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Daniel Valenzuela

Publications and source records attributed to Daniel Valenzuela.

7 recordsLinked to original sources
arXiv2022

The effect of complex dispersion and characteristic impedance on the gain of superconducting traveling-wave kinetic inductance parametric amplifiers

Superconducting traveling-wave parametric amplifiers are a promising amplification technology suitable for applications in submillimeter astronomy. Their implementation relies on the use of Floquet transmission lines in order to create strong stopbands to suppress undesired harmonics. In the design process, amplitude equations are used to predict their gain, operation frequency, and bandwidth. However, usual amplitude equations do not take into account the real and imaginary parts of the dispersion and characteristic impedance that results from the use of Floquet lines, hindering reliable design. In order to overcome this limitation, we have used the multiple-scales method to include those effects. We demonstrate that complex dispersion and characteristic impedance have a stark effect on the transmission line's gain, even suppressing it completely in certain cases. The equations presented here can, thus, guide to a better design and understanding of the properties of this kind of amplifiers.

physics.app-ph↗
arXiv2020

Lempel-Ziv-like Parsing in Small Space

Lempel-Ziv (LZ77 or, briefly, LZ) is one of the most effective and widely-used compressors for repetitive texts. However, the existing efficient methods computing the exact LZ parsing have to use linear or close to linear space to index the input text during the construction of the parsing, which is prohibitive for long inputs. An alternative is Relative Lempel-Ziv (RLZ), which indexes only a fixed reference sequence, whose size can be controlled. Deriving the reference sequence by sampling the text yields reasonable compression ratios for RLZ, but performance is not always competitive with that of LZ and depends heavily on the similarity of the reference to the text. In this paper we introduce ReLZ, a technique that uses RLZ as a preprocessor to approximate the LZ parsing using little memory. RLZ is first used to produce a sequence of phrases, and these are regarded as metasymbols that are input to LZ for a second-level parsing on a (most often) drastically shorter sequence. This parsing is finally translated into one on the original sequence. We analyze the new scheme and prove that, like LZ, it achieves the $k$th order empirical entropy compression $n H_k + o(n\logσ)$ with $k = o(\log_σn)$, where $n$ is the input length and $σ$ is the alphabet size. In fact, we prove this entropy bound not only for ReLZ but for a wide class of LZ-like encodings. Then, we establish a lower bound on ReLZ approximation ratio showing that the number of phrases in it can be $Ω(\log n)$ times larger than the number of phrases in LZ. Our experiments show that ReLZ is faster than existing alternatives to compute the (exact or approximate) LZ parsing, at the reasonable price of an approximation factor below $2.0$ in all tested scenarios, and sometimes below $1.05$, to the size of LZ.

cs.DS↗
arXiv2018

Hardness of Covering Alignment: Phase Transition in Post-Sequence Genomics

Covering alignment problems arise from recent developments in genomics; so called pan-genome graphs are replacing reference genomes, and advances in haplotyping enable full content of diploid genomes to be used as basis of sequence analysis. In this paper, we show that the computational complexity will change for natural extensions of alignments to pan-genome representations and to diploid genomes. More broadly, our approach can also be seen as a minimal extension of sequence alignment to labelled directed acyclic graphs (labeled DAGs). Namely, we show that finding a \emph{covering alignment} of two labeled DAGs is NP-hard even on binary alphabets. A covering alignment asks for two paths $R_1$ (red) and $G_1$ (green) in DAG $D_1$ and two paths $R_2$ (red) and $G_2$ (green) in DAG $D_2$ that cover the nodes of the graphs and maximize the sum of the global alignment scores: $\mathsf{as}(\mathsf{sp}(R_1),\mathsf{sp}(R_2))+\mathsf{as}(\mathsf{sp}(G_1),\mathsf{sp}(G_2))$, where $\mathsf{sp}(P)$ is the concatenation of labels on the path $P$. Pair-wise alignment of haplotype sequences forming a diploid chromosome can be converted to a two-path coverable labelled DAG, and then the covering alignment models the similarity of two diploids over arbitrary recombinations. We also give a reduction to the other direction, to show that such a recombination-oblivious diploid alignment is NP-hard on alphabets of size $3$.

cs.CC↗
arXiv2015

Interval scheduling maximizing minimum coverage

In the classical interval scheduling type of problems, a set of $n$ jobs, characterized by their start and end time, need to be executed by a set of machines, under various constraints. In this paper we study a new variant in which the jobs need to be assigned to at most $k$ identical machines, such that the minimum number of machines that are busy at the same time is maximized. This is relevant in the context of genome sequencing and haplotyping, specifically when a set of DNA reads aligned to a genome needs to be pruned so that no more than $k$ reads overlap, while maintaining as much read coverage as possible across the entire genome. We show that the problem can be solved in time $\min\left(O(n^2\log k / \log n),O(nk\log k)\right)$ by using max-flows. We also give an $O(n\log n)$-time approximation algorithm with approximation ratio $ρ=\frac{k}{\lfloor k/2 \rfloor}$.

cs.DS↗
arXiv2014

Compressed Spaced Suffix Arrays

Spaced seeds are important tools for similarity search in bioinformatics, and using several seeds together often significantly improves their performance. With existing approaches, however, for each seed we keep a separate linear-size data structure, either a hash table or a spaced suffix array (SSA). In this paper we show how to compress SSAs relative to normal suffix arrays (SAs) and still support fast random access to them. We first prove a theoretical upper bound on the space needed to store an SSA when we already have the SA. We then present experiments indicating that our approach works even better in practice.

cs.DS↗
arXiv2011

Practical Top-K Document Retrieval in Reduced Space

Supporting top-k document retrieval queries on general text databases, that is, finding the k documents where a given pattern occurs most frequently, has become a topic of interest with practical applications. While the problem has been solved in optimal time and linear space, the actual space usage is a serious concern. In this paper we study various reduced-space structures that support top-k retrieval and propose new alternatives. Our experimental results show that our novel algorithms and data structures dominate almost all the space/time tradeoff.

cs.DS↗