3 Search Results for "Shen, Yu-Ching"

Document
DOI: 10.4230/LIPIcs.CCC.2023.33
On the Impossibility of General Parallel Fast-Forwarding of Hamiltonian Simulation

Authors: Nai-Hui Chia, Kai-Min Chung, Yao-Ching Hsieh, Han-Hsuan Lin, Yao-Ting Lin, and Yu-Ching Shen

Published in: LIPIcs, Volume 264, 38th Computational Complexity Conference (CCC 2023)

Abstract
Hamiltonian simulation is one of the most important problems in the field of quantum computing. There have been extended efforts on designing algorithms for faster simulation, and the evolution time T for the simulation greatly affect algorithm runtime as expected. While there are some specific types of Hamiltonians that can be fast-forwarded, i.e., simulated within time o(T), for some large classes of Hamiltonians (e.g., all local/sparse Hamiltonians), existing simulation algorithms require running time at least linear in the evolution time T. On the other hand, while there exist lower bounds of Ω(T) circuit size for some large classes of Hamiltonian, these lower bounds do not rule out the possibilities of Hamiltonian simulation with large but "low-depth" circuits by running things in parallel. As a result, physical systems with system size scaling with T can potentially do a fast-forwarding simulation. Therefore, it is intriguing whether we can achieve fast Hamiltonian simulation with the power of parallelism. In this work, we give a negative result for the above open problem in various settings. In the oracle model, we prove that there are time-independent sparse Hamiltonians that cannot be simulated via an oracle circuit of depth o(T). In the plain model, relying on the random oracle heuristic, we show that there exist time-independent local Hamiltonians and time-dependent geometrically local Hamiltonians on n qubits that cannot be simulated via an oracle circuit of depth o(T/n^c), where the Hamiltonians act on n qubits, and c is a constant. Lastly, we generalize the above results and show that any simulators that are geometrically local Hamiltonians cannot do the simulation much faster than parallel quantum algorithms.
Cite as

Nai-Hui Chia, Kai-Min Chung, Yao-Ching Hsieh, Han-Hsuan Lin, Yao-Ting Lin, and Yu-Ching Shen. On the Impossibility of General Parallel Fast-Forwarding of Hamiltonian Simulation. In 38th Computational Complexity Conference (CCC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 264, pp. 33:1-33:45, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{chia_et_al:LIPIcs.CCC.2023.33,
  author =	{Chia, Nai-Hui and Chung, Kai-Min and Hsieh, Yao-Ching and Lin, Han-Hsuan and Lin, Yao-Ting and Shen, Yu-Ching},
  title =	{{On the Impossibility of General Parallel Fast-Forwarding of Hamiltonian Simulation}},
  booktitle =	{38th Computational Complexity Conference (CCC 2023)},
  pages =	{33:1--33:45},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-282-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{264},
  editor =	{Ta-Shma, Amnon},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2023.33},
  URN =		{urn:nbn:de:0030-drops-183038},
  doi =		{10.4230/LIPIcs.CCC.2023.33},
  annote =	{Keywords: Hamiltonian simulation, Depth lower bound, Parallel query lower bound}
}
Document
DOI: 10.4230/LIPIcs.STACS.2019.57
Random Noise Increases Kolmogorov Complexity and Hausdorff Dimension

Authors: Gleb Posobin and Alexander Shen

Published in: LIPIcs, Volume 126, 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019)

Abstract
Consider a bit string x of length n and Kolmogorov complexity alpha n (for some alpha<1). It is always possible to increase the complexity of x by changing a small fraction of bits in x [Harry Buhrman et al., 2005]. What happens with the complexity of x when we randomly change each bit independently with some probability tau? We prove that a linear increase in complexity happens with high probability, but this increase is smaller than in the case of arbitrary change considered in [Harry Buhrman et al., 2005]. The amount of the increase depends on x (strings of the same complexity could behave differently). We give exact lower and upper bounds for this increase (with o(n) precision). The same technique is used to prove the results about the (effective Hausdorff) dimension of infinite sequences. We show that random change increases the dimension with probability 1, and provide an optimal lower bound for the dimension of the changed sequence. We also improve a result from [Noam Greenberg et al., 2018] and show that for every sequence omega of dimension alpha there exists a strongly alpha-random sequence omega' such that the Besicovitch distance between omega and omega' is 0. The proofs use the combinatorial and probabilistic reformulations of complexity statements and the technique that goes back to Ahlswede, Gács and Körner [Ahlswede et al., 1976].
Cite as

Gleb Posobin and Alexander Shen. Random Noise Increases Kolmogorov Complexity and Hausdorff Dimension. In 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 126, pp. 57:1-57:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)

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@InProceedings{posobin_et_al:LIPIcs.STACS.2019.57,
  author =	{Posobin, Gleb and Shen, Alexander},
  title =	{{Random Noise Increases Kolmogorov Complexity and Hausdorff Dimension}},
  booktitle =	{36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019)},
  pages =	{57:1--57:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-100-9},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{126},
  editor =	{Niedermeier, Rolf and Paul, Christophe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2019.57},
  URN =		{urn:nbn:de:0030-drops-102969},
  doi =		{10.4230/LIPIcs.STACS.2019.57},
  annote =	{Keywords: Kolmogorov complexity, effective Hausdorff dimension, random noise}
}
Document
DOI: 10.4230/LITES-v003-i001-a005
A Survey on Static Cache Analysis for Real-Time Systems

Authors: Mingsong Lv, Nan Guan, Jan Reineke, Reinhard Wilhelm, and Wang Yi

Published in: LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1

Abstract
Real-time systems are reactive computer systems that must produce their reaction to a stimulus within given time bounds. A vital verification requirement is to estimate the Worst-Case Execution Time (WCET) of programs. These estimates are then used to predict the timing behavior of the overall system. The execution time of a program heavily depends on the underlying hardware, among which cache has the biggest influence. Analyzing cache behavior is very challenging due to the versatile cache features and complex execution environment. This article provides a survey on static cache analysis for real-time systems. We first present the challenges and static analysis techniques for independent programs with respect to different cache features. Then, the discussion is extended to cache analysis in complex execution environment, followed by a survey of existing tools based on static techniques for cache analysis. An outlook for future research is provided at last.
Cite as

Mingsong Lv, Nan Guan, Jan Reineke, Reinhard Wilhelm, and Wang Yi. A Survey on Static Cache Analysis for Real-Time Systems. In LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1, pp. 05:1-05:48, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2016)

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@Article{lv_et_al:LITES-v003-i001-a005,
  author =	{Lv, Mingsong and Guan, Nan and Reineke, Jan and Wilhelm, Reinhard and Yi, Wang},
  title =	{{A Survey on Static Cache Analysis for Real-Time Systems}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{05:1--05:48},
  ISSN =	{2199-2002},
  year =	{2016},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v003-i001-a005},
  doi =		{10.4230/LITES-v003-i001-a005},
  annote =	{Keywords: Hard real-time, Cache analysis, Worst-case execution time}
}
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