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In recent work by Arena, Canning, Clader, Haburcak, Li, Mok, and Tamborini it was proven that for infinitely many values of $g$ and $n$, there exist non-tautological algebraic cohomology classes on the moduli space $\mathcal{M}_{g,n}$ of smooth genus $g$, $n$-pointed curves. Here we show how a generalization of their technique allows to cover most of the remaining cases, proving the existence of non-tautological algebraic cohomology classes on the moduli space $\mathcal{M}_{g,n}$ for all but finitely many values of $g$ and $n$.

This paper explores artificial intelligence (AI) methods for the approximate compiling of unitaries, focusing on the use of fixed two-qubit gates and arbitrary single-qubit rotations typical in superconducting hardware. Our approach involves three main stages: identifying an initial template that approximates the target unitary, predicting initial parameters for this template, and refining these parameters to maximize the fidelity of the circuit. We propose AI-driven approaches for the first two stages, with a deep learning model that suggests initial templates and an autoencoder-like model that suggests parameter values, which are refined through gradient descent to achieve the desired fidelity. We demonstrate the method on 2 and 3-qubit unitaries, showcasing promising improvements over exhaustive search and random parameter initialization. The results highlight the potential of AI to enhance the transpiling process, supporting more efficient quantum computations on current and future quantum hardware.

In this paper we study higher even Gaussian maps of the canonical bundle on hyperelliptic curves and we determine their rank, giving explicit descriptions of their kernels. Then we use this descriptions to investigate the hyperelliptic Torelli map $j_h$ and its second fundamental form. We study isotropic subspaces of the tangent space $T_{{\mathcal H}_g, [C]}$ to the moduli space ${\mathcal H}_g$ of hyperelliptic curves of genus $g$ at a point $[C]$, with respect to the second fundamental form $\rho_{HE}$ of $j_h$. In particular, for any Weierstrass point $p \in C$, we construct a subspace $V_p$ of dimension $\lfloor\frac{g}{2} \rfloor$ of $T_{{\mathcal H}_g, [C]}$ generated by higher Schiffer variations at $p$, such that the only isotropic tangent direction $\zeta \in V_p$ for the image of $\rho_{HE}$ is the standard Schiffer variation $\xi_p$ at the Weierstrass point $p \in C$.

Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this development process, and one such tool could be Generative Artificial intelligence (GenAI). In this study, we introduce and use the Qiskit HumanEval dataset, a hand-curated collection of tasks designed to benchmark the ability of Large Language Models (LLMs) to produce quantum code using Qiskit - a quantum SDK. This dataset consists of more than 100 quantum computing tasks, each accompanied by a prompt, a canonical solution, a comprehensive test case, and a difficulty scale to evaluate the correctness of the generated solutions. We systematically assess the performance of a set of LLMs against the Qiskit HumanEval dataset's tasks and focus on the models ability in producing executable quantum code. Our findings not only demonstrate the feasibility of using LLMs for generating quantum code but also establish a new benchmark for ongoing advancements in the field and encourage further exploration and development of GenAI-driven tools for quantum code generation.

Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and effort required to build applications. This paper focuses on training Code LLMs to specialize in the field of quantum computing. We begin by discussing the unique needs of quantum computing programming, which differ significantly from classical programming approaches or languages. A Code LLM specializing in quantum computing requires a foundational understanding of quantum computing and quantum information theory. However, the scarcity of available quantum code examples and the rapidly evolving field, which necessitates continuous dataset updates, present significant challenges. Moreover, we discuss our work on training Code LLMs to produce high-quality quantum code using the Qiskit library. This work includes an examination of the various aspects of the LLMs used for training and the specific training conditions, as well as the results obtained with our current models. To evaluate our models, we have developed a custom benchmark, similar to HumanEval, which includes a set of tests specifically designed for the field of quantum computing programming using Qiskit. Our findings indicate that our model outperforms existing state-of-the-art models in quantum computing tasks. We also provide examples of code suggestions, comparing our model to other relevant code LLMs. Finally, we introduce a discussion on the potential benefits of Code LLMs for quantum computing computational scientists, researchers, and practitioners. We also explore various features and future work that could be relevant in this context.

This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By employing RL, we achieve near-optimal synthesis of Linear Function, Clifford, and Permutation circuits, up to 9, 11 and 65 qubits respectively, while being compatible with native device instruction sets and connectivity constraints, and orders of magnitude faster than optimization methods such as SAT solvers. We also achieve significant reductions in two-qubit gate depth and count for circuit routing up to 133 qubits with respect to other routing heuristics such as SABRE. We find the method to be efficient enough to be useful in practice in typical quantum transpiling pipelines. Our results set the stage for further AI-powered enhancements of quantum computing workflows.

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions., Comment: 65 pages, 15 figures; comments welcome

Online string matching is a computational problem involving the search for patterns or substrings in a large text dataset, with the pattern and text being processed sequentially, without prior access to the entire text. Its relevance stems from applications in data compression, data mining, text editing, and bioinformatics, where rapid and efficient pattern matching is crucial. Various solutions have been proposed over the past few decades, employing diverse techniques. Recently, weak recognition approaches have attracted increasing attention. This paper presents Hash Chain, a new algorithm based on a robust weak factor recognition approach that connects adjacent factors through hashing. Despite its O(nm) complexity, the algorithm exhibits a sublinear behavior in practice and achieves superior performance compared to the most effective algorithms.

The Longest Common Substring (LCS) and Longest Palindromic Substring (LPS) are classical problems in computer science, representing fundamental challenges in string processing. Both problems can be solved in linear time using a classical model of computation, by means of very similar algorithms, both relying on the use of suffix trees. Very recently, two sublinear algorithms for LCS and LPS in the quantum query model have been presented by Le Gall and Seddighin~\cite{GallS23}, requiring $\tilde{\mathcal{O}}(n^{5/6})$ and $\tilde{\mathcal{O}}(\sqrt{n})$ queries, respectively. However, while the query model is fascinating from a theoretical standpoint, its practical applicability becomes limited when it comes to crafting algorithms meant for actual execution on real hardware. In this paper we present, for the first time, a $\tilde{\mathcal{O}}(\sqrt{n})$ quantum algorithm for both LCS and LPS working in the circuit model of computation. Our solutions are simpler than previous ones and can be easily translated into quantum procedures. We also present actual implementations of the two algorithms as quantum circuits working in $\mathcal{O}(\sqrt{n}\log^5(n))$ and $\mathcal{O}(\sqrt{n}\log^4(n))$ time, respectively.

Quantum computation represents a computational paradigm whose distinctive attributes confer the ability to devise algorithms with asymptotic performance levels significantly superior to those achievable via classical computation. Recent strides have been taken to apply this computational framework in tackling and resolving various issues related to text processing. The resultant solutions demonstrate marked advantages over their classical counterparts. This study employs quantum computation to efficaciously surmount text processing challenges, particularly those involving string comparison. The focus is on the alignment of fixed-length substrings within two input strings. Specifically, given two input strings, $x$ and $y$, both of length $n$, and a value $d \leq n$, we want to verify the following conditions: the existence of a common prefix of length $d$, the presence of a common substring of length $d$ beginning at position $j$ (with $0 \leq j < n$) and, the presence of any common substring of length $d$ beginning in both strings at the same position. Such problems find applications as sub-procedures in a variety of problems concerning text processing and sequence analysis. Notably, our approach furnishes polylogarithmic solutions, a stark contrast to the linear complexity inherent in the best classical alternatives.

We give obstructions - in terms of Gaussian maps - for a marked Prym curve $(C,\alpha,T_d)$ to admit a singular model lying on an Enriques surface with only one $d$-ordinary point singularity and in such a way that $T_d$ corresponds to the divisor over the singular point.

We present a new variable-length computation-friendly encoding scheme, named SFDC (Succinct Format with Direct aCcesibility), that supports direct and fast accessibility to any element of the compressed sequence and achieves compression ratios often higher than those offered by other solutions in the literature. The SFDC scheme provides a flexible and simple representation geared towards either practical efficiency or compression ratios, as required. For a text of length $n$ over an alphabet of size $\sigma$ and a fixed parameter $\lambda$, the access time of the proposed encoding is proportional to the length of the character's code-word, plus an expected $\mathcal{O}((F_{\sigma - \lambda + 3} - 3)/F_{\sigma+1})$ overhead, where $F_j$ is the $j$-th number of the Fibonacci sequence. In the overall it uses $N+\mathcal{O}\big(n \left(\lambda - (F_{\sigma+3}-3)/F_{\sigma+1}\big) \right) = N + \mathcal{O}(n)$ bits, where $N$ is the length of the encoded string. Experimental results show that the performance of our scheme is, in some respects, comparable with the performance of DACs and Wavelet Tees, which are among of the most efficient schemes. In addition our scheme is configured as a \emph{computation-friendly compression} scheme, as it counts several features that make it very effective in text processing tasks. In the string matching problem, that we take as a case study, we experimentally prove that the new scheme enables results that are up to 29 times faster than standard string-matching techniques on plain texts., Comment: 33 pages

Distributed ledger technologies, also known as blockchains for enterprises, promise to significantly reduce the high cost of automating multi-party business workflows. We argue that a programming language for writing such on-ledger logic should satisfy three desiderata: (1) Provide concepts to capture the legal rules that govern real-world business workflows. (2) Include simple means for specifying policies for access and authorization. (3) Support the composition of simple workflows into complex ones, even when the simple workflows have already been deployed. We present the open-source smart contract language Daml based on Haskell with strict evaluation. Daml achieves these desiderata by offering novel primitives for representing, accessing, and modifying data on the ledger, which are mimicking the primitives of today's legal systems. Robust access and authorization policies are specified as part of these primitives, and Daml's built-in authorization rules enable delegation, which is key for workflow composability. These properties make Daml well-suited for orchestrating business workflows across multiple, otherwise heterogeneous parties. Daml contracts run (1) on centralized ledgers backed by a database, (2) on distributed deployments with Byzantine fault tolerant consensus, and (3) on top of conventional blockchains, as a second layer via an atomic commit protocol.

Positively charged cluster ions of phosphorus were formed upon electron ionization of doped helium nanodroplets. The vapors of red phosphorus and a phosphate sample were picked up into neutral and charged helium nanodroplets. Independent on the conditions used, the cluster size distributions exhibit pronounced odd-even oscillations that are opposite to almost all experimental and theoretical patterns published in the literature. The low temperature environment of the superfluid He matrix quenches fragmentation and the charged phosphorus clusters resemble the structure of the neutral precursors., Comment: 12 pages, 6 figures

We prove that the $k$-th Gaussian map $\gamma^k_{H}$ is surjective on a polarized unnodal Enriques surface $(S, H)$ with $\phi(H)>2k+4$. In particular, as a consequence, when $\phi(H)>4(k+2)$, we obtain the surjectivity of the $k$-th Gauss-Prym map $\gamma^k_{\omega_C\otimes\alpha}$ on smooth hyperplane sections $C\in \vert H\vert.$ In case $k=1$ it is sufficient to ask $\phi(H)>6$., Comment: Fixed some typos and improved the exposition of some parts from the first version

Defining the right metrics to properly represent the performance of a quantum computer is critical to both users and developers of a computing system. In this white paper, we identify three key attributes for quantum computing performance: quality, speed, and scale. Quality and scale are measured by quantum volume and number of qubits, respectively. We propose a speed benchmark, using an update to the quantum volume experiments that allows the measurement of Circuit Layer Operations Per Second (CLOPS) and identify how both classical and quantum components play a role in improving performance. We prescribe a procedure for measuring CLOPS and use it to characterize the performance of some IBM Quantum systems., Comment: Early draft of a proposed speed benchmark. Feedback requested

We present the Herschel Extragalactic Legacy Project (HELP). This project collates, curates, homogenises, and creates derived data products for most of the premium multi-wavelength extragalactic data sets. The sky boundaries for the first data release cover 1270 deg2 defined by the Herschel SPIRE extragalactic survey fields; notably the Herschel Multi-tiered Extragalactic Survey (HerMES) and the Herschel Atlas survey (H-ATLAS). Here, we describe the motivation and principal elements in the design of the project. Guiding principles are transparent or "open" methodologies with care for reproducibility and identification of provenance. A key element of the design focuses around the homogenisation of calibration, meta data and the provision of information required to define the selection of the data for statistical analysis. We apply probabilistic methods that extract information directly from the images at long wavelengths, exploiting the prior information available at shorter wavelengths and providing full posterior distributions rather than maximum likelihood estimates and associated uncertainties as in traditional catalogues. With this project definition paper we provide full access to the first data release of HELP; Data Release 1 (DR1), including a monolithic map of the largest SPIRE extragalactic field at 385 deg2 and 18 million measurements of PACS and SPIRE fluxes. We also provide tools to access and analyse the full HELP database. This new data set includes far-infrared photometry, photometric redshifts, and derived physical properties estimated from modelling the spectral energy distributions.

In this paper we investigate the \emph{approximate string matching problem} when the allowed edit operations are \emph{non-overlapping unbalanced translocations of adjacent factors}. Such kind of edit operations take place when two adjacent sub-strings of the text swap, resulting in a modified string. The two involved substrings are allowed to be of different lengths. Such large-scale modifications on strings have various applications. They are among the most frequent chromosomal alterations, accounted for 30\% of all losses of heterozygosity, a major genetic event causing inactivation of cancer suppressor genes. In addition, among other applications, they are frequent modifications accounted in musical or in natural language information retrieval. However, despite of their central role in so many fields of text processing, little attention has been devoted to the problem of matching strings allowing for this kind of edit operation. In this paper we present three algorithms for solving the problem, all of them with a $\bigO(nm^3)$ worst-case and a $\bigO(m^2)$-space complexity, where $m$ and $n$ are the length of the pattern and of the text, respectively. % In particular, our first algorithm is based on the dynamic-programming approach. Our second solution improves the previous one by making use of the Directed Acyclic Word Graph of the pattern. Finally our third algorithm is based on an alignment procedure. We also show that under the assumptions of equiprobability and independence of characters, our second algorithm has a $\bigO(n\log^2_{\sigma} m)$ average time complexity, for an alphabet of size $\sigma \geq 4$., Comment: arXiv admin note: substantial text overlap with arXiv:1812.00421

Disordered optical media are an emerging class of materials capable of strongly scattering light. Their study is relevant to investigate transport phenomena and for applications in imaging, sensing and energy storage. While such materials can be used to generate coherent light, their directional emission is typically hampered by their very multiple scattering nature. Here, we tune the out-of-plane directionality of coherent Raman light scattered by a fractal network of silicon nanowires. By visualizing Rayleigh scattering, photoluminescence and weakly localized Raman light from the random network of nanowires via real-space microscopy and Fourier imaging, we gain insight on the light transport mechanisms responsible for the material's inelastic coherent signal and for its directionality. The possibility of visualizing and manipulating directional coherent light in such networks of nanowires opens venues for fundamental studies of light propagation in disordered media as well as for the development of next generation optical devices based on disordered structures, inclusive of sensors, light sources and optical switches.

In recent years, the use of deep learning in language models gained much attention. Some research projects claim that they can generate text that can be interpreted as human-writing, enabling new possibilities in many application areas. Among the different areas related to language processing, one of the most notable in applying this type of modeling is programming languages. For years, the Machine Learning community has been researching this software engineering area, pursuing goals like applying different approaches to auto-complete, generate, fix, or evaluate code programmed by humans. Considering the increasing popularity of the Deep-Learning-enabled language models approach, we detected a lack of empirical papers that compare different deep learning architectures to create and use language models based on programming code. This paper compares different neural network architectures like AWD-LSTMs, AWD-QRNNs, and Transformer while using transfer learning and different tokenizations to see how they behave in building language models using a Python dataset for code generation and filling mask tasks. Considering the results, we discuss each approach's different strengths and weaknesses and what gaps we find to evaluate the language models or apply them in a real programming context.

Let $G$ be a simple finite graph and $G'$ be a subgraph of $G$. A $G'$-design $(X,\cal B)$ of order $n$ is said to be embedded into a $G$-design $(X\cup U,\cal C)$ of order $n+u$, if there is an injective function $f:\cal B\rightarrow \cal C$ such that $B$ is a subgraph of $f(B)$ for every $B\in\cal B$. The function $f$ is called an embedding of $(X,\cal B)$ into $(X\cup U,\cal C)$. If $u$ attains the minimum possible value, then $f$ is a minimum embedding. Here, by means of K\"{o}nig's Line Coloring Theorem and edge coloring properties a complete solution is given to the problem of determining a minimum embedding of any $K_3$-design (well-known as Steiner Triple System or, shortly, STS) into a 3-sun system or, shortly, a 3SS (i.e., a $G$-design where $G$ is a graph on six vertices consisting of a triangle with three pendant edges which form a 1-factor).

A group of experts, for instance climate scientists, is to choose among two policies $f$ and $g$. Consider the following decision rule. If all experts agree that the expected utility of $f$ is higher than the expected utility of $g$, the unanimity rule applies, and $f$ is chosen. Otherwise the precautionary principle is implemented and the policy yielding the highest minimal expected utility is chosen. This decision rule may lead to time inconsistencies when an intermediate period of partial resolution of uncertainty is added. We provide axioms that enlarge the initial group of experts with veto power, which leads to a set of probabilistic beliefs that is "rectangular" in a minimal sense. This makes this decision rule dynamically consistent and provides, as a byproduct, a novel behavioral characterization of rectangularity.

We consider models with any number of Higgs doublets and study the conditions for decoupling. We show that, under very general circumstances, all the quadratic coefficients of the scalar potential must be present, except in special cases, which include terms related to directions of vanishing vacuum expectation values. We give a few examples. Moreover, we show that the decoupling of all charged scalars implies the decoupling of all extra neutral scalars and vanishing $\mathcal{CP}$ violation in scalar-pseudoscalar mixing., Comment: New section added. Version to be published

Cartesian tree matching is the problem of finding all substrings in a given text which have the same Cartesian trees as that of a given pattern. In this paper, we deal with Cartesian tree matching for the case of multiple patterns. We present two fingerprinting methods, i.e., the parent-distance encoding and the binary encoding. By combining an efficient fingerprinting method and a conventional multiple string matching algorithm, we can efficiently solve multiple pattern Cartesian tree matching. We propose three practical algorithms for multiple pattern Cartesian tree matching based on the Wu-Manber algorithm, the Rabin-Karp algorithm, and the Alpha Skip Search algorithm, respectively. In the experiments we compare our solutions against the previous algorithm [18]. Our solutions run faster than the previous algorithm as the pattern lengths increase. Especially, our algorithm based on Wu-Manber runs up to 33 times faster., Comment: Submitted to WALCOM 2020

We study intertemporal decision making under uncertainty. We fully characterize discounted expected utility in a framework \`a la Savage. Despite the popularity of this model, no characterization is available in this setting. The concept of stationarity, introduced by Koopmans for deterministic discounted utility, plays a central role for both attitudes towards time and towards uncertainty. We show that a strong stationarity axiom characterizes discounted expected utility. When hedging considerations are taken into account, a weaker stationarity axiom generalizes discounted expected utility to Choquet discounted expected utility, allowing for non-neutral attitudes towards uncertainty.

Searching for all occurrences of a pattern in a text is a fundamental problem in computer science with applications in many other fields, like natural language processing, information retrieval and computational biology. Sampled string matching is an efficient approach recently introduced in order to overcome the prohibitive space requirements of an index construction, on the one hand, and drastically reduce searching time for the online solutions, on the other hand. In this paper we present a new algorithm for the sampled string matching problem, based on a characters distance sampling approach. The main idea is to sample the distances between consecutive occurrences of a given pivot character and then to search online the sampled data for any occurrence of the sampled pattern, before verifying the original text. From a theoretical point of view we prove that, under suitable conditions, our solution can achieve both linear worst-case time complexity and optimal average-time complexity. From a practical point of view it turns out that our solution shows a sub-linear behaviour in practice and speeds up online searching by a factor of up to 9, using limited additional space whose amount goes from 11% to 2.8% of the text size, with a gain up to 50% if compared with previous solutions.

Cartesian tree matching is the problem of finding all substrings of a given text which have the same Cartesian trees as that of a given pattern. So far there is one linear-time solution for Cartesian tree matching, which is based on the KMP algorithm. We improve the running time of the previous solution by introducing new representations. We present the framework of a binary filtration method and an efficient verification technique for Cartesian tree matching. Any exact string matching algorithm can be used as a filtration for Cartesian tree matching on our framework. We also present a SIMD solution for Cartesian tree matching suitable for short patterns. By experiments we show that known string matching algorithms combined on our framework of binary filtration and efficient verification produce algorithms of good performances for Cartesian tree matching., Comment: 14 pages, 3 figures, Submitted to SPIRE 2019

Establishing if multi-Higgs potentials are bounded from below (BFB) can be rather challenging, and it may impede efficient investigation of all phenomenological consequences of such models. In this paper, we find the necessary and sufficient BFB conditions for the Three-Higgs-Doublet model (3HDM) with the global symmetry group $U(1)\times U(1)$. We observed an important role played by charge-breaking directions in the Higgs space, even for situations when a good-looking neutral minimum exists. This remark is not limited to the particular model we consider but represents a rather general feature of elaborate multi-Higgs potentials which must be carefully dealt with. Also, applying this method to Weinberg's model (the $\mathbb{Z}_2 \times \mathbb{Z}_2$ symmetric 3HDM) turned out to be more challenging than was believed in the literature. In particular, we have found that the approach taken in a paper from 2009 does not lead to the necessary and sufficient BFB conditions for this case., Comment: 8 pages, 1 figure; v2: extra clarifications, matches the published version

Unbalanced translocations are among the most frequent chromosomal alterations, accounted for 30\% of all losses of heterozygosity, a major genetic event causing inactivation of tumor suppressor genes. Despite of their central role in genomic sequence analysis, little attention has been devoted to the problem of matching sequences allowing for this kind of chromosomal alteration. In this paper we investigate the \emph{approximate string matching} problem when the edit operations are non-overlapping unbalanced translocations of adjacent factors. In particular, we first present a $O(nm^3)$-time and $O(m^2)$-space algorithm based on the dynamic-programming approach. Then we improve our first result by designing a second solution which makes use of the Directed Acyclic Word Graph of the pattern. In particular, we show that under the assumptions of equiprobability and independence of characters, our algorithm has a $O(n\log^2_{\sigma} m)$ average time complexity, for an alphabet of size $\sigma$, still maintaining the $O(nm^3)$-time and the $O(m^2)$-space complexity in the worst case. To the best of our knowledge this is the first solution in literature for the approximate string matching problem allowing for unbalanced translocations of factors.

The abelian pattern matching problem consists in finding all substrings of a text which are permutations of a given pattern. This problem finds application in many areas and can be solved in linear time by a naive sliding window approach. In this short communication we present a new class of algorithms based on a new efficient fingerprint computation approach, called Heap-Counting, which turns out to be fast, flexible and easy to be implemented. It can be proved that our solutions have a linear worst case time complexity and, in addition, we present an extensive experimental evaluation which shows that our newly presented algorithms are among the most efficient and flexible solutions in practice for the abelian matching problem in strings., Comment: This is a short preliminary version of a full paper submitted to an international journal. Most examples, details, lemmas and theorems have been omitted

In this work we investigate the far-UV to NIR shape of the dust attenuation curve of a sample of IR selected dust obscured (U)LIRGs at z$\sim$2. The spectral energy distributions (SEDs) are fitted with CIGALE, a physically-motivated spectral synthesis model based on energy balance. Its flexibility allows us to test a wide range of different analytical prescriptions for the dust attenuation curve, including the well-known Calzetti and Charlot & Fall curves, and modified versions of them. The attenuation curves computed under the assumption of our reference double power-law model are in very good agreement with those derived, in previous works, with radiative transfer (RT) SED fitting. We investigate the position of our galaxies in the IRX-$\beta$ diagram and find this to be consistent with grayer slopes, on average, in the UV. We also find evidence for a flattening of the attenuation curve in the NIR with respect to more classical Calzetti-like recipes. This larger NIR attenuation yields larger derived stellar masses from SED fitting, by a median factor of $\sim$ 1.4 and up to a factor $\sim$10 for the most extreme cases. The star formation rate appears instead to be more dependent on the total amount of attenuation in the galaxy. Our analysis highlights the need for a flexible attenuation curve when reproducing the physical properties of a large variety of objects., Comment: 20 pages, 14 figures

String matching is the problem of finding all the substrings of a text which match a given pattern. It is one of the most investigated problems in computer science, mainly due to its very diverse applications in several fields. Recently, much research in the string matching field has focused on the efficiency and flexibility of the searching procedure and quite effective techniques have been proposed for speeding up the existing solutions. In this context, algorithms based on factors recognition are among the best solutions. In this paper, we present a simple and very efficient algorithm for string matching based on a weak factor recognition and hashing. Our algorithm has a quadratic worst-case running time. However, despite its quadratic complexity, experimental results show that our algorithm obtains in most cases the best running times when compared, under various conditions, against the most effective algorithms present in literature. In the case of small alphabets and long patterns, the gain in running times reaches 28%. This makes our proposed algorithm one of the most flexible solutions in practical cases., Comment: 11 pages, appeared in proceedings of the Prague Stringology Conference 2017

A solution to the existence problem of G-designs with given subdesigns is known when G is a triangle with p=0,1, or 2 disjoint pendent edges: for p=0, it is due to Doyen and Wilson, the first to pose such a problem for Steiner triple systems; for p=1 and p=2, the corresponding designs are kite systems and bull designs, respectively. Here, a complete solution to the problem is given in the remaining case where G is a 3-sun, i.e. a graph on six vertices consisting of a triangle with three pendent edges which form a 1-factor.

In this short note we present a comprehensive bibliography for the online exact string matching problem. The problem consists in finding all occurrences of a given pattern in a text. It is an extensively studied problem in computer science, mainly due to its direct applications to such diverse areas as text, image and signal processing, speech analysis and recognition, data compression, information retrieval, computational biology and chemistry. Since 1970 more than 120 string matching algorithms have been proposed. In this note we present a comprehensive list of (almost) all string matching algorithms. The list is updated to May 2016., Comment: 23 pages

We explore from a statistical point of view the far-infrared (far-IR) and sub-millimeter (sub-mm) properties of a large sample of LBGs (22,000) at z~3 in the COSMOS field. The large number of galaxies allows us to split it in several bins as a function of UV luminosity, UV slope, and stellar mass to better sample their variety. We perform stacking analysis in PACS (100 and 160 um), SPIRE (250, 350 and 500 um) and AzTEC (1.1 mm) images. Our stacking procedure corrects the biases induced by galaxy clustering and incompleteness of our input catalogue in dense regions. We obtain the full IR spectral energy distributions (SED) of subsamples of LBGs and derive the mean IR luminosity as a function of UV luminosity, UV slope, and stellar mass. The average IRX is roughly constant over the UV luminosity range, with a mean of 7.9 (1.8 mag). However, it is correlated with UV slope, and stellar mass. We investigate using a statistically-controlled stacking analysis as a function of (stellar mass, UV slope) the dispersion of the IRX-UVslope and IRX-M* plane. Our results enable us to study the average relation between star-formation rate (SFR) and stellar mass, and we show that our LBG sample lies on the main sequence of star formation at z~3., Comment: Accepted to A&A, 17 Pages, 14 Figures, 2 Tables

In this paper we present SABRINA (Sentiment Analysis: a Broad Resource for Italian Natural language Applications) a manually annotated prior polarity lexical resource for Italian natural language applications in the field of opinion mining and sentiment induction. The resource consists in two different sets, an Italian dictionary of more than 277.000 words tagged with their prior polarity value, and a set of polarity modifiers, containing more than 200 words, which can be used in combination with non neutral terms of the dictionary in order to induce the sentiment of Italian compound terms. To the best of our knowledge this is the first prior polarity manually annotated resource which has been developed for the Italian natural language., Comment: 10 pages, Accepted to NLPCS 2015, the 12th International Workshop on Natural Language Processing and Cognitive Science

We describe the search for Lyman-break galaxies (LBGs) near the sub-millimeter bright starburst galaxy HFLS3 at $z$$=$6.34 and a study on the environment of this massive galaxy during the end of reionization.We performed two independent selections of LBGs on images obtained with the \textit{Gran Telescopio Canarias} (GTC) and the \textit{Hubble Space Telescope} (HST) by combining non-detections in bands blueward of the Lyman-break and color selection. A total of 10 objects fulfilling the LBG selection criteria at $z$$>$5.5 were selected over the 4.54 and 55.5 arcmin$^2$ covered by our HST and GTC images, respectively. The photometric redshift, UV luminosity, and the star-formation rate of these sources were estimated with models of their spectral energy distribution. These $z$$\sim$6 candidates have physical properties and number densities in agreement with previous results. The UV luminosity function at $z$$\sim$6 and a Voronoi tessellation analysis of this field shows no strong evidence for an overdensity of relatively bright objects (m$_{F105W}$$<$25.9) associated with \textit{HFLS3}. However, the over-density parameter deduced from this field and the surface density of objects can not excluded definitively the LBG over-density hypothesis. Moreover we identified three faint objects at less than three arcseconds from \textit{HFLS3} with color consistent with those expected for $z$$\sim$6 galaxies. Deeper data are needed to confirm their redshifts and to study their association with \textit{HFLS3} and the galaxy merger that may be responsible for the massive starburst., Comment: 14 pages, 12 figures, accepted for publication in ApJ

In this article we completely determine the spectrum for uniformly resolvable decompositions of the complete graph K_v into r 1-factors and s classes containing only copies of h-suns.

In this paper we consider the problem concerning the existence of a resolvable G-design of order v and index {\lambda}. We solve the problem for the cases in which G is a connected subgraph of K_4.

Given a pattern x of length m and a text y of length n, both over an ordered alphabet, the order-preserving pattern matching problem consists in finding all substrings of the text with the same relative order as the pattern. It is an approximate variant of the well known exact pattern matching problem which has gained attention in recent years. This interesting problem finds applications in a lot of fields as time series analysis, like share prices on stock markets, weather data analysis or to musical melody matching. In this paper we present two new filtering approaches which turn out to be much more effective in practice than the previously presented methods. From our experimental results it turns out that our proposed solutions are up to 2 times faster than the previous solutions reducing the number of false positives up to 99%, Comment: 16 pages, 3 figures, submitted to SEA 2015 conference

We complement our previous analysis of a sample of z~1-2 luminous and ultra-luminous infrared galaxies ((U)LIRGs), by adding deep VLA radio observations at 1.4 GHz to a large data-set from the far-UV to the sub-mm, including Spitzer and Herschel data. Given the relatively small number of (U)LIRGs in our sample with high S/N radio data, and to extend our study to a different family of galaxies, we also include 6 well sampled near IR-selected BzK galaxies at z~1.5. From our analysis based on the radiative transfer spectral synthesis code GRASIL, we find that, while the IR luminosity may be a biased tracer of the star formation rate (SFR) depending on the age of stars dominating the dust heating, the inclusion of the radio flux offers significantly tighter constraints on SFR. Our predicted SFRs are in good agreement with the estimates based on rest-frame radio luminosity and the Bell (2003) calibration. The extensive spectro-photometric coverage of our sample allows us to set important constraints on the SF history of individual objects. For essentially all galaxies we find evidence for a rather continuous SFR and a peak epoch of SF preceding that of the observation by a few Gyrs. This seems to correspond to a formation redshift of z~5-6. We finally show that our physical analysis may affect the interpretation of the SFR-M* diagram, by possibly shifting, with respect to previous works, the position of the most dust obscured objects to higher M* and lower SFRs., Comment: 26 pages, 15 figures, 3 tables, accepted for publication in MNRAS on Dec. 4th, 2014

Long-duration gamma-ray bursts (LGRBs) are produced by the collapse of very massive stars. Due to the short lifetime of their progenitors, LGRBs pinpoint star-forming galaxies. We present here a multi-band search for the host galaxy of the long dark GRB 050219A within the enhanced Swift/XRT error circle. We used spectroscopic observations acquired with VLT/X-shooter to determine the redshift and star-formation rate of the putative host galaxy. We compared the results with the optical/IR spectral energy distribution obtained with different facilities. Surprisingly, the host galaxy is a old and quiescent early-type galaxy at z = 0.211 characterised by an unprecedentedly low specific star-formation rate. It is the first LGRB host to be also an early-type post-starburst galaxy. This is further evidence that GRBs can explode in all kind of galaxies, with the only requirement being an episode of star-formation., Comment: 11 pages, 10 figures, 3 tables; accepted for publication in Astronomy & Astrophysics

In this paper we consider uniformly resolvable decompositions of the complete graph K_v into subgraphs such that each resolution class contains only blocks isomorphic to the same graph. We completely determine the spectrum for the case in which all the resolution classes consist of either P_2, P_3 and P_4., Comment: arXiv admin note: text overlap with arXiv:1312.2113

It is established that up to isomorphism,there are only one (K_4-e)-design of order 6, three (K_4-e)-designs of order 10 and two (K_4-e)-designs of order 11. As an application of our enumerative results, we discuss the fine triangle intersection problem for (K_4-e)-designs of orders v=6,10,11.

Let Kv be the complete graph of order v and F be a set of 1-factors of Kv. In this article we study the existence of a resolvable decomposition of Kv - F into 3-stars when F has the minimum number of 1-factors. We completely solve the case in which F has the minimum number of 1- factors, with the possible exception of v in {40, 44, 52, 76, 92, 100, 280, 284, 328, 332, 428, 472, 476, 572}., Comment: arXiv admin note: text overlap with arXiv:1310.7403

In this work we explore the impact of the presence of an active galactic nucleus (AGN) on the mid- and far-infrared (IR) properties of galaxies as well as the effects of simultaneous AGN and starburst activity in these same galaxies. To do this we apply a multi-component, multi-band spectral synthesis technique to a sample of 250 micron selected galaxies of the Herschel Multi-tiered Extragalactic Survey, with IRS spectra available for all galaxies. Our results confirm that the inclusion of the IRS spectra plays a crucial role in the spectral analysis of galaxies with an AGN component improving the selection of the best-fit hot dust model (torus). We find a correlation between the obscured star formation rate (SFR) derived from the IR luminosity of the starburst component, SFR_IR and SFR_PAH, derived from the luminosity of the PAH features, L_PAH, with SFR_FIR taking higher values than SFR_PAH. The correlation is different for AGN- and starburst-dominated objects. The ratio of L_PAH to that of the starburst component, L_PAH/L_SB, is almost constant for AGN-dominated objects but decreases with increasing L_SB for starburst-dominated objects. SFR_FIR increases with the accretion luminosity, L_acc, with the increase less prominent for the very brightest, unobscured AGN-dominated sources. We find no correlation between the masses of the hot and cold dust components. We interpret this as a non-constant fraction of gas driven by the gravitational effects to the AGN while the starburst is ongoing. We also find no evidence of the AGN affecting the temperature of the cold dust component, though this conclusion is mostly based on objects with a non-dominant AGN component. We conclude that our findings do not provide evidence that the presence of AGN affects the star formation process in the host galaxy, but rather that the two phenomena occur simultaneously over a wide range of luminosities., Comment: 12 pages, 12 figures, 2 tables. Accepted for publication in MNRAS

We combine far-infrared photometry from Herschel (PEP/HERMES) with deep mid-infrared spectroscopy from Spitzer to investigate the nature and the mass assembly history of a sample of 31 Luminous and Ultraluminous Infrared Galaxies at z~1 and 2 selected in GOODS-S with 24 $\mu$m fluxes between 0.2 and 0.5 mJy. We model the data with a self-consistent physical model (GRASIL) which includes a state-of-the-art treatment of dust extinction and reprocessing. We find that all of our galaxies appear to require massive populations of old (>1 Gyr) stars and, at the same time, to host a moderate ongoing activity of SF (SFR < 100 M$_{\odot}$/yr). The bulk of the stars appear to have been formed a few Gyr before the observation in essentially all cases. Only five galaxies of the sample require a recent starburst superimposed on a quiescent star formation history (SFH). We also find discrepancies between our results and those based on optical-only SED fitting for the same objects; by fitting their observed Spectral Energy Distributions with our physical model we find higher extinctions (by $\Delta$A_{V} ~ 0.81 and 1.14) and higher stellar masses (by $\Delta$Log(M*) ~ 0.16 and 0.36 dex) for z~1 and z~2 (U)LIRGs, respectively. The stellar mass difference is larger for the most dust obscured objects. We also find lower SFRs than those computed from L_{IR} using the Kennicutt relation due to the significant contribution to the dust heating by intermediate-age stellar populations through 'cirrus' emission (~73% and ~66% of total L_{IR} for z~1 and z~2 (U)LIRGs, respectively)., Comment: 21 pages, 10 figures, 2 tables, accepted for publication in ApJ

Searching for all occurrences of a pattern in a text is a fundamental problem in computer science with applications in many other fields, like natural language processing, information retrieval and computational biology. In the last two decades a general trend has appeared trying to exploit the power of the word RAM model to speed-up the performances of classical string matching algorithms. In this model an algorithm operates on words of length w, grouping blocks of characters, and arithmetic and logic operations on the words take one unit of time. In this paper we use specialized word-size packed string matching instructions, based on the Intel streaming SIMD extensions (SSE) technology, to design very fast string matching algorithms in the case of short patterns. From our experimental results it turns out that, despite their quadratic worst case time complexity, the new presented algorithms become the clear winners on the average for short patterns, when compared against the most effective algorithms known in literature., Comment: 15 pages