Quantum secret sharing is the procedure of securely distributing information between multiple parties by exploiting the features of quantum mechanics. Many variants exist, but in this work, we report a high-dimensional realization of a single-photon secret sharing scheme for distributing classical keys amongst many nodes. The implementation, which makes use of twisted light, is realized for as high as 11 dimensions and for as many as 10 participants: the highest reported to date and which is easily extendable to even higher dimensions and many participants. Such a result is an important first step towards a future quantum network.
Noise is an unavoidable feature in most optical systems and many techniques exist to minimize its adverse effects. In this regard, spatial filtering is a commonly deployed technique to improve the quality of laser beams by optically filtering the noise. In the “textbook” example, the noise is usually assumed to be high frequency and the laser beam, Gaussian. In this case, the filtering is achieved by a simple pinhole placed at the common focal plane of two lenses. In this work, we describe how this process can be generalized to arbitrary beam profiles: spatial filtering of complex light.
Quantum secret sharing (QSS) is a cryptographic multiparty communication technique in which a secret is divided and shared among N parties and then securely reconstructed by (N-1) cooperating parties, making it perfect for storing and sharing highly sensitive data. Challenges in high dimensional state preparation, transformation and detection, the key steps of any QSS protocol, have so far hindered experimental realisation. Here, by taking advantage of the high-dimensional encoding space accessible by a photon's orbital angular momentum, we present a toolbox for realising practical high-dimensional single photon QSS schemes that are easily scalable in both dimension and number of participants. Our implementations realised a new record in both the number of participants (N=10) and the dimensionality (d=11), with the latter facilitating the transfer of 2.89 bits of information per photon. This work is an important step towards securely distributing information across a network of nodes.
This Conference Presentation, "Perfect vortex beams and their applications in classical and quantum information processing," was recorded at Photonics West 2020 held in San Francisco, California, United States.
Digital micromirror devices (DMDs) have become ubiquitous as spatial light modulators in the optics community, but ambiguity remains on how best to implement them in a laboratory environment. Here, we explicitly tackle the problem of generating high fidelity modes of structured light while maintaining optical efficiency. We present a theoretical characterization of the diffractive properties of the DMD, allowing us to motivate an alignment procedure that improves optical efficiency. We also present a set of best practice recommendations that cover aspects of DMD operation that are not immediately intuitive, these best practice recommendations ensure structured light is generated with the correct spatial profile and wavefront. We present experimental results that show efficiency improvements of up to 20%. Further, we demonstrate the creation of modes of structured light with fidelities in excess of 96%. The best practices presented here provide a pragmatic set of procedures for ensuring DMDs are used to their fullest potential.
Perfect (optical) vortices (PVs) have attracted significant interest in the optical community owing to their well-defined annular ring whose near-field radial profile is independent of orbital angular momentum (OAM). Although it is a general belief that it is not possible to perform quantitative OAM measurement of PVs by modal decomposition, here we show, both theoretically and experimentally, that the OAM content of a PV can be measured quantitatively in both the near- and far-fields, including superpositions of OAM within one perfect vortex. Our work will be of interest to the large community who seek to use such structured light fields in various applications, including optical trapping and tweezing and optical communications.
Ghost imaging gives the possibility of imaging objects with extremely low levels of light, which could be particularly useful for light-sensitive objects. In this study, we varied different important experimental parameters of our all-digital set-up, that condition both the acquisition time and quality of the reconstructed image, with the idea of finding the optimal ones. In addition to this, we introduced machine-learning techniques to include a recognition algorithm that further reduces the time necessary to identify the imaged object. This improvement in efficiency paves the way to use ghost imaging for living specimens.