Grimm in Wonderland: Prompt Engineering with Midjourney to Illustrate Fairytales

The quality of text-to-image generation is continuously improving, yet the boundaries of its applicability are still unclear. In particular, refinement of the text input with the objective of achieving better results - commonly called prompt engineering - so far seems to have not been geared towards work with pre-existing texts. We investigate whether text-to-image generation and prompt engineering could be used to generate basic illustrations of popular fairytales. Using Midjourney v4, we engage in action research with a dual aim: to attempt to generate 5 believable illustrations for each of 5 popular fairytales, and to define a prompt engineering process that starts from a pre-existing text and arrives at an illustration of it. We arrive at a tentative 4-stage process: i) initial prompt, ii) composition adjustment, iii) style refinement, and iv) variation selection. We also discuss three reasons why the generation model struggles with certain illustrations: difficulties with counts, bias from stereotypical configurations and inability to depict overly fantastic situations. Our findings are not limited to the specific generation model and are intended to be generalisable to future ones.Comment: 19th Conference on Information and Research science Connecting to Digital and Library Science, February 23-24, 2023, Bari, Ital

Learning Production Management with ”The Clock Manufacturing Game”

Purpose: Design a business game to provide hands-on training on processes, related to production management Methodology: A stepwise approach is taken. First learning goals, existing approaches and constraints are considered. As a next step a system of conceptual models is developed and finally the model is formalized to the level of detail, necessary for real implementation Findings: The methodology is applied for goals of common interest among teachers in industrial management. Constraints and game features are adapted to computer environments. Good practices for simulation and training games are also formulated. Practical implications: In the paper a strictly formalized game model is developed. In order for it to be able to fit both in trainees comprehension and computer's hardware, the model is simplified and abstracted-out of key concerns. These are stated explicitly. Value: The paper comes to meet specific needs in an area that covers rich and highly competitive industries. It both steps on previous experience and puts its focus in a poorly exploited field

Learning to Prompt in the Classroom to Understand AI Limits: A pilot study

Artificial intelligence's progress holds great promise in assisting society in addressing pressing societal issues. In particular Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amount of unstructured data. The consequent hype has also backfired, raising negative sentiment even after novel AI methods' surprising contributions. One of the causes, but also an important issue per se, is the rising and misleading feeling of being able to access and process any form of knowledge to solve problems in any domain with no effort or previous expertise in AI or problem domain, disregarding current LLMs limits, such as hallucinations and reasoning limits. Acknowledging AI fallibility is crucial to address the impact of dogmatic overconfidence in possibly erroneous suggestions generated by LLMs. At the same time, it can reduce fear and other negative attitudes toward AI. AI literacy interventions are necessary that allow the public to understand such LLM limits and learn how to use them in a more effective manner, i.e. learning to "prompt". With this aim, a pilot educational intervention was performed in a high school with 30 students. It involved (i) presenting high-level concepts about intelligence, AI, and LLM, (ii) an initial naive practice with ChatGPT in a non-trivial task, and finally (iii) applying currently-accepted prompting strategies. Encouraging preliminary results have been collected such as students reporting a) high appreciation of the activity, b) improved quality of the interaction with the LLM during the educational activity, c) decreased negative sentiments toward AI, d) increased understanding of limitations and specifically We aim to study factors that impact AI acceptance and to refine and repeat this activity in more controlled settings.Comment: Submitted to AIXIA 2023 22nd International Conference of the Italian Association for Artificial Intelligence 6 - 9 Nov, 2023, Rome, Ital

Gravitational waves from high-power twisted light

Recent advances in high-energy and high-peak-power laser systems have opened up new possibilities for fundamental physics research. In this work, the potential of twisted light for the generation of gravitational waves in the high frequency regime is explored for the first time. Focusing on Bessel beams, novel analytic expressions and numerical computations for the generated metric perturbations and associated powers are presented. Compelling evidence is provided that the properties of the generated gravitational waves, such as frequency, polarisation states and direction of emission, are controllable by the laser pulse parameters and optical arrangements

Quantum dynamics of simultaneously measured non-commuting observables.

In quantum mechanics, measurements cause wavefunction collapse that yields precise outcomes, whereas for non-commuting observables such as position and momentum Heisenberg's uncertainty principle limits the intrinsic precision of a state. Although theoretical work has demonstrated that it should be possible to perform simultaneous non-commuting measurements and has revealed the limits on measurement outcomes, only recently has the dynamics of the quantum state been discussed. To realize this unexplored regime, we simultaneously apply two continuous quantum non-demolition probes of non-commuting observables to a superconducting qubit. We implement multiple readout channels by coupling the qubit to multiple modes of a cavity. To control the measurement observables, we implement a 'single quadrature' measurement by driving the qubit and applying cavity sidebands with a relative phase that sets the observable. Here, we use this approach to show that the uncertainty principle governs the dynamics of the wavefunction by enforcing a lower bound on the measurement-induced disturbance. Consequently, as we transition from measuring identical to measuring non-commuting observables, the dynamics make a smooth transition from standard wavefunction collapse to localized persistent diffusion and then to isotropic persistent diffusion. Although the evolution of the state differs markedly from that of a conventional measurement, information about both non-commuting observables is extracted by keeping track of the time ordering of the measurement record, enabling quantum state tomography without alternating measurements. Our work creates novel capabilities for quantum control, including rapid state purification, adaptive measurement, measurement-based state steering and continuous quantum error correction. As physical systems often interact continuously with their environment via non-commuting degrees of freedom, our work offers a way to study how notions of contemporary quantum foundations arise in such settings

Cooling a nanomechanical resonator with quantum back-action

Quantum mechanics demands that the act of measurement must affect the measured object. When a linear amplifier is used to continuously monitor the position of an object, the Heisenberg uncertainty relationship requires that the object be driven by force impulses, called back-action. Here we measure the back-action of a superconducting single-electron transistor (SSET) on a radiofrequency nanomechanical resonator. The conductance of the SSET, which is capacitively coupled to the resonator, provides a sensitive probe of the latter's position;back-action effects manifest themselves as an effective thermal bath, the properties of which depend sensitively on SSET bias conditions. Surprisingly, when the SSET is biased near a transport resonance, we observe cooling of the nanomechanical mode from 550mK to 300mK-- an effect that is analogous to laser cooling in atomic physics. Our measurements have implications for nanomechanical readout of quantum information devices and the limits of ultrasensitive force microscopy (such as single-nuclear-spin magnetic resonance force microscopy). Furthermore, we anticipate the use of these backaction effects to prepare ultracold and quantum states of mechanical structures, which would not be accessible with existing technology.Comment: 28 pages, 7 figures; accepted for publication in Natur

Energy gain of wetted-foam implosions with auxiliary heating for inertial fusion studies

Low convergence ratio implosions (where wetted-foam layers are used to limit capsule convergence, achieving improved robustness to instability growth) and auxiliary heating (where electron beams are used to provide collisionless heating of a hotspot) are two promising techniques that are being explored for inertial fusion energy applications. In this paper, a new analytic study is presented to understand and predict the performance of these implosions. Firstly, conventional gain models are adapted to produce gain curves for fixed convergence ratios, which are shown to well-describe previously simulated results. Secondly, auxiliary heating is demonstrated to be well understood and interpreted through the burn-up fraction of the deuterium-tritium fuel, with the gradient of burn-up with respect to burn-averaged temperature shown to provide good qualitative predictions of the effectiveness of this technique for a given implosion. Simulations of auxiliary heating for a range of implosions are presented in support of this and demonstrate that this heating can have significant benefit for high gain implosions, being most effective when the burn-averaged temperature is between 5 and 20 keV

Energy gain of wetted-foam implosions with auxiliary heating for inertial fusion studies

Low convergence ratio implosions (where wetted-foam layers are used to limit capsule convergence, achieving improved robustness to instability growth) and auxiliary heating (where electron beams are used to provide collisionless heating of a hotspot) are two promising techniques that are being explored for inertial fusion energy applications. In this paper, a new analytic study is presented to understand and predict the performance of these implosions. Firstly, conventional gain models are adapted to produce gain curves for fixed convergence ratios, which are shown to well-describe previously simulated results. Secondly, auxiliary heating is demonstrated to be well understood and interpreted through the burn-up fraction of the deuterium-tritium fuel, with the gradient of burn-up with respect to burn-averaged temperature shown to provide good qualitative predictions of the effectiveness of this technique for a given implosion. Simulations of auxiliary heating for a range of implosions are presented in support of this and demonstrate that this heating can have significant benefit for high gain implosions, being most effective when the burn-averaged temperature is between 5 and 20 keV