High-fidelity holographic beam shaping with optimal transport and phase diversity
- URL: http://arxiv.org/abs/2408.17025v1
- Date: Fri, 30 Aug 2024 05:43:15 GMT
- Title: High-fidelity holographic beam shaping with optimal transport and phase diversity
- Authors: Hunter Swan, Andrii Torchylo, Michael J. Van de Graaff, Jan Rudolph, Jason M. Hogan,
- Abstract summary: A phase-only spatial light modulator (SLM) provides a powerful way to shape laser beams into arbitrary intensity patterns.
We show that optimal transport methods can generate approximate solutions to a problem of determining an appropriate SLM phase.
We also show that analogous algorithms can be used to measure the intensity and phase of the input beam incident upon the SLM.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A phase-only spatial light modulator (SLM) provides a powerful way to shape laser beams into arbitrary intensity patterns, but at the cost of a hard computational problem of determining an appropriate SLM phase. Here we show that optimal transport methods can generate approximate solutions to this problem that serve as excellent initializations for iterative phase retrieval algorithms, yielding vortex-free solutions with superior accuracy and efficiency. Additionally, we show that analogous algorithms can be used to measure the intensity and phase of the input beam incident upon the SLM via phase diversity imaging. These techniques furnish flexible and convenient solutions to the computational challenges of beam shaping with an SLM.
Related papers
- Rapid stochastic spatial light modulator calibration and pixel crosstalk optimisation [0.0]
Accurate calibration of the wavefront and intensity profile of the laser beam at the SLM display is key to the high fidelity of holographic potentials.
Here, we present a new calibration technique that is faster than previous methods while maintaining the same level of accuracy.
This approach allows us to measure the wavefront at the SLM to within $lambda /170$ in 5 minutes using only 10 SLM phase patterns.
arXiv Detail & Related papers (2024-08-14T17:11:50Z) - Align-Free Multi-Plane Phase Retrieval [15.356191612310935]
The multi-plane phase retrieval method provides a budget-friendly and effective way to perform phase imaging.
It often encounters alignment challenges due to shifts along the optical axis in experiments.
We introduce a novel Adaptive Cascade Calibrated (ACC) strategy for multi-plane phase retrieval that overcomes misalignment issues.
arXiv Detail & Related papers (2024-04-30T01:13:24Z) - Accelerating Diffusion Sampling with Optimized Time Steps [69.21208434350567]
Diffusion probabilistic models (DPMs) have shown remarkable performance in high-resolution image synthesis.
Their sampling efficiency is still to be desired due to the typically large number of sampling steps.
Recent advancements in high-order numerical ODE solvers for DPMs have enabled the generation of high-quality images with much fewer sampling steps.
arXiv Detail & Related papers (2024-02-27T10:13:30Z) - Physics-Inspired Degradation Models for Hyperspectral Image Fusion [61.743696362028246]
Most fusion methods solely focus on the fusion algorithm itself and overlook the degradation models.
We propose physics-inspired degradation models (PIDM) to model the degradation of LR-HSI and HR-MSI.
Our proposed PIDM can boost the fusion performance of existing fusion methods in practical scenarios.
arXiv Detail & Related papers (2024-02-04T09:07:28Z) - Shaping Single Photons through Multimode Optical Fibers using Mechanical
Perturbations [55.41644538483948]
We show an all-fiber approach for controlling the shape of single photons and the spatial correlations between entangled photon pairs.
We optimize these perturbations to localize the spatial distribution of a single photon or the spatial correlations of photon pairs in a single spot.
arXiv Detail & Related papers (2023-06-04T07:33:39Z) - Optimal Algorithms for the Inhomogeneous Spiked Wigner Model [89.1371983413931]
We derive an approximate message-passing algorithm (AMP) for the inhomogeneous problem.
We identify in particular the existence of a statistical-to-computational gap where known algorithms require a signal-to-noise ratio bigger than the information-theoretic threshold to perform better than random.
arXiv Detail & Related papers (2023-02-13T19:57:17Z) - Energy Efficiency Maximization in IRS-Aided Cell-Free Massive MIMO
System [2.9081408997650375]
In this paper, we consider an intelligent reflecting surface (IRS)-aided cell-free massive multiple-input multiple-output system, where the beamforming at access points and the phase shifts at IRSs are jointly optimized to maximize energy efficiency (EE)
To solve EE problem, we propose an iterative optimization algorithm by using quadratic transform and Lagrangian dual transform to find the optimum beamforming and phase shifts.
We further propose a deep learning based approach for joint beamforming and phase shifts design. Specifically, a two-stage deep neural network is trained offline using the unsupervised learning manner, which is then deployed online for
arXiv Detail & Related papers (2022-12-24T14:58:15Z) - Retrieving space-dependent polarization transformations via near-optimal
quantum process tomography [55.41644538483948]
We investigate the application of genetic and machine learning approaches to tomographic problems.
We find that the neural network-based scheme provides a significant speed-up, that may be critical in applications requiring a characterization in real-time.
We expect these results to lay the groundwork for the optimization of tomographic approaches in more general quantum processes.
arXiv Detail & Related papers (2022-10-27T11:37:14Z) - Centimeter-Wave Free-Space Time-of-Flight Imaging [25.15384123485028]
We propose a computational imaging method for all-optical free-space correlation before photo-conversion that achieves micron-scale depth resolution.
We propose an imaging approach with resonant polarization modulators and devise a novel optical dual-pass frequency-doubling which achieves high modulation contrast at more than 10GHz.
We validate the proposed method in simulation and experimentally, where it achieves micron-scale depth precision.
arXiv Detail & Related papers (2021-05-25T01:57:10Z) - Rapid characterisation of linear-optical networks via PhaseLift [51.03305009278831]
Integrated photonics offers great phase-stability and can rely on the large scale manufacturability provided by the semiconductor industry.
New devices, based on such optical circuits, hold the promise of faster and energy-efficient computations in machine learning applications.
We present a novel technique to reconstruct the transfer matrix of linear optical networks.
arXiv Detail & Related papers (2020-10-01T16:04:22Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.