The Supremum Norm of the Discrepancy Function: Recent Results and Connections

A great challenge in the analysis of the discrepancy function D_N is to obtain universal lower bounds on the L-infty norm of D_N in dimensions d \geq 3. It follows from the average case bound of Klaus Roth that the L-infty norm of D_N is at least (log N) ^{(d-1)/2}. It is conjectured that the L-infty bound is significantly larger, but the only definitive result is that of Wolfgang Schmidt in dimension d=2. Partial improvements of the Roth exponent (d-1)/2 in higher dimensions have been established by the authors and Armen Vagharshakyan. We survey these results, the underlying methods, and some of their connections to other subjects in probability, approximation theory, and analysis.Comment: 15 pages, 3 Figures. Reports on talks presented by the authors at the 10th international conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, Sydney Australia, February 2011. v2: Comments of the referee are incorporate

Coloring translates and homothets of a convex body

We obtain improved upper bounds and new lower bounds on the chromatic number as a linear function of the clique number, for the intersection graphs (and their complements) of finite families of translates and homothets of a convex body in \RR^n.Comment: 11 pages, 2 figure

Hebbian learning inspired estimation of the linear regression parameters from queries

Local learning rules in biological neural networks (BNNs) are commonly referred to as Hebbian learning. [26] links a biologically motivated Hebbian learning rule to a specific zeroth-order optimization method. In this work, we study a variation of this Hebbian learning rule to recover the regression vector in the linear regression model. Zeroth-order optimization methods are known to converge with suboptimal rate for large parameter dimension compared to first-order methods like gradient descent, and are therefore thought to be in general inferior. By establishing upper and lower bounds, we show, however, that such methods achieve near-optimal rates if only queries of the linear regression loss are available. Moreover, we prove that this Hebbian learning rule can achieve considerably faster rates than any non-adaptive method that selects the queries independently of the data

Precision spectroscopy with two correlated atoms

We discuss techniques that allow for long coherence times in laser spectroscopy experiments with two trapped ions. We show that for this purpose not only entangled ions prepared in decoherence-free subspaces can be used but also a pair of ions that are not entangled but subject to the same kind of phase noise. We apply this technique to a measurement of the electric quadrupole moment of the 3d D5/2 state of 40Ca+ and to a measurement of the linewidth of an ultrastable laser exciting a pair of 40Ca+ ions

Near-optimal mean value estimates for multidimensional Weyl sums

We obtain sharp estimates for multidimensional generalisations of Vinogradov's mean value theorem for arbitrary translation-dilation invariant systems, achieving constraints on the number of variables approaching those conjectured to be the best possible. Several applications of our bounds are discussed

On the ubiquity of trivial torsion on elliptic curves

The purpose of this paper is to give a "down--to--earth" proof of the well--known fact that a randomly chosen elliptic curve over the rationals is most likely to have trivial torsion

Nonextensive statistical effects in protoneutron stars

We investigate the bulk properties of protoneutron stars in the framework of a relativistic mean field theory based on nonextensive statistical mechanics, characterized by power-law quantum distributions. We study the relevance of nonextensive statistical effects on the beta-stable equation of state at fixed entropy per baryon, in presence and in absence of trapped neutrinos, for nucleonic and hyperonic matter. We show that nonextensive statistical effects could play a crucial role in the structure and in the evolution of the protoneutron stars also for small deviations from the standard Boltzmann-Gibbs statistics.Comment: 9 pages, 7 figure

A Single Laser System for Ground-State Cooling of 25-Mg+

We present a single solid-state laser system to cool, coherently manipulate and detect $^{25}$Mg$^+$ ions. Coherent manipulation is accomplished by coupling two hyperfine ground state levels using a pair of far-detuned Raman laser beams. Resonant light for Doppler cooling and detection is derived from the same laser source by means of an electro-optic modulator, generating a sideband which is resonant with the atomic transition. We demonstrate ground-state cooling of one of the vibrational modes of the ion in the trap using resolved-sideband cooling. The cooling performance is studied and discussed by observing the temporal evolution of Raman-stimulated sideband transitions. The setup is a major simplification over existing state-of-the-art systems, typically involving up to three separate laser sources

On the relationship between continuous- and discrete-time quantum walk

Quantum walk is one of the main tools for quantum algorithms. Defined by analogy to classical random walk, a quantum walk is a time-homogeneous quantum process on a graph. Both random and quantum walks can be defined either in continuous or discrete time. But whereas a continuous-time random walk can be obtained as the limit of a sequence of discrete-time random walks, the two types of quantum walk appear fundamentally different, owing to the need for extra degrees of freedom in the discrete-time case. In this article, I describe a precise correspondence between continuous- and discrete-time quantum walks on arbitrary graphs. Using this correspondence, I show that continuous-time quantum walk can be obtained as an appropriate limit of discrete-time quantum walks. The correspondence also leads to a new technique for simulating Hamiltonian dynamics, giving efficient simulations even in cases where the Hamiltonian is not sparse. The complexity of the simulation is linear in the total evolution time, an improvement over simulations based on high-order approximations of the Lie product formula. As applications, I describe a continuous-time quantum walk algorithm for element distinctness and show how to optimally simulate continuous-time query algorithms of a certain form in the conventional quantum query model. Finally, I discuss limitations of the method for simulating Hamiltonians with negative matrix elements, and present two problems that motivate attempting to circumvent these limitations.Comment: 22 pages. v2: improved presentation, new section on Hamiltonian oracles; v3: published version, with improved analysis of phase estimatio

Brain atrophy accelerates cognitive decline in cerebral small vessel disease: The LADIS study

Objective: To examine the independent contributions and combined interactions of medial temporal lobe atrophy (MTA), cortical and subcortical atrophy, and white matter lesion (WML) volume in longitudinal cognitive performance. Methods: A total of 477 subjects with age-relatedWMLwere evaluated with brain MRI and annual neuropsychological examinations in 3-year follow-up. Baseline MRI determinants of cognitive decline were analyzed with linear mixed models controlling for multiple confounders. Results: MTA and subcortical atrophy predicted significantly steeper rate of decline in global cognitive measures as well as compound scores for psychomotor speed, executive functions, and memory after adjusting for age, gender, education, lacunes/infarcts, and WML volume. Cortical atrophy independently predicted decline in psychomotor speed. WML volume remained significantly associated with cognitive decline even after controlling for the atrophy scores. Moreover, significant synergistic interactions were found between WML and atrophy measures in overall cognitive performance across time and the rate of cognitive decline. Synergistic effects were also observed between baseline lacunar infarcts and all atrophy measures on change in psychomotor speed. The main results remained robust after exclusion of subjects with clinical stroke or incident dementia, and after additional adjustments for progression of WML and lacunes. Conclusions: Brain atrophy and WML are independently related to longitudinal cognitive decline in small vessel disease. MTA, subcortical, and cortical atrophy seem to potentiate the effect ofWML and lacunes on cognitive decline