2 Search Results for "Cook, James"

Document
DOI: 10.4230/LIPIcs.CCC.2022.8
Trading Time and Space in Catalytic Branching Programs

Authors: James Cook and Ian Mertz

Published in: LIPIcs, Volume 234, 37th Computational Complexity Conference (CCC 2022)

Abstract
An m-catalytic branching program (Girard, Koucký, McKenzie 2015) is a set of m distinct branching programs for f which are permitted to share internal (i.e. non-source non-sink) nodes. While originally introduced as a non-uniform analogue to catalytic space, this also gives a natural notion of amortized non-uniform space complexity for f, namely the smallest value |G|/m for an m-catalytic branching program G for f (Potechin 2017). Potechin (2017) showed that every function f has amortized size O(n), witnessed by an m-catalytic branching program where m = 2^(2ⁿ-1). We recreate this result by defining a catalytic algorithm for evaluating polynomials using a large amount of space but O(n) time. This allows us to balance this with previously known algorithms which are efficient with respect to space at the cost of time (Cook, Mertz 2020, 2021). We show that for any ε ≥ 2n^(-1), every function f has an m-catalytic branching program of size O_ε(mn), where m = 2^(2^(ε n)). We similarly recreate an improved result due to Robere and Zuiddam (2021), and show that for d ≤ n and ε ≥ 2d^(-1), the same result holds for m = 2^binom(n, ≤ ε d) as long as f is a degree-d polynomial over 𝔽₂. We also show that for certain classes of functions, m can be reduced to 2^(poly n) while still maintaining linear or quasi-linear amortized size. In the other direction, we bound the necessary length, and by extension the amortized size, of any permutation branching program for an arbitrary function between 3n and 4n-4.
Cite as

James Cook and Ian Mertz. Trading Time and Space in Catalytic Branching Programs. In 37th Computational Complexity Conference (CCC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 234, pp. 8:1-8:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)

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@InProceedings{cook_et_al:LIPIcs.CCC.2022.8,
  author =	{Cook, James and Mertz, Ian},
  title =	{{Trading Time and Space in Catalytic Branching Programs}},
  booktitle =	{37th Computational Complexity Conference (CCC 2022)},
  pages =	{8:1--8:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-241-9},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{234},
  editor =	{Lovett, Shachar},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2022.8},
  URN =		{urn:nbn:de:0030-drops-165708},
  doi =		{10.4230/LIPIcs.CCC.2022.8},
  annote =	{Keywords: complexity theory, branching programs, amortized, space complexity, catalytic computation}
}
Document
DOI: 10.4230/LITES-v004-i001-a004
How Is Your Satellite Doing? Battery Kinetics with Recharging and Uncertainty

Authors: Holger Hermanns, Jan Krčál, and Gilles Nies

Published in: LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1

Abstract
The kinetic battery model is a popular model of the dynamic behaviour of a conventional battery, useful to predict or optimize the time until battery depletion. The model however lacks certain obvious aspects of batteries in-the-wild, especially with respect to the effects of random influences and the behaviour when charging up to capacity limits.This paper considers the kinetic battery model with limited capacity in the context of piecewise constant yet random charging and discharging. We provide exact representations of the battery behaviour wherever possible, and otherwise develop safe approximations that bound the probability distribution of the battery state from above and below. The resulting model enables the time-dependent evaluation of the risk of battery depletion. This is demonstrated in an extensive dependability study of a nano satellite currently orbiting the earth.
Cite as

Holger Hermanns, Jan Krčál, and Gilles Nies. How Is Your Satellite Doing? Battery Kinetics with Recharging and Uncertainty. In LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1, pp. 04:1-04:28, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2017)

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@Article{hermanns_et_al:LITES-v004-i001-a004,
  author =	{Hermanns, Holger and Kr\v{c}\'{a}l, Jan and Nies, Gilles},
  title =	{{How Is Your Satellite Doing? Battery Kinetics with Recharging and Uncertainty}},
  booktitle =	{LITES, Volume 4, Issue 1 (2017)},
  pages =	{04:1--04:28},
  journal =	{Leibniz Transactions on Embedded Systems},
  ISSN =	{2199-2002},
  year =	{2017},
  volume =	{4},
  number =	{1},
  editor =	{Hermanns, Holger and Kr\v{c}\'{a}l, Jan and Nies, Gilles},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001-a004},
  doi =		{10.4230/LITES-v004-i001-a004},
  annote =	{Keywords: Battery Power, Depletion Risk, Bounded Charging and Discharging, Stochastic Load, Distribution Bounds}
}
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