1,579 research outputs found
On Approaching the Ultimate Limits of Photon-Efficient and Bandwidth-Efficient Optical Communication
It is well known that ideal free-space optical communication at the quantum
limit can have unbounded photon information efficiency (PIE), measured in bits
per photon. High PIE comes at a price of low dimensional information efficiency
(DIE), measured in bits per spatio-temporal-polarization mode. If only temporal
modes are used, then DIE translates directly to bandwidth efficiency. In this
paper, the DIE vs. PIE tradeoffs for known modulations and receiver structures
are compared to the ultimate quantum limit, and analytic approximations are
found in the limit of high PIE. This analysis shows that known structures fall
short of the maximum attainable DIE by a factor that increases linearly with
PIE for high PIE.
The capacity of the Dolinar receiver is derived for binary coherent-state
modulations and computed for the case of on-off keying (OOK). The DIE vs. PIE
tradeoff for this case is improved only slightly compared to OOK with photon
counting. An adaptive rule is derived for an additive local oscillator that
maximizes the mutual information between a receiver and a transmitter that
selects from a set of coherent states. For binary phase-shift keying (BPSK),
this is shown to be equivalent to the operation of the Dolinar receiver.
The Dolinar receiver is extended to make adaptive measurements on a coded
sequence of coherent state symbols. Information from previous measurements is
used to adjust the a priori probabilities of the next symbols. The adaptive
Dolinar receiver does not improve the DIE vs. PIE tradeoff compared to
independent transmission and Dolinar reception of each symbol.Comment: 10 pages, 8 figures; corrected a typo in equation 3
Activity-dependent dynamics and sequestration of proteasomes in dendritic spines
The regulated degradation of proteins by the ubiquitin proteasome pathway is emerging as an important modulator of synaptic function and plasticity. The proteasome is a large, multi-subunit cellular machine that recognizes, unfolds and degrades target polyubiquitinated proteins. Here we report NMDA (N-methyl-D-aspartate) receptor-dependent redistribution of proteasomes from dendritic shafts to synaptic spines upon synaptic stimulation, providing a mechanism for local protein degradation. Using a proteasome-activity reporter and local perfusion, we show that synaptic stimulation regulates proteasome activity locally in the dendrites. We used restricted photobleaching of individual spines and dendritic shafts to reveal the dynamics that underlie proteasome sequestration, and show that activity modestly enhances the entry rate of proteasomes into spines while dramatically reducing their exit rate. Proteasome sequestration is persistent, reflecting an association with the actin-based cytoskeleton. Together, our data indicate that synaptic activity can promote the recruitment and sequestration of proteasomes to locally remodel the protein composition of synapses
Signal-to-noise ratio of Gaussian-state ghost imaging
The signal-to-noise ratios (SNRs) of three Gaussian-state ghost imaging
configurations--distinguished by the nature of their light sources--are
derived. Two use classical-state light, specifically a joint signal-reference
field state that has either the maximum phase-insensitive or the maximum
phase-sensitive cross correlation consistent with having a proper
representation. The third uses nonclassical light, in particular an entangled
signal-reference field state with the maximum phase-sensitive cross correlation
permitted by quantum mechanics. Analytic SNR expressions are developed for the
near-field and far-field regimes, within which simple asymptotic approximations
are presented for low-brightness and high-brightness sources. A high-brightness
thermal-state (classical phase-insensitive state) source will typically achieve
a higher SNR than a biphoton-state (low-brightness, low-flux limit of the
entangled-state) source, when all other system parameters are equal for the two
systems. With high efficiency photon-number resolving detectors, a
low-brightness, high-flux entangled-state source may achieve a higher SNR than
that obtained with a high-brightness thermal-state source.Comment: 12 pages, 4 figures. This version incorporates additional references
and a new analysis of the nonclassical case that, for the first time,
includes the complete transition to the classical signal-to-noise ratio
asymptote at high source brightnes
LaB-GATr: geometric algebra transformers for large biomedical surface and volume meshes
Many anatomical structures can be described by surface or volume meshes.
Machine learning is a promising tool to extract information from these 3D
models. However, high-fidelity meshes often contain hundreds of thousands of
vertices, which creates unique challenges in building deep neural network
architectures. Furthermore, patient-specific meshes may not be canonically
aligned which limits the generalisation of machine learning algorithms. We
propose LaB-GATr, a transfomer neural network with geometric tokenisation that
can effectively learn with large-scale (bio-)medical surface and volume meshes
through sequence compression and interpolation. Our method extends the recently
proposed geometric algebra transformer (GATr) and thus respects all Euclidean
symmetries, i.e. rotation, translation and reflection, effectively mitigating
the problem of canonical alignment between patients. LaB-GATr achieves
state-of-the-art results on three tasks in cardiovascular hemodynamics
modelling and neurodevelopmental phenotype prediction, featuring meshes of up
to 200,000 vertices. Our results demonstrate that LaB-GATr is a powerful
architecture for learning with high-fidelity meshes which has the potential to
enable interesting downstream applications. Our implementation is publicly
available
Classical capacity of bosonic broadcast communication and a new minimum output entropy conjecture
Previous work on the classical information capacities of bosonic channels has
established the capacity of the single-user pure-loss channel, bounded the
capacity of the single-user thermal-noise channel, and bounded the capacity
region of the multiple-access channel. The latter is a multi-user scenario in
which several transmitters seek to simultaneously and independently communicate
to a single receiver. We study the capacity region of the bosonic broadcast
channel, in which a single transmitter seeks to simultaneously and
independently communicate to two different receivers. It is known that the
tightest available lower bound on the capacity of the single-user thermal-noise
channel is that channel's capacity if, as conjectured, the minimum von Neumann
entropy at the output of a bosonic channel with additive thermal noise occurs
for coherent-state inputs. Evidence in support of this minimum output entropy
conjecture has been accumulated, but a rigorous proof has not been obtained. In
this paper, we propose a new minimum output entropy conjecture that, if proved
to be correct, will establish that the capacity region of the bosonic broadcast
channel equals the inner bound achieved using a coherent-state encoding and
optimum detection. We provide some evidence that supports this new conjecture,
but again a full proof is not available.Comment: 13 pages, 7 figure
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