We study a family of Mean Field Games arising in modeling the behavior of strategic economic agents which move across space maximizing their utility from consumption and have the possibility to accumulate resources for production (such as human capital). The resulting mean field game PDE system is not covered in the actual literature on the topic as it displays weaker assumptions on the regularity of the data (in particular Lipschitz continuity and boundedness of the objective are lost), state constraints, and a non-standard interaction term. We obtain a first result on the existence of solution of the mean field game PDE system.

The second Gravitational-Wave Transient Catalog reported on 39 compact binary coalescences observed by the Advanced LIGO and Advanced Virgo detectors between 1 April 2019 15:00 UTC and 1 October 2019 15:00 UTC. We present GWTC-2.1, which reports on a deeper list of candidate events observed over the same period. We analyze the final version of the strain data over this period with improved calibration and better subtraction of excess noise, which has been publicly released. We employ three matched-filter search pipelines for candidate identification, and estimate the astrophysical probability for each candidate event. While GWTC-2 used a false alarm rate threshold of 2 per year, we include in GWTC-2.1, 1201 candidates that pass a false alarm rate threshold of 2 per day. We calculate the source properties of a subset of 44 high-significance candidates that have an astrophysical probability greater than 0.5. Of these candidates, 36 have been reported in GWTC-2. If the 8 additional high-significance candidates presented here are astrophysical, the mass range of events that are unambiguously identified as binary black holes (both objects $\geq 3M_\odot$) is increased compared to GWTC-2, with total masses from $\sim 14 M_\odot$for GW190924_021846 to$\sim 182 M_\odot$ for GW190426_190642. The primary components of two new candidate events (GW190403_051519 and GW190426_190642) fall in the mass gap predicted by pair instability supernova theory. We also expand the population of binaries with significantly asymmetric mass ratios reported in GWTC-2 by an additional two events (the mass ratio is less than $0.65$ and $0.44$ at $90\%$ probability for GW190403_051519 and GW190917_114630 respectively), and find that 2 of the 8 new events have effective inspiral spins \chi_\mathrm{eff} > 0 (at $90\%$ credibility), while no binary is consistent with \chi_\mathrm{eff} < 0 at the same significance.

Image Representation learning via input reconstruction is a common technique in machine learning for generating representations that can be effectively utilized by arbitrary downstream tasks. A well-established approach is using autoencoders to extract latent representations at the network's compression point. These representations are valuable because they retain essential information necessary for reconstructing the original input from the compressed latent space. In this paper, we propose an alternative learning objective. Instead of using the raw input as the reconstruction target, we employ the Discrete Fourier Transform (DFT) of the input. The DFT provides meaningful global information at each frequency level, making individual frequency components useful as separate learning targets. When dealing with multidimensional input data, the DFT offers remarkable flexibility by enabling selective transformation across specific dimensions while preserving others in the computation. Moreover, certain types of input exhibit distinct patterns in their frequency distributions, where specific frequency components consistently contain most of the magnitude, allowing us to focus on a subset of frequencies rather than the entire spectrum. These characteristics position the DFT as a viable learning objective for representation learning and we validate our approach by achieving 52.8% top-1 accuracy on CIFAR-10 with ResNet-50 and outperforming the traditional autoencoder by 12.8 points under identical architectural configurations. Additionally, we demonstrate that training on only the lower-frequency components - those with the highest magnitudes yields results comparable to using the full frequency spectrum, with only minimal reductions in accuracy.

In this paper we study projective algebras in varieties of (bounded) commutative integral residuated lattices from an algebraic (as opposed to categorical) point of view. In particular we use a well-established construction in residuated lattices: the ordinal sum. Its interaction with divisibility makes our results have a better scope in varieties of divisibile commutative integral residuated lattices, and it allows us to show that many such varieties have the property that every finitely presented algebra is projective. In particular, we obtain results on (Stonean) Heyting algebras, certain varieties of hoops, and product algebras. Moreover, we study varieties with a Boolean retraction term, showing for instance that in a variety with a Boolean retraction term all finite Boolean algebras are projective. Finally, we connect our results with the theory of Unification.

We formalize a novel modeling framework for achieving interpretability in deep learning, anchored in the principle of inference equivariance. While the direct verification of interpretability scales exponentially with the number of variables of the system, we show that this complexity can be mitigated by treating interpretability as a Markovian property and employing neural re-parametrization techniques. Building on these insights, we propose a new modeling paradigm -- neural generation and interpretable execution -- that enables scalable verification of equivariance. This paradigm provides a general approach for designing Neural Interpretable Reasoners that are not only expressive but also transparent.

In this paper we continue to study varieties of K-lattices, focusing on their bounded versions. These (bounded) commutative residuated lattices arise from a specific kind of construction: the {\em twist-product} of a lattice. Twist-products were first considered by Kalman in 1958 to deal with order involutions on plain lattices, but the extension of this concept to residuated lattices has attracted some attention lately.

In this paper we investigate two logics from an algebraic point of view. The two logics are: MALL (multiplicative-additive Linear Logic) and LL (classical Linear Logic). Both logics turn out to be strongly algebraizable in the sense of Blok and Pigozzi and their equivalent algebraic semantics are, respectively, the variety of Girard algebras and the variety of girales. We show that any variety of girales has equationally definable principale congruences and we classify all varieties of Girard algebras having this property. Also we investigate the structure of the algebras in question, thus obtaining a representation theorem for Girard algebras and girales. We also prove that congruence lattices of girales are really congruence lattices of Heyting algebras and we construct examples in order to show that the variety of girales contains infinitely many nonisomorphic finite simple algebras.

We search for gravitational-wave signals associated with gamma-ray bursts detected by the Fermi and Swift satellites during the second half of the third observing run of Advanced LIGO and Advanced Virgo (1 November 2019 15:00 UTC-27 March 2020 17:00 UTC).We conduct two independent searches: a generic gravitational-wave transients search to analyze 86 gamma-ray bursts and an analysis to target binary mergers with at least one neutron star as short gamma-ray burst progenitors for 17 events. We find no significant evidence for gravitational-wave signals associated with any of these gamma-ray bursts. A weighted binomial test of the combined results finds no evidence for sub-threshold gravitational wave signals associated with this GRB ensemble either. We use several source types and signal morphologies during the searches, resulting in lower bounds on the estimated distance to each gamma-ray burst. Finally, we constrain the population of low luminosity short gamma-ray bursts using results from the first to the third observing runs of Advanced LIGO and Advanced Virgo. The resulting population is in accordance with the local binary neutron star merger rate.

"PyTorch, Explain!" is a Python module integrating a variety of state-of-the-art approaches to provide logic explanations from neural networks. This package focuses on bringing these methods to non-specialists. It has minimal dependencies and it is distributed under the Apache 2.0 licence allowing both academic and commercial use. Source code and documentation can be downloaded from the github repository: this https URL.

Cygnus X-3 is a microquasar consisting of an accreting compact object orbiting around a Wolf-Rayet star. It has been detected at radio frequencies and up to high-energy gamma rays (above 100 MeV). However, many models also predict a very high energy (VHE) emission (above hundreds of GeV) when the source displays relativistic persistent jets or transient ejections. Therefore, detecting such emission would improve the understanding of the jet physics. The imaging atmospheric Cherenkov telescope MAGIC observed Cygnus X-3 for about 70 hours between 2006 March and 2009 August in different X-ray/radio spectral states and also during a period of enhanced gamma-ray emission. MAGIC found no evidence for a VHE signal from the direction of the microquasar. An upper limit to the integral flux for energies higher than 250 GeV has been set to 2.2 x 10-12 photons cm-2 s-1 (95% confidence level). This is the best limit so far to the VHE emission from this source. The non-detection of a VHE signal during the period of activity in the high-energy band sheds light on the location of the possible VHE radiation favoring the emission from the innermost region of the jets, where absorption is significant. The current and future generations of Cherenkov telescopes may detect a signal under precise spectral conditions.

The discovery of rapidly variable Very High Energy (VHE; E > 100 GeV) gamma-ray emission from 4C +21.35 (PKS 1222+216) by MAGIC on 2010 June 17, triggered by the high activity detected by the Fermi Large Area Telescope (LAT) in high energy (HE; E > 100 MeV) gamma-rays, poses intriguing questions on the location of the gamma-ray emitting region in this flat spectrum radio quasar. We present multifrequency data of 4C +21.35 collected from centimeter to VHE during 2010 to investigate the properties of this source and discuss a possible emission model. The first hint of detection at VHE was observed by MAGIC on 2010 May 3, soon after a gamma-ray flare detected by Fermi-LAT that peaked on April 29. The same emission mechanism may therefore be responsible for both the HE and VHE emission during the 2010 flaring episodes. Two optical peaks were detected on 2010 April 20 and June 30, close in time but not simultaneous with the two gamma-ray peaks, while no clear connection was observed between the X-ray an gamma-ray emission. An increasing flux density was observed in radio and mm bands from the beginning of 2009, in accordance with the increasing gamma-ray activity observed by Fermi-LAT, and peaking on 2011 January 27 in the mm regime (230 GHz). We model the spectral energy distributions (SEDs) of 4C +21.35 for the two periods of the VHE detection and a quiescent state, using a one-zone model with the emission coming from a very compact region outside the broad line region. The three SEDs can be fit with a combination of synchrotron self-Compton and external Compton emission of seed photons from a dust torus, changing only the electron distribution parameters between the epochs. The fit of the optical/UV part of the spectrum for 2010 April 29 seems to favor an inner disk radius of <6 gravitational radii, as one would expect from a prograde-rotating Kerr black hole.

MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes located in the Canary island of La Palma, Spain. During summer 2011 and 2012 it underwent a series of upgrades, involving the exchange of the MAGIC-I camera and its trigger system, as well as the upgrade of the readout system of both telescopes. We use observations of the Crab Nebula taken at low and medium zenith angles to assess the key performance parameters of the MAGIC stereo system. For low zenith angle observations, the standard trigger threshold of the MAGIC telescopes is ~50GeV. The integral sensitivity for point-like sources with Crab Nebula-like spectrum above 220GeV is (0.66+/-0.03)% of Crab Nebula flux in 50 h of observations. The angular resolution, defined as the sigma of a 2-dimensional Gaussian distribution, at those energies is < 0.07 degree, while the energy resolution is 16%. We also re-evaluate the effect of the systematic uncertainty on the data taken with the MAGIC telescopes after the upgrade. We estimate that the systematic uncertainties can be divided in the following components: < 15% in energy scale, 11-18% in flux normalization and +/-0.15 for the energy spectrum power-law slope.

The MEG experiment, designed to search for the mu+->e+ gamma decay at a 10^-13 sensitivity level, completed data taking in 2013. In order to increase the sensitivity reach of the experiment by an order of magnitude to the level of 6 x 10-14 for the branching ratio, a total upgrade, involving substantial changes to the experiment, has been undertaken, known as MEG II. We present both the motivation for the upgrade and a detailed overview of the design of the experiment and of the expected detector performance.

A simulation tool based on GEMC framework to describe the MRPC telescope of the Extreme Energy Events (EEE) Project is presented. The EEE experiment is mainly devoted to the study of the secondary cosmic muons by using MRPC telescope distributed in high schools and research centres in Italy and at CERN. This takes into account the muon interactions with EEE telescopes and the structures surrounding the experimental apparata; it consists of a dedicated event generator producing realistic muon distribution and a detailed geometry description of the detector. Microscopic behaviour of MRPCs has been included to produce experimental-like data. A method to estimate the chamber effciency directly from data has been implemented and tested by comparing the experimental and simulated polar angle distribution of muons.

We present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, {\tt PyStoch}, enable us to perform the radiometer map-making at every frequency bin. We perform the search at 3072 {\tt{HEALPix}} equal area pixels uniformly tiling the sky and in every frequency bin of width $1/32$~Hz in the range $20-1726$~Hz, except for bins that are likely to contain instrumental artefacts and hence are notched. We do not find any statistically significant evidence for the existence of narrowband gravitational-wave signals in the analyzed frequency bins. Therefore, we place $95\%$ confidence upper limits on the gravitational-wave strain for each pixel-frequency pair, the limits are in the range $(0.030 - 9.6) \times10^{-24}$. In addition, we outline a method to identify candidate pixel-frequency pairs that could be followed up by a more sensitive (and potentially computationally expensive) search, e.g., a matched-filtering-based analysis, to look for fainter nearly monochromatic coherent signals. The ASAF analysis is inherently independent of models describing any spectral or spatial distribution of power. We demonstrate that the ASAF results can be appropriately combined over frequencies and sky directions to successfully recover the broadband directional and isotropic results.

In 2005 and 2006, the MAGIC telescope has observed very high energy gamma-ray emission from the distant BL Lac object PG 1553+113. The overall significance of the signal is 8.8 sigma for 18.8h observation time. The light curve shows no significant flux variations on a daily time-scale, the flux level during 2005 was, however, significantly higher compared to 2006. The differential energy spectrum between ~90 GeV and 500 GeV is well described by a power law with photon index Gamma = 4.2 +- 0.3. The combined 2005 and 2006 energy spectrum provides an upper limit of z=0.74 on the redshift of the object.

We present a search for continuous gravitational-wave signals from the young, energetic X-ray pulsar PSR J0537-6910 using data from the second and third observing runs of LIGO and Virgo. The search is enabled by a contemporaneous timing ephemeris obtained using NICER data. The NICER ephemeris has also been extended through 2020 October and includes three new glitches. PSR J0537-6910 has the largest spin-down luminosity of any pulsar and is highly active with regards to glitches. Analyses of its long-term and inter-glitch braking indices provided intriguing evidence that its spin-down energy budget may include gravitational-wave emission from a time-varying mass quadrupole moment. Its 62 Hz rotation frequency also puts its possible gravitational-wave emission in the most sensitive band of LIGO/Virgo detectors. Motivated by these considerations, we search for gravitational-wave emission at both once and twice the rotation frequency. We find no signal, however, and report our upper limits. Assuming a rigidly rotating triaxial star, our constraints reach below the gravitational-wave spin-down limit for this star for the first time by more than a factor of two and limit gravitational waves from the $l=m=2$ mode to account for less than 14% of the spin-down energy budget. The fiducial equatorial ellipticity is limited to less than about 3e-5, which is the third best constraint for any young pulsar.

The paper copes with the task of automatic assessment of second language proficiency from the language learners' spoken responses to test prompts. The task has significant relevance to the field of computer assisted language learning. The approach presented in the paper relies on two separate modules: (1) an automatic speech recognition system that yields text transcripts of the spoken interactions involved, and (2) a multiple classifier system based on deep learners that ranks the transcripts into proficiency classes. Different deep neural network architectures (both feed-forward and recurrent) are specialized over diverse representations of the texts in terms of: a reference grammar, the outcome of probabilistic language models, several word embeddings, and two bag-of-word models. Combination of the individual classifiers is realized either via a probabilistic pseudo-joint model, or via a neural mixture of experts. Using the data of the third Spoken CALL Shared Task challenge, the highest values to date were obtained in terms of three popular evaluation metrics.

We present the first joint analysis of gamma-ray data from the MAGIC Cherenkov telescopes and the Fermi Large Area Telescope (LAT) to search for gamma-ray signals from dark matter annihilation in dwarf satellite galaxies. We combine 158 hours of Segue 1 observations with MAGIC with 6-year observations of 15 dwarf satellite galaxies by the Fermi-LAT. We obtain limits on the annihilation cross-section for dark matter particle masses between 10 GeV and 100 TeV - the widest mass range ever explored by a single gamma-ray analysis. These limits improve on previously published Fermi-LAT and MAGIC results by up to a factor of two at certain masses. Our new inclusive analysis approach is completely generic and can be used to perform a global, sensitivity-optimized dark matter search by combining data from present and future gamma-ray and neutrino detectors.

Timed Concurrent Constraint Programming (tcc) is a declarative model for concurrency offering a logic for specifying reactive systems, i.e. systems that continuously interact with the environment. The universal tcc formalism (utcc) is an extension of tcc with the ability to express mobility. Here mobility is understood as communication of private names as typically done for mobile systems and security protocols. In this paper we consider the denotational semantics for tcc, and we extend it to a "collecting" semantics for utcc based on closure operators over sequences of constraints. Relying on this semantics, we formalize a general framework for data flow analyses of tcc and utcc programs by abstract interpretation techniques. The concrete and abstract semantics we propose are compositional, thus allowing us to reduce the complexity of data flow analyses. We show that our method is sound and parametric with respect to the abstract domain. Thus, different analyses can be performed by instantiating the framework. We illustrate how it is possible to reuse abstract domains previously defined for logic programming to perform, for instance, a groundness analysis for tcc programs. We show the applicability of this analysis in the context of reactive systems. Furthermore, we make also use of the abstract semantics to exhibit a secrecy flaw in a security protocol. We also show how it is possible to make an analysis which may show that tcc programs are suspension free. This can be useful for several purposes, such as for optimizing compilation or for debugging.