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In an accompanying publication, the MeerKAT Pulsar Timing Array (MPTA) collaboration reports tentative evidence for the presence of a stochastic gravitational-wave background, following observations of similar signals from the European and Indian Pulsar Timing Arrays, NANOGrav, the Parkes Pulsar Timing Array and the Chinese Pulsar Timing Array. If such a gravitational-wave background signal originates from a population of inspiraling supermassive black-hole binaries, the signal may be anisotropically distributed on the sky. In this Letter we evaluate the anisotropy of the MPTA signal using a spherical harmonic decomposition. We discuss complications arising from the covariance between pulsar pairs and regularisation of the Fisher matrix. Applying our method to the 4.5 yr dataset, we obtain two forms of sky maps for the three most sensitive MPTA frequency bins between 7 -21 nHz. Our "clean maps'' estimate the distribution of gravitational-wave strain power with minimal assumptions. Our radiometer maps answer the question: is there a statistically significant point source? We find a noteworthy hotspot in the 7 nHz clean map with a $p$-factor of $p=0.015$ (not including trial factors). Future observations are required to determine if this hotspot is of astrophysical origin.

Pulsar Timing Arrays search for nanohertz-frequency gravitational waves by regularly observing ensembles of millisecond pulsars over many years to look for correlated timing residuals. Recently the first evidence for a stochastic gravitational wave background has been presented by the major Arrays, with varying levels of significance ($\sim$2-4$\sigma$). In this paper we present the results of background searches with the MeerKAT Pulsar Timing Array. Although of limited duration (4.5 yr), the $\sim$ 250,000 arrival times with a median error of just $3 \mu$s on 83 pulsars make it very sensitive to spatial correlations. Detection of a gravitational wave background requires careful modelling of noise processes to ensure that any correlations represent a fit to the underlying background and not other misspecified processes. Under different assumptions about noise processes we can produce either what appear to be compelling Hellings-Downs correlations of high significance (3-3.4$\sigma$) with a spectrum close to that which is predicted, or surprisingly, under slightly different assumptions, ones that are insignificant. This appears to be related to the fact that many of the highest precision MeerKAT Pulsar Timing Array pulsars are in close proximity and dominate the detection statistics. The sky-averaged characteristic strain amplitude of the correlated signal in our most significant model is $h_{c, {\rm yr}} = 7.5^{+0.8}_{-0.9} \times 10^{-15}$ measured at a spectral index of $\alpha=-0.26$, decreasing to $h_{c, {\rm yr}} = 4.8^{+0.8}_{-0.9} \times 10^{-15}$ when assessed at the predicted $\alpha=-2/3$. These data will be valuable as the International Pulsar Timing Array project explores the significance of gravitational wave detections and their dependence on the assumed noise models.

Pulsar timing arrays are ensembles of regularly observed millisecond pulsars timed to high precision. Each pulsar in an array could be affected by a suite of noise processes, most of which are astrophysically motivated. Analysing them carefully can be used to understand these physical processes. However, the primary purpose of these experiments is to detect signals that are common to all pulsars, in particular signals associated with a stochastic gravitational wave background. To detect this, it is paramount to appropriately characterise other signals that may otherwise impact array sensitivity or cause a spurious detection. Here we describe the second data release and first detailed noise analysis of the pulsars in the MeerKAT Pulsar Timing Array, comprising high-cadence and high-precision observations of $83$ millisecond pulsars over $4.5$ years. We use this analysis to search for a common signal in the data, finding a process with an amplitude of $\log_{10}\mathrm{A_{CURN}} = -14.25^{+0.21}_{-0.36}$ and spectral index $\gamma_\mathrm{CURN} = 3.60^{+1.31}_{-0.89}$. Fixing the spectral index at the value predicted for a background produced by the inspiral of binary supermassive black holes, we measure the amplitude to be $\log_{10}\mathrm{A_{CURN}} = -14.28^{+0.21}_{-0.21}$ at a significance expressed as a Bayes factor of $\ln(\mathcal{B}) = 4.46$. Under both assumptions, the amplitude that we recover is larger than those reported by other PTA experiments. We use the results of this analysis to forecast our sensitivity to a gravitational wave background possessing the spectral properties of the common signal we have measured.

Convection in planets and stars is predicted to occur in the "ultimate regime'' of diffusivity-free, rapidly rotating turbulence, in which flows are characteristically unaffected by viscous and thermal diffusion. Boundary layer diffusion, however, has historically hindered experimental study of this regime. Here, we utilize the boundary-independent oscillatory thermal-inertial mode of rotating convection to realize the diffusivity-free scaling in liquid metal laboratory experiments. This oscillatory style of convection arises in rotating liquid metals (low Prandtl number fluids) and is driven by the temperature gradient in the fluid bulk, thus remaining independent of diffusive boundary dynamics. We triply verify the existence of the diffusivity-free regime via measurements of heat transfer efficiency $Nu$, dimensionless flow velocities $Re$, and internal temperature anomalies $\theta$, all of which are in quantitative agreement with planar asymptotically-reduced models. Achieving the theoretical diffusivity-free scalings in desktop-sized laboratory experiments provides the validation necessary to extrapolate and predict the convective flows in remote geophysical and astrophysical systems.

Social robots are required not only to understand human intentions but also to effectively communicate their intentions or own internal states to users. This study explores the use of sonification to provide explicit auditory feedback, enhancing mutual understanding in HRI. We introduce a novel sonification approach that conveys the robot's internal state, linked to its perception of nearby individuals and their interaction intentions. The approach is evaluated through a two-fold user study: an online video-based survey with $26$ participants and live experiments with $10$ participants. Results indicate that while sonification improves the robot's expressivity and communication effectiveness, the design of the auditory feedback needs refinement to enhance user experience. Participants found the auditory cues useful but described the sounds as uninteresting and unpleasant. These findings underscore the importance of carefully designed auditory feedback in developing more effective and engaging HRI systems.

We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domestic and frequent therapies. We build a supervised approach using information from the muscular activity of the forearm and the motion of the exoskeleton to reconstruct the hand's opening degree and compliance level. Such information can be used to evaluate the therapy progress and develop adaptive control behaviors. Our approach is validated with a real light exoskeleton. The experiments demonstrate good predictive performance of our approach when trained on data coming from a single user and tested on the same user, even across different sessions. This generalization capability makes our system promising for practical use in real rehabilitation.

Rotating turbulent convection occurs ubiquitously in natural convective systems encompassing planetary cores, oceans, and atmospheres, as well as in many industrial applications. While the global heat and mass transfer of water-like rotating Rayleigh-B\'enard convection is well-documented, the characteristics of rotating convection in liquid metals remain less well understood. In this study, we characterize rotating Rayleigh-B\'enard convection in liquid gallium (Prandtl number $Pr \approx 0.027$) within a slender cylinder (diameter-to-height aspect ratio $\Gamma = D/H = 1/2$) using novel thermovelocimetric diagnostic techniques that integrate simultaneous multi-point thermometry and ultrasonic Doppler velocity measurements. This approach experimentally reveals the formation of a stable azimuthal wavenumber $m = 2$ global-scale vortical structure at low supercriticality. We propose that enhanced wall modes facilitated by the slender cylinder geometry interact with the bulk flow to create these large-scale axialized vortices. Our findings extend results from the previous $Pr \sim 1$ studies across various cylindrical aspect ratios. In particular, we find evidence of a different scaling for wall mode precession frequency that possibly exists in liquid metal, offering new insights into the coupling effects in low-$Pr$ rotating convective turbulence., Comment: 10 main text + 4 appendix figures

We consider a service robot that offers chocolate treats to people passing in its proximity: it has the capability of predicting in advance a person's intention to interact, and to actuate an "offering" gesture, subtly extending the tray of chocolates towards a given target. We run the system for more than 5 hours across 3 days and two different crowded public locations; the system implements three possible behaviors that are randomly toggled every few minutes: passive (e.g. never performing the offering gesture); or active, triggered by either a naive distance-based rule, or a smart approach that relies on various behavioral cues of the user. We collect a real-world dataset that includes information on 1777 users with several spontaneous human-robot interactions and study the influence of robot actions on people's behavior. Our comprehensive analysis suggests that users are more prone to engage with the robot when it proactively starts the interaction. We release the dataset and provide insights to make our work reproducible for the community. Also, we report qualitative observations collected during the acquisition campaign and identify future challenges and research directions in the domain of social human-robot interaction.

Methodologies for combining the accuracy of data-driven models with extrapolability of physics-based models are described and tested, for the task of building transport models of tokamak fusion reactors that extrapolate well to new operational regimes. Information from multiple physics simulations (the ASTRA transport code with gyro-Bohm and TGLF estimates for turbulent diffusion) as well as multiple distinct experiments (DIII-D and AUG tokamaks) are considered. Applications of the methodology to the task of commissioning and controlling a new reactor such as ITER are discussed.

The eclipses seen in the radio emission of some pulsars can be invaluable to study the properties of the material from the companion stripped away by the pulsar. We present a study of six consecutive eclipses of PSR J0024-7204O in the globular cluster 47 Tucanae as seen by the MeerKAT radio telescope in the UHF (544-1088 MHz) band. A high scintillation state boosted the signal during one of the orbits and allowed a detailed study of the eclipse properties. We measure significant dispersion measure (DM) variations and detect strong scattering that seems to be the dominating mechanism of the eclipses at these frequencies. A complete drop in the linear polarization together with a small increase in the rotation measure suggests the presence of a magnetic field of $\sim 2$ mG. The study of multiple eclipses allowed us to measure difference in the lengths of the eclipses and DM differences of $\sim 0.01$ pc cm$^{-3}$ in consecutive orbits. One orbit in particular shows a delay in recovery of the linear polarization and a visible delay in the arrival of the pulses caused by a stronger scattering event. We suggest that these are caused by a higher variance of density fluctuations during the event., Comment: 14 pages, 8 figures, 9 tables. Accepted for publication on Monthly Notices of the Royal Astronomical Society

Millisecond pulsars are subject to accelerations in globular clusters (GCs) that manifest themselves in both the first and second spin period time derivatives, and can be used to explore the mass distribution of the potentials they inhabit. Here we report on over 20 yr of pulsar timing observations of five millisecond radio pulsars in the core of the core-collapse GC NGC 6752 with the Parkes (Murriyang) and MeerKAT radio telescopes, which have allowed us to measure the proper motions, positions, and first and second time derivatives of the pulsars. The pulsar timing parameters indicate that all the pulsars in the core experience accelerations and jerks that can be explained only if an amount of nonluminous mass of at least 2.56x10^3 M_SUN is present in the core of NGC 6752. On the other hand, our studies highly disfavor the presence of an intermediate-mass black hole at the center of the cluster, with a mass equal to or greater than ~3000M_SUN., Comment: Published in ApJ. Replaced with the final published version

Although tokamaks are one of the most promising devices for realizing nuclear fusion as an energy source, there are still key obstacles when it comes to understanding the dynamics of the plasma and controlling it. As such, it is crucial that high quality models are developed to assist in overcoming these obstacles. In this work, we take an entirely data driven approach to learn such a model. In particular, we use historical data from the DIII-D tokamak to train a deep recurrent network that is able to predict the full time evolution of plasma discharges (or "shots"). Following this, we investigate how different training and inference procedures affect the quality and calibration of the shot predictions.

For a service robot, it is crucial to perceive as early as possible that an approaching person intends to interact: in this case, it can proactively enact friendly behaviors that lead to an improved user experience. We solve this perception task with a sequence-to-sequence classifier of a potential user intention to interact, which can be trained in a self-supervised way. Our main contribution is a study of the benefit of features representing the person's gaze in this context. Extensive experiments on a novel dataset show that the inclusion of gaze cues significantly improves the classifier performance (AUROC increases from 84.5% to 91.2%); the distance at which an accurate classification can be achieved improves from 2.4 m to 3.2 m. We also quantify the system's ability to adapt to new environments without external supervision. Qualitative experiments show practical applications with a waiter robot.

We report the discovery of ten new pulsars in the globular cluster Terzan 5 as part of the Transients and Pulsars with MeerKAT (TRAPUM) Large Survey Project. We observed Terzan 5 at L-band (856--1712 MHz) with the MeerKAT radio telescope for four hours on two epochs, and performed acceleration searches of 45 out of 288 tied-array beams covering the core of the cluster. We obtained phase-connected timing solutions for nine discoveries, covering nearly two decades of archival observations from the Green Bank Telescope for all but one. Highlights include PSR J1748$-$2446ao which is an eccentric ($e = 0.32$) wide-orbit (orbital period $P_{\rm b} = 57.55$ d) system. We were able to measure the rate of advance of periastron ($\dot{\omega}$) for this system allowing us to determine a total mass of $3.17 \pm \, 0.02\, \rm M_{\odot}$. With a minimum companion mass ($M_{\rm c}$) of $\sim 0.8\, \rm M_{\odot}$, PSR J1748$-$2446ao is a candidate double neutron star (DNS) system. If confirmed to be a DNS, it would be the fastest spinning pulsar ($P = 2.27$ ms) and the longest orbital period measured for any known DNS system. PSR J1748$-$2446ap has the second highest eccentricity for any recycled pulsar ($e \sim 0.905$) and for this system we can measure the total mass ($1.997 \pm 0.006\, \rm M_{\odot}$) and also estimate the individual pulsar and companion masses. PSR J1748$-$2446ar is an eclipsing redback (minimum $M_{\rm c} \sim 0.34\, \rm M_{\odot}$) system whose properties confirm it to be the counterpart to a previously published source identified in radio and X-ray imaging. With these discoveries, the total number of confirmed pulsars in Terzan 5 is 49, the highest for any globular cluster so far. These discoveries further enhance the rich set of pulsars known in Terzan 5 and provide scope for a deeper understanding of binary stellar evolution, cluster dynamics and ensemble population studies., Comment: 23 pages, 11 figures, 5 tables, published in A&A

Using MeerKAT, we have discovered three new millisecond pulsars (MSPs) in the bulge globular cluster M62: M62H, M62I, and M62J. All three are in binary systems, which means all ten known pulsars in the cluster are in binaries. M62H has a planetary-mass companion with a median mass $M_{\rm c,med} \sim 3$ M$_{\rm J}$ and a mean density of $\rho \sim 11$ g cm$^{-3}$. M62I has an orbital period of 0.51 days and a $M_{\rm c,med} \sim 0.15$ M$_{\odot}$. Neither of these low-mass systems exhibit eclipses. M62J has only been detected in the two UHF band (816 MHz) observations with a flux density $S_{816} = 0.08$ mJy. The non-detection in the L-band (1284 MHz) indicates it has a relatively steep spectrum ($\beta < -3.1$). We also present 23-yr-long timing solutions obtained using data from the Parkes "Murriyang", Effelsberg and MeerKAT telescopes for the six previously known pulsars. For all these pulsars, we measured the second spin-period derivatives and the rate of change of orbital period caused by the gravitational field of the cluster, and their proper motions. From these measurements, we conclude that the pulsars' maximum accelerations are consistent with the maximum cluster acceleration assuming a core-collapsed mass distribution. Studies of the eclipses of the redback M62B and the black widow M62E at four and two different frequency bands, respectively, reveal a frequency dependence with longer and asymmetric eclipses at lower frequencies. The presence of only binary MSPs in this cluster challenges models which suggest that the MSP population of core-collapsed clusters should be dominated by isolated MSPs., Comment: 22 pages, 8 figures, 6 tables. Accepted for publication in MNRAS

Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constraint greatly inhibits the range of applications that can leverage quantum computers. Moreover, as the available qubits increase, the computational complexity grows exponentially, posing additional challenges. Consequently, there is an urgent need to use qubits efficiently and mitigate both present limitations and future complexities. To address this, existing quantum applications attempt to integrate classical and quantum systems in a hybrid framework. In this study, we concentrate on quantum deep learning and introduce a collaborative classical-quantum architecture called co-TenQu. The classical component employs a tensor network for compression and feature extraction, enabling higher-dimensional data to be encoded onto logical quantum circuits with limited qubits. On the quantum side, we propose a quantum-state-fidelity-based evaluation function to iteratively train the network through a feedback loop between the two sides. co-TenQu has been implemented and evaluated with both simulators and the IBM-Q platform. Compared to state-of-the-art approaches, co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting. Additionally, it outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits., Comment: IEEE Transactions on Quantum Engineering

B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and Sars-CoV-2 infections. We show that different lineages converge to the same responding CDR3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.

Autonomous drone racing competitions are a proxy to improve unmanned aerial vehicles' perception, planning, and control skills. The recent emergence of autonomous nano-sized drone racing imposes new challenges, as their ~10cm form factor heavily restricts the resources available onboard, including memory, computation, and sensors. This paper describes the methodology and technical implementation of the system winning the first autonomous nano-drone racing international competition: the IMAV 2022 Nanocopter AI Challenge. We developed a fully onboard deep learning approach for visual navigation trained only on simulation images to achieve this goal. Our approach includes a convolutional neural network for obstacle avoidance, a sim-to-real dataset collection procedure, and a navigation policy that we selected, characterized, and adapted through simulation and actual in-field experiments. Our system ranked 1st among seven competing teams at the competition. In our best attempt, we scored 115m of traveled distance in the allotted 5-minute flight, never crashing while dodging static and dynamic obstacles. Sharing our knowledge with the research community, we aim to provide a solid groundwork to foster future development in this field., Comment: 8 pages, 10 Figures, 3 Tables, This paper has been accepted for publication in the IEEE Robotics and Automation Letters (RAL). Copyright 2023 IEEE

Rotating convective turbulence is ubiquitously found across geophysical settings, such as surface and subsurface oceans, planetary atmospheres, molten metal planetary cores, magma chambers, and magma oceans. Depending on the thermal and material properties of the system, buoyant convection can be driven thermally or compositionally, where a Prandtl number ($Pr = \nu / \kappa_i$) defines the characteristic diffusion properties of the system, with $\kappa_i = \kappa_T$ representing thermal diffusion and $\kappa_i = \kappa_C$ representing chemical diffusion. These numbers vary widely for geophysical systems; for example, the liquid iron undergoing thermal-compositional convection in Earth's core is defined by $Pr_T \approx 0.1$ and $Pr_C \approx 100$, while a thermally-driven liquid silicate magma ocean is defined by $Pr_T \approx 100$. Currently, most numerical and laboratory data for rotating convective flows exists at $Pr = O(1)$; high $Pr$ rotating convection relevant to compositionally-driven core flow and other systems is less commonly studied. Here, we address this deficit by carrying out a broad suite of rotating convection experiments made over a range of $Pr$ values, employing water and three different silicone oils as our working fluids ($Pr = $ 6, 41, 206, and 993). Using measurements of flow velocities (Reynolds, $Re$) and heat transfer efficiency (Nusselt, $Nu$), a baroclinic torque balance is found to describe the turbulence regardless of Prandtl number so long as $Re$ is sufficiently large ($Re \gtrsim 10$). Estimated turbulent scales are found to remain close to onset scales in all experiments, a result that may extrapolate to planetary settings. Lastly, we use our data to build $Pr$-dependent predictive nondimensional and dimensional scaling relations for rotating convective velocities that can be applied across a broad range of geophysical fluid dynamical settings.

We present the results of observations aimed at discovering and studying pulsars in the core-collapsed globular cluster (GC) NGC 6522 performed by the MeerTIME and TRAPUM Large Survey Project with the MeerKAT telescope. We have discovered two new isolated pulsars bringing the total number of known pulsars in the cluster to six. PSR J1803$-$3002E is a mildly recycled pulsar with spin period of 17.9 ms while pulsar PSR J1803$-$3002F is a slow pulsar with spin period of 148.1 ms. The presence of isolated and slow pulsars is expected in NGC 6522 and confirms the predictions of previous theories for clusters at this stage in evolution. We further present a tentative timing solution for the millisecond pulsar (MSP) PSR J1803$-$3002C combining older observations taken with the Parkes 64m radio telescope, Murriyang. This solution implies a relatively small characteristic age of the pulsar in contrast with the old age of the GC. The presence of a slow pulsar and an apparently young MSP, both rare in GCs, suggests that their formation might be linked to the evolutionary stage of the cluster., Comment: 8 pages, 5 figues, 3 tables. Accepted for publication in Astronomy and Astrophysics