Role of plasma edge in the direct launch Ion Bernstein Wave experiment in TFTR

Two types of direct IBW launching, EPW {R_arrow} IBW and CESICW {R_arrow} IBW are investigated using two numerical codes, Full Hot Plasma Ray-Tracing Code and SEMAL Full Wave Slab Code, for the TFTR direct launch IBW experimental parameters. The measured density profiles (by microwave reflectometry) in TFTR appear to be satisfactory for IBW launching while the observed stored energy rise compared to the expected value (ray tracing + TRANSP) indicates only up to 50% of launched power is reaching the plasma core. Possible causes of IBW inefficiency are also discussed

Improvements in the CHERS system for DT experiments on TFTR

Improvements in the charge exchange recombination spectroscopy (CHERS) system have resulted in accurate measurements of T{sub i} and V{sub {phi}} profiles during DT experiments. These include moving the spectrometer detector array and electronics farther away from the tokamak to a low neutron flux location. This relocation has also improved access to all components of the system. Also, a nonplasma-viewing calibration fiber system was added to monitor the change in fiber transmission due to the high flux DT neutrons. Narrowband filtered light transmitted through the calibration fiber is now used as a reference for the VO measurement. At the highest neutron flux of {approximately} 2.5 {times} 10{sup 18} neutrons/see (fusion power {approximately} 6.2 MW) a modest 5% decrease in fiber transmission was observed. Corrections for transmission loss are made and T{sub i} (r,t) and absolute V{sub phi} (r,t) profiles are automatically calculated within four minutes of every shot

Turing machines can be efficiently simulated by the General Purpose Analog Computer

The Church-Turing thesis states that any sufficiently powerful computational model which captures the notion of algorithm is computationally equivalent to the Turing machine. This equivalence usually holds both at a computability level and at a computational complexity level modulo polynomial reductions. However, the situation is less clear in what concerns models of computation using real numbers, and no analog of the Church-Turing thesis exists for this case. Recently it was shown that some models of computation with real numbers were equivalent from a computability perspective. In particular it was shown that Shannon's General Purpose Analog Computer (GPAC) is equivalent to Computable Analysis. However, little is known about what happens at a computational complexity level. In this paper we shed some light on the connections between this two models, from a computational complexity level, by showing that, modulo polynomial reductions, computations of Turing machines can be simulated by GPACs, without the need of using more (space) resources than those used in the original Turing computation, as long as we are talking about bounded computations. In other words, computations done by the GPAC are as space-efficient as computations done in the context of Computable Analysis

Towards an Axiomatization of Simple Analog Algorithms

International audienceWe propose a formalization of analog algorithms, extending the framework of abstract state machines to continuous-time models of computation

The general purpose analog computer and computable analysis are two equivalent paradigms of analog computation

In this paper we revisit one of the rst models of analog computation, Shannon's General Purpose Analog Computer (GPAC). The GPAC has often been argued to be weaker than computable analysis. As main contribution, we show that if we change the notion of GPACcomputability in a natural way, we compute exactly all real computable functions (in the sense of computable analysis). Moreover, since GPACs are equivalent to systems of polynomial di erential equations then we show that all real computable functions can be de ned by such models

Solving analytic differential equations in polynomial time over unbounded domains

In this paper we consider the computational complexity of solving initial-value problems de ned with analytic ordinary diferential equations (ODEs) over unbounded domains of Rn and Cn, under the Computable Analysis setting. We show that the solution can be computed in polynomial time over its maximal interval of de nition, provided it satis es a very generous bound on its growth, and that the function admits an analytic extension to the complex plane