum network (2017, background): “Furthermore, the entangled state coherence time could be significantly improved by exploiting long-lived nuclear spin quantum memories [10, 28, 29].”
- Deterministic enhancement of coherent photon generation from a nitrogen-vacancy center in ultrapure diamond (2017, background): “In the longer term, a quantum internet built using this approach depends on entanglement distillation [43], high-efficiency photon frequency conversion to the infrared [44], and coupling NV centers to a photonic cavity.”
- A link layer protocol for quantum networks (2019, unknown): “An example of this is the use of entanglement distillation [35, 53] where two lower quality pairs are combined into one higher quality one.”
- Almost-linear time decoding algorithm for topological codes (2017, background): “Experimental efforts have made rapid progress in recent years [3, 41, 2, 15, 34, 14, 36, 49, 48, 40], and may soon have the capabilities to demonstrate small-scale error correction.”