arXiv subjects

Daniel Nieto

Publications and source records attributed to Daniel Nieto.

14 recordsLinked to original sources

arXiv2026

Accurate Decoding of Natural Sentences from Non-Invasive Brain Recordings

Restoring communication for people who have lost the ability to speak or move after a brain injury is a major challenge. While intracranial implants now enable high-performing brain-computer-interfaces, non-invasive alternatives are still lagging behind. Here, we present Brain2Qwerty v2, a model that can decode the production of natural sentences solely from real-time magnetoencephalography (MEG) recordings. By collecting 22,000 sentences typed by nine subjects, each recorded for 10 hours, our model leverages character, word and sentence-level representations to achieve an average word error rate (WER) of 39%. For our best participant, the model accurately decodes half of the sentences with one word error or less. Critically, decoding accuracy log-linearly improves with data volume, suggesting that the performance gap with intracranial approaches could be partially bridged through data scaling. We show that AI enables this performance in three main ways: the substitution of hand-crafted pipelines for event detection with deep learning, the finetuning of large language models to extract semantic representations, and the deployment of AI agents to iteratively refine our decoding pipeline via automated code development. Together, these results show that non-invasive brain-to-text decoding starts to operate at a level of accuracy previously thought exclusive to surgical implants, opening a path toward safe and efficient brain-computer-interfaces.

cs.CL↗

arXiv2022

Constraining branon dark matter from observations of the dwarf spheroidal galaxies with the MAGIC telescopes

We present the first branon dark matter (DM) search in the very high-energy gamma-ray band with observations of the dwarf spheroidal galaxy Segue~1 carried out by the Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescope system. Branons are new degrees of freedom that appear in flexible brane-world models corresponding to brane fluctuations. They behave as weakly interacting massive particles, which are natural DM candidates. In the absence of a gamma-ray signal in the Segue~1 data, we place constraints on the branon DM parameter space by using a binned likelihood analysis. Our most constraining limit to the thermally-averaged annihilation cross-section (at $95\%$ confidence level) corresponds to $ \langle σv \rangle \simeq 1.4 \times 10^{-23}~\text{cm}^{3}\text{s}^{-1} $ at a branon DM mass of $ \sim 0.7~\text{TeV}$.

astro-ph.HE↗

arXiv2022

Constraining branon dark matter from observations of the Segue 1 dwarf spheroidal galaxy with the MAGIC telescopes

We present the first search for signatures of brane-world extra-dimensional dark matter (DM) in the very-high-energy gamma-ray band by scrutinizing observations of the dwarf spheroidal galaxy Segue 1 with the Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescope system. Branons are new degrees of freedom that appear within flexible brane-world models: they are weakly interacting massive particles and natural DM candidates. The ground-based gamma-ray telescopes MAGIC could indirectly detect branon DM in the multi-TeV mass range by observing secondary products of DM annihilation into Standard Model particles. In the absence of a signal, we place constraints on the branon DM parameter space by using a binned likelihood analysis of almost 160-hours deep exposure on the Segue 1 dwarf spheroidal galaxy by the MAGIC telescopes. Our most stringent limit to the thermally-averaged annihilation cross-section (at $95\%$ confidence level) corresponds to $ \langle σv \rangle \simeq 1.4 \times 10^{-23}~\text{cm}^{3}\text{s}^{-1} $ at a branon mass of $ \sim 0.7~\text{TeV}$.

astro-ph.HE↗

arXiv2021

Reconstruction of stereoscopic CTA events using deep learning with CTLearn

The Cherenkov Telescope Array (CTA), conceived as an array of tens of imaging atmospheric Cherenkov telescopes (IACTs), is an international project for a next-generation ground-based gamma-ray observatory, aiming to improve on the sensitivity of current-generation instruments a factor of five to ten and provide energy coverage from 20 GeV to more than 300 TeV. Arrays of IACTs probe the very-high-energy gamma-ray sky. Their working principle consists of the simultaneous observation of air showers initiated by the interaction of very-high-energy gamma rays and cosmic rays with the atmosphere. Cherenkov photons induced by a given shower are focused onto the camera plane of the telescopes in the array, producing a multi-stereoscopic record of the event. This image contains the longitudinal development of the air shower, together with its spatial, temporal, and calorimetric information. The properties of the originating very-high-energy particle (type, energy, and incoming direction) can be inferred from those images by reconstructing the full event using machine learning techniques. In this contribution, we present a purely deep-learning driven, full-event reconstruction of simulated, stereoscopic IACT events using CTLearn. CTLearn is a package that includes modules for loading and manipulating IACT data and for running deep learning models, using pixel-wise camera data as input.

astro-ph.IM↗

arXiv2020

Cherenkov Telescope Array sensitivity to branon dark matter models

In the absence of a clear hint of dark matter (DM) signals in the GeV regime so far, heavy, $\mathcal{O}$(TeV) DM candidates are gradually earning more and more attention within the community. Among others, extra-dimensional \textit{brane-world} models may produce thermal DM candidates with masses up to 100 TeV. These heavy DM candidates could be detected with the next generation of very-high-energy gamma-ray observatories such as the Cherenkov Telescope Array (CTA). In this work, we study the sensitivity of CTA to branon DM via the observation of representative astrophysical DM targets, namely dwarf spheroidal galaxies. In particular, we focus on Draco and Sculptor, two well-known dwarfs visible from the Northern and Southern Hemisphere, respectively. For each of these targets, we simulated 300\,h of CTA observations and studied the sensitivity of both CTA-North and CTA-South to branon annihilations using the latest publicly available instrument response functions and most recent analysis tools. We computed annihilation cross section values needed to reach a $5σ$ detection as a function of the branon mass. Additionally, in the absence of a predicted DM signal, we obtained $2σ$ upper limits on the annihilation cross section. These limits lie $1.5-2$ orders of magnitude above the thermal relic cross section value, depending on the considered branon mass. Yet, CTA will allow to exclude a significant portion of the brane tension-mass parameter space in the $0.1-60$ TeV branon mass range, and up to tensions of $\sim 10$ TeV. More importantly, CTA will significantly enlarge the region already excluded by AMS and CMS, and will provide valuable complementary information to future SKA radio observations. We conclude that CTA will possess potential to constrain brane-world models and, more in general, TeV DM candidates.

astro-ph.HE↗

arXiv2020

Investigating a Deep Learning Method to Analyze Images from Multiple Gamma-ray Telescopes

Imaging atmospheric Cherenkov telescope (IACT) arrays record images from air showers initiated by gamma rays entering the atmosphere, allowing astrophysical sources to be observed at very high energies. To maximize IACT sensitivity, gamma-ray showers must be efficiently distinguished from the dominant background of cosmic-ray showers using images from multiple telescopes. A combination of convolutional neural networks (CNNs) with a recurrent neural network (RNN) has been proposed to perform this task. Using CTLearn, an open source Python package using deep learning to analyze data from IACTs, with simulated data from the upcoming Cherenkov Telescope Array (CTA), we implement a CNN-RNN network and find no evidence that sorting telescope images by total amplitude improves background rejection performance.

astro-ph.IM↗

arXiv2019

Unidentified Gamma-ray Sources as Targets for Indirect Dark Matter Detection with the Fermi-Large Area Telescope

One of the predictions of the $Λ$CDM cosmological framework is the hierarchical formation of structure, giving rise to dark matter (DM) halos and subhalos. When the latter are massive enough they retain gas (i.e., baryons) and become visible. This is the case of the dwarf satellite galaxies in the Milky Way (MW). Below a certain mass, halos may not accumulate significant amounts of baryons and remain completely dark. However, if DM particles are Weakly Interacting Massive Particles (WIMPs), we expect them to annihilate in subhalos, producing gamma rays which can be detected with the Fermi satellite. Using the three most recent point-source Fermi Large Area Telescope (LAT) catalogs (3FGL, 2FHL and 3FHL), we search for DM subhalo candidates among the unidentified sources, i.e., sources with no firm association to a known astrophysical object. We apply several selection criteria based on the expected properties of the DM-induced emission from subhalos, which allow us to significantly reduce the list of potential candidates. Then, by characterizing the minimum detection flux of the instrument and comparing our sample to predictions from the Via Lactea II (VL-II) N-body cosmological simulation, we place conservative and robust constraints on the $\langleσv\rangle-m_{DM}$ parameter space. For annihilation via the $τ^+τ^-$ channel, we put an upper limit of $4\times 10^{-26}~(5\times 10^{-25})~cm^3~s^{-1}$ for a mass of 10 (100) GeV. A critical improvement over previous treatments is the repopulation we made to include low-mass subhalos below the VL-II mass resolution. With more advanced subhalo candidate filtering the sensitivity reach of our method can potentially improve these constraints by a factor 3 (2) for $τ^+τ^-$ ($b \bar{b}$) channel.

astro-ph.HE↗

arXiv2018

Strategies for the Follow-up of Gravitational Wave Transients with the Cherenkov Telescope Array

The observation of the electromagnetic counterpart of gravitational-wave (GW) transient GW170817 demonstrated the potential in extracting astrophysical information from multimessenger discoveries. The forthcoming deployment of the first telescopes of the Cherenkov Telescope Array (CTA) observatory will coincide with Advanced LIGO/Virgo's next observing run, O3, enabling the monitoring of gamma-ray emission at E > 20 GeV, and thus particle acceleration, from GW sources. CTA will not be greatly limited by the precision of GW localization as it will be be capable of rapidly covering the GW error region with sufficient sensitivity. We examine the current status of GW searches and their follow-up effort, as well as the status of CTA, in order to identify some of the general strategies that will enhance CTA's contribution to multimessenger discoveries.

astro-ph.HE↗

arXiv2015

Hunting for dark matter subhalos among the Fermi-LAT sources with VERITAS

The distribution of dark matter in the Galaxy, according to state-of-the-art simulations, shows not only a smooth halo component but also a rich substructure where a hierarchy of dark matter subhalos of different masses is found. We present a search for potential dark matter subhalos in our Galaxy exploiting the high (HE, 100 MeV -- 100 GeV) and very-high-energy (VHE, >100 GeV) gamma-ray bands. We assume a scenario where the dark matter is composed of weakly interacting massive particles of mass over 100 GeV, and is capable of self-annihilation into standard model products. Under such a hypothesis, most of the photons created by the annihilation of dark matter particles are predicted to lay in the HE gamma-ray band, where the Fermi-Large Area Telescope is the most sensitive instrument to date. However, the distinctive spectral cut-off located at the dark matter particle mass is expected in the VHE gamma-ray band, thus making imaging atmospheric Cherenkov telescopes like VERITAS the best suited instruments for follow-up observations and the characterization of a potential dark matter signature. We report on the ongoing VERITAS program to hunt for these dark matter subhalos, particularly focusing on two promising dark matter subhalo candidates selected among the Fermi-LAT Second Source Catalog unassociated high-energy gamma-ray sources.

astro-ph.HE↗

arXiv2014

Cherenkov Telescope Array is Well Suited to Follow Up Gravitational Wave Transients

The first gravitational-wave (GW) observations will greatly benefit from the detection of coincident electromagnetic counterparts. Electromagnetic follow-ups will nevertheless be challenging for GWs with poorly reconstructed directions. GW source localization can be inefficient (i) if only two GW observatories are in operation; (ii) if the detectors' sensitivities are highly non-uniform; (iii) for events near the detectors' horizon distance. For these events, follow-up observations will need to cover 100-1000 square degrees of the sky over a limited period of time, reducing the list of suitable telescopes. We demonstrate that the Cherenkov Telescope Array will be capable of following up GW event candidates over the required large sky area with sufficient sensitivity to detect short gamma-ray bursts, which are thought to originate from compact binary mergers, out to the horizon distance of advanced LIGO/Virgo. CTA can therefore be invaluable starting with the first multimessenger detections, even with poorly reconstructed GW source directions. This scenario also provides a further scientific incentive for GW observatories to further decrease the delay of their event reconstruction.

astro-ph.HE↗

arXiv2013

Prospects for Indirect Detection of Dark Matter with CTA

We discuss the prospects for indirect detection of dark matter (DM) with the Cherenkov Telescope Array (CTA), a future ground-based gamma-ray observatory that will be sensitive to gamma rays in the energy range from a few tens of GeV to 100 TeV. We consider the detectability of DM annihilation in different astrophysical targets with a focus on the Galactic Center (GC) region. With a deep observation of the GC, CTA will be sensitive to DM particles with mass greater than 100 GeV and an annihilation cross section close to the thermal relic value.

astro-ph.HE↗

arXiv2013

Schwarzschild-Couder telescope for the Cherenkov Telescope Array: Development of the Optical System

The CTA (Cherenkov Telescope Array) is the next generation ground-based experiment for very high-energy (VHE) gamma-ray observations. It will integrate several tens of imaging atmospheric Cherenkov telescopes (IACTs) with different apertures into a single astronomical instrument. The US part of the CTA collaboration has proposed and is developing a novel IACT design with a Schwarzschild-Couder (SC) aplanatic two mirror optical system. In comparison with the traditional single mirror Davies-Cotton IACT the SC telescope, by design, can accommodate a wide field-of-view, with significantly improved imaging resolution. In addition, the reduced plate scale of an SC telescope makes it compatible with highly integrated cameras assembled from silicon photo multipliers. In this submission we report on the status of the development of the SC optical system, which is part of the effort to construct a full-scale prototype telescope of this type at the Fred Lawrence Whipple Observatory in southern Arizona.

astro-ph.IM↗

arXiv2013

Search for Dark Matter Subhalos in the High-Energy Gamma-ray Band with Fermi and the Cherenkov Telescope Array

We discuss the potential for the detection of dark matter and the characterization of its particle nature via the observation of dark matter subhalos. Specifically, we discuss the search for dark matter Galactic subhalos in the gamma-ray band with the Large Area Telescope on-board the Fermi gamma-ray Space Telescope, and the future generation of imaging atmospheric Cherenkov telescopes, best represented by the planned Cherenkov Telescope Array.

astro-ph.HE↗

arXiv2009

The MAGIC Data Center

The MAGIC I telescope produces currently around 100TByte of raw data per year that is calibrated and reduced on-site at the Observatorio del Roque de los Muchachos (La Palma). Since February 2007 most of the data have been stored and further processed in the Port d'Informacio Cientifica (PIC), Barcelona. This facility, which supports the GRID Tier 1 center for LHC in Spain, provides resources to give the entire MAGIC Collaboration access to the reduced telescope data. It is expected that the data volume will increase by a factor 3 after the start-up of the second telescope, MAGIC II. The project to improve the MAGIC Data Center to meet these requirements is presented. In addition, we discuss the production of high level data products that will allow a more flexible analysis and will contribute to the international network of astronomical data (European Virtual Observatory). For this purpose, we will have to develop a new software able to adapt the analysis process to different data taking conditions, such as different trigger configurations or mono/stereo telescope observations.

astro-ph.IM↗