Energy-Efficient Circuit Design

We initiate the theoretical investigation of energy-efficient circuit design. We assume that the circuit design specifies the circuit layout as well as the supply voltages for the gates. To obtain maximum energy efficiency, the circuit design must balance the conflicting demands of minimizing the energy used per gate, and minimizing the number of gates in the circuit; If the energy supplied to the gates is small, then functional failures are likely, necessitating a circuit layout that is more fault-tolerant, and thus that has more gates. By leveraging previous work on fault-tolerant circuit design, we show general upper and lower bounds on the amount of energy required by a circuit to compute a given relation. We show that some circuits would be asymptotically more energy-efficient if heterogeneous supply voltages were allowed, and show that for some circuits the most energy-efficient supply voltages are homogeneous over all gates. In the traditional approach to circuit design the supply voltages for each transistor/gate are set sufficiently high so that with sufficiently high probability no transistor fails. We show that if there is a better (in terms of worst-case relative error with respect to energy) method than the traditional approach then $P=NP$, and thus there is a complexity theoretic obstacle to achieving energy savings with Near-Threshold computing. We show that almost all Boolean functions require circuits that use exponential energy. This is not an immediate consequence of Shannon's classic result that most functions require exponential sized circuits of faultless gates because, as we show, the same circuit layout can compute many different functions, depending on the value of the supply voltage. If the error bound must vanish as the number of inputs increases, we show that a natural class of functions can be computed with asymptotically less energy using heterogeneous supply voltages than is possible using homogeneous supply voltages. We also prove upper bounds on the asymptotic energy savings achieved by using heterogeneous supply voltages over homogeneous supply voltages for a class of functions, and also show a relation that can bypass this bound

Quantum harmonic oscillator systems with disorder

We study many-body properties of quantum harmonic oscillator lattices with disorder. A sufficient condition for dynamical localization, expressed as a zero-velocity Lieb-Robinson bound, is formulated in terms of the decay of the eigenfunction correlators for an effective one-particle Hamiltonian. We show how state-of-the-art techniques for proving Anderson localization can be used to prove that these properties hold in a number of standard models. We also derive bounds on the static and dynamic correlation functions at both zero and positive temperature in terms of one-particle eigenfunction correlators. In particular, we show that static correlations decay exponentially fast if the corresponding effective one-particle Hamiltonian exhibits localization at low energies, regardless of whether there is a gap in the spectrum above the ground state or not. Our results apply to finite as well as to infinite oscillator systems. The eigenfunction correlators that appear are more general than those previously studied in the literature. In particular, we must allow for functions of the Hamiltonian that have a singularity at the bottom of the spectrum. We prove exponential bounds for such correlators for some of the standard models

Explicitly correlated trial wave functions in Quantum Monte Carlo calculations of excited states of Be and Be-

We present a new form of explicitly correlated wave function whose parameters are mainly linear, to circumvent the problem of the optimization of a large number of non-linear parameters usually encountered with basis sets of explicitly correlated wave functions. With this trial wave function we succeeded in minimizing the energy instead of the variance of the local energy, as is more common in quantum Monte Carlo methods. We applied this wave function to the calculation of the energies of Be 3P (1s22p2) and Be- 4So (1s22p3) by variational and diffusion Monte Carlo methods. The results compare favorably with those obtained by different types of explicitly correlated trial wave functions already described in the literature. The energies obtained are improved with respect to the best variational ones found in literature, and within one standard deviation from the estimated non-relativistic limitsComment: 19 pages, no figures, submitted to J. Phys.

Percentile Queries in Multi-Dimensional Markov Decision Processes

Markov decision processes (MDPs) with multi-dimensional weights are useful to analyze systems with multiple objectives that may be conflicting and require the analysis of trade-offs. We study the complexity of percentile queries in such MDPs and give algorithms to synthesize strategies that enforce such constraints. Given a multi-dimensional weighted MDP and a quantitative payoff function $f$, thresholds $v_i$ (one per dimension), and probability thresholds $\alpha_i$, we show how to compute a single strategy to enforce that for all dimensions $i$, the probability of outcomes $\rho$ satisfying $f_i(\rho) \geq v_i$ is at least $\alpha_i$. We consider classical quantitative payoffs from the literature (sup, inf, lim sup, lim inf, mean-payoff, truncated sum, discounted sum). Our work extends to the quantitative case the multi-objective model checking problem studied by Etessami et al. in unweighted MDPs.Comment: Extended version of CAV 2015 pape