90 research outputs found
Optimal measurements for quantum spatial superresolution
We construct optimal measurements, achieving the ultimate precision predicted
by quantum theory, for the simultaneous estimation of centroid, separation, and
relative intensities of two incoherent point sources using a linear optical
system. We discuss the physical feasibility of the scheme, which could pave the
way for future practical implementations of quantum inspired imaging.Comment: 7 pages. 3 color figures. Title change
Axial superlocalization with vortex beams
Improving axial resolution is of paramount importance for three-dimensional optical imaging systems. Here, we investigate the ultimate precision in axial localization using vortex beams. For Laguerre-Gauss beams, this limit can be achieved with just an intensity scan. The same is not true for superpositions of Laguerre-Gauss beams, in particular for those with intensity profiles that rotate on defocusing. Microscopy methods based on rotating vortex beams may thus benefit from replacing traditional intensity sensors with advanced mode-sorting techniques
Neural-network quantum state tomography
We revisit the application of neural networks techniques to quantum state
tomography. We confirm that the positivity constraint can be successfully
implemented with trained networks that convert outputs from standard
feed-forward neural networks to valid descriptions of quantum states. Any
standard neural-network architecture can be adapted with our method. Our
results open possibilities to use state-of-the-art deep-learning methods for
quantum state reconstruction under various types of noise.Comment: 8 pages, 4 color figures. Comments are most welcom
Intensity-based axial localization at the quantum limit
We derive fundamental precision bounds for single-point axial localization. For Gaussian beams, this ultimate limit can be achieved with a single intensity scan, provided the camera is placed at one of two optimal transverse detection planes. Hence, for axial localization there is no need of more complicated detection schemes. The theory is verified with an experimental demonstration of axial resolution 3 orders of magnitude below the classical depth of focus
Enhancing axial localization with wavefront control
Enhancing the ability to resolve axial details is crucial in
three-dimensional optical imaging. We provide experimental evidence showcasing
the ultimate precision achievable in axial localization using vortex beams. For
Laguerre-Gauss (LG) beams, this remarkable limit can be attained with just a
single intensity scan. This proof-of-principle demonstrates that microscopy
techniques based on LG vortex beams can potentially benefit from the introduced
quantum-inspired superresolution protocol.Comment: 10 pages, 6 figures. Comments welcom
Adaptive compressive tomography with no a priori information
Quantum state tomography is both a crucial component in the field of quantum
information and computation, and a formidable task that requires an incogitably
large number of measurement configurations as the system dimension grows. We
propose and experimentally carry out an intuitive adaptive compressive
tomography scheme, inspired by the traditional compressed-sensing protocol in
signal recovery, that tremendously reduces the number of configurations needed
to uniquely reconstruct any given quantum state without any additional a priori
assumption whatsoever (such as rank information, purity, etc) about the state,
apart from its dimension.Comment: 6 pages, 4 figure
Multiscale Bone Remodelling with Spatial P Systems
Many biological phenomena are inherently multiscale, i.e. they are
characterized by interactions involving different spatial and temporal scales
simultaneously. Though several approaches have been proposed to provide
"multilayer" models, only Complex Automata, derived from Cellular Automata,
naturally embed spatial information and realize multiscaling with
well-established inter-scale integration schemas. Spatial P systems, a variant
of P systems in which a more geometric concept of space has been added, have
several characteristics in common with Cellular Automata. We propose such a
formalism as a basis to rephrase the Complex Automata multiscaling approach
and, in this perspective, provide a 2-scale Spatial P system describing bone
remodelling. The proposed model not only results to be highly faithful and
expressive in a multiscale scenario, but also highlights the need of a deep and
formal expressiveness study involving Complex Automata, Spatial P systems and
other promising multiscale approaches, such as our shape-based one already
resulted to be highly faithful.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
Computational Modeling for the Activation Cycle of G-proteins by G-protein-coupled Receptors
In this paper, we survey five different computational modeling methods. For
comparison, we use the activation cycle of G-proteins that regulate cellular
signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving
example. Starting from an existing Ordinary Differential Equations (ODEs)
model, we implement the G-protein cycle in the stochastic Pi-calculus using
SPiM, as Petri-nets using Cell Illustrator, in the Kappa Language using
Cellucidate, and in Bio-PEPA using the Bio-PEPA eclipse plug in. We also
provide a high-level notation to abstract away from communication primitives
that may be unfamiliar to the average biologist, and we show how to translate
high-level programs into stochastic Pi-calculus processes and chemical
reactions.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
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