173 research outputs found
A Short Wavelength GigaHertz Clocked Fiber-Optic Quantum Key Distribution System
A quantum key distribution system has been developed, using standard
telecommunications optical fiber, which is capable of operating at clock rates
of greater than 1 GHz. The quantum key distribution system implements a
polarization encoded version of the B92 protocol. The system employs
vertical-cavity surface-emitting lasers with emission wavelengths of 850 nm as
weak coherent light sources, and silicon single photon avalanche diodes as the
single photon detectors. A distributed feedback laser of emission wavelength
1.3 micro-metres, and a linear gain germanium avalanche photodiode was used to
optically synchronize individual photons over the standard telecommunications
fiber. The quantum key distribution system exhibited a quantum bit error rate
of 1.4%, and an estimated net bit rate greater than 100,000 bits-per-second for
a 4.2 km transmission range. For a 10 km fiber range a quantum bit error rate
of 2.1%, and estimated net bit rate of greater than 7,000 bits-per-second was
achieved.Comment: Pre-press versio
Lidar waveform based analysis of depth images constructed using sparse single-photon data
This paper presents a new Bayesian model and algorithm used for depth and
intensity profiling using full waveforms from the time-correlated single photon
counting (TCSPC) measurement in the limit of very low photon counts. The model
proposed represents each Lidar waveform as a combination of a known impulse
response, weighted by the target intensity, and an unknown constant background,
corrupted by Poisson noise. Prior knowledge about the problem is embedded in a
hierarchical model that describes the dependence structure between the model
parameters and their constraints. In particular, a gamma Markov random field
(MRF) is used to model the joint distribution of the target intensity, and a
second MRF is used to model the distribution of the target depth, which are
both expected to exhibit significant spatial correlations. An adaptive Markov
chain Monte Carlo algorithm is then proposed to compute the Bayesian estimates
of interest and perform Bayesian inference. This algorithm is equipped with a
stochastic optimization adaptation mechanism that automatically adjusts the
parameters of the MRFs by maximum marginal likelihood estimation. Finally, the
benefits of the proposed methodology are demonstrated through a serie of
experiments using real data
Robust Bayesian target detection algorithm for depth imaging from sparse single-photon data
This paper presents a new Bayesian model and associated algorithm for depth
and intensity profiling using full waveforms from time-correlated single-photon
counting (TCSPC) measurements in the limit of very low photon counts (i.e.,
typically less than 20 photons per pixel). The model represents each Lidar
waveform as an unknown constant background level, which is combined in the
presence of a target, to a known impulse response weighted by the target
intensity and finally corrupted by Poisson noise. The joint target detection
and depth imaging problem is expressed as a pixel-wise model selection and
estimation problem which is solved using Bayesian inference. Prior knowledge
about the problem is embedded in a hierarchical model that describes the
dependence structure between the model parameters while accounting for their
constraints. In particular, Markov random fields (MRFs) are used to model the
joint distribution of the background levels and of the target presence labels,
which are both expected to exhibit significant spatial correlations. An
adaptive Markov chain Monte Carlo algorithm including reversible-jump updates
is then proposed to compute the Bayesian estimates of interest. This algorithm
is equipped with a stochastic optimization adaptation mechanism that
automatically adjusts the parameters of the MRFs by maximum marginal likelihood
estimation. Finally, the benefits of the proposed methodology are demonstrated
through a series of experiments using real data.Comment: arXiv admin note: text overlap with arXiv:1507.0251
Experimental high-dimensional two-photon entanglement and violations of generalised Bell inequalities
Quantum entanglement plays a vital role in many quantum information and
communication tasks. Entangled states of higher dimensional systems are of
great interest due to the extended possibilities they provide. For example,
they allow the realisation of new types of quantum information schemes that can
offer higher information-density coding and greater resilience to errors than
can be achieved with entangled two-dimensional systems. Closing the detection
loophole in Bell test experiments is also more experimentally feasible when
higher dimensional entangled systems are used. We have measured previously
untested correlations between two photons to experimentally demonstrate
high-dimensional entangled states. We obtain violations of Bell-type
inequalities generalised to d-dimensional systems with up to d = 12.
Furthermore, the violations are strong enough to indicate genuine
11-dimensional entanglement. Our experiments use photons entangled in orbital
angular momentum (OAM), generated through spontaneous parametric
down-conversion (SPDC), and manipulated using computer controlled holograms
Optimizing the use of detector arrays for measuring intensity correlations of photon pairs
Intensity correlation measurements form the basis of many experiments based on spontaneous parametric down-conversion. In the most common situation, two single-photon avalanche diodes and coincidence electronics are used in the detection of the photon pairs, and the coincidence count distributions are measured by making use of some scanning procedure. Here we analyze the measurement of intensity correlations using multielement detector arrays. By considering the detector parameters such as the detection and noise probabilities, we found that the mean number of detected photons that maximizes the visibility of the two-photon correlations is approximately equal to the mean number of noise events in the detector array. We provide expressions predicting the strength of the measured intensity correlations as a function of the detector parameters and on the mean number of detected photons. We experimentally test our predictions by measuring far-field intensity correlations of spontaneous parametric down-conversion with an electron multiplying charge-coupled device camera, finding excellent agreement with the theoretical analysis
3.3 Gigahertz Clocked Quantum Key Distribution System
A fibre-based quantum key distribution system operating up to a clock
frequency of 3.3GHz is presented. The system demonstrates significantly
increased key exchange rate potential and operates at a wavelength of 850nm.Comment: Presented at ECOC 05, Glasgow, UK, (September 2005
Detection-dependent six-photon NOON state interference
NOON state interference (NOON-SI) is a powerful tool to improve the phase
sensing precision, and can play an important role in quantum sensing and
quantum imaging. However, most of the previous NOON-SI experiments only
investigated the center part of the interference pattern, while the full range
of the NOON-SI pattern has not yet been well explored.In this Letter, we
experimentally and theoretically demonstrate up to six-photon NOON-SI and study
the properties of the interference patterns over the full range.The
multi-photons were generated at a wavelength of 1584 nm from a PPKTP crystal in
a parametric down conversion process.It was found that the shape, the coherence
time and the visibility of the interference patterns were strongly dependent on
the detection schemes.This experiment can be used for applications which are
based on the envelope of the NOON-SI pattern, such as quantum spectroscopy and
quantum metrology.Comment: 5 pages, 3 figure
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 a very high volume of data. This is
particularly evident when imaging through obscurants or in high ambient
background light conditions. This paper proposes a multiscale approach for 3D
surface detection from the photon timing histogram to permit a significant
reduction in data volume. The resulting surfaces are background-free and can be
used to infer depth and reflectivity information about the target. We
demonstrate this by proposing a hierarchical Bayesian model for 3D
reconstruction and spectral classification of multispectral single-photon LiDAR
data. The reconstruction method promotes spatial correlation between
point-cloud estimates and uses a coordinate gradient descent algorithm for
parameter estimation. Results on simulated and real data show the benefits of
the proposed target detection and reconstruction approaches when compared to
state-of-the-art processing algorithm
Ghost displacement
We describe a technique whereby a coherent amplitude can be imprinted nonlocally on to a beam of light with thermal statistics that has no phase information on average. We have successfully performed the first experimental realisation. The technique could have applications in the sharing of quantum information and in covert quantum imaging scenarios
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