29,742 research outputs found
Scalable Ellipsoidal Classification for Bipartite Quantum States
The Separability Problem is approached from the perspective of Ellipsoidal
Classification. A Density Operator of dimension N can be represented as a
vector in a real vector space of dimension , whose components are the
projections of the matrix onto some selected basis. We suggest a method to test
separability, based on successive optimization programs. First, we find the
Minimum Volume Covering Ellipsoid that encloses a particular set of properly
vectorized bipartite separable states, and then we compute the Euclidean
distance of an arbitrary vectorized bipartite Density Operator to this
ellipsoid. If the vectorized Density Operator falls inside the ellipsoid, it is
regarded as separable, otherwise it will be taken as entangled. Our method is
scalable and can be implemented straightforwardly in any desired dimension.
Moreover, we show that it allows for detection of Bound Entangled StatesComment: 8 pages, 5 figures, 3 tables. Revised version, to appear in Physical
Review
Fitting Jump Models
We describe a new framework for fitting jump models to a sequence of data.
The key idea is to alternate between minimizing a loss function to fit multiple
model parameters, and minimizing a discrete loss function to determine which
set of model parameters is active at each data point. The framework is quite
general and encompasses popular classes of models, such as hidden Markov models
and piecewise affine models. The shape of the chosen loss functions to minimize
determine the shape of the resulting jump model.Comment: Accepted for publication in Automatic
Quantum teleportation scheme by selecting one of multiple output ports
The scheme of quantum teleportation, where Bob has multiple (N) output ports
and obtains the teleported state by simply selecting one of the N ports, is
thoroughly studied. We consider both deterministic version and probabilistic
version of the teleportation scheme aiming to teleport an unknown state of a
qubit. Moreover, we consider two cases for each version: (i) the state employed
for the teleportation is fixed to a maximally entangled state, and (ii) the
state is also optimized as well as Alice's measurement. We analytically
determine the optimal protocols for all the four cases, and show the
corresponding optimal fidelity or optimal success probability. All these
protocols can achieve the perfect teleportation in the asymptotic limit of
. The entanglement properties of the teleportation scheme are also
discussed.Comment: 14 pages, 4 figure
Big Data and the Internet of Things
Advances in sensing and computing capabilities are making it possible to
embed increasing computing power in small devices. This has enabled the sensing
devices not just to passively capture data at very high resolution but also to
take sophisticated actions in response. Combined with advances in
communication, this is resulting in an ecosystem of highly interconnected
devices referred to as the Internet of Things - IoT. In conjunction, the
advances in machine learning have allowed building models on this ever
increasing amounts of data. Consequently, devices all the way from heavy assets
such as aircraft engines to wearables such as health monitors can all now not
only generate massive amounts of data but can draw back on aggregate analytics
to "improve" their performance over time. Big data analytics has been
identified as a key enabler for the IoT. In this chapter, we discuss various
avenues of the IoT where big data analytics either is already making a
significant impact or is on the cusp of doing so. We also discuss social
implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski
(eds.) Big Data Analysis: New algorithms for a new society, Springer Series
on Studies in Big Data, to appea
Cortical pain responses in human infants
Despite the recent increase in our understanding of the development of pain processing, it is still not known whether premature infants are capable of processing pain at a cortical level. In this study, changes in cerebral oxygenation over the somatosensory cortex were measured in response to noxious stimulation using real-time near-infrared spectroscopy in 18 infants aged between 25 and 45 weeks postmenstrual age. The noxious stimuli were heel lances performed for routine blood sampling; no blood tests were performed solely for the purpose of the study. Noxious stimulation produced a clear cortical response, measured as an increase in total hemoglobin concentration [HbT] in the contralateral somatosensory cortex, from 25 weeks (mean Delta[HbT] = 7.74 mu mol/L; SE, 1.10). Cortical responses were significantly greater in awake compared with sleeping infants, with a mean difference of 6.63 mu mol/L [95% confidence interval (CI) limits: 2.35, 10.91 mu mol/L; mean age, 35.2 weeks]. In awake infants, the response in the contralateral somatosensory cortex increased with age ( regression coefficient, 0.698 mu mol/L/week; 95% CI limits: 0.132, 1.265 mu mol/L/week) and the latency decreased with age (regression coefficient, -0.9861 mu mol/L/week; 95% CI limits: -1.5361, -0.4361 mu mol/L/week; age range, 25-38 weeks). The response was modality specific because no response was detected after non-noxious stimulation of the heel, even when accompanied by reflex withdrawal of the foot. We conclude that noxious information is transmitted to the preterm infant cortex from 25 weeks, highlighting the potential for both higher-level pain processing and pain-induced plasticity in the human brain from a very early age
Ultranarrow resonance peaks in the transmission and reflection spectra of a photonic crystal cavity with Raman gain
The Raman gain of a probe light in a three-state -scheme placed
into a defect of a one-dimensional photonic crystal is studied theoretically.
We show that there exists a pump intensity range, where the transmission and
reflection spectra of the probe field exhibit \textit{simultaneously} occurring
narrow peaks (resonances) whose position is determined by the Raman resonance.
Transmission and reflection coefficients can be larger than unity at pump
intensities of order tens of W/cm. When the pump intensity is
outside this region, the peak in the transmission spectrum turns into a narrow
dip. The nature of narrow resonances is attributed to a drastic dispersion of
the nonlinear refractive index in the vicinity of the Raman transition, which
leads to a significant reduction of the group velocity of the probe wave.Comment: 9 pages, 3 figure
How to identify the youngest protostars
We study the transition from a prestellar core to a Class 0 protostar, using
SPH to simulate the dynamical evolution, and a Monte Carlo radiative transfer
code to generate the SED and isophotal maps. For a prestellar core illuminated
by the standard interstellar radiation field, the luminosity is low and the SED
peaks at ~190 micron. Once a protostar has formed, the luminosity rises (due to
a growing contribution from accretion onto the protostar) and the peak of the
SED shifts to shorter wavelengths (~80-100 micron). However, by the end of the
Class 0 phase, the accretion rate is falling, the luminosity has decreased, and
the peak of the SED shifts back towards longer wavelengths (90-150 micron). In
our simulations, the density of material around the protostar remains
sufficiently high well into the Class 0 phase that the protostar only becomes
visible in the NIR if it is displaced from the centre dynamically. Raw submm/mm
maps of Class 0 protostars tend to be much more centrally condensed than those
of prestellar cores. However, when convolved with a typical telescope beam, the
difference in central concentration is less marked, although the Class 0
protostars appear more circular. Our results suggest that, if a core is deemed
to be prestellar on the basis of having no associated IRAS source, no cm radio
emission, and no outflow, but it has a circular appearance and an SED which
peaks at wavelengths below ~170 micron, it may well contain a very young Class
0 protostar.Comment: Accepted by A&A (avaliable with high-res images at
http://carina.astro.cf.ac.uk/pub/Dimitrios.Stamatellos/publications
Quantum lost property: a possible operational meaning for the Hilbert-Schmidt product
Minimum error state discrimination between two mixed states \rho and \sigma
can be aided by the receipt of "classical side information" specifying which
states from some convex decompositions of \rho and \sigma apply in each run. We
quantify this phenomena by the average trace distance, and give lower and upper
bounds on this quantity as functions of \rho and \sigma. The lower bound is
simply the trace distance between \rho and \sigma, trivially seen to be tight.
The upper bound is \sqrt{1 - tr(\rho\sigma)}, and we conjecture that this is
also tight. We reformulate this conjecture in terms of the existence of a pair
of "unbiased decompositions", which may be of independent interest, and prove
it for a few special cases. Finally, we point towards a link with a notion of
non-classicality known as preparation contextuality.Comment: 3 pages, 1 figure. v2: Less typos in text and less punctuation in
titl
Robust Quantum Error Correction via Convex Optimization
We present a semidefinite program optimization approach to quantum error
correction that yields codes and recovery procedures that are robust against
significant variations in the noise channel. Our approach allows us to optimize
the encoding, recovery, or both, and is amenable to approximations that
significantly improve computational cost while retaining fidelity. We
illustrate our theory numerically for optimized 5-qubit codes, using the
standard [5,1,3] code as a benchmark. Our optimized encoding and recovery
yields fidelities that are uniformly higher by 1-2 orders of magnitude against
random unitary weight-2 errors compared to the [5,1,3] code with standard
recovery. We observe similar improvement for a 4-qubit decoherence-free
subspace code.Comment: 4 pages, including 3 figures. v2: new example
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