33,463 research outputs found
Noise and Disturbance of Qubit Measurements: An Information-Theoretic Characterisation
Information-theoretic definitions for the noise associated with a quantum
measurement and the corresponding disturbance to the state of the system have
recently been introduced [F. Buscemi et al., Phys. Rev. Lett. 112, 050401
(2014)]. These definitions are invariant under relabelling of measurement
outcomes, and lend themselves readily to the formulation of state-independent
uncertainty relations both for the joint estimate of observables (noise-noise
relations) and the noise-disturbance tradeoff. Here we derive such relations
for incompatible qubit observables, which we prove to be tight in the case of
joint estimates, and present progress towards fully characterising the
noise-disturbance tradeoff. In doing so, we show that the set of obtainable
noise-noise values for such observables is convex, whereas the conjectured form
for the set of obtainable noise-disturbance values is not. Furthermore,
projective measurements are not optimal with respect to the joint-measurement
noise or noise-disturbance tradeoffs. Interestingly, it seems that four-outcome
measurements are needed in the former case, whereas three-outcome measurements
are optimal in the latter.Comment: Minor changes, corresponds to final published version. 14 pages, 5
figure
Using the INSPIRAL program to search for gravitational waves from low-mass binary inspiral
The INSPIRAL program is the LIGO Scientific Collaboration's computational
engine for the search for gravitational waves from binary neutron stars and
sub-solar mass black holes. We describe how this program, which makes use of
the FINDCHIRP algorithm (discussed in a companion paper), is integrated into a
sophisticated data analysis pipeline that was used in the search for low-mass
binary inspirals in data taken during the second LIGO science run.Comment: 11 pages, 3 figures, submitted to Classical and Quantum Gravity for
the special issue of the GWDAW9 Proceeding
The Cost of US Pharmaceutical Price Reductions: A Financial Simulation Model of R&D Decisions
Previous empirical studies that have examined the links between pharmaceutical price controls, profits, cash flows, and investment in research and development (R&D) have been largely based on retrospective statistical analyses of firm- and/or industry-level data. These studies, which have contributed numerous insights and findings to the literature, relied upon ad hoc reduced-form model specifications. In the current paper we take a very different approach: a prospective micro-simulation approach. Using Monte Carlo techniques we model how future price controls in the U.S. will impact early-stage product development decisions in the pharmaceutical industry. This is done within the context of a net present value (NPV) framework that appropriately reflects the uncertainty associated with R&D project technical success, development costs, and future revenues. Using partial-information estimators calibrated with the most contemporary clinical and economic data available, we demonstrate how pharmaceutical price controls will significantly diminish the incentives to undertake early-stage R&D investment. For example, we estimate that cutting prices by 40 to 50 percent in the U.S. will lead to between 30 to 60 percent fewer R&D projects being undertaken (in early-stage development). Given the recent legislative efforts to control prescription drug prices in the U.S., and the likelihood that price controls will prevail as a result, it is important to better understand the firm response to such a regulatory change.
Von Neumann Normalisation of a Quantum Random Number Generator
In this paper we study von Neumann un-biasing normalisation for ideal and
real quantum random number generators, operating on finite strings or infinite
bit sequences. In the ideal cases one can obtain the desired un-biasing. This
relies critically on the independence of the source, a notion we rigorously
define for our model. In real cases, affected by imperfections in measurement
and hardware, one cannot achieve a true un-biasing, but, if the bias "drifts
sufficiently slowly", the result can be arbitrarily close to un-biasing. For
infinite sequences, normalisation can both increase or decrease the
(algorithmic) randomness of the generated sequences. A successful application
of von Neumann normalisation---in fact, any un-biasing transformation---does
exactly what it promises, un-biasing, one (among infinitely many) symptoms of
randomness; it will not produce "true" randomness.Comment: 27 pages, 2 figures. Updated to published versio
Gaze-based teleprosthetic enables intuitive continuous control of complex robot arm use: Writing & drawing
Eye tracking is a powerful mean for assistive technologies for people with movement disorders, paralysis and amputees. We present a highly intuitive eye tracking-controlled robot arm operating in 3-dimensional space based on the user's gaze target point that enables tele-writing and drawing. The usability and intuitive usage was assessed by a “tele” writing experiment with 8 subjects that learned to operate the system within minutes of first time use. These subjects were naive to the system and the task and had to write three letters on a white board with a white board pen attached to the robot arm's endpoint. The instructions are to imagine they were writing text with the pen and look where the pen would be going, they had to write the letters as fast and as accurate as possible, given a letter size template. Subjects were able to perform the task with facility and accuracy, and movements of the arm did not interfere with subjects ability to control their visual attention so as to enable smooth writing. On the basis of five consecutive trials there was a significant decrease in the total time used and the total number of commands sent to move the robot arm from the first to the second trial but no further improvement thereafter, suggesting that within writing 6 letters subjects had mastered the ability to control the system. Our work demonstrates that eye tracking is a powerful means to control robot arms in closed-loop and real-time, outperforming other invasive and non-invasive approaches to Brain-Machine-Interfaces in terms of calibration time (<;2 minutes), training time (<;10 minutes), interface technology costs. We suggests that gaze-based decoding of action intention may well become one of the most efficient ways to interface with robotic actuators - i.e. Brain-Robot-Interfaces - and become useful beyond paralysed and amputee users also for the general teleoperation of robotic and exoskeleton in human augmentation
The Background Field Method as a Canonical Transformation
We construct explicitly the canonical transformation that controls the full
dependence (local and non-local) of the vertex functional of a Yang-Mills
theory on a background field. After showing that the canonical transformation
found is nothing but a direct field-theoretic generalization of the Lie
transform of classical analytical mechanics, we comment on a number of possible
applications, and in particular the non perturbative implementation of the
background field method on the lattice, the background field formulation of the
two particle irreducible formalism, and, finally, the formulation of the
Schwinger-Dyson series in the presence of topologically non-trivial
configurations.Comment: 11 pages, REVTeX. References added, some explanations extended. Final
version to appear in the journa
On the definition and characterisation of multipartite causal (non)separability
The concept of causal nonseparability has been recently introduced, in
opposition to that of causal separability, to qualify physical processes that
locally abide by the laws of quantum theory, but cannot be embedded in a
well-defined global causal structure. While the definition is unambiguous in
the bipartite case, its generalisation to the multipartite case is not so
straightforward. Two seemingly different generalisations have been proposed,
one for a restricted tripartite scenario and one for the general multipartite
case. Here we compare the two, showing that they are in fact inequivalent. We
propose our own definition of causal (non)separability for the general case,
which---although a priori subtly different---turns out to be equivalent to the
concept of "extensible causal (non)separability" introduced before, and which
we argue is a more natural definition for general multipartite scenarios. We
then derive necessary, as well as sufficient conditions to characterise
causally (non)separable processes in practice. These allow one to devise
practical tests, by generalising the tool of witnesses of causal
nonseparability
Parrondo's games with chaotic switching
This paper investigates the different effects of chaotic switching on
Parrondo's games, as compared to random and periodic switching. The rate of
winning of Parrondo's games with chaotic switching depends on coefficient(s)
defining the chaotic generator, initial conditions of the chaotic sequence and
the proportion of Game A played. Maximum rate of winning can be obtained with
all the above mentioned factors properly set, and this occurs when chaotic
switching approaches periodic behavior.Comment: 11 pages, 9 figure
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