Related papers: Machine learning reveals complex behaviours in opt…
Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties…
We present a magnetic trapping scheme for cold 87Rb atoms based on light-induced fictitious magnetic fields generated by the evanescent field of an optical nanofiber (ONF) integrated with an optical tweezers. We calculate and compare the…
Optical neural networks offer a route to low-latency and energy-efficient inference by encoding computation in light propagation. However, most existing implementations rely on planar photonic circuits or discretely spaced diffractive…
Single-shot images are the standard readout of experiments with ultracold atoms -- the tarnished looking glass into their many-body physics. The efficient extraction of observables from single-shot images is thus crucial. Here, we…
Viscously damped objects driven through a periodically modulated potential energy landscape can become kinetically locked in to commensurate directions through the landscape, and thus can be deflected away from the driving direction. We…
Calibration of optically trapped particles in-vivo has been complicated given the frequency dependence and spatial inhomogeneity of the cytoplasmic viscosity, and the requirement of accurate knowledge of the medium refractive index.…
We recently demonstrated that strings of trapped atoms inside a standing wave optical dipole trap can be rearranged using optical tweezers [Y. Miroshnychenko et al., Nature, in press (2006)]. This technique allows us to actively set the…
Deep learning has shown that learned functions can dramatically outperform hand-designed functions on perceptual tasks. Analogously, this suggests that learned optimizers may similarly outperform current hand-designed optimizers, especially…
We show how state-dependent optical potentials can be used to trap a pair of molecules in different internal states at a separation much smaller than the wavelength of the trapping light. This close spacing greatly enhances the…
Normal thermal fluctuations of the cell membrane have been studied extensively using high resolution microscopy and focused light, particularly at the peripheral regions of a cell. We use a single probe particle attached non-specifically to…
We propose an enantioselective scheme to sort homogeneous chiral particles using optical tweezers. For a certain range of material parameters, we show that a highly focused circularly-polarized laser beam traps particles of a specific…
Aerosol particles play an important role in the climate system by absorbing and scattering radiation and influencing cloud properties. They are also one of the biggest sources of uncertainty for climate modeling. Many climate models do not…
Microplastics (MPs) are ubiquitous pollutants with demonstrated potential to impact ecosystems and human health. Their microscopic size complicates detection, classification, and removal, especially in biological and environmental samples.…
Collective coherent scattering of laser light by an ensemble of polarizable point particles creates long range interactions, whose properties can be tailored by choice of injected laser powers, frequencies and polarizations. We use a…
Contemporary approaches to optical multiple micro-manipulation typically involve careful pre-engineering of the laser beam shape. In various biomedical and microfluidic scenarios, especially those necessitating unconventional specimen…
Many wormlike micellar systems exhibit appreciable shear thinning due to shear induced alignment. As the micelles get aligned introducing directionality in the system, the viscoelastic properties are no longer expected to be isotropic. An…
Optical tweezers have revolutionized particle manipulation at the micro- and nanoscale, playing a critical role in fields such as plasmonics, biophysics, and nanotechnology. While traditional optical trapping methods primarily rely on…
Microscopically controlled neutral atoms in optical tweezers and lattices have led to exciting advances in the study of quantum information and quantum many-body systems. The light shifts of atomic levels from the trapping potential in…
Optical processors, built with "optical neurons", can efficiently perform high-dimensional linear operations at the speed of light. Thus they are a promising avenue to accelerate large-scale linear computations. With the current advances in…
Machine learning has recently been applied and deployed at several light source facilities in the domain of Accelerator Physics. We introduce an approach based on machine learning to produce a fast-executing model that predicts the…