Search

Millicharge particles (mCPs) are viable dark matter candidates motivated by many standard model extensions. We show that despite of the tiny coupling with the photon, millicharged dark matters can convert efficiently to photons through annihilation processes in the Earth magnetic field background, which generates a monochromatic quasi static magnetic field signal with angular frequency being twice the millicharged particle mass. By recasting null results from the SuperMAG and the SNIPE Hunt collaborations, we constrain the effective charge of bosonic millicharged dark matter in the mass ranges $10^{-18}-3.5 \times 10^{-17}\,\text{eV}$ and $10^{-15}-10^{-14}\,\text{eV}$. Our bounds surpass current stellar cooling constraints by more than ten orders of magnitude, making this proposal a powerful tool to search for millicharged dark matter., Comment: 7 pages, 2 figures, + Supplemental Materials(5 pages, 2 figures)

The design (shape) of a robot is usually decided before the control is implemented. This might limit how well the design is adapted to a task, as the suitability of the design is given by how well the robot performs in the task, which requires both a design and a controller. The co-optimization or simultaneous optimization of the design and control of robots addresses this limitation by producing a design and control that are both adapted to the task. In this paper, we investigate some of the challenges inherent in the co-optimization of design and control. We show that retraining the controller of a robot with additional resources after the co-optimization process terminates significantly improves the robot's performance. In addition, we demonstrate that the resources allocated to training the controller for each design influence the design complexity, where simpler designs are associated with lower training budgets. The experimentation is conducted in four publicly available simulation environments for co-optimization of design and control, making the findings more applicable to the general case. The results presented in this paper hope to guide other practitioners in the co-optimization of design and control of robots.

We consider Thomson-like processes between dark matter dark photons and free electrons in the Milky Way. The result is a radio signal background that can be detectable with current or future radio telescope arrays. In particular, we computed sensitivity prospects for the Atacama Large Millimeter Array (ALMA) radio telescope and for the future Square Kilometer Array (SKA), concluding that unconstrained parameter space in a wide range of dark photon masses can be probed., Comment: 6 pages, 3 figures

Population-based evolutionary algorithms are often considered when approaching computationally expensive black-box optimization problems. They employ a selection mechanism to choose the best solutions from a given population after comparing their objective values, which are then used to generate the next population. This iterative process explores the solution space efficiently, leading to improved solutions over time. However, these algorithms require a large number of evaluations to provide a quality solution, which might be computationally expensive when the evaluation cost is high. In some cases, it is possible to replace the original objective function with a less accurate approximation of lower cost. This introduces a trade-off between the evaluation cost and its accuracy. In this paper, we propose a technique capable of choosing an appropriate approximate function cost during the execution of the optimization algorithm. The proposal finds the minimum evaluation cost at which the solutions are still properly ranked, and consequently, more evaluations can be computed in the same amount of time with minimal accuracy loss. An experimental section on four very different problems reveals that the proposed approach can reach the same objective value in less than half of the time in certain cases.

The axion is a hypothetical elementary particle that could solve the long-standing strong CP problem in particle physics and the dark matter mystery in the cosmos. Due to the stimulation of the ambient photons, the axion dark matter decay into photons is significantly enhanced so that its echo signal could be detected by terrestrial telescopes. As a pathfinder, we study the expected sensitivity of searching for the axion dark matter in the mass range between $0.41$ and $1.6\mu\text{eV}$ with the 21 CentiMeter Array (21CMA). We aim to cover the whole 21CMA frequency range in two years by using a 1MW emitter. We find that the resulting sensitivity on the axion-photon coupling could surpass other existing limits by about one order of magnitude., Comment: 7 pages, 6 figures

We consider the effects of a local axion dark matter background on the $g-2$ of the electron. We calculate loop corrections to the photon-electron vertex and determine analytical formulas for the spin and cyclotron frequencies when the electron is in an external magnetic field. By comparing with current measurements of these observables, we are able to place the strongest constraint on the axion-elecron coupling for axion masses below $3\times10^{-18}\text{eV}$., Comment: 6 pages, 2 figures

Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g. in robotics applications. Often when evaluating solution over a fixed time period it becomes clear that the objective value will not increase with additional computation time (for example when a two wheeled robot continuously spins on the spot). In such cases, it makes sense to stop the evaluation early to save computation time. However, most approaches to stop the evaluation are problem specific and need to be specifically designed for the task at hand. Therefore, we propose an early stopping method for direct policy search. The proposed method only looks at the objective value at each time step and requires no problem specific knowledge. We test the introduced stopping criterion in five direct policy search environments drawn from games, robotics and classic control domains, and show that it can save up to 75% of the computation time. We also compare it with problem specific stopping criteria and show that it performs comparably, while being more generally applicable.

Earth can act as a transducer to convert ultralight bosonic dark matter (axions and hidden photons) into an oscillating magnetic field with a characteristic pattern across its surface. Here we describe the first results of a dedicated experiment, the Search for Non-Interacting Particles Experimental Hunt (SNIPE Hunt), that aims to detect such dark-matter-induced magnetic-field patterns by performing correlated measurements with a network of magnetometers in relatively quiet magnetic environments (in the wilderness far from human-generated magnetic noise). Our experiment constrains parameter space describing hidden-photon and axion dark matter with Compton frequencies in the 0.5-5.0 Hz range. Limits on the kinetic-mixing parameter for hidden-photon dark matter represent the best experimental bounds to date in this frequency range., Comment: 22 pages, 12 figures. Accepted for publication in PRD. Minor changes in text and updated / improved limits

An experimental comparison of two or more optimization algorithms requires the same computational resources to be assigned to each algorithm. When a maximum runtime is set as the stopping criterion, all algorithms need to be executed in the same machine if they are to use the same resources. Unfortunately, the implementation code of the algorithms is not always available, which means that running the algorithms to be compared in the same machine is not always possible. And even if they are available, some optimization algorithms might be costly to run, such as training large neural-networks in the cloud. In this paper, we consider the following problem: how do we compare the performance of a new optimization algorithm B with a known algorithm A in the literature if we only have the results (the objective values) and the runtime in each instance of algorithm A? Particularly, we present a methodology that enables a statistical analysis of the performance of algorithms executed in different machines. The proposed methodology has two parts. First, we propose a model that, given the runtime of an algorithm in a machine, estimates the runtime of the same algorithm in another machine. This model can be adjusted so that the probability of estimating a runtime longer than what it should be is arbitrarily low. Second, we introduce an adaptation of the one-sided sign test that uses a modified p-value and takes into account that probability. Such adaptation avoids increasing the probability of type I error associated with executing algorithms A and B in different machines.

The axion dark matter echo technique, proposed in Ref. [1], aims to search for axion dark matter by detecting the electromagnetic echo coming from stimulated decay of ambient axion dark matter interacting with a radio-microwave outgoing beam. In this work we consider deviations from the standard halo model (SHM) in the form of fine grained streams that are present in the solar system and use them as a target for the axion echo method, which demonstrates to be very sensitive to particular local axion dark matter phase space distributions. We show that the extremely small dispersion of the streams works in favor of the echo method performance, improving its sensitivity in the axion-photon coupling up to two orders of magnitude, with respect to the isotropic SHM. We also discuss the possibility of targeting high density dark matter hairs formed when fine grained streams focus by the inner Earth's gravitational field., Comment: 9 pages, 4 figures. Any critical feedback the next two weeks is welcomed

Non-deterministic measurements are common in real-world scenarios: the performance of a stochastic optimization algorithm or the total reward of a reinforcement learning agent in a chaotic environment are just two examples in which unpredictable outcomes are common. These measures can be modeled as random variables and compared among each other via their expected values or more sophisticated tools such as null hypothesis statistical tests. In this paper, we propose an alternative framework to visually compare two samples according to their estimated cumulative distribution functions. First, we introduce a dominance measure for two random variables that quantifies the proportion in which the cumulative distribution function of one of the random variables stochastically dominates the other one. Then, we present a graphical method that decomposes in quantiles i) the proposed dominance measure and ii) the probability that one of the random variables takes lower values than the other. With illustrative purposes, we re-evaluate the experimentation of an already published work with the proposed methodology and we show that additional conclusions (missed by the rest of the methods) can be inferred. Additionally, the software package RVCompare was created as a convenient way of applying and experimenting with the proposed framework.

The existence of hidden sectors weakly coupled to the visible one has been extensively studied as a way to extend the Standard Model (SM) and to provide a good dark matter candidate. In this work we analyze two models in which gauge and scalar hidden fields interact with the visible sector which, for simplicity we take as an Abelian Higgs model. In one of them, the hidden sector consists of an uncharged scalar. The connection with the visible Abelian Higgs sector is in this case provided by the interaction between the scalars in the two sectors and also by the coupling between the hidden scalar and the visible squared field strength. This model can be seen as an extension of previously studied ones both in high energy and in condensed matter physics and the solutions that we find indicate that it could be relevant in connection to establishing the dark matter relic density. In the second model, both sectors correspond to spontaneously broken gauge theories and hence they feature classical vortex solutions. Introducing three different portals between the two sectors, we analyze the dependence of the model dynamics on the portal parameters and discuss the physical implications in connection with dark matter and gravitational radiation issues., Comment: Matches the final version published in Int.J.Mod.Phys.A 37 (2022)

We demonstrate that ultralight axion dark matter with a coupling to photons induces an oscillating global terrestrial magnetic field signal in the presence of the background geomagnetic field of the Earth. This signal is similar in structure to that of dark-photon dark matter that was recently pointed out and searched for in [arXiv:2106.00022] and [arXiv:2108.08852]. It has a global vectorial pattern fixed by the Earth's geomagnetic field, is temporally coherent on long time scales, and has a frequency set by the axion mass $m_a$. In this work, we both compute the detailed signal pattern, and undertake a search for this signal in magnetometer network data maintained by the SuperMAG Collaboration. Our analysis identifies no strong evidence for an axion dark-matter signal in the axion mass range $2\times10^{-18}\text{eV} \lesssim m_a \lesssim 7\times10^{-17}\text{eV}$. Assuming the axion is all of the dark matter, we place constraints on the axion-photon coupling $g_{a\gamma}$ in the same mass range; at their strongest, for masses $3\times 10^{-17}\text{eV} \lesssim m_a \lesssim 4\times 10^{-17}\text{eV}$, these constraints are comparable to those obtained by the CAST helioscope., Comment: 24 pages, 1 figure. Published version

It was recently shown that a powerful beam of radio/microwave radiation sent out to space can produce detectable back-scattering via the stimulated decay of ambient axion dark matter. This echo is a faint and narrow signal centered at an angular frequency close to half the axion mass. In this article, we provide a detailed analytical and numerical analysis of this signal, considering the effects of the axion velocity distribution as well as the outgoing beam shape. In agreement with the original proposal, we find that the divergence of the outgoing beam does not affect the echo signal, which is only constrained by the axion velocity distribution. Moreover, our findings are relevant for the optimization of the experimental parameters in order to attain maximal signal to noise or minimal energy consumption., Comment: Matches published version

This work presents ReBeatICG, a real-time, low-complexity beat-to-beat impedance cardiography (ICG) delineation algorithm that allows hemodynamic parameters monitoring. The proposed procedure relies only on the ICG signal compared to most algorithms found in the literature that rely on synchronous electrocardiogram signal (ECG) recordings. ReBeatICG was designed with implementation on an ultra-low-power microcontroller (MCU) in mind. The detection accuracy of the developed algorithm is tested against points manually labeled by cardiologists. It achieves a detection Gmean accuracy of 94.9%, 98.6%, 90.3%, and 84.3% for the B, C, X, and O points, respectively. Furthermore, several hemodynamic parameters were calculated based on annotated characteristic points and compared with values generated from the cardiologists' annotations. ReBeatICG achieved mean error rates of 0.11ms, 9.72ms, 8.32ms, and 3.97% for HR, LVET, IVRT, and relative C-point amplitude, respectively.

A person's passage of time perception (POTP) is strongly linked to their mental state and stress response, and can therefore provide an easily quantifiable means of continuous mental health monitoring. In this work, we develop a custom experiment and Machine Learning (ML) models for predicting POTP from biomarkers acquired from wearable biosensors. We first confirm that individuals experience time passing slower than usual during fear or sadness (p = 0.046) and faster than usual during cognitive tasks (p = 2 x 10^-5). Then, we group together the experimental segments associated with fast, slow, and normal POTP, and train a ML model to classify between these states based on a person's biomarkers. The classifier had a weighted average F-1 score of 79%, with the fast-passing time class having the highest F-1 score of 93%. Next, we classify each individual's POTP regardless of the task at hand, achieving an F-1 score of 77.1% when distinguishing time passing faster rather than slower than usual. In the two classifiers, biomarkers derived from the respiration, electrocardiogram, skin conductance, and skin temperature signals contributed most to the classifier output, thus enabling real-time POTP monitoring using noninvasive, wearable biosensors.

Continuous and multimodal stress detection has been performed recently through wearable devices and machine learning algorithms. However, a well-known and important challenge of working on physiological signals recorded by conventional monitoring devices is missing data due to sensors insufficient contact and interference by other equipment. This challenge becomes more problematic when the user/patient is mentally or physically active or stressed because of more frequent conscious or subconscious movements. In this paper, we propose ReLearn, a robust machine learning framework for stress detection from biomarkers extracted from multimodal physiological signals. ReLearn effectively copes with missing data and outliers both at training and inference phases. ReLearn, composed of machine learning models for feature selection, outlier detection, data imputation, and classification, allows us to classify all samples, including those with missing values at inference. In particular, according to our experiments and stress database, while by discarding all missing data, as a simplistic yet common approach, no prediction can be made for 34% of the data at inference, our approach can achieve accurate predictions, as high as 78%, for missing samples. Also, our experiments show that the proposed framework obtains a cross-validation accuracy of 86.8% even if more than 50% of samples within the features are missing., Comment: 7 pages

Taking a two interacting scalar toy model with interaction term $g\phi\chi^2$, we study the production of $\chi$ particles coming from the decay of an asymptotic and highly occupied beam of $\phi$ particles. We perform a nonperturbative analysis coming from parametric resonant instabilities and investigate the possibility that massive $\chi$ particles are produced from decays of massless $\phi$ particles from the beam. Although this process is not present in a perturbative analysis, our nonperturbative approach allows it to happen under certain conditions. For a momentum $p$ of the beam particles and a mass $m_\chi$ of the produced ones, we find that the decay is allowed if the energy density of the beam exceeds the instability threshold $p^2 m_\chi^4/(2g^2)$. We also provide an analytical expression for the spontaneous decay rate at the earliest time., Comment: 10 pages, 5 figures

We investigate a scenario where the dark matter of the Universe is made from very light hidden photons transforming under a $Z_{2}$-symmetry. In contrast to the usual situation, kinetic mixing is forbidden by the symmetry and the dark photon interacts with the Standard Model photon only via an axion-like particle acting as a "messenger". Focusing on signatures involving the ordinary photon, our survey of the phenomenology includes limits from cosmological stability, CMB distortions, astrophysical energy loss, light-shining-through-walls experiments, helioscopes and solar X-ray observations., Comment: 45 pages, 8 figures

Axion--photon interactions can lead to an enhancement of the electromagnetic field by parametric resonance in the presence of a cold axion background, for modes with a frequency close to half the axion mass. In this paper, we study the role of the axion momentum dispersion as well as the effects of a background gravitational potential, which can detune the resonance due to gravitational redshift. We show, by analytical as well as numerical calculations, that the resonance leads to an exponential growth of the photon field only if (a) the axion momentum spread is smaller than the inverse resonance length, and (b) the gravitational detuning distance is longer than the resonance length. For realistic parameter values, both effects strongly suppress the resonance and prevent the exponential growth of the photon field. In particular, the redshift due to the gravitational potential of our galaxy prevents the resonance from developing for photons in the observable frequency range, even assuming that all the dark matter consists of a perfectly cold axion condensate. For axion clumps with masses below $\sim 10^{-13}\, M_\odot$, the momentum spread condition is more restrictive, whereas, for more massive clumps, the redshift condition dominates., Comment: 34 pages, 10 figures