Integrated Calendar

The Microlensing planet searches are being radically transformed. The event rate is in process of increasing 15-fold to ~50/year in 2015. While this is still small compared to other techniques, microlensing is uniquely capable of probing low-mass planets in the cold outer parts of solar systems. Once thought to be a "purely statistical" method, microlens planet detections now frequently yield detailed information about individual systems, including masses, distances, and orbital motion. These include terrestrial mass planets in Earth-like orbits, multi-planet systems, and planets in binary systems. Microlensing is yielding full orbital solutions of binary lenses (a prospect once
considered preposterous) which opens the way for direct testing by RV followup. I review the recent discoveries made possible by the microlensing revolution, and discuss a second revolution that is now just in its planning stages.

This talk outlines the main experimental results regarding the research of nanosecond time-scale discharge in gases as air, H2 and He2, conducted at P≥105 Pa. Discharges were ignited in gas filled chambers, with interelectrode gap ≤3cm, by application of high-voltage (HV) pulses ≤200 kV in amplitude and duration ≤5ns at FWHM to a blade cathode. The discharge is ignited by runaway electrons (RAE), responsible for pre-ionization of the gas, thus allowing for the discharge to develop during single nanoseconds. In the last 4 years we have investigated this discharge using a variety of non-disturbing diagnostics with temporal resolution close to a single nanosecond: fast-framing imaging, x-ray foil spectroscopy, electron beam imaging, electron beam foil spectroscopy, optical emission spectroscopy and Coherent anti-Stokes Raman Scattering. Profound conclusions were drawn regarding the dynamics of the discharge and dependence on the gas and pressure, energy spectrum of RAE and the x-ray radiation, RAE emission mechanism, plasma parameters such as electron density and temperature, intensity of electric fields present in the plasma channels and conductivity of the discharge plasma.

One of the fundamental challenges for describing intelligent systems is quantifying the balance between their physical - metabolic and energetic - requirements, and information processing requirements for sensing and acting. Both statistical mechanics and information theory provide many examples for such computational tradeoffs. The question is if we can extend these principles to living and intelligent systems that are far from thermodynamic equilibrium. Starting form Large Deviation Theory (the asymptotic theory behind statistical mechanics) we can obtain connections between costs and reward rates and control and sensing information rates, for systems in "metabolic information equilibrium" with stationary stochastic environments (Tishby & Polani, 2010). This result can be considered as the canonical equilibrium characterization for systems that obtain a certain value through interactions with a stochastic environment, but have no new learning (e.g. "stupid" cleaning robots). The affect of learning can be considered by revisiting the sub-extensivity of predictive information in stationary environments (Bialek, Nemenman & Tishby 2002) and combining it with the requirement of computational tractability of planning. We argue that planning is possible if the information flow terms remain proportional to the reward terms on the one hand, but still bounded by the sub-extensive predictive information on the other hand.
I will discuss the possible implications of this new computational principle to the emergence of hierarchical representations via a renormalization scheme for the Bellman equation - the canonical equation of planning and control.