Hasil untuk "Arts in general"

Ivan C. H. Liu, Hsiao-Yuan Chen

Quantum mechanics occupies a central position in contemporary science while remaining largely inaccessible to direct sensory experience. This paper proposes a roadmap to quantum aesthetics that examines how quantum concepts become aesthetic phenomena through artistic mediation rather than direct representation. Two complementary and orthogonal approaches are articulated. The first, a pioneering top-down approach, employs text-prompt-based generative AI to probe quantum aesthetics as a collective cultural construct embedded in large-scale training data. By systematically modulating the linguistic weight of the term "quantum," generative models are used as experimental environments to reveal how quantum imaginaries circulate within contemporary visual culture. The second, a bottom-up approach, derives aesthetic form directly from quantum-mechanical structures through the visualization of quantum-generated data, exemplified here by hydrogen atomic orbitals calculated from the Schrödinger equation. These approaches are framed not as competing methods but as intersecting paths within a navigable field of artistic research. They position quantum aesthetics as an emergent field of artistic research shaped by cultural imagination, computational mediation, and physical law, opening new directions for artistic practice and pedagogy at the intersection of art, data, artificial intelligence and quantum science.

Xinyu Ning, Yan Zhuo, Xian Wang et al.

With the continuous advancement of technology, the application of generative artificial intelligence (AI) in various fields is gradually demonstrating great potential, particularly when combined with Extended Reality (XR), creating unprecedented possibilities. This survey article systematically reviews the applications of generative AI in XR, covering as much relevant literature as possible from 2023 to 2025. The application areas of generative AI in XR and its key technology implementations are summarised through PRISMA screening and analysis of the final 26 articles. The survey highlights existing articles from the last three years related to how XR utilises generative AI, providing insights into current trends and research gaps. We also explore potential opportunities for future research to further empower XR through generative AI, providing guidance and information for future generative XR research.

S. Mildiner Moraga, E. Aarts

Hidden Markov models (HMMs) are probabilistic methods in which observations are seen as realizations of a latent Markov process with discrete states that switch over time. Moving beyond standard statistical tests, HMMs offer a statistical environment to optimally exploit the information present in multivariate time series, uncovering the latent dynamics that rule them. Here, we extend the Poisson HMM to the multilevel framework, accommodating variability between individuals with continuously distributed individual random effects following a lognormal distribution, and describe how to estimate the model in a fully parametric Bayesian framework. The proposed multilevel HMM enables probabilistic decoding of hidden state sequences from multivariate count time-series based on individual-specific parameters, and offers a framework to quantificate between-individual variability formally. Through a Monte Carlo study we show that the multilevel HMM outperforms the HMM for scenarios involving heterogeneity between individuals, demonstrating improved decoding accuracy and estimation performance of parameters of the emission distribution, and performs equally well when not between heterogeneity is present. Finally, we illustrate how to use our model to explore the latent dynamics governing complex multivariate count data in an empirical application concerning pilot whale diving behaviour in the wild, and how to identify neural states from multi-electrode recordings of motor neural cortex activity in a macaque monkey in an experimental set up. We make the multilevel HMM introduced in this study publicly available in the R-package mHMMbayes in CRAN.

S. Varona, S. Saner, O. Băzăvan et al.

We show that recent experiments in hybrid qubit-oscillator devices that measure the phase-space characteristic function of the oscillator via the qubit can be seen through the lens of functional calculus and path integrals, drawing a clear analogy with the generating functional of a quantum field theory. This connection suggests an expansion of the characteristic function in terms of Feynman diagrams, exposing the role of the real-time bosonic propagator, and identifying the external source functions with certain time-dependent couplings that can be controlled experimentally. By applying maximum-likelihood techniques, we show that the ``measurement'' of these Feynman diagrams can be reformulated as a problem of multi-parameter point estimation that takes as input a set of Ramsey-type measurements of the qubit. By numerical simulations that consider leading imperfections in trapped-ion devices, we identify the optimal regimes in which Feynman diagrams could be reconstructed from measured data with low systematic and stochastic errors. We discuss how these ideas can be generalized to finite temperatures via the Schwinger-Keldysh formalism, contributing to a bottom-up approach to probe quantum simulators of lattice field theories by systematically increasing the qubit-oscillator number.

Yuying Tang, Ningning Zhang, Mariana Ciancia et al.

The rapid proliferation of AI-generated image tools is transforming the art and design fields, challenging traditional notions of creativity and impacting both professional and non-professional users. For the purposes of this paper, we define 'professional users' as individuals who self-identified in our survey as 'artists,' 'designers,' 'filmmakers,' or 'art and design students,' and 'non-professional users' as individuals who self-identified as 'others.' This study explores how AI-generated image tools influence these different user groups. Through an online survey (N=380) comprising 173 professional users and 207 non-professional users, we examine differences in the utilization of AI tools, user satisfaction and challenges, applications in creative processes, perceptions and impacts, and acceptance levels. Our findings indicate persistent concerns about image quality, cost, and copyright issues. Additionally, the usage patterns of non-professional users suggest that AI tools have the potential to democratize creative processes, making art and design tasks more accessible to individuals without traditional expertise. This study provides insights into the needs of different user groups and offers recommendations for developing more user-centered AI tools, contributing to the broader discussion on the future of AI in the art and design fields.

Grusha Prasad, Forrest Davis

The rapid growth in natural language processing (NLP) over the last couple years has generated student interest and excitement in learning more about the field. In this paper, we present two types of students that NLP courses might want to train. First, an "NLP engineer" who is able to flexibly design, build and apply new technologies in NLP for a wide range of tasks. Second, an "NLP scholar" who is able to pose, refine and answer questions in NLP and how it relates to the society, while also learning to effectively communicate these answers to a broader audience. While these two types of skills are not mutually exclusive -- NLP engineers should be able to think critically, and NLP scholars should be able to build systems -- we think that courses can differ in the balance of these skills. As educators at Small Liberal Arts Colleges, the strengths of our students and our institution favors an approach that is better suited to train NLP scholars. In this paper we articulate what kinds of skills an NLP scholar should have, and then adopt a backwards design to propose course components that can aid the acquisition of these skills.

Tao Long, Weirui Peng

Digital art portfolios serve as impactful mediums for artists to convey their visions, weaving together visuals, audio, interactions, and narratives. However, without technical backgrounds, design students often find it challenging to translate creative ideas into tangible codes and designs, given the lack of tailored resources for the non-technical, academic support in art schools, and a comprehensive guiding tool throughout the mentally demanding process. Recognizing the role of companionship in code learning and leveraging generative AI models' capabilities in supporting creative tasks, we present PortfolioMentor, a coding companion chatbot for IDEs. This tool guides and collaborates with students through proactive suggestions and responsible Q&As for learning, inspiration, and support. In detail, the system starts with the understanding of the task and artist's visions, follows the co-creation of visual illustrations, audio or music suggestions and files, click-scroll effects for interactions, and creative vision conceptualization, and finally synthesizes these facets into a polished interactive digital portfolio.

Sahaj Garg

Realtime virtual data of objects and human presence in a large area holds a valuable key in enabling many experiences and applications in various industries and with exponential rise in the technological development of artificial intelligence, computer vision has expanded the possibilities of tracking and classifying things through just video inputs, which is also surpassing the limitations of most popular and common hardware setups known traditionally to detect human pose and position, such as low field of view and limited tracking capacity. The benefits of using computer vision in application development is large as it augments traditional input sources (like video streams) and can be integrated in many environments and platforms. In the context of new media interactive arts, based on physical movements and expanding over large areas or gallaries, this research presents a novel way and a framework towards obtaining data and virtual representation of objects/people - such as three-dimensional positions, skeltons/pose and masks from a single rgb camera. Looking at the state of art through some recent developments and building on prior research in the field of computer vision, the paper also proposes an original method to obtain three dimensional position data from monocular images, the model does not rely on complex training of computer vision systems but combines prior computer vision research and adds a capacity to represent z depth, ieto represent a world position in 3 axis from a 2d input source.

Alexei Belochitski, Vladimir Krasnopolsky

The ability of Machine-Learning (ML) based model components to generalize to the previously unseen inputs, and the resulting stability of the models that use these components, has been receiving a lot of recent attention, especially when it comes to ML-based parameterizations. At the same time, ML-based emulators of existing parameterizations can be stable, accurate, and fast when used in the model they were specifically designed for. In this work we show that shallow-neural-network-based emulators of radiative transfer parameterizations developed almost a decade ago for a state-of-the-art GCM are robust with respect to the substantial structural and parametric change in the host model: when used in the AMIP-like experiment with the new model, they not only remain stable, but generate realistic output. Aspects of neural network architecture and training set design potentially contributing to stability of ML-based model components are discussed.

G. Martín-Vázquez, G. Aarts, M. Müller et al.

The generating functional of a self-interacting scalar quantum field theory (QFT), which contains all the relevant information about real-time dynamics and scattering experiments, can be mapped onto a collection of multipartite-entangled two-level sensors via an interferometric protocol that exploits a specific set of source functions. Although one typically focuses on impulsive delta-like sources, as these give direct access to $n$-point Feynman propagators, we show in this work that using always-on harmonic sources can simplify substantially the sensing protocol. In a specific regime, the effective real-time dynamics of the quantum sensors can be described by a quantum Ising model with long-range couplings, the range and strength of which contains all the relevant information about the renormalisation of the QFT, which can now be extracted in the absence of multi-partite entanglement. We present a detailed analysis of how this sensing protocol can be relevant to characterise the long-wavelength QFT that describes quantised sound waves of trapped-ion crystals in the vicinity of a structural phase transition, opening a new route to characterise the associated renormalisation of sound.

Simon Vandevelde, Bram Aerts, Joost Vennekens

Knowledge-based AI typically depends on a knowledge engineer to construct a formal model of domain knowledge -- but what if domain experts could do this themselves? This paper describes an extension to the Decision Model and Notation (DMN) standard, called Constraint Decision Model and Notation (cDMN). DMN is a user-friendly, table-based notation for decision logic, which allows domain experts to model simple decision procedures without the help of IT staff. cDMN aims to enlarge the expressiveness of DMN in order to model more complex domain knowledge, while retaining DMN's goal of being understandable by domain experts. We test cDMN by solving the most complex challenges posted on the DM Community website. We compare our own cDMN solutions to the solutions that have been submitted to the website and find that our approach is competitive. Moreover, cDMN is able to solve more challenges than any other approach.

Saheb Soroushfar, Reza Saffari, Sudhaker Upadhyay

In this paper, we study thermodynamics and thermodynamic geometry of a black hole surrounded by the perfect fluid in Rastall theory. In particular, we calculate the physical quantity like mass, temperature and heat capacity of the system for two different cases. From the resulting heat capacity, we emphasize stability of the system. Following Weinhold, Ruppiner, Quevedo and HPEM formalism, thermodynamic geometry of this black hole in Rastall gravity is also analyzed. We find that the singular points of the curvature scalar of Ruppeiner and HPEM metrics entirely coincides with zero points of the heat capacity. But there is another divergence of HPEM metric which coincides with the singular points of heat capacity, so we can extract more information of HPEM metric compared with Ruppeiner metric. However, we are unable to find any physical data about the system from the Weinhold and Quevedo formalism.

Donald Fortescue, Gwenhaël de Wasseige

We present the result of a cross-disciplinary collaboration between Prof. Donald Fortescue of the California College of the Arts in San Francisco and the Dr. Gwenhael de Wasseige of the IceCube Collaboration. The work presented was initiated during Fortescue's US National Science Foundation funded Antarctic Artists and Writers Fellowship at the South Pole in the austral summer of 2016/17. One outcome of this collaboration is the video work Axis Mundi - a timelapse movie captured during 24 hours at the South Pole, combined with a simultaneous sampling of IceCube data transduced into sound. Axis Mundi captures the rotation of the Earth in space, the transient motions of the atmosphere, and the passage of subatomic particles through the polar ice, to provide a means for us to physically engage with these phenomena. We detail how both the timelapse and the transduction of atmospheric muon data have been realized and discuss the benefits of such a collaboration.

Sudhaker Upadhyay

In this paper, we consider a charged rotating AdS black holes in four dimensions and study the effects of leading-order thermal corrections on the thermodynamics of such system explicitly. The first-order corrected thermodynamical quantities also satisfy the first-law of thermodynamics of the black holes. The holographic duality between the charged rotating AdS black holes and Van der Waals fluid is also emphasized through the $P-v$ diagram. Finally, we study the effects of the leading-order thermal corrections on the stability of the charged rotating black holes.

V. S. Schmid, C. Aerts

Pulsating binary stars are ideal targets for testing the theory of stellar structure and evolution. Fundamental parameters can be derived to high precision from binary modelling and provide crucial constraints for seismic modelling. High-order gravity modes are sensitive to the conditions near the convective core and therefore allow for a determination of parameters describing interior physics, especially the convective-core overshooting parameter. KIC\,10080943 is a binary system that contains two gravity- and pressure-mode hybrid pulsators. A detailed observational study has provided fundamental and seismic parameters for both components. We aim to find a model that is able to predict the observed g-mode period spacings and stellar parameters of both components of KIC 10080943. By calculating model grids with the stellar evolution code MESA and the seismic code GYRE, we can compare theoretical properties to the observed mean period spacing and position in the Hertzsprung-Russell diagram. The masses of our best models are somewhat below the values estimated from binarity, which is a consequence of the low observed mean g-mode period spacing. We find that the amount of core overshooting and diffusive mixing can be well constrained by the equal-age requirement for the two stars, however, we find no significant difference for different shapes of core overshooting. The measured rotation rates are within the limit of validity for the first-order perturbation approximation. We can find a good fit by using the traditional approximation for the pulsations, when taking slightly younger models with a higher asymptotic period spacing. This is because the zonal modes experience a slight shift due to the Coriolis force, which the first-order perturbation approximation ignores.

Giovanni Manfredi

The scope of this paper is twofold. First, we derive rigorously a low-velocity and Galilei-covariant limit of the gravitoelectromagnetic (GEM) equations. Subsequently, these reduced GEM equations are coupled to the Schrödinger equation with gravitoelectric and gravitomagnetic potentials. The resulting extended Schrödinger-Newton equations constitute a minimal model where the three fundamental constants of nature ($G$, $\hbar$, and $c$) appear naturally. We show that the relativistic correction coming from the gravitomagnetic potential scales as the ratio of the mass of the system to the Planck mass, and that it reinforces the standard Newtonian (gravitoelectric) attraction. The theory is further generalized to many particles through a Wigner function approach.

Mohammad Hassan Murad, Saba Fatema

This paper presents a new family of interior solutions of Einstein-Maxwell field equations in general relativity for a static spherically symmetric distribution of a charged perfect fluid with a particular form of charge distribution. This solution gives us wide range of parameter, K, for which the solution is well behaved hence, suitable for modeling of superdense star. For this solution the gravitational mass of a star is maximized with all degree of suitability by assuming the surface density equal to normal nuclear density, 2.5E17 kg/m3. By this model we obtain the mass of the Crab pulsar, MCrab 1.3679 solar mass and radius 13.21 km, constraining the moment of inertia > 1.61E38 kg m2 for the conservative estimate of Crab nebula of 2 solar mass . And MCrab = 1.9645 solar mass with radius 14.38 km constraining the moment of inertia > 3.04E38 kg m2 for the newest estimate of Crab nebula mass, 4.6 solar mass. These results are quite well in agreement with the possible values of mass and radius of Crab pulsar. Besides this, our model yields moments of inertia for PSR J0737-3039A and PSR J0737-3039B, I_A = 1.4285E38 kg m2 and I_B=1.3647E38 kg m2 respectively. It has been observed that under well behaved conditions this class of solutions gives us the overall maximum gravitational mass of super dense object, Mmax, 4.7487 solar mass with radius R(Mmax) = 15.24 km, surface redshift 0.9878, charge 7.91E20 C, and central density 4.31 times nuclear density.

Marc Moniez

Microlensing is now a very popular observational astronomical technique. The investigations accessible through this effect range from the dark matter problem to the search for extra-solar planets. In this review, the techniques to search for microlensing effects and to determine optical depths through the monitoring of large samples of stars will be described. The consequences of the published results on the knowledge of the Milky-Way structure and its dark matter component will be discussed. The difficulties and limitations of the ongoing programs and the perspectives of the microlensing optical depth technique as a probe of the Galaxy structure will also be detailed.

M. Briquet, K. Lefever, K. Uytterhoeven et al.

We present the results of a detailed analysis of 121 ground-based high-resolution high S/N spectroscopic measurements spread over 3 years for the Beta Cephei star Theta Ophiuchi. We discovered Theta Oph to be a triple system. In addition to the already known Speckle B5 companion of the B2 primary, we showed the presence of a low-mass spectroscopic companion and we derived an orbital period of 56.71 days with an eccentricity of 0.1670. After removing the orbit we determined two frequencies for the primary in the residual radial velocities: f1 = 7.1160 c/d and f2 = 7.4676 c/d. We also found the presence of f3 = 7.3696 c/d by means of a two dimensional frequency search across the Si III 4567 A profiles. We identified the m-value of the main mode with frequency f1 by taking into account the photometric identifications of the degrees l. By means of the moment method and the amplitude and phase variations across the line profile, we derived (l1,m1) = (2,-1). This result allows us to fix the mode identifications of the whole quintuplet for which three components were detected in photometry. This is of particular use for our forthcoming seismic modelling of the primary. We also determined stellar parameters of the primary by non-local thermodynamic equilibrium hydrogen, helium and silicon line profile fitting and we obtained Teff = 24000 K and log g = 4.1, which is consistent with photometrically determined values.

Christian Corda

A derivation of the optical axis lenght fluctations due by tilts of the mirrors of the Fabry-Perot cavity of long-baseline interferometers for the detection of gravitational waves in presence of the gravitational field of the earth is discussed. By comparing with the typical tilt-induced noises it is shown that this potential signal, which is considered a weak source of noise, is negligible for the first generation of gravitational waves interferometers, but, in principle, this effect could be used for high precision measures of the gravitational acceleration if advanced projects will achieve an high sensitivity. In that case the precision of the misure could be higher than the gravimeter realized by the Istituto di Metrologia ``Gustavo Colonnetti''.