591 research outputs found
Adiabatic Quantum Computing with Phase Modulated Laser Pulses
Implementation of quantum logical gates for multilevel system is demonstrated
through decoherence control under the quantum adiabatic method using simple
phase modulated laser pulses. We make use of selective population inversion and
Hamiltonian evolution with time to achieve such goals robustly instead of the
standard unitary transformation language.Comment: 19 pages, 6 figures, submitted to JOP
Bayesian inference of physiologically meaningful parameters from body sway measurements
The control of the human body sway by the central nervous system, muscles, and conscious brain is of interest since body sway carries information about the physiological status of a person. Several models have been proposed to describe body sway in an upright standing position, however, due to the statistical intractability of the more realistic models, no formal parameter inference has previously been conducted and the expressive power of such models for real human subjects remains unknown. Using the latest advances in Bayesian statistical inference for intractable models, we fitted a nonlinear control model to posturographic measurements, and we showed that it can accurately predict the sway characteristics of both simulated and real subjects. Our method provides a full statistical characterization of the uncertainty related to all model parameters as quantified by posterior probability density functions, which is useful for comparisons across subjects and test settings. The ability to infer intractable control models from sensor data opens new possibilities for monitoring and predicting body status in health applications.Peer reviewe
Improved Error-Scaling for Adiabatic Quantum State Transfer
We present a technique that dramatically improves the accuracy of adiabatic
state transfer for a broad class of realistic Hamiltonians. For some systems,
the total error scaling can be quadratically reduced at a fixed maximum
transfer rate. These improvements rely only on the judicious choice of the
total evolution time. Our technique is error-robust, and hence applicable to
existing experiments utilizing adiabatic passage. We give two examples as
proofs-of-principle, showing quadratic error reductions for an adiabatic search
algorithm and a tunable two-qubit quantum logic gate.Comment: 10 Pages, 4 figures. Comments are welcome. Version substantially
revised to generalize results to cases where several derivatives of the
Hamiltonian are zero on the boundar
EPR study of some rare-earth ions (Dy3+, Tb3+, and Nd3+) in YBa2Cu3O6-compound
We investigate the low temperature X-band electron paramagnetic resonance (EPR) of YBa2Cu3Ox compounds with xâ
6.0 doped with Dy3+, Tb3+, and Nd3. The EPR spectra of Dy3+ and Tb3+ have been identified. The EPR of Tb3+ is used also to study the effect of suppression of high Tc superconductivity by doping with Tb3+. The EPR of Nd3+ is probably masked by the intense resonance of Cu2+. All experimental EPR results compare well with theoretical estimations. © 2003 Elsevier Science (USA). All rights reserved
Electron paramagnetic resonance of Tb 3+ ions in YBa 2Cu 3O 6
The first observation of electron paramagnetic resonance (EPR) of Tb 3+ doped into YBa 2 Cu 3O 6 is reported. EPR is used to determine the local symmetry of the rare-earth ion and to study the effect of suppression of high-T c superconductivity by doping. The distance between the lowest singlets of Tb 3+ ion Î â
7.1 GHz ⥠0.24 cm -1 and g-factor g â„ â 17.9 have been estimated from measurements. Both these parameters are in a good agreement with the corresponding calculated values. No evidence of Tb 4+ ions was found. © 2000 Plenum Publishing Corporation
Parameter estimation for biochemical reaction networks using Wasserstein distances
We present a method for estimating parameters in stochastic models of
biochemical reaction networks by fitting steady-state distributions using
Wasserstein distances. We simulate a reaction network at different parameter
settings and train a Gaussian process to learn the Wasserstein distance between
observations and the simulator output for all parameters. We then use Bayesian
optimization to find parameters minimizing this distance based on the trained
Gaussian process. The effectiveness of our method is demonstrated on the
three-stage model of gene expression and a genetic feedback loop for which
moment-based methods are known to perform poorly. Our method is applicable to
any simulator model of stochastic reaction networks, including Brownian
Dynamics.Comment: 22 pages, 8 figures. Slight modifications/additions to the text;
added new section (Section 4.4) and Appendi
Generation and Suppression of Decoherence in Artificial Environment for Qubit System
It is known that a quantum system with finite degrees of freedom can simulate
a composite of a system and an environment if the state of the hypothetical
environment is randomized by external manipulation. We show theoretically that
any phase decoherence phenomena of a single qubit can be simulated with a
two-qubit system and demonstrate experimentally two examples: one is phase
decoherence of a single qubit in a transmission line, and the other is that in
a quantum memory. We perform NMR experiments employing a two-spin molecule and
clearly measure decoherence for both cases. We also prove experimentally that
the bang-bang control efficiently suppresses decoherence.Comment: 25 pages, 7 figures; added reference
Almost uniform sampling via quantum walks
Many classical randomized algorithms (e.g., approximation algorithms for
#P-complete problems) utilize the following random walk algorithm for {\em
almost uniform sampling} from a state space of cardinality : run a
symmetric ergodic Markov chain on for long enough to obtain a random
state from within total variation distance of the uniform
distribution over . The running time of this algorithm, the so-called {\em
mixing time} of , is , where
is the spectral gap of .
We present a natural quantum version of this algorithm based on repeated
measurements of the {\em quantum walk} . We show that it
samples almost uniformly from with logarithmic dependence on
just as the classical walk does; previously, no such
quantum walk algorithm was known. We then outline a framework for analyzing its
running time and formulate two plausible conjectures which together would imply
that it runs in time when is
the standard transition matrix of a constant-degree graph. We prove each
conjecture for a subclass of Cayley graphs.Comment: 13 pages; v2 added NSF grant info; v3 incorporated feedbac
The Rule of Law: Measurement and Deep Roots
This paper does three things. First, based on a limited number of theoretically established dimensions, it proposes a new de facto indicator for the rule of law. It is the first such indicator to take the quality of legal norms explicitly into account. Second, using this indicator we shed new light on the relationship between the rule of law and the political system of a country. Presidential governments tend to score significantly lower on the rule of law indicator than parliamentary ones. Many presidential democracies are even outperformed by dictatorships. The observation that political systems hardly predetermine the rule of law level raises the question why the authority of law differs across societies in its capacity to constrain the behavior of public officials. Third, because of this question, we investigate the roots of the rule of law. As theory on this specific question is scarce and the rule of law is closely associated with income levels, we draw on a topical literature that deals with the fundamental causes of economic development. Our findings suggest that specific determinants of long-run development operate via the rule of law, whereas others are not related to the rule of law at all. Our empirical evidence does, however, support not only the âprimacy of institutionsâ view, but also the important role that human capital, which European settlers brought to their colonies, played in historical economic development
Quantum random walks with history dependence
We introduce a multi-coin discrete quantum random walk where the amplitude
for a coin flip depends upon previous tosses. Although the corresponding
classical random walk is unbiased, a bias can be introduced into the quantum
walk by varying the history dependence. By mixing the biased random walk with
an unbiased one, the direction of the bias can be reversed leading to a new
quantum version of Parrondo's paradox.Comment: 8 pages, 6 figures, RevTe
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