Storing single photons emitted by a quantum memory on a highly excited Rydberg state

Distante, Emanuele; Farrera, Pau; Padrón-Brito, Auxiliadora; Paredes-Barato, David; Heinze, Georg; Riedmatten, Hugues de

doi:10.1038/ncomms14072

Cited by 50 publications

(39 citation statements)

References 46 publications

(87 reference statements)

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“…Figure 1 illustrates the principles of NIR-II image-guided ovarian tumor resection based on in vivo self-assembly of DNA functionalized NIR-II lanthanide probes for improved tumor targeting by two-staged in sequence injection. The NIR-II fluorescence NaGdF 4 : 5% Nd@NaGdF 4 DCNPs were fabricated by the successive layer-by-layer (SILAR) method with uniform particle size of ~7.5 nm and highly efficient 1060 nm NIR-II emission under 808 nm laser irradiation 27 (Figs. 1 and 2a, d, e ).…”

Section: Resultsmentioning

confidence: 99%

“…The contrast agent emitting within the NIR-II light has diminished atuofluorescence and allows centimeters imaging depth at low resolution and microscale resolution of anatomical feature that are otherwise unresolvable within the traditional NIR-I region. Thus far, NIR-II contrast agents including SWNTs 23 , 24 , QDs 25 , 26 , DCNPs 27 – 29 , and organic dyes 30 – 33 have been established for in vivo imaging of vascular flow, lymphatic, and tumors. Although the organic dyes shows great potentials to facilitate Food and Drug Administration approval and clinical translation, these small molecule probes typically experienced short time tumor retention because of their rapid clearance, which hindered the following precision imaging guided resection.…”

Section: Discussionmentioning

confidence: 99%

“…However, these agents are suboptimal for reflectance-based intraoperative imaging due to limited penetration depth (1–3 mm) and high-tissue autofluorescence 20 – 22 . Second-window near-infrared fluorescence (NIR-II, 900–1700 nm) probes such as single-walled carbon nanotubes (SWNTs) 23 , 24 , quantum dots (QDs) 25 , 26 , lanthanide-based downconversion nanoparticles (DCNPs) 27 – 29 , and organic dyes 30 – 33 are promising for in vivo fluorescence imaging due to sub-10-µm high-resolution imaging at a few centimeters tissue penetration depth and low-tissue autofluorescence 23 – 33 , which are promising candidates for both preoperative imaging and intraoperative reality 28 . Especially, DCNPs play a very important role in the NIR-II fluorescent bioimaging applications due to their distinct properties, such as highly controlled particle size, nonphotobleaching, long lifetime and high-efficiency optical properties 27 – 29 .…”

Section: Introductionmentioning

confidence: 99%

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NIR-II nanoprobes in-vivo assembly to improve image-guided surgery for metastatic ovarian cancer

et al. 2018

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Local recurrence is a common cause of treatment failure for patients with solid tumors. Tumor-specific intraoperative fluorescence imaging may improve staging and debulking efforts in cytoreductive surgery and, thereby improve prognosis. Here, we report in vivo assembly of the second near-infrared window (NIR-II) emitting downconversion nanoparticles (DCNPs) modified with DNA and targeting peptides to improve the image-guided surgery for metastatic ovarian cancer. The NIR-II imaging quality with DCNPs is superior to that of clinically approved ICG with good photostability and deep tissue penetration (8 mm). Stable tumor retention period experienced 6 h by in vivo assembly of nanoprobes can be used for precise tumor resection. Superior tumor-to-normal tissue ratio is successfully achieved to facilitate the abdominal ovarian metastases surgical delineation. Metastases with ≤1 mm can be completely excised under NIR-II bioimaging guidance. This novel technology provides a general new basis for the future design of nanomaterials for medical applications.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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NIR-II nanoprobes in-vivo assembly to improve image-guided surgery for metastatic ovarian cancer

et al. 2018

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“…Our work addresses both the limits and potentials of all-optical scalability as an alternative route towards long distance quantum communication. While the conventional route based on the standard quantum repeater model [19][20][21][22][23][24] relies more on the development of the platforms for light-matter interaction and long-lived quantum memories [64][65][66], our protocol, by removing the necessity of all the other demanding technologies, puts more weight on the photon sources. The major challenge for implementing our protocol is thus the preparation of large, multi-photon entangled encoded states.…”

Section: Discussionmentioning

confidence: 99%

Fundamental building block for all-optical scalable quantum networks

2019

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Major obstacles against efficient long distance quantum communication are photon losses during transmission and the probabilistic nature of Bell measurement causing exponential scaling in time and resource with distance. To overcome these difficulties, while conventional quantum repeaters require matter-based operations with long-lived quantum memories, recent proposals have employed encoded multiple photons in entanglement, providing an alternative way for scalability. In pursuing scalable quantum communications, naturally arising questions are thus whether any ultimate limit exists in all-optical scalability, and whether and how it can be achieved. Motivated by these questions, we derive the fundamental limits of the efficiency and loss-tolerance of the Bell measurement with multiple photons, restricted not by protocols but by the laws of physics, i.e. linear optics and no-cloning theorem. We then propose a Bell measurement scheme with linear optics, which enables one to reach both the fundamental limits: one by linear optics and the other by the no-cloning theorem. The quantum repeater based on our scheme allows one to achieve fast and efficient quantum communication over arbitrary long distances, outperforming previous all-photonic and matter-based protocols. Our work provides a fundamental building block for quantum networks within but toward the ultimate limits of all-optical scalability.arXiv:1804.09342v3 [quant-ph]

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“…The evaluation of (97) and (98) therefore is yielded in an iterative manner through theα mk (B), α mk (A),β kt (A),β kt (B) and η mkt , and the K * optimal number of bases, K, is determined with respect to (89) such that K * = arg max…”

Section: Factorization Unitarymentioning

confidence: 99%

Optimizing High-Efficiency Quantum Memory with Quantum Machine Learning for Near-Term Quantum Devices

Gyöngyösi

Imre

2020

Sci Rep

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Quantum memories are a fundamental of any global-scale quantum Internet, high-performance quantum networking and near-term quantum computers. A main problem of quantum memories is the low retrieval efficiency of the quantum systems from the quantum registers of the quantum memory. Here, we define a novel quantum memory called high-retrieval-efficiency (HRE) quantum memory for near-term quantum devices. An HRE quantum memory unit integrates local unitary operations on its hardware level for the optimization of the readout procedure and utilizes the advanced techniques of quantum machine learning. We define the integrated unitary operations of an HRE quantum memory, prove the learning procedure, and evaluate the achievable output signal-to-noise ratio values. We prove that the local unitaries of an HRE quantum memory achieve the optimization of the readout procedure in an unsupervised manner without the use of any labeled data or training sequences. We show that the readout procedure of an HRE quantum memory is realized in a completely blind manner without any information about the input quantum system or about the unknown quantum operation of the quantum register. We evaluate the retrieval efficiency of an HRE quantum memory and the output SNR (signalto-noise ratio). The results are particularly convenient for gate-model quantum computers and the near-term quantum devices of the quantum Internet.1. We define a novel quantum memory called high-retrieval-efficiency (HRE) quantum memory.2. An HRE quantum memory unit integrates local unitary operations on its hardware level for the optimization of the readout procedure and utilizes the advanced techniques of quantum machine learning.3. We define the integrated unitary operations of an HRE quantum memory, prove the learning procedure, and evaluate the achievable output signal-to-noise ratio values. We prove that local unitaries of an HRE quantum memory achieve the optimization of the readout procedure in an unsupervised manner without the use of any labeled data or training sequences.4. We evaluate the retrieval efficiency of an HRE quantum memory and the output SNR.5. The proposed results are convenient for gate-model quantum computers and near-term quantum devices.This paper is organized as follows. Section 2 defines the system model and the problem statement. Section 3 evaluates the integrated local unitary operations of an HRE quantum memory. Section 4 proposes the retrieval efficiency in terms of the achievable output SNR values. Finally, Section 5 concludes the results. Supplemental material is included in the Appendix.

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Storing single photons emitted by a quantum memory on a highly excited Rydberg state

Cited by 50 publications

References 46 publications

NIR-II nanoprobes in-vivo assembly to improve image-guided surgery for metastatic ovarian cancer

NIR-II nanoprobes in-vivo assembly to improve image-guided surgery for metastatic ovarian cancer

Fundamental building block for all-optical scalable quantum networks

Optimizing High-Efficiency Quantum Memory with Quantum Machine Learning for Near-Term Quantum Devices

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