Reversibility of laser filamentation

We investigate the reversibility of laser filamentation, a self-sustained, non-linear propagation regime including dissipation and time-retarded effects. We show that even losses related to ionization marginally affect the possibility of reverse propagating ultrashort pulses back to the initial conditions, although they make it prone to finite-distance blow-up susceptible to prevent backward propagation.Comment: 12 pages, 3 figure

Oblivious transfer and quantum channels

We show that oblivious transfer can be seen as the classical analogue to a quantum channel in the same sense as non-local boxes are for maximally entangled qubits.Comment: Invited Paper at the 2006 IEEE Information Theory Workshop (ITW 2006

Non-linear Synthesis of Complex Laser Waveforms at Remote Distances

Strong deformation of ultrashort laser pulse shapes is unavoidable when delivering high intensities at remote distances due to non-linear effects taking place while propagating. Relying on the reversibility of laser filamentation, we propose to explicitly design laser pulse shapes so that propagation serves as a non-linear field synthesizer at a remote target location. Such an approach allows, for instance, coherent control of molecules at a remote distance, in the context of standoff detection of pathogens or explosives.Comment: 17 pages, 6 figure

Essays on Natural Experiments in Behavioral Finance and Trade

Natural Experiments; Behavioral Finance; Trade

Linearity of charge measurement in laser filaments

We evaluate the linearity of three electric measurement techniques of the initial electron density in laser filaments by comparing their results for a pair of filaments and for the sum of each individual filament. The conductivity measured between two plane electrodes in a longitudinal configuration is linear within 2% provided the electric field is kept below 100 kV/m. Furthermore, simulations show that the signal behaves like the amount of generated free electrons. The slow ionic current measured with plane electrodes in a parallel configuration is representative of the ionic charge available in the filament, after several $\mu$s, when the free electrons have recombined. It is linear within 2% with the amount of ions and is insensitive to misalignment. Finally, the fast polarization signal in the same configuration deviates from linearity by up to 80% and can only be considered as a semi-qualitative indication of the presence of charges, e.g., to characterize the filament length.Comment: 17 pages, 7 figure

LIPIcs

A deterministic finite automaton (DFA) is composite if its language L() can be decomposed into an intersection ⋂_{i = 1}^k L(_i) of languages of smaller DFAs. Otherwise, is prime. This notion of primality was introduced by Kupferman and Mosheiff in 2013, and while they proved that we can decide whether a DFA is composite, the precise complexity of this problem is still open, with a doubly-exponential gap between the upper and lower bounds. In this work, we focus on permutation DFAs, i.e., those for which the transition monoid is a group. We provide an NP algorithm to decide whether a permutation DFA is composite, and show that the difficulty of this problem comes from the number of non-accepting states of the instance: we give a fixed-parameter tractable algorithm with the number of rejecting states as the parameter. Moreover, we investigate the class of commutative permutation DFAs. Their structural properties allow us to decide compositionality in NL, and even in LOGSPACE if the alphabet size is fixed. Despite this low complexity, we show that complex behaviors still arise in this class: we provide a family of composite DFAs each requiring polynomially many factors with respect to its size. We also consider the variant of the problem that asks whether a DFA is k-factor composite, that is, decomposable into k smaller DFAs, for some given integer k ∈ ℕ. We show that, for commutative permutation DFAs, restricting the number of factors makes the decision computationally harder, and yields a problem with tight bounds: it is NP-complete. Finally, we show that in general, this problem is in PSPACE, and it is in LOGSPACE for DFAs with a singleton alphabet

The Brown Algal Virus EsV-1 Particle Contains a Putative Hybrid Histidine Kinase

AbstractThe Ectocarpus siliculosus virus, EsV-1, occurs worldwide in all populations of the filamentous marine brown alga E. siliculosus. We have screened an expression library of EsV-1 restriction fragments and identified a DNA clone with the potential to code for a 52-kDa histidine protein kinase. The derived amino acid sequence includes all homology boxes diagnostic for histidine protein kinases and, in addition, amino acid motifs that are commonly found in response regulators of bacterial two-component signal transduction proteins. Thus, the novel viral protein can be classified as a hybrid histidine protein kinase of a type that has previously been detected in fungi, slime molds, and plants. By using purified antibodies, we found that the protein with its potential kinase activity is located on the outer shell of viral particles. This is the first report on a two-component regulator-like protein in viruses and could provide the basis for speculations with regard to the evolution of EsV-1 and related viruses

Reverse-time analysis and boundary classification of directional biological dynamics with multiplicative noise

The dynamics of living systems often serves the purpose of reaching functionally important target states. We previously proposed a theory to analyze stochastic biological dynamics evolving towards target states in reverse time. However, a large class of systems in biology can only be adequately described using state-dependent noise, which had not been discussed. For example, in gene regulatory networks, biochemical signaling networks or neuronal circuits, count fluctuations are the dominant noise component. We characterize such dynamics as an ensemble of target state aligned (TSA) trajectories and characterize its temporal evolution in reverse-time by generalized Fokker-Planck and stochastic differential equations with multiplicative noise. We establish the classification of boundary conditions for target state modeling for a wide range of power law dynamics, and derive a universal low-noise approximation of the final phase of target state convergence. Our work expands the range of theoretically tractable systems in biology and enables novel experimental design strategies for systems that involve target states