Fast heating of ultrahigh-density plasma as a step towards laser fusion ignition

ate studies(2) and fusion energy research(3,4). Laser-driven implosions of spherical polymer shells have, for example, achieved an increase in density of 1,000 times relative to the solid state(5). These densities are large enough to enable controlled fusion, but to achieve energy gain a small volume of compressed fuel (known as the 'spark') must be heated to temperatures of about 10(8) K (corresponding to thermal energies in excess of 10 keV). In the conventional approach to controlled fusion, the spark is both produced and heated by accurately timed shock waves(4), but this process requires both precise implosion symmetry and a very large drive energy. In principle, these requirements can be significantly relaxed by performing the compression and fast heating separately(6-10); however, this 'fast ignitor' approach(7) also suffers drawbacks, such as propagation losses and deflection of the ultra-intense laser pulse by the plasma surrounding the compressed fuel. Here we employ a new compression geometry that eliminates these problems; we combine production of compressed matter in a laser-driven implosion with picosecond-fast heating by a laser pulse timed to coincide with the peak compression. Our approach therefore permits efficient compression and heating to be carried out simultaneously, providing a route to efficient fusion energy production.

Temperature, predator-prey interaction strength and population stability

Warming could strongly stabilize or destabilize populations and food webs by changing the interaction strengths between predators and their prey. Predicting the consequences of warming requires understanding how temperature affects ingestion (energy gain) and metabolism (energy loss). Here, we studied the temperature dependence of metabolism and ingestion in laboratory experiments with terrestrial arthropods (beetles and spiders). From this data, we calculated ingestion efficiencies (ingestion/metabolism) and per capita interaction strengths in the short and long term. Additionally, we investigated if and how body mass changes these temperature dependencies. For both predator groups, warming increased metabolic rates substantially, whereas temperature effects on ingestion rates were weak. Accordingly, the ingestion efficiency (the ratio of ingestion to metabolism) decreased in all treatments. This result has two possible consequences: on the one hand, it suggests that warming of natural ecosystems could increase intrinsic population stability, meaning less fluctuations in population density; on the other hand, decreasing ingestion efficiencies may also lead to higher extinction risks because of starvation. Additionally, predicted long-term per capita interaction strengths decreased with warming, which suggests an increase in perturbation stability of populations, i.e., a higher probability of returning to the same equilibrium density after a small perturbation. Together, these results suggest that warming has complex and potentially profound effects on predator-prey interactions and food-web stability.

Gain saturation of the Ni-like X-ray lasers

Driven by a double 75 ps pulse with 2.2 ns separation, saturated operation of nickel-like Ag, In, Sn, and Sm X-ray lasers have been demonstrated with only 75 J drive energy on target. The variation of X-ray laser output with target length is found to fit well to a simple model for an amplified spontaneous emission (ASE) laser including saturation. Small signal gains of similar to 10 cm(-1), effective gain length products of similar to 18, and saturation irradiance of (1-5)x 10(10) W/cm(2) are measured for these lasers using a fitting procedure. (C) 1998 Elsevier Science B.V. All rights reserved.

GAIN SCALING RELATIONSHIPS FOR NE-LIKE GE SLAB TARGETS

The gain coefficient of the strongest 3p --> 3s, J = 2 --> 1 lasing transition at 23.6 nm in the Ne-like Ge collisional excitation scheme has been measured, using the fundamental wavelength from a Nd:glass laser (1.06-mu-m), for a range of incident intensities on massive stripe targets up to 2.2 cm in length. From a threshold incident laser intensity of approximately 6 x 10(12) W/cm2, the gain coefficient rises to approximately 4.5 cm-1 for an irradiation intensity of approximately 2.5 x 10(13) W/cm2, tending towards still higher gain coefficients at higher incident intensities. For targets of maximum length, a gain-length product gL almost-equal-to 10 was reached with a resultant output power at 23.6 nm estimated to be at the approximately kW level. The beam divergence decreased with length to a minimum of approximately 7 mrad but no significant trend in beam pointing with plasma length was observed. From the trend in the gain coefficient, it appears that for a fixed energy laser irradiating a approximately 100-mu-m wide slab targets, an incident intensity of I(i) approximately 1.2 x 10(13) W/cm2 represents an optimum working level, assuming that plasma length is not limited by refractive effects. In addition to the usual valence electron excited 3p --> 3s transitions, the gain coefficient for the core excited 1s(2)2s2p(6)3d --> 1s(2)2s2p(6)3p transition at 19.9 nm has been measured to be approximately 1.5 cm-1 for an incident irradiance of approximately 2.5 x 10(13) W/cm2.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

Experimental demonstration of particle energy, conversion efficiency and spectral shape required for ion-based fast ignition

Research on fusion fast ignition (FI) initiated by laser-driven ion beams has made substantial progress in the last years. Compared with electrons, FI based on a beam of quasi-monoenergetic ions has the advantage of a more localized energy deposition, and stiffer particle transport, bringing the required total beam energy close to the theoretical minimum. Due to short pulse laser drive, the ion beam can easily deliver the 200 TW power required to ignite the compressed D-T fuel. In integrated calculations we recently simulated ion-based FI targets with high fusion gain targets and a proof of principle experiment [1]. These simulations identify three key requirements for the success of ion-driven fast ignition (IFI): (1) the generation of a sufficiently high-energetic ion beam (approximate to 400-500 MeV for C), with (2) less than 20% energy spread at (3) more than 10% conversion efficiency of laser to beam energy. Here we present for the first time new experimental results, demonstrating all three parameters in separate experiments. Using diamond nanotargets and ultrahigh contrast laser pulses we were able to demonstrate >500 MeV carbon ions, as well as carbon pulses with Delta E/E

How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?

Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems. © 2010 IEEE.

Energy-Aware Rate and Description Allocation Optimized Video Streaming for Mobile D2D Communications

The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

An investigation of IAQ, thermal comfort and Sick Building Syndrome symptoms in UK energy efficient homes

Purpose
– Concern of the deterioration of indoor environmental quality as a result of energy efficient building design strategies is growing. Apprehensions of the effect of airtight, super insulated envelopes, the reduction of infiltration, and the reliance on mechanical systems to provide adequate ventilation (air supply) is promoting emerging new research in this field. The purpose of this paper is to present the results of an indoor air quality (IAQ) and thermal comfort investigation in UK energy efficient homes, through a case study investigation.

Design/methodology/approach
– The case study dwellings consisted of a row of six new-build homes which utilize mechanical ventilation with heat recovery (MVHR) systems, are built to an average airtightness of 2m3/m2/hr at 50 Pascal’s, and constructed without a central heating system. Physical IAQ measurements and occupant interviews were conducted during the summer and winter months over a 24-hour period, to gain information on occupant activities, perception of the interior environment, building-related health and building use.

Findings
– The results suggest inadequate IAQ and perceived thermal comfort, insufficient use of purge ventilation, presence of fungal growth, significant variances in heating patterns, occurrence of sick building syndrome symptoms and issues with the MVHR system.

Practical implications
– The findings will provide relevant data on the applicability of airtight, mechanically ventilated homes in a UK climate, with particular reference to IAQ.

Originality/value
– IAQ data of this nature is essentially lacking, particularly in the UK context. The findings will aid the development of effective sustainable design strategies that are appropriate to localized climatic conditions and sensitive to the health of building occupants.

Extended Energy Vector Prediction of Ambisonically Reproduced Image Direction at Off-Centre Listening Positions

This paper presents an extension to the energy vector, well known in the Ambisonics literature, to improve its predictions of localisation at off-centre listening positions. In determining the source direction, a perceptual weight is assigned to each loudspeaker gain, taking into account the relative arrival times, levels, and directions of the loudspeaker signals. The proposed model is evaluated alongside the original energy vector and two binaural models through comparison with the results of recent perceptual studies. The extended version was found to provide results that were at least 50% more accurate than the second best predictor for two experiments involving off-centre listeners with first- and third-order Ambisonics systems.

Energy efficiency optimization in hardware-constrained large-scale MIMO systems

Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.