Preparing multi-partite entanglement of photons and matter qubits

We show how to make event-ready multi-partite entanglement between qubits which may be encoded on photons or matter systems. Entangled states of matter systems, which can also act as single photon sources, can be generated using the entangling operation presented in quant-ph/0408040. We show how to entangle such sources with photon qubits, which may be encoded in the dual rail, polarization or time-bin degrees of freedom. We subsequently demonstrate how projective measurements of the matter qubits can be used to create entangled states of the photons alone. The state of the matter qubits is inherited by the generated photons. Since the entangling operation can be used to generate cluster states of matter qubits for quantum computing, our procedure enables us to create any (entangled) photonic quantum state that can be written as the outcome of a quantum computer.Comment: 10 pages, 4 figures; to appear in Journal of Optics

Numerical method for a class of optimal control problems subject to nonsmooth functional constraints

AbstractIn this paper, we consider a class of optimal control problems which is governed by nonsmooth functional inequality constraints involving convolution. First, we transform it into an equivalent optimal control problem with smooth functional inequality constraints at the expense of doubling the dimension of the control variables. Then, using the Chebyshev polynomial approximation of the control variables, we obtain an semi-infinite quadratic programming problem. At last, we use the dual parametrization technique to solve the problem

Optimal design of nonuniform FIR transmultiplexer using semi-infinite programming

This paper considers an optimum nonuniform FIR transmultiplexer design problem subject to specifications in the frequency domain. Our objective is to minimize the sum of the ripple energy for all the individual filters, subject to the specifications on amplitude and aliasing distortions, and to the passband and stopband specifications for the individual filters. This optimum nonuniform transmultiplexer design problem can be formulated as a quadratic semi-infinite programming problem. The dual parametrization algorithm is extended to this nonuniform transmultiplexer design problem. If the lengths of the filters are sufficiently long and the set of decimation integers is compatible, then a solution exists. Since the problem is formulated as a convex problem, if a solution exists, then the solution obtained is unique and the local solution is a global minimum

Triangle Diagram with Off-Shell Coulomb T-Matrix for (In-)Elastic Atomic and Nuclear Three-Body Processes

The driving terms in three-body theories of elastic and inelastic scattering of a charged particle off a bound state of two other charged particles contain the fully off-shell two-body Coulomb T-matrix describing the intermediate-state Coulomb scattering of the projectile with each of the charged target particles. Up to now the latter is usually replaced by the Coulomb potential, either when using the multiple-scattering approach or when solving three-body integral equations. General properties of the exact and the approximate on-shell driving terms are discussed, and the accuracy of this approximation is investigated numerically, both for atomic and nuclear processes including bound-state excitation, for energies below and above the corresponding three-body dissociation threshold, over the whole range of scattering angles.Comment: 22 pages, 11 figures, figures can be obtained upon request from the Authors, revte

Bond option pricing under the CKLS model

Consider the European call option written on a zero coupon bond. Suppose the call option has maturity T and strike price K while the bond has maturity S T . We propose a numerical method for evaluating the call option price under the Chan, Karolyi, Longstaff and Sanders (CKLS) model in which the increment of the short rate over a time interval of length dt , apart from being independent and stationary, is having the quadratic-normal distribution with mean zero and variance dt. The key steps in the numerical procedure include (i) the discretization of the CKLS model; (ii) the quadratic approximation of the time-T bond price as a function of the short rate rT at time T; and (iii) the application of recursive formulas to find the moments of r(t+dt) given the value of r(t). The numerical results thus found show that the option price decreases as the parameter in the CKLS model increases, and the variation of the option price is slight when the underlying distribution of the increment departs from the normal distribution

Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

Electrostatics in wind-blown sand

Wind-blown sand, or "saltation," is an important geological process, and the primary source of atmospheric dust aerosols. Significant discrepancies exist between classical saltation theory and measurements. We show here that these discrepancies can be resolved by the inclusion of sand electrification in a physically based saltation model. Indeed, we find that electric forces enhance the concentration of saltating particles and cause them to travel closer to the surface, in agreement with measurements. Our results thus indicate that sand electrification plays an important role in saltation.Comment: 4 journal pages, 5 figures, and supplementary material. Article is in press at PR

Path Planning for Underactuated Dubins Micro-robots Using Switching Control

In this paper, we develop an optimal path planning strategy for under-actuated Dubins micro-robots. Such robots are non-holonomic robots constrained to move along circular paths of fixed curvature clockwise or counter-clockwise. Our objective is to investigate the coverage and optimal path problems, as well as multi-robot cooperation, for a switching control scheme. Our methods are based on elementary geometry and optimal control techniques. The results in this paper show that the trajectories of micro-robots can cover the entire two-dimensional plane, and that the proposed switching control scheme allows multiple robots to cooperate. In addition, we deduce the minimum-time path under the switching control scheme by converting the robot model into the traditional Dubins vehicle model

The interferometric baselines and GRAVITY astrometric error budget

GRAVITY is a new generation beam combination instrument for the VLTI. Its goal is to achieve microarsecond astrometric accuracy between objects separated by a few arcsec. This $10^6$ accuracy on astrometric measurements is the most important challenge of the instrument, and careful error budget have been paramount during the technical design of the instrument. In this poster, we will focus on baselines induced errors, which is part of a larger error budget.Comment: SPIE Meeting 2014 -- Montrea