arXiv subjects

Paulo Garcia

Publications and source records attributed to Paulo Garcia.

At least 19 recordsLinked to original sources

arXiv2026

GRAVITY+: reducing non-common-path aberrations for sub-10 {\mu}as astrometric accuracy

GRAVITY is a state-of-the-art instrument for near-infrared astrometric interferometry that routinely achieves astrometric accuracy of 30-100 microarcsecond in its phase-referenced dual-field mode. However, its fundamental limit is not yet reached, and can still be improved by several factors. In this paper, we focus on the effect of systematics, and in particular the effect of non-common path aberrations between the science channel and the metrology signal in the GRAVITY Fiber Coupler. Through comprehensive laboratory measurements using a dedicated fiber coupler replica and phase-shifting interferometry at 1908 nm, we have characterized these high-order wavefront errors with nanometer precision in the laboratory. We characterized on-sky the effect of these high-order wavefront imperfections on narrow-angle astrometry, using observations of the binary system GJ65. As part of the GRAVITY+ project, high-precision mirrors designed for nanometer-level surface quality, bringing an order of magnitude improvement over existing GRAVITY injection optics, are currently in production and will be installed in the fiber coupler units by the end of 2027. This upgrade is expected to enable astrometric accuracy at the sub-10 microarcsecond level in dual-field mode with integration times of just a few minutes.

astro-ph.IM↗

arXiv2026

Using VLTI/GRAVITY+ to determine the identity of a third planet candidate in the PDS 70 system

Detections of protoplanets are rare and protoplanetary disk features mischaracterized as planets are common. PDS 70 is one of only two stars known to host multiple confirmed protoplanets, PDS 70 b and c, and repeat detections of a third point-like source in the system suggest the presence of third inner planet. However, previous observations of this third source are insufficient to distinguish whether it is a planet or a concentrated dust clump in Keplerian motion. Our observations with VLTI/GRAVITY+ did not re-detect this point-like source, suggesting that it is, in fact, a dust clump and not a planet. These observations demonstrate how the angular resolving power of VLTI/GRAVITY+ can be used to distinguish between protoplanets and protoplanetary disk features.

astro-ph.EP↗

arXiv2026

A New Quaternion-Joint Cable-Driven Redundant Manipulator Configuration and its Control Through FABRIK and Residual Reinforcement Learning

Robotic arms capable of traversing arbitrary spatial paths, especially in highly obstructed workspaces, are highly desired across several industries. Quaternion-joints have recently empowered a specific class of robotic arms -- cable-driven redundant manipulators -- beyond its prior capabilities. Specifically, quaternion-joints reduce the number of required motors per degree of freedom, paving the way for more compact solutions.An ongoing challenge is that the complexity of the kinematic model of quaternion joints challenges a priori decisions on manipulator configurations and imposes higher computational demands on the control system and its non-linearities amplify all discrepancies between design and physical artifact arising from fabrication imprecision. Here we show a that a 4-segment, 8-joint manipulator can achieve a broader workspace than extant configurations, at lower hardware cost, and that Residual Reinforcement Learning outperforms extant state-of-the-art methods -- specifically, the FABRIK algorithm -- on the control of such manipulator. Our results show that this configuration is more workspace-effective than prior designs, and that Residual Reinforcement Learning outperforms FABRIK by three orders of magnitude on positional and orientational accuracy, effecting precise control of the novel 4-segment, 8-joint manipulator. Additionally, the control implementation is simpler: we describe the complete FABRIK process for control and corresponding learning implementation. Our methodology is applicable to the design of new systems, providing designers with further tools for the development of this class of manipulators and corresponding control systems for novel configurations.

cs.RO↗

arXiv2026

Greedy Kalman-Swarm: Improving State Estimation in Robot Swarms in Harsh Environments

State estimation is a fundamental requirement in robotics, where the accurate determination of a robot's state is essential for stable operation despite inherent process disturbances and sensor noise. Traditionally, this is achieved through Kalman filtering, providing a statistically optimal estimate by balancing predictive models with noisy measurements. In the context of robotic swarms, the challenge shifts from individual accuracy to collective coordination, where the integration of global dynamics can significantly enhance the precision of the entire group. Existing estimation techniques rely on centralized processing or heavy communication protocols to reach a global consensus, which are frequently impractical in real-world deployments. Here we show that a localized, "greedy" approach to distributed state estimation (termed "Greedy Kalman-Swarm") allows individual robots to leverage relative inter-robot sensing for improved accuracy without requiring full data availability or global communication. Simulations in communication-constrained environments show robots can effectively integrate all currently available neighbor data at each iteration to refine their internal states, yet remain robust and functional even when data is missing. This results in a performance profile that strikes a balance between the low overhead of independent estimation and the high accuracy of centralized systems, specifically under harsh or dynamic environmental conditions. Our results demonstrate that global state awareness can be emergent rather than enforced, providing a scalable framework for maintaining swarm cohesion in unpredictable terrains. We anticipate that this decentralized methodology will serve as a foundation for more resilient autonomous systems, particularly in search-and-rescue or space exploration missions where reliable, high-bandwidth communication cannot be guaranteed.

cs.RO↗

arXiv2026

Direct spectroscopic confirmation of the young embedded proto-planet WISPIT 2c

WISPIT 2 is a nearby young star with a multi-ringed disk which was recently confirmed to host a ~4.9 MJup gas giant planet embedded in a large (60 au) gap at a radial separation of 57 au from the host star. We confirm and characterise a second, close-in planet in the WISPIT 2 system using a combination of new VLT/SPHERE H-band dual-polarisation imaging and VLTI/GRAVITY K-band interferometric observations of the WISPIT 2 system. The GRAVITY detection is consistent with a point-like source while its extracted K-band spectrum shows CO band-head absorption at 2.3 microns and a continuum shape consistent with a young giant planet. From the GRAVITY data we extract a medium resolution K-band spectrum of the companion and fit atmospheric model grids using the species tool with nested sampling to constrain its effective temperature, radius, and luminosity. We infer Teff of 1500-2600 K, a radius of 0.91-2.2 RJup, and a luminosity of (-3.47)-(-3.63). Comparison with evolutionary tracks implies a mass range of 8-12 MJup, approximately twice as massive as the previously confirmed WISPIT 2b. The astrometry rules out a background source and marginally detects orbital motion of WISPIT 2c, which needs further follow-up observations for confirmation. WISPIT 2 now becomes an analogue to PDS 70, offering a second laboratory for studying the formation and early evolution of a multi-planet system within its natal disk.

astro-ph.EP↗

arXiv2026

On the Exact Algorithmic Extraction of Finite Tesselations Through Prime Extraction of Minimal Representative Forms

The identification of repeating patterns in discrete grids is rudimentary within symbolic reasoning, algorithm synthesis and structural optimization across diverse computational domains. Although statistical approaches targeting noisy data can approximately recognize patterns, symbolic analysis utilizing deterministic extraction of periodic structures is underdeveloped. This paper aims to fill this gap by employing a hierarchical algorithm that discovers exact tessellations in finite planar grids, addressing the problem where multiple independent patterns may coexist within a hierarchical structure. The proposed method utilizes composite discovery (dual inspection and breadth-first pruning) for identifying rectangular regions with internal repetition, normalization to a minimal representative form, and prime extraction (selective duplication and hierarchical memoization) to account for irregular dimensions and to achieve efficient computation time. We evaluate scalability on grid sizes from 2x2 to 32x32, showing overlap detection on simple repeating tiles exhibits processing time under 1ms, while complex patterns which require exhaustive search and systematic exploration shows exponential growth. This algorithm provides deterministic behavior for exact, axis-aligned, rectangular tessellations, addressing a critical gap in symbolic grid analysis techniques, applicable to puzzle solving reasoning tasks and identification of exact repeating structures in discrete symbolic domains.

cs.CV↗

arXiv2025

Architecting Large Action Models for Human-in-the-Loop Intelligent Robots

The realization of intelligent robots, operating autonomously and interacting with other intelligent agents, human or artificial, requires the integration of environment perception, reasoning, and action. Classic Artificial Intelligence techniques for this purpose, focusing on symbolic approaches, have long-ago hit the scalability wall on compute and memory costs. Advances in Large Language Models in the past decade (neural approaches) have resulted in unprecedented displays of capability, at the cost of control, explainability, and interpretability. Large Action Models aim at extending Large Language Models to encompass the full perception, reasoning, and action cycle; however, they typically require substantially more comprehensive training and suffer from the same deficiencies in reliability. Here, we show it is possible to build competent Large Action Models by composing off-the-shelf foundation models, and that their control, interpretability, and explainability can be effected by incorporating symbolic wrappers and associated verification on their outputs, achieving verifiable neuro-symbolic solutions for intelligent robots. Our experiments on a multi-modal robot demonstrate that Large Action Model intelligence does not require massive end-to-end training, but can be achieved by integrating efficient perception models with a logic-driven core. We find that driving action execution through the generation of Planning Domain Definition Language (PDDL) code enables a human-in-the-loop verification stage that effectively mitigates action hallucinations. These results can support practitioners in the design and development of robotic Large Action Models across novel industries, and shed light on the ongoing challenges that must be addressed to ensure safety in the field.

cs.RO↗

arXiv2025

Dynamic Reconfiguration of Robotic Swarms: Coordination and Control for Precise Shape Formation

Coordination of movement and configuration in robotic swarms is a challenging endeavor. Deciding when and where each individual robot must move is a computationally complex problem. The challenge is further exacerbated by difficulties inherent to physical systems, such as measurement error and control dynamics. Thus, how to best determine the optimal path for each robot, when moving from one configuration to another, and how to best perform such determination and effect corresponding motion remains an open problem. In this paper, we show an algorithm for such coordination of robotic swarms. Our methods allow seamless transition from one configuration to another, leveraging geometric formulations that are mapped to the physical domain through appropriate control, localization, and mapping techniques. This paves the way for novel applications of robotic swarms by enabling more sophisticated distributed behaviors.

cs.RO↗

arXiv2025

On the evolutionary cognitive pressure for experiential awareness: do machines need it?

The consciousness standing for artificial intelligence divides opinions across epistemological positions. Whether or not machines can be conscious, and whether we can ascertain the truth of such a proposition for any given case, has consequential ethical implications. This challenge is exacerbated by the lack of consensus on the nature of consciousness. We address an orthogonal problem: regardless of this nature of, is it \textit{required} for machines? Specifically, we focus on a constituent element of consciousness -experiential awareness- and examine why it arose evolutionarily in biological organisms, from a computational perspective. We show that, because of evolutionary "baggage" -autonomous neurological reactions- experiential awareness is necessary for higher-level reasoning to be possible. The implication is that, given artificial systems are architected without such legacy considerations, it is possible to design them with an arbitrary level of intelligence, without the need for experiential awareness. This possibility simplifies ethical considerations on artificial intelligence, and opens new approaches to the discernment of artificial consciousness.

q-bio.NC↗

arXiv2025

Substrate-Timing-Independence for Meta-State Stability of Distributed Robotic Swarms

Emergent properties in distributed systems arise due to timing unpredictability; asynchronous state evolution within each sub-system may lead the macro-system to faulty meta-states. Empirical validation of correctness is often prohibitively expensive, as the size of the state-space is too large to be tractable. In robotic swarms this problem is exacerbated, when compared to software systems, by the variability of the implementation substrate across the design, or even the deployment, process. We present an approach for formally reasoning about the correctness of robotic swarm design in a substrate-timing-independent way. By leveraging concurrent process calculi (namely, Communicating Sequential Processes), we introduce a methodology that can automatically identify possible causes of faulty meta-states and correct such designs such that meta-states are consistently stable, even in the presence of timing variability due to substrate changes. We evaluate this approach on a robotic swarm with a clearly identified fault, realized in both simulation and reality. Results support the research hypothesis, showing that the swarm reaches an illegal meta-state before the correction is applied, but behaves consistently correctly after the correction. Our techniques are transferable across different design methodologies, contributing to the toolbox of formal methods for roboticists.

cs.RO↗

arXiv2025

Sagittarius A* near-infrared flares polarization as a probe of space-time I: Non-rotating exotic compact objects

The center of our galaxy hosts Sagittarius~A*, a supermassive compact object of $\sim 4.3\times 10^6$ solar masses, usually associated with a black hole. Nevertheless, black holes possess a central singularity, considered unphysical, and an event horizon, which leads to loss of unitarity in a quantum description of the system. To address these theoretical inconsistencies, alternative models, collectively known as exotic compact objects, have been proposed. In this paper, we investigate the potential detectability of signatures associated with non-rotating exotic compact objects within the Sgr~A* polarized flares dataset, as observed through GRAVITY and future instruments. We examine a total of eight distinct metrics, originating from four different categories of static and spherically symmetric compact objects: Black Holes, Boson stars, Fluid spheres, and Gravastars. Our approach involves utilizing a toy model that orbits the compact object in the equatorial plane. Using simulated astrometric and polarimetric data with present GRAVITY and future GRAVITY+ uncertainties, we fit the datasets across all metrics examined. We evaluated the detectability of the metric for each dataset based on the resulting $\chi^2_\mathrm{red}$ and BIC-based Bayes factors. Plunge-through images of ECOs affect polarization and astrometry. With GRAVITY's present uncertainties, none of the metric model is discernible. GRAVITY+'s improved sensitivity allows detection of some exotic compact object models. However, enhancing the astrophysical complexity of the hot spot model diminishes these outcomes. Presently, GRAVITY's uncertainties do not allow us to detect exotic compact object metric. With GRAVITY+'s enhanced sensitivity, we can expect to uncover additional exotic compact object models and use Sgr~A* as a laboratory for fundamental physics.

astro-ph.HE↗

arXiv2025

GRAVITY+ adaptive optics (GPAO) tests in Europe

We present in this proceeding the results of the test phase of the GRAVITY+ adaptive optics. This extreme AO will enable both high-dynamic range observations of faint companions (including exoplanets) thanks to a 40x40 sub-apertures wavefront control, and sensitive observations (including AGNs) thanks to the addition of a laser guide star to each UT of the VLT. This leap forward is made thanks to a mostly automated setup of the AO, including calibration of the NCPAs, that we tested in Europe on the UT+atmosphere simulator we built in Nice. We managed to reproduce in laboratory the expected performances of all the modes of the AO, including under non-optimal atmospheric or telescope alignment conditions, giving us the green light to proceed with the Assembly, Integration and Verification phase in Paranal.

astro-ph.IM↗

arXiv2024

First Resolution of Microlensed Images of a Binary-Lens Event

We resolve the multiple images of the binary-lens microlensing event ASASSN-22av using the GRAVITY instrument of the Very Large Telescope Interferometer (VLTI). The light curves show weak binary-lens perturbations, complicating the analysis, but the joint modeling with the VLTI data breaks several degeneracies, arriving at a strongly favored solution. Thanks to precise measurements of angular Einstein radius θ_E = 0.724 +/- 0.002 mas and microlens parallax, we determine that the lens system consists of two M dwarfs with masses of M_1 = 0.258 +/- 0.008 M_sun and M_2 = 0.130 +/- 0.007 M_sun, a projected separation of r_\perp = 6.83 +/- 0.31 au and a distance of D_L = 2.29 +/- 0.08 kpc. The successful VLTI observations of ASASSN-22av open up a new path for studying intermediate-separation (i.e., a few astronomical units) stellar-mass binaries, including those containing dark compact objects such as neutron stars and stellar-mass black holes.

astro-ph.SR↗

arXiv2024

Simplified model(s) of the GRAVITY+ adaptive optics system(s) for performance prediction

In the context of the GRAVITY+ upgrade, the adaptive optics (AO) systems of the GRAVITY interferometer are undergoing a major lifting. The current CILAS deformable mirrors (DM, 90 actuators) will be replaced by ALPAO kilo-DMs (43x43, 1432 actuators). On top of the already existing 9x9 Shack-Hartmann wavefront sensors (SH-WFS) for infrared (IR) natural guide star (NGS), new 40x40 SH-WFSs for visible (VIS) NGS will be deployed. Lasers will also be installed on the four units of the Very Large Telescope to provide a laser guide star (LGS) option with 30x30 SH-WFSs and with the choice to either use the 9x9 IR-WFSs or 2x2 VIS-WFSs for low order sensing. Thus, four modes will be available for the GRAVITY+ AO system (GPAO): IR-NGS, IR-LGS, VIS-NGS and VIS-LGS. To prepare the instrument commissioning and help the observers to plan their observations, a tool is needed to predict the performances of the different modes and for different observing conditions (NGS magnitude, science object magnitude, turbulence conditions...) We developed models based on a Mar{é}chal approximation to predict the Strehl ratio of the four GPAO modes in order to feed the already existing tool that simulates the GRAVITY performances. Waiting for commissioning data, our model was validated and calibrated using the TIPTOP toolbox, a Point Spread Function simulator based on the computation of Power Spectrum Densities. In this work, we present our models of the NGS modes of GPAO and their calibration with TIPTOP.

astro-ph.IM↗

arXiv2024

Open loop calibration and closed loop non-perturbative estimation of the lateral errors of an adaptive optics system: examples with GRAVITY+ and CHARA experimental data

Performances of an adaptive optics (AO) system are directly linked with the quality of its alignment. During the instrument calibration, having open loop fast tools with a large capture range are necessary to quickly assess the system misalignment and to drive it towards a state allowing to close the AO loop. During operation, complex systems are prone to misalignments (mechanical flexions, rotation of optical elements, etc.) that potentially degrade the AO performances, creating a need for a monitoring tool to tackle their driftage. In this work, we first present an improved perturbative method to quickly assess large lateral errors in open loop. It uses the spatial correlation of the measured interaction matrix of a limited number of 2D spatial modes with a synthetic model. Then, we introduce a novel solution to finely measure and correct these lateral errors via the closed loop telemetry. Non-perturbative, this method consequently does not impact the science output of the instrument. It is based on the temporal correlation of 2D spatial frequencies in the deformable mirror commands. It is model-free (no need of an interaction matrix model) and sparse in the Fourier space, making it fast and easily scalable to complex systems such as future extremely large telescopes. Finally, we present some results obtained on the development bench of the GRAVITY+ extreme AO system (Cartesian grid, 1432 actuators). In addition, we show with on-sky results gathered with CHARA and GRAVITY/CIAO that the method is adaptable to non-conventional AO geometries (hexagonal grids, 60 actuators).

eess.SP↗

arXiv2024

Improving constraints on the extended mass distribution in the Galactic Center with stellar orbits

Studying the orbital motion of stars around Sagittarius A* in the Galactic Center provides a unique opportunity to probe the gravitational potential near the supermassive black hole at the heart of our Galaxy. Interferometric data obtained with the GRAVITY instrument at the Very Large Telescope Interferometer (VLTI) since 2016 has allowed us to achieve unprecedented precision in tracking the orbits of these stars. GRAVITY data have been key to detecting the in-plane, prograde Schwarzschild precession of the orbit of the star S2, as predicted by General Relativity. By combining astrometric and spectroscopic data from multiple stars, including S2, S29, S38, and S55 - for which we have data around their time of pericenter passage with GRAVITY - we can now strengthen the significance of this detection to an approximately $10 σ$ confidence level. The prograde precession of S2's orbit provides valuable insights into the potential presence of an extended mass distribution surrounding Sagittarius A*, which could consist of a dynamically relaxed stellar cusp comprised of old stars and stellar remnants, along with a possible dark matter spike. Our analysis, based on two plausible density profiles - a power-law and a Plummer profile - constrains the enclosed mass within the orbit of S2 to be consistent with zero, establishing an upper limit of approximately $1200 \, M_\odot$ with a $1 σ$ confidence level. This significantly improves our constraints on the mass distribution in the Galactic Center. Our upper limit is very close to the expected value from numerical simulations for a stellar cusp in the Galactic Center, leaving little room for a significant enhancement of dark matter density near Sagittarius A*.

astro-ph.GA↗

arXiv2024

Preserving Power Optimizations Across the High Level Synthesis of Distinct Application-Specific Circuits

We evaluate the use of software interpretation to push High Level Synthesis of application-specific accelerators toward a higher level of abstraction. Our methodology is supported by a formal power consumption model that computes the power consumption of accelerator components, accurately predicting the power consumption on new designs from prior optimization estimations. We demonstrate how our approach simplifies the re-use of power optimizations across distinct designs, by leveraging the higher level of design abstraction, using two accelerators representative of the robotics domain, implemented through the Bambu High Level Synthesis tool. Results support the research hypothesis, achieving predictions accurate within +/- 1%.

cs.PL↗

arXiv2024

Cyber Physical Games

We describe a formulation of multi-agents operating within a Cyber-Physical System, resulting in collaborative or adversarial games. We show that the non-determinism inherent in the communication medium between agents and the underlying physical environment gives rise to environment evolution that is a probabilistic function of agents' strategies. We name these emergent properties Cyber Physical Games and study its properties. We present an algorithmic model that determines the most likely system evolution, approximating Cyber Physical Games through Probabilistic Finite State Automata, and evaluate it on collaborative and adversarial versions of the Iterated Boolean Game, comparing theoretical results with simulated ones. Results support the validity of the proposed model, and suggest several required research directions to continue evolving our understanding of Cyber Physical System, as well as how to best design agents that must operate within such environments.

cs.DC↗