Experimental plug and play quantum coin flipping

Pappa, Anna; Jouguet, Paul; Lawson, Thomas; Chailloux, André; Legré, M; Trinkler, Patrick; Kerenidis, Iordanis; Diamanti, Eleni

doi:10.1038/ncomms4717

Cited by 55 publications

(114 citation statements)

References 44 publications

(70 reference statements)

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“…(8), this time with an apparent fractal dimension of D = 1.1, as indicated by the solid (red) line superimposed on the data in Figure 4(b). The nearly linear structure suggested by this low fractal dimension is consistent with atomic force microscopy images of BSA aggregates 37 .…”

Section: Experimental Studies Of Model Fractal Aggregatessupporting

confidence: 81%

Holographic characterization of colloidal fractal aggregates

et al. 2016

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In-line holographic microscopy images of micrometer-scale fractal aggregates can be interpreted with an effective-sphere model to obtain each aggregate’s size and the population-averaged fractal dimension. We demonstrate this technique experimentally using model fractal clusters of polystyrene nanoparticles and fractal protein aggregates composed of bovine serum albumin and bovine pancreas insulin.

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Section: Experimental Studies Of Model Fractal Aggregatessupporting

confidence: 81%

Holographic characterization of colloidal fractal aggregates

et al. 2016

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“…For example, a great range of quantum communication protocols beyond QKD have been studied in recent years 161 and their development has directly benefited from research in QKD. These include, for instance, quantum bit commitment, [162][163][164] quantum secret sharing, [165][166][167] quantum coin flipping, 168,169 quantum fingerprinting, 170,171 quantum digital signatures, 172,173 blind quantum computing 174,175 and position-based quantum cryptography. [176][177][178] It is known that some of those protocols, such as quantum bit commitment and position-based quantum cryptography, cannot be perfectly achieved with unconditional security.…”

Section: Resultsmentioning

confidence: 99%

Practical challenges in quantum key distribution

Diamanti¹,

Lo²,

Qi³

et al. 2016

npj Quantum Inf

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582

447

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Quantum key distribution (QKD) promises unconditional security in data communication and is currently being deployed in commercial applications. Nonetheless, before QKD can be widely adopted, it faces a number of important challenges such as secret key rate, distance, size, cost and practical security. Here, we survey those key challenges and the approaches that are currently being taken to address them. For thousands of years, human beings have been using codes to keep secrets. With the rise of the Internet and recent trends to the Internet of Things, our sensitive personal financial and health data as well as commercial and national secrets are routinely being transmitted through the Internet. In this context, communication security is of utmost importance. In conventional symmetric cryptographic algorithms, communication security relies solely on the secrecy of an encryption key. If two users, Alice and Bob, share a long random string of secret bits-the key-then they can achieve unconditional security by encrypting their message using the standard one-time-pad encryption scheme. The central question then is: how do Alice and Bob share a secure key in the first place? This is called the key distribution problem. Unfortunately, all classical methods to distribute a secure key are fundamentally insecure because in classical physics there is nothing preventing an eavesdropper, Eve, from copying the key during its transit from Alice to Bob. On the other hand, standard asymmetric or public-key cryptography solves the key distribution problem by relying on computational assumptions such as the hardness of factoring. Therefore, such schemes do not provide information-theoretic security because they are vulnerable to future advances in hardware and algorithms, including the construction of a large-scale quantum computer.

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“…This proposal is consistent with previous ex situ studies that have demonstrated that bovine insulin forms filamentary aggregates. 44–46 …”

Section: Resultsmentioning

confidence: 99%

Holographic Characterization of Protein Aggregates

Wang

Zhong

Ruffner

et al. 2016

Journal of Pharmaceutical Sciences

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We demonstrate how holographic video microscopy can be used to detect, count, and characterize individual micrometer-scale protein aggregates as they flow down a microfluidic channel in their native buffer. Holographic characterization directly measures the radius and refractive index of subvisible protein aggregates and offers insights into their morphologies. The measurement proceeds fast enough to build up population averages for time-resolved studies and lends itself to tracking trends in protein aggregation arising from changing environmental factors. Information on individual particle’s refractive indexes can be used to differentiate protein aggregates from such contaminants as silicone droplets. These capabilities are demonstrated through measurements on samples of bovine pancreas insulin aggregated through centrifugation and of bovine serum albumin aggregated by complexation with a polyelectrolyte. Differentiation is demonstrated with samples that have been spiked with separately characterized silicone spheres. Holographic characterization measurements are compared with results obtained with microflow imaging and dynamic light scattering.

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Experimental plug and play quantum coin flipping

Cited by 55 publications

References 44 publications

Holographic characterization of colloidal fractal aggregates

Holographic characterization of colloidal fractal aggregates

Practical challenges in quantum key distribution

Holographic Characterization of Protein Aggregates

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