Search

Tidal interactions between galaxies often give rise to tidal tails, which can harbor concentrations of stars and interstellar gas resembling dwarf galaxies. Some of these tidal dwarf galaxies (TDGs) have the potential to detach from their parent galaxies and become independent entities, but their long-term survival is uncertain. In this study, we conducted a search for detached TDGs associated with a sample of 39 interacting galaxy pairs in the local Universe using infrared, ultraviolet, and optical images. We employed IR colors and UV/optical/IR spectral energy distributions to identify potential interlopers, such as foreground stars or background quasars. Through spectroscopic observations using the Boller and Chivens spectrograph at San Pedro M\'artir Observatory, we confirmed that six candidate TDGs are at the same redshift as their putative parent galaxy pairs. We identified and measured emission lines in the optical spectra and calculated nebular oxygen abundances, which range from log(O/H) = 8.10 $\pm$ 0.01 to 8.51 $\pm$ 0.02. We have serendipitously discovered an additional detached TDG candidate in Arp72 using available spectra from SDSS. Utilizing the photometric data and the CIGALE code for stellar population and dust emission fitting, we derived the stellar masses, stellar population ages, and stellar metallicities for these detached TDGs. Compared to standard mass-metallicity relations for dwarf galaxies, five of the seven candidates have higher than expected metallicities, confirming their tidal origins. One of the seven candidates remains unclear due to large uncertainties in metallicity, and another has stellar and nebular metallicities compatible with those of a preexisting dwarf galaxy. The latter object is relatively compact in the optical relative to its stellar mass, in contrast to the other candidate TDGs [abridged]., Comment: Accepted for publication in Astronomy and Astrophysics. 15 pages, 9 figures, 6 tables

Network Phylogenetic Diversity (Network-PD) is a measure for the diversity of a set of species based on a rooted phylogenetic network (with branch lengths and inheritance probabilities on the reticulation edges) describing the evolution of those species. We consider the \textsc{Max-Network-PD} problem: given such a network, find~$k$ species with maximum Network-PD score. We show that this problem is fixed-parameter tractable (FPT) for binary networks, by describing an optimal algorithm running in $\mathcal{O}(2^r \log (k)(n+r))$~time, with~$n$ the total number of species in the network and~$r$ its reticulation number. Furthermore, we show that \textsc{Max-Network-PD} is NP-hard for level-1 networks, proving that, unless P$=$NP, the FPT approach cannot be extended by using the level as parameter instead of the reticulation number.

Phylogenetic Diversity (PD) is a measure of the overall biodiversity of a set of present-day species (taxa) within a phylogenetic tree. In Maximize Phylogenetic Diversity (MPD) one is asked to find a set of taxa (of bounded size/cost) for which this measure is maximized. MPD is a relevant problem in conservation planning, where there are not enough resources to preserve all taxa and minimizing the overall loss of biodiversity is critical. We consider an extension of this problem, motivated by real-world concerns, in which each taxon not only requires a certain amount of time to save, but also has an extinction time after which it can no longer be saved. In addition there may be multiple teams available to work on preservation efforts in parallel; we consider two variants of the problem based on whether teams are allowed to collaborate on the same taxa. These problems have much in common with machine scheduling problems, (with taxa corresponding to tasks and teams corresponding to machines), but with the objective function (the phylogenetic diversity) inspired by biological considerations. Our extensions are, in contrast to the original MPD, NP-hard, even in very restricted cases. We provide several algorithms and hardness-results and thereby show that the problems are fixed-parameter tractable (FPT) when parameterized the target phylogenetic diversity, and that the problem where teams are allowed to collaborate is FPT when parameterized the acceptable loss of diversity.

To measure the tree-likeness of a directed acyclic graph (DAG), a new width parameter that considers the directions of the arcs was recently introduced: scanwidth. We present the first algorithm that efficiently computes the exact scanwidth of general DAGs. For DAGs with one root and scanwidth $k$ it runs in $O(k \cdot n^k \cdot m)$ time. The algorithm also functions as an FPT algorithm with complexity $O(2^{4 \ell - 1} \cdot \ell \cdot n + n^2)$ for phylogenetic networks of level-$\ell$, a type of DAG used to depict evolutionary relationships among species. Our algorithm performs well in practice, being able to compute the scanwidth of synthetic networks up to 30 reticulations and 100 leaves within 500 seconds. Furthermore, we propose a heuristic that obtains an average practical approximation ratio of 1.5 on these networks. While we prove that the scanwidth is bounded from below by the treewidth of the underlying undirected graph, experiments suggest that for networks the parameters are close in practice., Comment: 32 pages, 15 figures

Despite the advantage quantum computers are expected to deliver when performing simulations compared to their classical counterparts, the current noisy intermediate-scale quantum (NISQ) devices remain limited in their capabilities. The training of parameterized quantum circuits (PQCs) remains a significant practical challenge, exacerbated by the requirement of shallow circuit depth necessary for their hardware implementation. Hybrid methods employing classical computers alongside quantum devices, such as the Variational Quantum Eigensolver (VQE), have proven useful for analyzing the capabilities of NISQ devices to solve relevant optimization problems. Still, in the simulation of complex structures involving the many-body problem in quantum mechanics, major issues remain about the representation of the system and obtaining results which clearly outperform classical computational devices. In this research contribution we propose the use of parameterized Tensor Networks (TNs) to attempt an improved performance of the VQE algorithm. A joint approach is presented where the Hamiltonian of a system is encapsulated into a Matrix Product Operator (MPO) within a parameterized unitary TN hereby splitting up the optimization task between the TN and the VQE. We show that the hybrid TN-VQE implementation improves the convergence of the algorithm in comparison to optimizing randomly-initialized quantum circuits via VQE.

PyPWA is a toolkit designed to optimize parametric models describing data and generate simulated distributions according to a model. Its software has been written within the python ecosystem with the goal of performing Amplitude or Partial Wave Analysis (PWA) in nuclear and particle physics experiments. We briefly describe the general features of amplitude analysis and the PyPWA software design and usage. We provide benchmarks of the scaling and an example of its application.

Phylogenetic networks are used to represent the evolutionary history of species. Recently, the new class of orchard networks was introduced, which were later shown to be interpretable as trees with additional horizontal arcs. This makes the network class ideal for capturing evolutionary histories that involve horizontal gene transfers. Here, we study the minimum number of additional leaves needed to make a network orchard. We demonstrate that computing this proximity measure for a given network is NP-hard and describe a tight upper bound. We also give an equivalent measure based on vertex labellings to construct a mixed integer linear programming formulation. Our experimental results, which include both real-world and synthetic data, illustrate the effectiveness of our implementation., Comment: 19 pages, 6 figures

We present a novel method for improving the quantum simulation of the ground state energy of molecules. We perform a pre-processing step classically, which reduces the dimensionality of the problem by generating a custom mapping which excludes states which violate problem constraints. Subsequently, a specialized measurement scheme is used to extract the expectation value of the problem Hamiltonian through this mapping. We demonstrate that this method reduces the amount of quantum resources needed to run a Variational Quantum Eigensolver (VQE) algorithm without making any approximations to the physics of the quantum chemistry problem., Comment: 18 pages

Clinical trials are an integral component of medical research. Trials require careful design to, for example, maintain the safety of participants, use resources efficiently and allow clinically meaningful conclusions to be drawn. Adaptive clinical trials (i.e. trials that can be altered based on evidence that has accrued) are often more efficient, informative and ethical than standard or non-adaptive trials because they require fewer participants, target more promising treatments, and can stop early with sufficient evidence of effectiveness or harm. The design of adaptive trials requires the pre-specification of adaptions that are permissible throughout the conduct of the trial. Proposed adaptive designs are then usually evaluated through simulation which provides indicative metrics of performance (e.g. statistical power and type-1 error) under different scenarios. Trial simulation requires assumptions about the data generating process to be specified but correctly specifying these in practice can be difficult, particularly for new and emerging diseases. To address this, we propose an approach to design adaptive clinical trials without needing to specify the complete data generating process. To facilitate this, we consider a general Bayesian framework where inference about the treatment effect on a time-to-event outcome can be performed via the partial likelihood. As a consequence, the proposed approach to evaluate trial designs is robust to the specific form of the baseline hazard function. The benefits of this approach are demonstrated through the redesign of a recent clinical trial to evaluate whether a third dose of a vaccine provides improved protection against gastroenteritis in Australian Indigenous infants.

The maximum parsimony distance $d_{\textrm{MP}}(T_1,T_2)$ and the bounded-state maximum parsimony distance $d_{\textrm{MP}}^t(T_1,T_2)$ measure the difference between two phylogenetic trees $T_1,T_2$ in terms of the maximum difference between their parsimony scores for any character (with $t$ a bound on the number of states in the character, in the case of $d_{\textrm{MP}}^t(T_1,T_2)$). While computing $d_{\textrm{MP}}(T_1, T_2)$ was previously shown to be fixed-parameter tractable with a linear kernel, no such result was known for $d_{\textrm{MP}}^t(T_1,T_2)$. In this paper, we prove that computing $d_{\textrm{MP}}^t(T_1, T_2)$ is fixed-parameter tractable for all~$t$. Specifically, we prove that this problem has a kernel of size $O(k \lg k)$, where $k = d_{\textrm{MP}}^t(T_1, T_2)$. As the primary analysis tool, we introduce the concept of leg-disjoint incompatible quartets, which may be of independent interest.

Given a rooted, binary phylogenetic network and a rooted, binary phylogenetic tree, can the tree be embedded into the network? This problem, called \textsc{Tree Containment}, arises when validating networks constructed by phylogenetic inference methods.We present the first algorithm for (rooted) \textsc{Tree Containment} using the treewidth $t$ of the input network $N$ as parameter, showing that the problem can be solved in $2^{O(t^2)}\cdot|N|$ time and space.

We use the benefits and components of classical computers every day. However, there are many types of problems which, as they grow in size, their computational complexity grows larger than classical computers will ever be able to solve. Quantum computing (QC) is a computation model that uses quantum physical properties to solve such problems. QC is at the early stage of large-scale adoption in various industry domains to take advantage of the algorithmic speed-ups it has to offer. It can be applied in a variety of areas, such as computer science, mathematics, chemical and biochemical engineering, and the financial industry. The main goal of this paper is to give an overview to chemical and biochemical researchers and engineers who may not be familiar with quantum computation. Thus, the paper begins by explaining the fundamental concepts of QC. The second contribution this publication tries to tackle is the fact that the chemical engineering literature still lacks a comprehensive review of the recent advances of QC. Therefore, this article reviews and summarizes the state of the art to gain insight into how quantum computation can benefit and optimize chemical engineering issues. A bibliography analysis covers the comprehensive literature in QC and analyzes quantum computing research in chemical engineering on various publication topics, using Clarivate analytics covering the years 1990 to 2020. After the bibliographic analysis, relevant applications of QC in chemical and biochemical engineering are highlighted and a conclusion offers an outlook of future directions within the field.

Phylogenetic networks are used in biology to represent evolutionary histories. The class of orchard phylogenetic networks was recently introduced for their computational benefits, without any biological justification. Here, we show that orchard networks can be interpreted as trees with additional \emph{horizontal} arcs. Therefore, they are closely related to tree-based networks, where the difference is that in tree-based networks the additional arcs do not need to be horizontal. Then, we use this new characterization to show that the space of orchard networks is connected under the rNNI rearrangement move, with a diameter of at most $4kn+n\lceil \log_2(n) \rceil +2k+6n-8$., Comment: 14 pages, 11 figures

The FCC-ee is a proposed future high-energy, high-intensity and high-precision lepton collider. Here, we present the latest development for the FCC-ee interaction regions, which shall ensure optimum conditions for the particle physics experiments. We discuss measures of background reduction and a revised interaction region layout including a low impedance compact beam chamber design. We also discuss the possible impact of the radiation generated in the interaction region including beamstrahlung., Comment: 3 pp, 5 figs, presented at IPAC21, May 24-28th, 2021

Recently it was shown that a certain class of phylogenetic networks, called level-$2$ networks, cannot be reconstructed from their associated distance matrices. In this paper, we show that they can be reconstructed from their induced shortest and longest distance matrices. That is, if two level-$2$ networks induce the same shortest and longest distance matrices, then they must be isomorphic. We further show that level-$2$ networks are reconstructible from their shortest distance matrices if and only if they do not contain a subgraph from a family of graphs. A generator of a network is the graph obtained by deleting all pendant subtrees and suppressing degree-$2$ vertices. We also show that networks with a leaf on every generator side is reconstructible from their induced shortest distance matrix, regardless of level., Comment: 59 pages, 9 figures

The solenoidal large intensity device (SoLID) at Jefferson Lab will push the boundaries of luminosity for a large-acceptance detector, which necessitates the use of a light-gas threshold Cherenkov counter for online event selection. Due to the high luminosity, the single-photon background rate in this counter can exceed 160 kHz/cm$^2$ at the photosensors. Therefore, it is essential to validate the high-rate limits of the planned photosensors and readout electronics in order to mitigate the risk of failure. We report on the design and an early set of studies carried out using a small telescopic Cherenkov device in a high-rate environment up to 60 kHz/cm$^2$, in Hall C at Jefferson Lab. Commercially available multi-anode photomultipliers (MaPMT) and low-cost large-area picosecond photodetectors (LAPPD) were tested using the JLab FADC250 modules for readout. The test beam results show that the MaPMT array and the internal stripline LAPPD can detect and identify single-electron and pair-production events in high-rate environments. Due to its higher quantum efficiency, the MaPMT array provided a better separation between the single-electron and the pair-production events compared to the internal stripline LAPPD. A GEANT4 simulation confirms the experimental performance of our telescopic device., Comment: 16 pages, 11 figures

We study the problem of finding a temporal hybridization network for a set of phylogenetic trees that minimizes the number of reticulations. First, we introduce an FPT algorithm for this problem on an arbitrary set of $m$ binary trees with $n$ leaves each with a running time of $O(5^k\cdot n\cdot m)$, where $k$ is the minimum temporal hybridization number. We also present the concept of temporal distance, which is a measure for how close a tree-child network is to being temporal. Then we introduce an algorithm for computing a tree-child network with temporal distance at most $d$ and at most $k$ reticulations in $O((8k)^d5^ k\cdot n\cdot m)$ time. Lastly, we introduce a $O(6^kk!\cdot k\cdot n^2)$ time algorithm for computing a minimum temporal hybridization network for a set of two nonbinary trees. We also provide an implementation of all algorithms and an experimental analysis on their performance.

Phylogenetic networks can represent evolutionary events that cannot be described by phylogenetic trees. These networks are able to incorporate reticulate evolutionary events such as hybridization, introgression, and lateral gene transfer. Recently, network-based Markov models of DNA sequence evolution have been introduced along with model-based methods for reconstructing phylogenetic networks. For these methods to be consistent, the network parameter needs to be identifiable from data generated under the model. Here, we show that the semi-directed network parameter of a triangle-free, level-1 network model with any fixed number of reticulation vertices is generically identifiable under the Jukes-Cantor, Kimura 2-parameter, or Kimura 3-parameter constraints., Comment: 24 pages, 10 figures

We analyse TESS photometry of DMPP-1 (HD 38677; TIC 66560666), a nearby F8V star hosting hot super-Earth planets and a warm Neptune. Using the Transit Least Squares algorithm and other methods we find a transit signal at $P=3.2854^{+0.0032}_{-0.0025}$ d with depth 87$^{+25}_{-30}$ ppm and false alarm probability 1.6%. This is shallower than hitherto published TESS discoveries. The 3.285 d signal is recovered for several, but not all, methods for detrending stellar astrophysical variability. Further observations are needed to improve the significance of the detection. If this transit were due to an Earth-like rocky planet it would have been detected in the RV data, but it is not. The TESS data cover seven individual transits, one of which is consistent with zero depth. The insolation of the putative planet is $990 {\rm S_{\oplus}}$, typical of fluxes experienced by the three known catastrophically disintegrating exoplanets (CDEs). The transits can be self-consistently attributed to a CDE with a mass below the RV detection threshold. We searched for transits of the known RV planets, finding null results and detection thresholds of $< 100$ ppm, which we quantify for each. The DMPP-1 planetary system was discovered as a consequence of circumstellar gas attributed to ablation of hot planets. The RV planets may have been ablated to near-pure iron cores. We place limits on the orbital inclinations of the RV planets where the expected transit depth exceeds the detection threshold. If the 3.2854 day transit detection is confirmed, e.g. with CHEOPS photometry, DMPP-1 would be a first-rate target for JWST spectroscopy., Comment: Accepted for publication in ApJL

Phylogenetic networks are used to study evolutionary relationships between species in biology. Such networks are often categorized into classes by their topological features, which stem from both biological and computational motivations. We study two network classes in this paper: tree-based networks and orchard networks. Tree-based networks are those that can be obtained by inserting edges between the edges of an underlying tree. Orchard networks are a recently introduced generalization of the class of tree-child networks. Structural characterizations have already been discovered for tree-based networks; this is not the case for orchard networks. In this paper, we introduce cherry covers---a unifying characterization of both network classes---in which we decompose the edges of the networks into so-called cherry shapes and reticulated cherry shapes. We show that cherry covers can be used to characterize the class of tree-based networks as well as the class of orchard networks. Moreover, we also generalize these results to non-binary networks.

Maximum parsimony distance is a measure used to quantify the dissimilarity of two unrooted phylogenetic trees. It is NP-hard to compute, and very few positive algorithmic results are known due to its complex combinatorial structure. Here we address this shortcoming by showing that the problem is fixed parameter tractable. We do this by establishing a linear kernel i.e., that after applying certain reduction rules the resulting instance has size that is bounded by a linear function of the distance. As powerful corollaries to this result we prove that the problem permits a polynomial-time constant-factor approximation algorithm; that the treewidth of a natural auxiliary graph structure encountered in phylogenetics is bounded by a function of the distance; and that the distance is within a constant factor of the size of a maximum agreement forest of the two trees, a well studied object in phylogenetics., Comment: 27 pages, 7 figures

Phylogenetic networks are important for the study of evolution. The number of methods to find such networks is increasing, but most such methods can only reconstruct small networks. To find bigger networks, one can attempt to combine small networks. In this paper, we study the {\sc Network Hybridization} problem, a problem of combining networks into another network with low complexity. We characterize this complexity via a restricted problem, {\sc Tree-child Network Hybridization}, and we present an FPT algorithm to efficiently solve this restricted problem.

In this article, we investigate different parsimony-based approaches towards finding recombination breakpoints in a multiple sequence alignment. This recombination detection task is crucial in order to avoid errors in evolutionary analyses caused by mixing together portions of sequences which had a different evolution history. Following an overview of the field of recombination detection, we formulate four computational problems for this task with different objective functions. The four problems aim to minimize (1) the total homoplasy of all blocks (2) the maximum homoplasy per block (3) the total homoplasy ratio of all blocks and (4) the maximum homoplasy ratio per block. We describe algorithms for each of these problems, which are fixed-parameter tractable (FPT) when the characters are binary. We have implemented and tested the algorithms on simulated data, showing that minimizing the total homoplasy gives, in most cases, the most accurate results. Our implementation and experimental data have been made publicly available. Finally, we also consider the problem of combining blocks into non-contiguous blocks consisting of at most p contiguous parts. Fixing the homoplasy h of each block to 0, we show that this problem is NP-hard when p >= 3, but polynomial-time solvable for p = 2. Furthermore, the problem is FPT with parameter h for binary characters when p = 2. A number of interesting problems remain open.

We present the first fixed-parameter algorithm for constructing a tree-child phylogenetic network that displays an arbitrary number of binary input trees and has the minimum number of reticulations among all such networks. The algorithm uses the recently introduced framework of cherry picking sequences and runs in $O((8k)^k \mathrm{poly}(n, t))$ time, where $n$ is the number of leaves of every tree, $t$ is the number of trees, and $k$ is the reticulation number of the constructed network. Moreover, we provide an efficient parallel implementation of the algorithm and show that it can deal with up to $100$ input trees on a standard desktop computer, thereby providing a major improvement over previous phylogenetic network construction methods., Comment: Code available at https://github.com/nzeh/tree_child_code

Numerous lung diseases, such as idiopathic pulmonary fibrosis (IPF), exhibit dilation of the airways. Accurate measurement of dilatation enables assessment of the progression of disease. Unfortunately the combination of image noise and airway bifurcations causes high variability in the profiles of cross-sectional areas, rendering the identification of affected regions very difficult. Here we introduce a noise-robust method for automatically detecting the location of progressive airway dilatation given two profiles of the same airway acquired at different time points. We propose a probabilistic model of abrupt relative variations between profiles and perform inference via Reversible Jump Markov Chain Monte Carlo sampling. We demonstrate the efficacy of the proposed method on two datasets; (i) images of healthy airways with simulated dilatation; (ii) pairs of real images of IPF-affected airways acquired at 1 year intervals. Our model is able to detect the starting location of airway dilatation with an accuracy of 2.5mm on simulated data. The experiments on the IPF dataset display reasonable agreement with radiologists. We can compute a relative change in airway volume that may be useful for quantifying IPF disease progression. The code is available at https://github.com/quan14/Modelling_Airway_Geometry_as_Stock_Market_Data, Comment: 14 pages, 7 figures, Accepted to The 10th International Workshop on Machine Learning in Medical Imaging (MLMI 2019). In conjunction with MICCAI 2019, Shenzhen, China

This paper studies the relationship between undirected (unrooted) and directed (rooted) phylogenetic networks. We describe a polynomial-time algorithm for deciding whether an undirected nonbinary phylogenetic network, given the locations of the root and reticulation vertices, can be oriented as a directed nonbinary phylogenetic network. Moreover, we characterize when this is possible and show that, in such instances, the resulting directed nonbinary phylogenetic network is unique. In addition, without being given the location of the root and the reticulation vertices, we describe an algorithm for deciding whether an undirected binary phylogenetic network $N$ can be oriented as a directed binary phylogenetic network of a certain class. The algorithm is fixed-parameter tractable (FPT) when the parameter is the level of $N$ and is applicable to classes of directed phylogenetic networks that satisfy certain conditions. As an example, we show that the well-studied class of binary tree-child networks satisfies these conditions., Comment: contains an appendix with additional results not presented in the journal version