Translated object identification for efficient ghost imaging.

Alignment of a single-pixel quantum ghost imaging setup is complex and requires extreme precision. Due to misalignment, easily created by human error in the alignment process, reconstructed images are often translated off the central imaging axis. This becomes problematic for intelligent object detection and identification in fast imaging cases, as these algorithms are unable to achieve early image identification.

Imaging the temporal profile of structured optical modes.

Spatially structured optical modes exhibit a group velocity lower than c, resulting in a measurable temporal delay with respect to plane waves. Here, we develop a technique to image this temporal delay and measure it across a set of optical modes. An inevitable consequence of spatially varying delay is temporal broadening of the mode.

Path Tracing-Inspired Modeling of Non-Line-of-Sight SPAD Data.

Non-Line of Sight (NLOS) imaging has gained attention for its ability to detect and reconstruct objects beyond the direct line of sight, using scattered light, with applications in surveillance and autonomous navigation. This paper presents a versatile framework for modeling the temporal distribution of photon detections in direct Time of Flight (dToF) Lidar NLOS systems. Our approach accurately accounts for key factors such as material reflectivity, object distance, and occlusion by utilizing a proof-of-principle simulation realized with the Unreal Engine.

Human activity recognition using a single-photon direct time-of-flight sensor.

Single-Photon Avalanche Diode (SPAD) direct Time-of-Flight (dToF) sensors provide depth imaging over long distances, enabling the detection of objects even in the absence of contrast in colour or texture. However, distant objects are represented by just a few pixels and are subject to noise from solar interference, limiting the applicability of existing computer vision techniques for high-level scene interpretation. We present a new SPAD-based vision system for human activity recognition, based on convolutional and recurrent neural networks, which is trained entirely on synthetic data.

The importance of molecular axis alignment and symmetry-breaking in photoelectron elliptical dichroism.

Photoelectron angular distributions (PADs) produced from the photoionization of chiral molecules using elliptically polarized light exhibit a forward/backward asymmetry with respect to the optical propagation direction. By recording these distributions using the velocity-map imaging (VMI) technique, the resulting photoelectron elliptical dichroism (PEELD) has previously been demonstrated as a promising spectroscopic tool for studying chiral molecules in the gas phase. The use of elliptically polarized laser pulses, however, produces PADs (and consequently, PEELD distributions) that do not exhibit cylindrical symmetry about the propagation axis.

The critical impact of traumatic muscle loss on fracture healing: Basic science and clinical aspects.

Musculoskeletal trauma, specifically fractures, is a leading cause of patient morbidity and disability worldwide. In approximately 20% of cases with fracture and related traumatic muscle loss, bone healing is impaired leading to fracture nonunion. Over the past few years, several studies have demonstrated that bone and the surrounding muscle tissue interact not only anatomically and mechanically but also through biochemical pathways and mediators.

Instant Detection of Synthetic Cannabinoids on Physical Matrices, Implemented on a Low-Cost, Ultraportable Device.

Synthetic cannabinoids (SCs) make up a class of novel psychoactive substances (NPS), used predominantly in prisons and homeless communities in the U.K. SCs can have severe side effects, including psychosis, stroke, and seizures, with numerous reported deaths associated with their use.

3D target detection and spectral classification for single-photon LiDAR data.

3D single-photon LiDAR imaging has an important role in many applications. However, full deployment of this modality will require the analysis of low signal to noise ratio target returns and very high volume of data. This is particularly evident when imaging through obscurants or in high ambient background light conditions.

Simultaneously Sorting Overlapping Quantum States of Light.

The efficient manipulation, sorting, and measurement of optical modes and single-photon states is fundamental to classical and quantum science. Here, we realize simultaneous and efficient sorting of nonorthogonal, overlapping states of light, encoded in the transverse spatial degree of freedom. We use a specifically designed multiplane light converter to sort states encoded in dimensions ranging from d=3 to d=7.

Video super-resolution for single-photon LIDAR.

3D time-of-flight (ToF) image sensors are used widely in applications such as self-driving cars, augmented reality (AR), and robotics. When implemented with single-photon avalanche diodes (SPADs), compact, array format sensors can be made that offer accurate depth maps over long distances, without the need for mechanical scanning. However, array sizes tend to be small, leading to low lateral resolution, which combined with low signal-to-background ratio (SBR) levels under high ambient illumination, may lead to difficulties in scene interpretation.

The development of a creative work rehabilitation organisation.

Work as therapy has a place in mental healthcare, but there is disagreement about how and why it might be helpful, and how best to conceptualise or represent those benefits. Over the last 50 years, occupational and industrial therapy sheltered workshops have been key elements in the provision of work activities in psychiatric settings, and community-based horticultural activities and creative craft work have offered additional approaches. Using archival material, interviews, witness seminars and personal reflections, this article charts the birth and initial growth of Restore, a charity providing creative work-based services in Oxfordshire between 1977 and 1988.

Fundamental limits to depth imaging with single-photon detector array sensors.

Single-Photon Avalanche Detector (SPAD) arrays are a rapidly emerging technology. These multi-pixel sensors have single-photon sensitivities and pico-second temporal resolutions thus they can rapidly generate depth images with millimeter precision. Such sensors are a key enabling technology for future autonomous systems as they provide guidance and situational awareness.

The processes and context of innovation in mental healthcare: Oxfordshire as a case study.

This article introduces the four following articles and the Classic Text. They describe the development of a sequence of innovative local mental health services in Oxfordshire, and explore the processes of innovation, led by the humane pragmatism practised by Dr Bertram Mandelbrote, who was Physician Superintendent at Littlemore Hospital in Oxford from 1959 to 1988. The articles describe emerging patterns of therapeutic community practice, and trace the events leading to a set of discrete service developments outside the hospital.

Rapid nanometer-precision autocorrelator.

The precise measurement of a target depth has applications in biophysics and nanophysics, and non-linear optical methods are sensitive to intensity changes on very small length scales. By exploiting the high sensitivity of an autocorrelator's dependency on path length, we propose a technique that achieves ≈30 nm depth precision for each pixel in 30 seconds. Our method images up-converted pulses from a non-linear crystal using a sCMOS (scientific Complementary Metal-Oxide-Semiconductor) camera and converts the intensity recorded by each pixel to a delay.

Innovation in mental health care: Bertram Mandelbrote, the Phoenix Unit and the therapeutic community approach.

Bertram Mandelbrote was Physician Superintendent and Consultant Psychiatrist at Littlemore Hospital in Oxford from 1959 to 1988. A humane pragmatist rather than theoretician, Mandelbrote was known for his facilitating style of leadership and working across organisational boundaries. He created the Phoenix Unit, an innovative admission unit run on therapeutic community lines which became a hub for community outreach.

Pixels2Pose: Super-resolution time-of-flight imaging for 3D pose estimation.

Single-photon-sensitive depth sensors are being increasingly used in next-generation electronics for human pose and gesture recognition. However, cost-effective sensors typically have a low spatial resolution, restricting their use to basic motion identification and simple object detection. Here, we perform a temporal to spatial mapping that drastically increases the resolution of a simple time-of-flight sensor, i.

Propagation-induced revival of entanglement in the angle-OAM bases.

Although the continuous-variable position-momentum entanglement of photon pairs produced by parametric down-conversion has applicability in several quantum information applications, it is not suitable for applications involving long-distance propagation. This is because entanglement in the position-momentum bases, as seen through Einstein-Podolsky-Rosen (EPR)-correlation measurements, decays very rapidly with photons propagating away from the source. In contrast, in this article, we show that in the continuous-variable bases of angle-orbital angular momentum (OAM), the entanglement, as seen through EPR-correlation measurements, exhibits a remarkably different behavior.

Arbitrary image reinflation: A deep learning technique for recovering 3D photoproduct distributions from a single 2D projection.

Many charged particle imaging measurements rely on the inverse Abel transform (or related methods) to reconstruct three-dimensional (3D) photoproduct distributions from a single two-dimensional (2D) projection image. This technique allows for both energy- and angle-resolved information to be recorded in a relatively inexpensive experimental setup, and its use is now widespread within the field of photochemical dynamics. There are restrictions, however, as cylindrical symmetry constraints on the overall form of the distribution mean that it can only be used with a limited range of laser polarization geometries.

High-speed object detection with a single-photon time-of-flight image sensor.

3D time-of-flight (ToF) imaging is used in a variety of applications such as augmented reality (AR), computer interfaces, robotics and autonomous systems. Single-photon avalanche diodes (SPADs) are one of the enabling technologies providing accurate depth data even over long ranges. By developing SPADs in array format with integrated processing combined with pulsed, flood-type illumination, high-speed 3D capture is possible.

Measuring dimensionality and purity of high-dimensional entangled states.

High-dimensional entangled states are promising candidates for increasing the security and encoding capacity of quantum systems. While it is possible to witness and set bounds for the entanglement, precisely quantifying the dimensionality and purity in a fast and accurate manner remains an open challenge. Here, we report an approach that simultaneously returns the dimensionality and purity of high-dimensional entangled states by simple projective measurements.

Intensity-corrected 4D light-in-flight imaging.

Light-in-flight (LIF) imaging is the measurement and reconstruction of light's path as it moves and interacts with objects. It is well known that relativistic effects can result in apparent velocities that differ significantly from the speed of light. However, less well known is that Rayleigh scattering and the effects of imaging optics can lead to observed intensities changing by several orders of magnitude along light's path.

Robust super-resolution depth imaging via a multi-feature fusion deep network.

The number of applications that use depth imaging is increasing rapidly, e.g. self-driving autonomous vehicles and auto-focus assist on smartphone cameras.