Quasi-hermitian Quantum Mechanics in Phase Space

We investigate quasi-hermitian quantum mechanics in phase space using standard deformation quantization methods: Groenewold star products and Wigner transforms. We focus on imaginary Liouville theory as a representative example where exact results are easily obtained. We emphasize spatially periodic solutions, compute various distribution functions and phase-space metrics, and explore the relationships between them.Comment: Accepted by Journal of Mathematical Physic

Passage-time distributions from a spin-boson detector model

The passage-time distribution for a spread-out quantum particle to traverse a specific region is calculated using a detailed quantum model for the detector involved. That model, developed and investigated in earlier works, is based on the detected particle's enhancement of the coupling between a collection of spins (in a metastable state) and their environment. We treat the continuum limit of the model, under the assumption of the Markov property, and calculate the particle state immediately after the first detection. An explicit example with 15 boson modes shows excellent agreement between the discrete model and the continuum limit. Analytical expressions for the passage-time distribution as well as numerical examples are presented. The precision of the measurement scheme is estimated and its optimization discussed. For slow particles, the precision goes like $E^{-3/4}$, which improves previous $E^{-1}$ estimates, obtained with a quantum clock model.Comment: 11 pages, 6 figures; minor changes, references corrected; accepted for publication in Phys. Rev.

A Theory of Errors in Quantum Measurement

It is common to model random errors in a classical measurement by the normal (Gaussian) distribution, because of the central limit theorem. In the quantum theory, the analogous hypothesis is that the matrix elements of the error in an observable are distributed normally. We obtain the probability distribution this implies for the outcome of a measurement, exactly for the case of 2x2 matrices and in the steepest descent approximation in general. Due to the phenomenon of `level repulsion', the probability distributions obtained are quite different from the Gaussian.Comment: Based on talk at "Spacetime and Fundamental Interactions: Quantum Aspects" A conference to honor A. P. Balachandran's 65th Birthda

Model-free preference-based reinforcement learning

Specifying a numeric reward function for reinforcement learning typically requires a lot of hand-tuning from a human expert. In contrast, preference-based reinforcement learning (PBRL) utilizes only pairwise comparisons between trajectories as a feedback signal, which are often more intuitive to specify. Currently available approaches to PBRL for control problems with continuous state/action spaces require a known or estimated model, which is often not available and hard to learn. In this paper, we integrate preference-based estimation of the reward function into a model-free reinforcement learning (RL) algorithm, resulting in a model-free PBRL algorithm. Our new algorithm is based on Relative Entropy Policy Search (REPS), enabling us to utilize stochastic policies and to directly control the greediness of the policy update. REPS decreases exploration of the policy slowly by limiting the relative entropy of the policy update, which ensures that the algorithm is provided with a versatile set of trajectories, and consequently with informative preferences. The preference-based estimation is computed using a sample-based Bayesian method, which can also estimate the uncertainty of the utility. Additionally, we also compare to a linear solvable approximation, based on inverse RL. We show that both approaches perform favourably to the current state-of-the-art. The overall result is an algorithm that can learn non-parametric continuous action policies from a small number of preferences

Policy evaluation with temporal differences: a survey and comparison

Policy evaluation is an essential step in most reinforcement learning approaches. It yields a value function, the quality assessment of states for a given policy, which can be used in a policy improvement step. Since the late 1980s, this research area has been dominated by temporal-difference (TD) methods due to their data-efficiency. However, core issues such as stability guarantees in the off-policy scenario, improved sample efficiency and probabilistic treatment of the uncertainty in the estimates have only been tackled recently, which has led to a large number of new approaches. This paper aims at making these new developments accessible in a concise overview, with foci on underlying cost functions, the off-policy scenario as well as on regularization in high dimensional feature spaces. By presenting the first extensive, systematic comparative evaluations comparing TD, LSTD, LSPE, FPKF, the residual- gradient algorithm, Bellman residual minimization, GTD, GTD2 and TDC, we shed light on the strengths and weaknesses of the methods. Moreover, we present alternative versions of LSTD and LSPE with drastically improved off-policy performance

Quasi-bound states in continuum

We report the prediction of quasi-bound states (resonant states with very long lifetimes) that occur in the eigenvalue continuum of propagating states for a wide region of parameter space. These quasi-bound states are generated in a quantum wire with two channels and an adatom, when the energy bands of the two channels overlap. A would-be bound state that lays just below the upper energy band is slightly destabilized by the lower energy band and thereby becomes a resonant state with a very long lifetime (a second QBIC lays above the lower energy band).Comment: 4 pages, 4figures, 1 tabl

3C 295, a cluster and its cooling flow at z=0.46

We present ROSAT HRI data of the distant and X-ray luminous (L_x(bol)=2.6^ {+0.4}_{-0.2} 10^{45}erg/sec) cluster of galaxies 3C 295. We fit both a one-dimensional and a two-dimensional isothermal beta-model to the data, the latter one taking into account the effects of the point spread function (PSF). For the error analysis of the parameters of the two-dimensional model we introduce a Monte-Carlo technique. Applying a substructure analysis, by subtracting a cluster model from the data, we find no evidence for a merger, but we see a decrement in emission South-East of the center of the cluster, which might be due to absorption. We confirm previous results by Henry & Henriksen(1986) that 3C 295 hosts a cooling flow. The equations for the simple and idealized cooling flow analysis presented here are solely based on the isothermal beta-model, which fits the data very well, including the center of the cluster. We determine a cooling flow radius of 60-120kpc and mass accretion rates of dot{M}=400-900 Msun/y, depending on the applied model and temperature profile. We also investigate the effects of the ROSAT PSF on our estimate of dot{M}, which tends to lead to a small overestimate of this quantity if not taken into account. This increase of dot{M} (10-25%) can be explained by a shallower gravitational potential inferred by the broader overall profile caused by the PSF, which diminishes the efficiency of mass accretion. We also determine the total mass of the cluster using the hydrostatic approach. At a radius of 2.1 Mpc, we estimate the total mass of the cluster (M{tot}) to be (9.2 +/- 2.7) 10^{14}Msun. For the gas to total mass ratio we get M{gas}/M{tot} =0.17-0.31, in very good agreement with the results for other clusters of galaxies, giving strong evidence for a low density universe.Comment: 26 pages, 7 figures, accepted for publication in Ap

Supernova Inelastic Neutrino-Nucleus Cross Sections from High-Resolution Electron Scattering Experiments and Shell-Model Calculations

Highly precise data on the magnetic dipole strength distributions from the Darmstadt electron linear accelerator for the nuclei 50Ti, 52Cr and 54Fe are dominated by isovector Gamow-Teller-like contributions and can therefore be translated into inelastic total and differential neutral-current neutrino-nucleus cross sections at supernova neutrino energies. The results agree well with large-scale shell-model calculations, validating this model.Comment: 5 pages, 4 figures, RevTeX 4, version accepted in Phys. Rev. Letter

Learning concurrent motor skills in versatile solution spaces

Future robots need to autonomously acquire motor skills in order to reduce their reliance on human programming. Many motor skill learning methods concentrate on learning a single solution for a given task. However, discarding information about additional solutions during learning unnecessarily limits autonomy. Such favoring of single solutions often requires re-learning of motor skills when the task, the environment or the robot’s body changes in a way that renders the learned solution infeasible. Future robots need to be able to adapt to such changes and, ideally, have a large repertoire of movements to cope with such problems. In contrast to current methods, our approach simultaneously learns multiple distinct solutions for the same task, such that a partial degeneration of this solution space does not prevent the successful completion of the task. In this paper, we present a complete framework that is capable of learning different solution strategies for a real robot Tetherball task

Local Unitary Quantum Cellular Automata

In this paper we present a quantization of Cellular Automata. Our formalism is based on a lattice of qudits, and an update rule consisting of local unitary operators that commute with their own lattice translations. One purpose of this model is to act as a theoretical model of quantum computation, similar to the quantum circuit model. It is also shown to be an appropriate abstraction for space-homogeneous quantum phenomena, such as quantum lattice gases, spin chains and others. Some results that show the benefits of basing the model on local unitary operators are shown: universality, strong connections to the circuit model, simple implementation on quantum hardware, and a wealth of applications.Comment: To appear in Physical Review