Accurate Wavefront Reconstruction with Optical Vortex Sensors Enables Stable Phase Tracking in Incoming Beams

Measuring the shape of light waves, known as wavefront sensing, is crucial in many optical applications, and researchers continually seek more accurate and robust methods. Magdalena Łukowicz, Aleksandra K. Korzeniewska, and Kamil Kalinowski, all from Wrocław University of Science and Technology, alongside colleagues including Rafał Cichowski and Rosario Porras-Aguilar, present a novel approach that significantly improves wavefront reconstruction. Their work introduces stable, swirling points in light, called vortices, within a well-established optical system, the Shack-Hartmann sensor, transforming how the sensor detects changes in light direction. The team demonstrates that this technique outperforms conventional methods across a wide range of noisy conditions, achieving a clearer and more accurate measurement of wavefronts without increasing the complexity of the sensor itself, and opening new possibilities for optical systems operating in challenging environments.

Optical Vortices Improve Wavefront Aberration Measurement

Scientists have developed the Optical Vortex Wavefront Sensor (OVWS), a new technique for measuring how light waves are distorted as they travel. Building upon the well-established Shack-Hartmann (S-H) sensor, the team introduced optical vortices, stable points of phase change, into the incoming light within each section of the sensor. This innovative approach refines the method of tracking wavefront distortions by focusing on a different quantity and how it is detected, without fundamentally altering the S-H sensor’s operating principle. Researchers utilized spatial light modulators to precisely control the phase of light, enabling dynamic control over the light field.

The study pioneered a method that combines the adaptability of these light controllers with the unique properties of optical vortices, which appear as dark points in the light’s intensity distribution. This creates a system that bridges traditional interferometric and angle-based wavefront measurement techniques. Experiments were conducted across a wide range of signal-to-noise ratios, from very faint signals to bright, saturated conditions, to thoroughly evaluate the sensor’s performance. The researchers demonstrated lower residual phase variance across all tested conditions when comparing the OVWS to a conventional S-H sensor, indicating improved accuracy in reconstructing the wavefront and a more robust measurement in challenging conditions. This innovative approach offers a pathway to more accurate and robust wavefront sensing for applications ranging from astronomy to precision metrology.

Vortex Sensor Outperforms Traditional Wavefront Measurement

This work presents a novel optical vortex wavefront sensor (OVWS) that significantly enhances noise resistance compared to traditional Shack-Hartmann (S-H) sensors. The core innovation lies in replacing conventional light beams with optical vortices, creating phase singularities, or points of zero intensity, within each section of the sensor. This allows for a dedicated tracking algorithm, based on a mathematical transformation, to pinpoint these singularities with greater precision. Experiments demonstrate that the OVWS consistently achieves lower root mean square (RMS) reconstruction errors across a broad signal-to-noise ratio (SNR) range.

Researchers rigorously tested localization performance under controlled conditions, generating numerous random light distributions at each noise level for both conventional and vortex-based sensors. The results quantitatively demonstrate that the vortex-based light provides improved noise resistance, maintaining lower RMS reconstruction errors throughout the tested range, even at low SNR. These findings establish a new benchmark for wavefront sensing, offering a pathway to more robust and accurate optical measurements in challenging environments.

Vortex Sensor Enhances Wavefront Phase Accuracy

This work introduces the Optical Vortex Wavefront Sensor, a novel approach to angle-based sensing that enhances the capabilities of traditional Shack-Hartmann architectures. By incorporating phase singularities, stable points within the wavefront, into each section of the sensor, the team developed a system that improves resilience to shot noise and enhances the accuracy of wavefront phase retrieval. This modification enables a dedicated tracking algorithm capable of high-precision spot detection without increasing system complexity. Evaluations conducted across a broad signal-to-noise ratio range consistently demonstrate the superior performance of the Optical Vortex Wavefront Sensor compared to conventional Shack-Hartmann sensors.

The team validated this improvement through both numerical simulations and experimental results, showcasing the sensor’s ability to accurately reconstruct wavefronts even in challenging conditions. Furthermore, the sensor’s versatility is demonstrated by its successful application in correcting optical element misalignments within a real optical system. The authors acknowledge that a natural next step involves developing a refractive version of the sensor, which would integrate a microlens with a spiral phase plate within each section, and that the quality of the generated optical vortex will depend on the section diameter and the ability to create a smooth phase gradient. The team has submitted patent applications for both holographic and refractive implementations of this new sensor concept.

👉 More information
🗞 Accurate and Noise-Robust Wavefront Reconstruction with an Optical Vortex Wavefront Sensor
🧠 ArXiv: https://arxiv.org/abs/2510.07998

Rohail T.

Rohail T.

As a quantum scientist exploring the frontiers of physics and technology. My work focuses on uncovering how quantum mechanics, computing, and emerging technologies are transforming our understanding of reality. I share research-driven insights that make complex ideas in quantum science clear, engaging, and relevant to the modern world.

Latest Posts by Rohail T.:

Topology-aware Machine Learning Enables Better Graph Classification with 0.4 Gain

Llms Enable Strategic Computation Allocation with ROI-Reasoning for Tasks under Strict Global Constraints

January 10, 2026
Lightweight Test-Time Adaptation Advances Long-Term EMG Gesture Control in Wearable Devices

Lightweight Test-Time Adaptation Advances Long-Term EMG Gesture Control in Wearable Devices

January 10, 2026
Deep Learning Control AcDeep Learning Control Achieves Safe, Reliable Robotization for Heavy-Duty Machineryhieves Safe, Reliable Robotization for Heavy-Duty Machinery

Generalist Robots Validated with Situation Calculus and STL Falsification for Diverse Operations

January 10, 2026