We introduce a variational quantum computing approach for quantum state reconstruction within a discretized logical framework, using experimental measurement data as input. By mapping the reconstruction cost function onto an Ising model, the problem can be solved using a variational eigensolver on present-day quantum hardware identifying dominant logical elements of the density matrix. As a proof of concept, we demonstrate the method on quantum structured light, in particular, entangled photons carrying orbital angular momentum and show that the reconstruction procedure can yield reliable performance even on noisy devices. Our results highlight the potential of variational algorithms as a complementary approach to quantum state tomography, particularly for high-dimensional structured light, where classical approaches can face bottlenecks.
Quantum ghost imaging harnesses entangled photon pairs to form images using light that never directly interacts with the object. Conventional approaches rely on pixelated detectors or spatial masks, where the resolution is fundamentally limited by the pixel size and thus bounded by the Rayleigh criterion. In this work, we present a modal approach that replaces pixel-based detection with measurements in a basis of structured modes. By reconstructing images through tailored spatial modes, we decouple resolution from the physical limitations of detectors and instead tie it to the system’s optical precision and computational control. We demonstrate that even non-orthogonal modal sets can achieve high fidelity image reconstruction by exploiting modal sparsity, significantly reducing the number of required measurements. Using phase-only approximations of Hermite-Gaussian modes, we avoid the loss associated with complex amplitude modulation while retaining high reconstruction fidelity. The result is a high-resolution, high-efficiency quantum ghost imaging technique powered by structured light, opening new possibilities for photon-efficient imaging in low-light and quantum-limited regimes, such as biological microscopy and remote sensing.
A structured-light-based approach to magneto-optical rotation (MOR) magnetometry is proposed, in which magnetically induced polarization rotation is converted into a directly observable spatial displacement. A radially polarized Laguerre--Gaussian beam propagating through cold
87Rb atoms in the presence of a longitudinal magnetic field experiences circular birefringence, which induces a relative phase shift between the
σ+ and
σ− polarization components. This phase shift manifests itself as the angular rotation of a petal-shaped interference pattern, enabling the MOR angle to be determined directly from the spatial intensity distribution. Unlike conventional MOR detection techniques based on balanced polarimetry or Stokes-parameter reconstruction, the proposed method requires only a fixed-axis polarization projection and avoids computationally intensive polarization analysis. By translating polarization rotation into a topology-dependent spatial observable, the scheme enables direct and spatially resolved magnetic-field measurements. Furthermore, the use of electromagnetically induced transparency (EIT) allows low-loss operation while preserving high sensitivity. These characteristics make the proposed technique a promising platform for optical magnetometry and structured-light-based quantum sensing.