arXiv subjects

Nathaniel R. Miller

Publications and source records attributed to Nathaniel R. Miller.

3 recordsLinked to original sources

arXiv2025

Cost vector analysis & multi-path entanglement routing in quantum networks

We present a static framework for analysing quantum routing protocols that we call the \textit{cost-vector formalism}. Here, quantum networks are recast as multi-graphs where edges represent two-qubit entanglement resources that \textit{could} exist under some sequence of operations. Each edge is weighted with a \textit{transmission probability} that represents the likelihood of the pair existing and a \textit{coherence probability} which is the likelihood that the pair is suitable for teleportation. Routing operations such as entanglement swapping and purification are then interpreted as \textit{contractions on the multi-graph} with relatively simple rules for updating the edge-weights. Moreover, we extend our formalism to include routing scenarios over time by developing a compatible resource theory for quantum memories. We develop rudimentary greedy algorithms for routing in this framework and test them over a variety of toy networking scenarios. Our results indicate that congestion in quantum networks does not improve significantly when more nodes (computers) are added. Rather, we find that congestion is all but eliminated by waiting a small amount of time.

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arXiv2021

Smart Quantum Statistical Imaging beyond the Abbe-Rayleigh Criterion

The manifestation of the wave nature of light through diffraction imposes limits on the resolution of optical imaging. For over a century, the Abbe-Rayleigh criterion has been utilized to assess the spatial resolution limits of optical instruments. Recently, there has been an enormous impetus in overcoming the Abbe-Rayleigh resolution limit by projecting target light beams onto spatial modes. These conventional schemes for superresolution rely on a series of spatial projective measurements to pick up phase information that is used to boost the spatial resolution of optical systems. Unfortunately, these schemes require a priori information regarding the coherence properties of "unknown" light beams. Furthermore, they require stringent alignment and centering conditions that cannot be achieved in realistic scenarios. Here, we introduce a smart quantum camera for superresolving imaging. This camera exploits the self-learning features of artificial intelligence to identify the statistical fluctuations of unknown mixtures of light sources at each pixel. This is achieved through a universal quantum model that enables the design of artificial neural networks for the identification of quantum photon fluctuations. Our camera overcomes the inherent limitations of existing superresolution schemes based on spatial mode projection. Thus, our work provides a new perspective in the field of imaging with important implications for microscopy, remote sensing, and astronomy.

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arXiv2021

Versatile Super-Sensitive Metrology Using Induced Coherence

We theoretically analyze the phase sensitivity of the Induced-Coherence (Mandel-Type) Interferometer, including the case where the sensitivity is "boosted" into the bright input regime with coherent-light seeding. We find scaling which reaches below the shot noise limit, even when seeding the spatial mode which does not interact with the sample - or when seeding the undetected mode. It is a hybrid of a linear and a non-linear (Yurke-Type) interferometer, and aside from the supersensitivity, is distinguished from other systems by "preferring" an imbalance in the gains of the two non-linearities (with the second gain being optimal at low values), and non-monotonic behavior of the sensitivity as a function of the gain of the second non-linearity. Furthermore, the setup allows use of subtracted intensity measurements, instead of direct (additive) or homodyne measurements - a significant practical advantage. Bright, super-sensitive phase estimation of an object with different light fields for interaction and detection is possible, with various potential applications, especially in cases where the sample may be sensitive to light, or is most interesting in frequency domains outside what is easily detected, or when desiring bright-light phase estimation with sensitive/delicate detectors. We use an analysis in terms of general squeezing and discover that super-sensitivity occurs only in this case - that is, the effect is not present with the spontaneous-parametric-down-conversion approximation, which many previous analyses and experiments have focused on.

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