The detection of exoplanets using astrometry has long been an area of interest, but is fraught with challenges. The Gaia mission is fundamentally reshaping this field thanks to its unprecedentedly precise all-sky astrometric observations. The 2022 release of Gaia DR3 brought the first exoplanets discovered from the Gaia astrometry, including a new candidate around the bright ($V=6.6$) solar-type star HD 12800. However, two years after announcement, the Gaia exoplanet candidate was retracted. In this work we report radial velocity observations of HD 12800 acquired with the TRES spectrograph, which we began immediately after the release of Gaia DR3. Our observations failed to detect the planet candidate; nonetheless, we emphasise that the originally proposed companion would have been easily detected in our radial velocity observations. We conclude with a discussion on the role of intermediate-precision ($\approx$10 m s$^{-1}$) RV spectrographs in the follow-up of Gaia astrometric exoplanet candidates, relevant to the forthcoming release of Gaia DR4. We argue that such observations may play an important role in planet confirmation for stars between approximately $8<G<12$, likely to represent a significant fraction of Gaia exoplanet discoveries.

We investigate weak mixing for some classes of interval translation mappings. We give two distinct proofs that a typical Bruin-Troubetzkoy interval translation mapping is weakly mixing. Moreover, we show that the second approach extends to other classes of interval translation mappings. In particular, we show that Bruin interval translation mappings on any number of intervals are typically weak mixing. Finally, we construct the first examples of non weak mixing Bruin-Troubetzkoy ITM of infinite type.

Despite significant advances in responsible AI research, industry adoption remains limited, leaving many HCI contributions underutilized in practice. This position paper argues that current research often fails to account for the fundamental need for capitalist enterprises to create value. To achieve immediate real-world impact, responsible AI research must explore how to design responsibly within capitalism. We call for a move beyond the dichotomy of "ethics vs. business" toward a more productive framing of "ethics and business." We propose ideation as a practical design strategy for generating ethically preferable alternatives that also meet business objectives. By aligning ethics with enterprise realities, we expand the space of responsible design that can actually be built.

Debugging consumes a substantial portion of the software development lifecycle, yet the effectiveness of Large Language Models(LLMs) in this task is not well understood. Competitive programming offers a rich benchmark for such evaluation, given its diverse problem domains and strict efficiency requirements. We present an empirical study of LLM-based debugging on competitive programming problems and introduce DePro, a test-case driven approach that assists programmers by correcting existing code rather than generating new solutions. DePro combines brute-force reference generation, stress testing, and iterative LLM-guided refinement to identify and resolve errors efficiently.Experiments on 13 faulty user submissions from Codeforces demonstrate that DePro consistently produces correct solutions, reducing debugging attempts by up to 64% and debugging time by an average of 7.6 minutes per problem compared to human programmers and zero-shot LLM debugging.

The first measurement of the elliptic flow coefficient of (anti)${}^3_Λ$H and the study of the $v_2$ of $^3\overline{\mathrm{He}}$ measured in Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 5.36$ TeV with the ALICE detector are presented. Based on the large data sample of approximately five billion events collected in 2023 during the LHC Run 3 data taking, these measurements provide important insights into the production mechanism of (anti)(hyper)nuclei, as well as into the phase-space distributions of nucleons and hyperons produced in heavy-ion collisions. The results are discussed in the context of hydrodynamic and coalescence models, highlighting how the measurement of the elliptic flow of nuclei, such as helium and hypertriton, provides critical constraints on hadronization models.

A finite element solution coupled with an interior penalty discontinuous Galerkin solution are defined for the approximation of the coupled 3D-1D solute transport problem. Under sufficient regularity for the weak solutions, optimal error bounds are derived for the 3D concentration and 1D concentration, that are optimal with respect to the time step size and the mesh sizes. Numerical results verify the theoretical results.

Nonlinear phononics provides a powerful ultrafast route to control lattice excitations, enabling access to hidden quantum orders, phononic computing, and quantum transduction. However, dynamic control of anharmonic phonon interactions remains limited, as these interactions are typically fixed by the equilibrium crystal lattice and lack external tunability. Emergent ferrons in ferroelectrics, which are collective oscillations of the spontaneous electric polarization, may offer a promising platform to overcome this limitation by combining intrinsic phononic nonlinearity with direct electrical control of the ferroelectric order parameter. Here we report electrically controllable nonlinear ferron upconversion in the van der Waals ferroelectric NbOI2. We show that resonant THz excitation of a 3.1 THz ferron drives coherent upconversion to a 7.0 THz optical phonon. Using two-dimensional THz spectroscopy, we directly resolve off-diagonal coupling features and establish the nonlinear upconversion pathway. Supported by first-principles calculations and analytical modeling, we identify the microscopic origin as a cubic anharmonic lattice coupling. Importantly, in situ electric-field switching enables nonvolatile control of both the ferron dynamics and the associated upconversion process. The phase reversal and hysteretic behavior across the coercive fields establish that the ferron-mediated nonlinear phononic interaction is strongly dependent on the underlying ferroelectric order parameter. These results introduce ferron upconversion as a new and universal regime of nonlinear phononics in ferroelectrics and establish an electrically programmable platform for coherent lattice control, paving the way for ferronic information processing and quantum phononic transduction.

Given a divisor on a tropical curve, we associate to each point of the curve a Weierstrass gap sequence. We investigate structural properties of these gap sequences and explore their relationship with the Weierstrass gap sequences of line bundles on algebraic curves via the tropicalization process.

It is shown that for any finite positive measure $μ$ defined on a measure space $(S, Σ)$, and any Banach or Fréchet space $Z$, the control measure Theorem of Talagrand (T) is true for the case when the (stochastic) vector measure $\boldsymbol{m}:\mathcal{E} \to L_0(μ,Z)$, defined on another measurable space $(E, \mathcal{E})$, takes values in $L_{0}(μ,Z)$, the Bochner space of vector-valued functions associated to $μ$ and $Z$. As a consequence, we also obtain a Rybakov type result for this control. Finally, we give the relation of this result to bounded multiplier properties (BMP) of $F$-spaces and pose various open problems related to it.

This paper evaluates the effect of a short, interactive popularisation talk on upper-secondary students' interest in Economics. This contrasts with previous research, which has primarily examined impersonal interventions to boost interest in Economics. The intervention presents Economics as an empirical social science engaged with real-world social problems. Using a cluster-randomised field experiment conducted during secondary-school campus visits in Spain, we find no statistically significant average effect on stated interest in studying Economics. However, the intervention generates substantial heterogeneity: those with stronger altruistic preferences become significantly more likely to express interest after the talk. These findings suggest that informational outreach may shape who perceives the discipline as aligned with their motivations, even if it does not substantially increase overall interest. More broadly, they indicate that presenting Economics as empirical and socially relevant may broaden the profile of those who consider the field.

Bounding the correlations predicted by quantum theory is an important challenge in quantum information science. Today's leading approach is semidefinite programming relaxations, but existing methods still cannot account for many relevant types of constraints. Here, we propose a semidefinite relaxation methodology that can incorporate a breadth of constraints needed in various quantum correlation problems, thereby generalising the seminal Navascués-Pironio-Acín hierarchy. It yields useful results at reasonable computational cost. We showcase the methodology and its features by using it to address five different quantum information problems. These are (i) entanglement witnessing from imperfect measurement devices, (ii) certifying measurements from fidelity-constrained sources, (iii) computing dimensionality in genuine multi-particle entangled states, (iv) benchmarking dimensionality for state preparation devices, and (v) finding uncertainty relations for nearly anti-commuting observables. These applications reflect both the usefulness and versatility of the methodology, as well as its potential for broader relevance in the field.

The first measurements of the average transverse-momentum fraction ($\langle z \rangle$) as a function of transverse momentum ($p_{\rm T}$) for strange baryons ($Λ$ and $\barΛ$) and strange mesons ($K_{\rm S}^0$), produced in mini-jets defined through angular correlations in pp collisions at $\sqrt{s} = 13$ TeV, are reported by the ALICE Collaboration at the LHC. The observable is obtained using a novel method, where the angular correlation between the strange hadrons and inclusive charged hadrons is weighted by the $p_{\rm T}$ of correlated particles at small angular distance. As a function of strange particles' $p_{\rm T}$, the results reveal a flat trend for strange mesons and a decreasing trend for strange baryons in the measured $p_{\rm T}$ region, indicating distinct hadronization mechanisms for $K_{\rm S}^0$ and $Λ$($\barΛ$). The measurements are compared to Monte Carlo models, namely PYTHIA~8 (with both Monash and Color Rope tunes) and the AMPT (A Multi-Phase Transport) model with string melting. None of these models provides a satisfactory description of the $\langle z \rangle$ distributions at low and intermediate $p_{\rm T}$.

We present a model for gas heating, driven by dynamical friction from orbiting subhalos within dark matter halos. Using data from the TNG50 simulation, we derive the subhalo mass function and calculate the dynamical friction heating rate for a wide range of halo masses and redshifts from $z = 15$ to 0. Our results show that, by converting gravitational potential energy into thermal energy, dynamical friction is an important mechanism for galaxy quenching in massive halos at low redshifts, consistent with previous studies. Additionally, we find that in the early universe at $z \sim 15$, heating rates can be comparable to the molecular hydrogen cooling rates in metal-free minihalos. This can suppress gas cooling and fragmentation and does increase the critical molecular fraction for Pop III star formation by up to one order of magnitude, thereby making Pop III star formation more difficult. In combination with the Lyman-Werner background, the dynamical friction heating mechanism favors the formation of direct-collapse black hole (DCBH) seeds in atomic cooling halos, even when the average H$_2$ fraction is $\sim 10^{-5}$ during the minihalo progenitor phase. Dynamical friction heating at a fixed host halo mass can vary by two orders of magnitude due to the scatter in the number of subhalos. To capture dynamical friction heating in simulations, it is necessary to resolve subhalos with a subhalo to host halo mass ratio $ψ\gtrsim 0.05$.

We study adaptive network models in which coupling weights evolve on a fast time scale relative to the phase dynamics of the nodes. Using Geometric Singular Perturbation Theory (GSPT), we prove that, although the microscopic system is strictly pairwise, the effective slow dynamics on the invariant slow manifold can exhibit genuinely higher-order structure. More precisely, Fenichel reduction produces explicit $O(\varepsilon)$ triplet terms in the reduced phase dynamics. In addition, we give a rigorous criterion ensuring that these terms are irreducible, in the sense that the reduced vector field does not admit a pairwise decomposition in node coordinates. We derive the first-order slow-manifold correction explicitly, formulate the irreducibility criterion via mixed second derivatives, and verify it for the adaptive Kuramoto phase oscillator model. The results show that the class of pairwise-coupled fast--slow adaptive network systems is not closed under slow-manifold reduction.

This study quantifies survivorship bias in India's NIFTY Smallcap 250 index using a dataset of 1,437 stocks over nine years (2016-2025). By reconstructing historical index composition through market capitalization ranking and comparing equal-weight portfolios of current constituents versus all historical members, I show that survivor-only backtesting overstates annual returns by 4.94 percentage points (23.3%) and Sharpe ratios by 0.097 (9.1%). The analysis reveals an 82.5% turnover rate, including delisted (16.1%), graduated (33.1%), and demoted stocks (33.2%), with all categories contributing to bias. Using bhavcopy data that includes delisted securities, the reconstruction achieves 100% accuracy for current constituents and an estimated 85-90% accuracy historically. These findings highlight that survivorship bias is materially larger in emerging market small-caps and that using only current index members can significantly overstate strategy performance. Briefly, the methodology reconstructs historical index membership using a price-volume-based ranking approach to enable survivor-free backtesting.

Altermagnets (AMs) exhibit vanishing net magnetization but strong momentum-dependent spin splitting enforced by crystal symmetry. Here, we explore the non-Hermitian effects in dissipative two-dimensional AMs. We show that symmetry-compliant dissipation naturally induces an imaginary staggered exchange field, driving a NH topological phase transition absent in conventional antiferromagnets. In the topologically nontrivial phase, hybrid skin-topological modes driven by altermagnetic d-wave anisotropy emerge, as captured by the chiral skin effect framework. In the gapless phase, we elucidate the creation and annihilation dynamics of exceptional points. Crucially, we analytically prove via the transfer matrix method that corner states are deterministically controlled by the boundary sublattice termination. Owing to the symmetry constraints and the robustness of chiral states, these findings hold universally across all topological AMs. A general framework is established for controlling topological corner states, offering a new strategy for designing magnetic materials with tailored non-Hermitian properties.

We perform forecasts for the Hubble parameter H_0 and for the parameter Xi_0 that describes modified gravitational-wave propagation, using information from the binary neutron star (BNS) mass function, for Einstein Telescope (ET), taken either in the triangle or in the ``2L'' configuration, as well as for detector network made by ET together with a 40-km Cosmic Explorer (CE). We restrict ourselves to BNSs with a large signal-to-noise ratio, SNR>50, which still give O(10^3) events yr-1, and we perform a full joint cosmology-population Bayesian inference. We find that, for ET in isolation, the two ET configurations perform comparably, yielding uncertainties of 12% and 11% on H_0 for the triangular and 2L designs, respectively, and 18% uncertainty on Xi_0 in both cases. For networks including ET and CE, we can constrain H_0 and Xi_0 to precisions of 9% and 6%, respectively. These results should be taken as a very conservative estimate of third-generation detectors' capabilities as a consequence of the high SNR cut. We project the constraints on the Lambda CDM expansion history and find that ET alone (triangular and 2L configurations) achieves its best precision on H(z) at z=0.23 and z=0.28, yielding a 10% and 6% precision, respectively. When CE is added to the network, the precision improves to 4% and 3% at z=0.37 and z=0.38, respectively.

Let $X$ be a Riemann surface equipped with an anti-holomorphic involution $σ_X$. We show that this induces a natural anti-holomorphic involution on the space of parabolic $\mathrm{SL}(r,\mathbb{C})$-opers. The fixed-point locus of this involution is defined as real slice. We further study the induced involutions on different descriptions of parabolic $\mathrm{SL}(r,\mathbb{C})$-opers, in particular differential operators, and prove that these involutions coincide.

This paper presents the first measurements of $Ξ$ and $Ω$ hyperon yields at the highest multiplicities reached in pp collisions at $\sqrt{s} = 13$ TeV. This measurement exploits the high-multiplicity pp collisions collected by ALICE with dedicated triggers. The selected collisions are characterised by about 30 charged particles per unit of rapidity, over four times more than in minimum-bias pp collisions at the same centre-of-mass energy, and about twice as many as in minimum-bias p-Pb or very peripheral Pb-Pb collisions at similar energies. The production yields and average transverse momenta of the hyperons agree with trends indicated by previous measurements in pp collisions at lower multiplicities. The difference in average transverse momenta between pp and p-Pb collisions, observed with the new high-multiplicity pp data, provides additional insight into the underlying particle production mechanisms in small systems. The results support a strong correlation between multi-strange hadron production and final-state multiplicity regardless of the collision system at the LHC energies, extending this observation to the highest multiplicity reached in pp collisions. The comparison with several state-of-the-art models (Pythia8.2 with the Monash 2013 tune, Pythia8.2 with Ropes, and EPOS4) suggests that the description of strange-hadron production is improved by recently introduced features such as interactions between overlapping strings in Pythia8.2 with Ropes and the collective expansion of high-density string regions in EPOS4.

Spatiotemporally correlated errors are widespread in quantum devices and are particularly adversarial to error correcting schemes. To characterize these errors, we propose and validate a nonparametric quantum noise spectroscopy (QNS) protocol to estimate both spectra and static errors associated with spatiotemporally correlated dephasing noise and fluctuating quantum crosstalk on two qubits. Our scheme reconstructs the real and imaginary components of the two-qubit cross-spectrum by using fixed total time pulse sequences and single qubit and joint two-qubit measurements to separately resolve spatially correlated noise processes. We benchmark our protocol by reconstructing the spectra of spatiotemporally correlated noise processes engineered via the Schrödinger Wave Autoregressive Moving Average technique, emulating dephasing errors. Furthermore, we show that the protocol can outperform existing comb-based QNS protocols. Our results demonstrate the utility of our protocol in characterizing spatiotemporally correlated noise and quantum crosstalk in a multi-qubit device for potential use in noise-adapted control or error protection schemes.

In-body communication is an upcoming field with significant implications for medical diagnostics and therapeutic interventions. Microbubbles have gained attention due to their distinct physical properties, making them promising candidates to facilitate communication within the human body. This work explores the use of microbubbles as communication carriers, with a particular focus on their detection and the application of a modulation scheme. Through experimental analysis the feasibility and effectiveness of microbubble-based communication is tested. Filtering and peak detection methods are applied to accurately identify the presence of microbubbles despite noise, demonstrating the feasibility of microbubble-based communication systems for future biomedical applications. The results offer insights into signal integrity, noise challenges, and the optimization of detection algorithms, providing a foundation for future advancements in this field.

This letter reports on the first evidence of Higgs-boson production at high transverse momentum in the $b\bar{b}$ final state, reconstructed in a single large-radius jet. The results are based on proton proton collision data recorded by the ATLAS detector at the Large Hadron Collider at a centre-of-mass energies of 13 TeV and 13.6 TeV, corresponding to a total integrated luminosity of 301 fb$^{-1}$. The study profits from the large background suppression provided by the use of a new transformer-based algorithm for jet identification and the sharper mass and transverse momentum, $p_{\text{T}}$, resolution from a dedicated regression model. The yield relative to the Standard Model prediction, for Higgs bosons produced at $p_{\text{T}}$ larger than 450 GeV is measured to be $1.53\pm 0.27\text{(stat.)}\ ^{+0.33}_{-0.27}\text{(syst.)}\pm 0.17\text{(theo.)}$ corresponding to an observed (expected) significance of $3.8σ(2.5σ)$ relative to the background-only hypothesis. Results are also obtained in three Higgs boson $p_{\text{T}}$ intervals and found to be compatible with Standard Model predictions.

In patients with biochemical recurrence of prostate cancer and negative PSMA PET/CT, radiomics features extracted from recurrence-prone organs can predict clinical progression and progression-free survival. In a cohort of 132 patients, combining PET/CT radiomics with clinical variables significantly improved prognostic performance (C-index 0.74 vs. 0.65). Model performance was influenced by reader diagnostic certainty and remained robust on external validation. These findings suggest that radiomics from visually negative scans capture subclinical disease and provide added value for risk stratification.

CONTEXT. One of the most difficult and unexplored regions of the Milky Way is the highly extincted in-plane central region within the Galactic coordinates $10^\circ \lesssim |\ell |\lesssim 30^\circ $, $|b|\lesssim 3^\circ $, where we have the long-bar and 3 kpc arm with intermediate-age stellar population, whose morphological properties are still unclear. AIMS. We aim to advance our knowledge of the morphology of these two components. METHODS. We examined star counts of bright M giants in WISE-4.6$μ$m and its distribution of distances derived from spectroscopic parallaxes with APOGEE-DR17. We also examined the distribution of distances of young OGLE-O-rich Mira variable stars, and reviewed the literature on red clump distance determination within that area. RESULTS. We corroborate the asymmetry between positive and negative longitudes in in-plane regions, thus confirming the necessity to include a long bar. We obtain an average angle between the major axis of the long bar and the line Sun-Galactic centre of $α=27.4^\circ \pm 1.5^\circ $, aligned with the triaxial bulge and a semi-major-axis length $\approx 4$ kpc. The tips of the long bar are in contact with the elliptical 3 kpc arm, with the major axis again aligned with the bulge and the long bar's major axes, whose tangential lines of sight correspond to $\ell =-22^\circ $ and $\ell=+27^\circ $. In the range of 50 degrees in the sky between these two longitudes, the stellar near 3 kpc arm is clearly detected at heliocentric distances around 5 kpc, and the stellar far 3 kpc arm is tentatively detected at heliocentric distances of 9-12 kpc.

Electrostatic interactions fundamentally govern the structure, stability, and dynamics of charged (bio)matter, yet the impact of heterogeneous and anisotropic charge distributions on the behavior of protein solutions remains elusive. Here, we introduce a versatile multiscale framework that directly connects molecular-level electrostatics to collective properties via a colloid-inspired coarse-grained modeling combined with neural network-assisted optimization. Using monoclonal antibodies as model system, our inverse design approach identifies charge patterns capable of reliably reproducing experimental structure factors, osmotic compressibility and collective diffusion coefficients in a wide region of protein concentrations. Close inspection of our data further uncovers how specific physical features and spatial arrangements of localized charge patches significantly influence the solution structure. This transferable strategy provides a predictive pathway to decode and control charge-driven interactions in complex biomolecules and, more generally, in heterogeneously-charged soft matter systems, with immediate relevance to protein formulation and biomaterials engineering.

We show that stack-theoretic resolution of singularities preserving normal crossings (partial desingularization) by weighted blowings-up, can be obtained in a simple direct way from a splitting theorem of the first and third authors, using the algorithm of Abramovich, Temkin and Włodarczyk for resolution of singularities by weighted blowings-up.

We study a so-called semi-ergodic brickwork dual-unitary circuits where, in the infinite volume limit, the two-point correlation functions of single-site operators exhibit ergodic behavior along one light ray and non-ergodic behavior along the other light ray. Here, however, we study intermediate and long-time dynamics of a system in a finite, large volume. Under such dynamics, the Heisenberg evolution of a single traceless single-site operator lies within a restricted subspace, and this time evolution can be mapped to a simpler problem of a single qutrit scattering with a bunch of qubits sequentially. Despite the model being non-integrable and free from any quenched disorder, the operator entanglement grows at most logarithmic in time, contrary to prior expectations. The auto-correlation function can be written in terms of a sum of products of $SO(3)$ matrices, allowing for a random matrix prediction for the auto-correlation function at late times. The operator size distribution also becomes bimodal at certain times, displaying intermediate behavior between chaotic and free systems.

Self-interacting dark matter (SIDM) models feature short-range interactions between dark matter (DM) particles that lead to larger diversity in the inner parts of galactic rotation curves and potentially unique gravitational lensing signatures. Satellite galaxies and dark subhalos provide a valuable testing ground for such models. We develop a simulation framework to explore subhalo evolution and its gravothermal collapse for velocity- and angle-dependent self-interacting cross section in these SIDM models. Our results are essential for testing these models. We perform N-body simulations, treating the host halo analytically and modelling the scattering-induced subhalo-halo interaction process using virtual host particles, a central innovation of our work. We use the Eddington inversion method to accurately model the local velocity distribution in the halo. Our approach is significantly less computationally expensive than simulations with a fully resolved host, while incorporating tidal stripping and tidal heating. We test both isotropic and forward-dominated self-scattering, which represent limiting cases for the angular dependence of the self-interaction cross section. Environmental effects, especially the scattering-induced subhalo-halo interaction, have a strong impact on the subhalo evolution and drive a complex structural evolution. As a result, SIDM subhalos have a larger range of central densities and density profile slopes compared to collisionless DM. Our cost-efficient simulation framework enables modelling of SIDM subhalos in realistic environments. Our results highlight the necessity of accurately modelling the scattering-induced subhalo-halo interaction to predict SIDM subhalo density profiles. For the SIDM models we investigate, the enhanced diversity in the mass profiles of subhalos would leave an observable imprint on strong lensing systems and satellite galaxies.

We study a control architecture for nonlinear constrained systems that integrates a performance-boosting (PB) controller with a scheduled Predictive Safety Filter (PSF). The PSF acts as a pre-stabilizing base controller that enforces state and input constraints. The PB controller, parameterized as a causal operator, influences the PSF in two ways: it proposes a performance input to be filtered, and it provides a scheduling signal to adjust the filter's Lyapunov-decrease rate. We prove two main results: (i) Stability by design: any controller adhering to this parametrization maintains closed-loop stability of the pre-stabilized system and inherits PSF safety. (ii) Trajectory-set expansion: the architecture strictly expands the set of safe, stable trajectories achievable by controllers combined with conventional PSFs, which rely on a pre-defined Lyapunov decrease rate to ensure stability. This scheduling allows the PB controller to safely execute complex behaviors, such as transient detours, that are provably unattainable by standard PSF formulations. We demonstrate this expanded capability on a constrained inverted pendulum task with a moving obstacle.

We derive cosmological parameter constraints from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) galaxy clustering data, based on a joint full-shape analysis of the power spectrum multipoles and the bispectrum monopole using the ShapeFit framework. This is the follow-up of our previous work, in which we obtained for the first time constraints on the ShapeFit parameters using the bispectrum of DESI DR1. Here we present the first ShapeFit cosmological inference results using the bispectrum of DESI DR1. We recover values for the matter density parameter and Hubble constant of respectively $Ω_m=0.310\pm0.012$ and $H_0=[68.92\pm0.97]\,\mathrm{km\, s^{-1} Mpc^{-1}}$, consistent with previous results from the full DESI DR1 dataset that did not use the bispectrum signal. The inclusion of the bispectrum significantly tightens the constraints on the amplitude of fluctuations, reducing the error-bars in $\ln(A_s\times10^{10})$ by approximately 20\%, compared to using the power spectrum alone. We also explore extended cosmological models by performing fits for the evolving dark energy equation of state $w_0w_a$, and the sum of neutrino masses $\sum m_ν$. In these cases, we obtain constraints slightly larger than the ones from previous works from the DESI collaboration, due to not combining the full-shape results with other probes in all tracers. We find no strong evidence of deviations from standard $Λ$CDM, with the dark energy equation-of-state remaining within 2$σ$ from a cosmological constant $Λ$, and the neutrino mass being consistent with the normal hierarchy, $\sum m_ν<0.1\,[eV]$ at 95\% confidence limit. These constraints are broadly consistent with other DESI DR1 analyses, thus validating the robustness of the ShapeFit compression approach and the inclusion of the bispectrum for cosmological inference.