612 research outputs found
Frequency-modulated continuous-wave LiDAR compressive depth-mapping
We present an inexpensive architecture for converting a frequency-modulated
continuous-wave LiDAR system into a compressive-sensing based depth-mapping
camera. Instead of raster scanning to obtain depth-maps, compressive sensing is
used to significantly reduce the number of measurements. Ideally, our approach
requires two difference detectors. % but can operate with only one at the cost
of doubling the number of measurments. Due to the large flux entering the
detectors, the signal amplification from heterodyne detection, and the effects
of background subtraction from compressive sensing, the system can obtain
higher signal-to-noise ratios over detector-array based schemes while scanning
a scene faster than is possible through raster-scanning. %Moreover, we show how
a single total-variation minimization and two fast least-squares minimizations,
instead of a single complex nonlinear minimization, can efficiently recover
high-resolution depth-maps with minimal computational overhead. Moreover, by
efficiently storing only data points from measurements of an
pixel scene, we can easily extract depths by solving only two linear equations
with efficient convex-optimization methods
Compressive Wavefront Sensing with Weak Values
We demonstrate a wavefront sensor based on the compressive sensing,
single-pixel camera. Using a high-resolution spatial light modulator (SLM) as a
variable waveplate, we weakly couple an optical field's transverse-position and
polarization degrees of freedom. By placing random, binary patterns on the SLM,
polarization serves as a meter for directly measuring random projections of the
real and imaginary components of the wavefront. Compressive sensing techniques
can then recover the wavefront. We acquire high quality, 256x256 pixel images
of the wavefront from only 10,000 projections. Photon-counting detectors give
sub-picowatt sensitivity
Fast Hadamard transforms for compressive sensing of joint systems: measurement of a 3.2 million-dimensional bi-photon probability distribution
We demonstrate how to efficiently implement extremely high-dimensional
compressive imaging of a bi-photon probability distribution. Our method uses
fast-Hadamard-transform Kronecker-based compressive sensing to acquire the
joint space distribution. We list, in detail, the operations necessary to
enable fast-transform-based matrix-vector operations in the joint space to
reconstruct a 16.8 million-dimensional image in less than 10 minutes. Within a
subspace of that image exists a 3.2 million-dimensional bi-photon probability
distribution. In addition, we demonstrate how the marginal distributions can
aid in the accuracy of joint space distribution reconstructions
Spaceborne VHSIC multiprocessor system for AI applications
A multiprocessor system, under design for space-station applications, makes use of the latest generation symbolic processor and packaging technology. The result will be a compact, space-qualified system two to three orders of magnitude more powerful than present-day symbolic processing systems
Tootling With a Randomized Independent Group Contingency in a High School Setting
Tootling is a procedure where students report their classmates’ positive and prosocial behavior. The present study examined the effects of tootling on students’ disruptive and academically engaged behavior in three general education high school classrooms. An A-B-A-B withdrawal design was used to assess the effects of the intervention. Students wrote tootles anonymously on paper slips and placed them into a marked container. Unlike previous tootling studies, a randomized independent group contingency procedure was used to reward the students to reduce the number of steps required to implement the intervention. At the end of the class period, teachers randomly drew three of the submitted tootles and rewarded those students whom the tootles were written about. Teachers also randomly drew and rewarded two students who submitted a tootle. All three classrooms displayed decreases in disruptive behavior and increases in academically engaged behavior during intervention phases. Effect size calculations for both disruptive and academically engaged behavior indicated strong effects. The results of this study suggest that a modified tootling procedure utilizing a randomized independent group contingency can be an effective intervention for teachers to improve the behavior of students in a high school setting.
Masters thesis: http://aquila.usm.edu/masters_theses/114
Compressive Direct Imaging of a Billion-Dimensional Optical Phase-Space
Optical phase-spaces represent fields of any spatial coherence, and are
typically measured through phase-retrieval methods involving a computational
inversion, interference, or a resolution-limiting lenslet array. Recently, a
weak-values technique demonstrated that a beam's Dirac phase-space is
proportional to the measurable complex weak-value, regardless of coherence.
These direct measurements require scanning through all possible
position-polarization couplings, limiting their dimensionality to less than
100,000. We circumvent these limitations using compressive sensing, a numerical
protocol that allows us to undersample, yet efficiently measure
high-dimensional phase-spaces. We also propose an improved technique that
allows us to directly measure phase-spaces with high spatial resolution and
scalable frequency resolution. With this method, we are able to easily measure
a 1.07-billion-dimensional phase-space. The distributions are numerically
propagated to an object placed in the beam path, with excellent agreement. This
protocol has broad implications in signal processing and imaging, including
recovery of Fourier amplitudes in any dimension with linear algorithmic
solutions and ultra-high dimensional phase-space imaging.Comment: 7 pages, 5 figures. Added new larger dataset and fixed typo
Position-Momentum Bell-Nonlocality with Entangled Photon Pairs
Witnessing continuous-variable Bell nonlocality is a challenging endeavor,
but Bell himself showed how one might demonstrate this nonlocality. Though Bell
nearly showed a violation using the CHSH inequality with sign-binned
position-momentum statistics of entangled pairs of particles measured at
different times, his demonstration is subject to approximations not realizable
in a laboratory setting. Moreover, he doesn't give a quantitative estimation of
the maximum achievable violation for the wavefunction he considers. In this
article, we show how his strategy can be reimagined using the transverse
positions and momenta of entangled photon pairs measured at different
propagation distances, and we find that the maximum achievable violation for
the state he considers is actually very small relative to the upper limit of
. Although Bell's wavefunction does not produce a large violation of
the CHSH inequality, other states may yet do so.Comment: 6 pages, 3 figure
Photon counting compressive depth mapping
We demonstrate a compressed sensing, photon counting lidar system based on
the single-pixel camera. Our technique recovers both depth and intensity maps
from a single under-sampled set of incoherent, linear projections of a scene of
interest at ultra-low light levels around 0.5 picowatts. Only two-dimensional
reconstructions are required to image a three-dimensional scene. We demonstrate
intensity imaging and depth mapping at 256 x 256 pixel transverse resolution
with acquisition times as short as 3 seconds. We also show novelty filtering,
reconstructing only the difference between two instances of a scene. Finally,
we acquire 32 x 32 pixel real-time video for three-dimensional object tracking
at 14 frames-per-second.Comment: 16 pages, 8 figure
Compressively characterizing high-dimensional entangled states with complementary, random filtering
The resources needed to conventionally characterize a quantum system are
overwhelmingly large for high- dimensional systems. This obstacle may be
overcome by abandoning traditional cornerstones of quantum measurement, such as
general quantum states, strong projective measurement, and assumption-free
characterization. Following this reasoning, we demonstrate an efficient
technique for characterizing high-dimensional, spatial entanglement with one
set of measurements. We recover sharp distributions with local, random
filtering of the same ensemble in momentum followed by position---something the
uncertainty principle forbids for projective measurements. Exploiting the
expectation that entangled signals are highly correlated, we use fewer than
5,000 measurements to characterize a 65, 536-dimensional state. Finally, we use
entropic inequalities to witness entanglement without a density matrix. Our
method represents the sea change unfolding in quantum measurement where methods
influenced by the information theory and signal-processing communities replace
unscalable, brute-force techniques---a progression previously followed by
classical sensing.Comment: 13 pages, 7 figure
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