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Children can experience scientific concepts by using materials in their everyday world to perform safe and fun experiments.

The purpose of the present paper is to clarify, as far as it is possible, the overall picture of experimental results in the field of non-conventional phenomena in nuclear matter published in the scientific literature, accumulated in the past few decades and still missing a widely accepted interpretation. Completeness of the collection of the experiments is not among the aims of the effort; the focus is on adopting a more comprehensive and integral approach through the analysis of the different experimental layouts and different results, searching for common features and analogous factual outcomes in order to obtain a consistent reading of many experimental evidences that appear, so far, to lack a classification in a logic catalogue, which might be compared to a building rather than a collection of single stones. Particular attention is put on the issue of reproducibility of experiments and on the reasons why such a limitation is a frequent characteristic of many experimental activities reported in published papers. This approach is innovative as compared with those already available in the scientific literature. In a synoptical table, a comprehensive classification is given of the twenty experiments examined in terms of types of evidences that are ascertained by the experimenters in their published papers but are “unexpected” according to well-established physical theories. Examples of such unexpected evidences (named also non-conventional or weird) evidences are: excess heat generation, isotope production, reduction of radioactivity levels, and production of neutrons or alpha particles. These evidences are classified taking into account both the material where the evidence takes place (solutions, metals, rocks and artificial materials) and the stimulation techniques (supply of electric voltage, irradiation by photons, mechanical pressure) used to generate the evidences (which do not appear in the absence of such stimuli at an appropriate intensity). Also, in our paper, “identity cards” are provided for each experiment examined, including details that emerged during the experiment and were reported in each respective paper, that sometimes are not given adequate consideration either by the author of the experiment or in other review papers. The analysis of the details provides suggestions (also referred to as clues in this papers) used to formulate the content of the second part of each identity card, where inferences deduced from facts are outlined in view of presenting tentative interpretation at the microscopic level. This is done by concentrating attention on the clues repeated in different experiments in order to yield possible explanations of the “unexpected” evidences. The main outcome of such analysis is that, in all examined cases, a common “operation” can be identified: the stimulation techniques mentioned above can be interpreted as a sort of compression producing a ramp of energy densification (with reference to volumes in space or time coordinates). Here we use the term “compression” to indicate an operation activated by the experimenter; as such, it is objective. We consider energy densification an inference of possible consequences of the operation on the status of the system. Five types of densifications were identified. This reading in terms of energy densification is in accordance with the predictions of the Deformed Space Time theory, reported in the scientific literature, in the context of a generalization of the Einstein relativity theory, according to which the existence of energy thresholds is found to separate, for each interaction, the flat metric part from the deformed metric part and the appearance of new microscopic effects as a consequence of trespassing such thresholds. The phenomena occurring in the deformed part of the interaction metric are governed by the energy density in the space-time (volume and time interval). This energy density is computed from the threshold energies and is peculiar to the phenomenology under consideration. As a conclusion, it is suggested that the revealed qualified information, homogenized and elaborated on, might help in repeating, with proper adjustments and adequate additional instrumentation, some key experiments, in order to ensure systematic reproducibility, which is a prerequisite for interpretations and explanations to be sound and credible, as well in deriving from such an effort, indications for new experiments. It is uncomfortable that, after thirty years, there are still pending questions to which the most acknowledged physical theories are not capable of giving an answer. Even a definitive demonstration that all these experiments have decisive faults would be preferable than leaving the issue unaddressed. Major research agencies, for instance in the USA and in Europe, are moving in this direction.

Learn what water is, how we use it, and why our world may be running dry.

Demonstration of an optomechanical system that works as a quantum interface between light and micro-mechanical motion. Nanomechanical oscillators coupled to optic cavities The possibility of controlling the quantum states of micro- and nanomechanical oscillators has been of great interest in recent years. Although various mechanical resonators have been cooled to their quantum ground state, there are few reports of experiments in which this quantum regime is further explored and used, for example, to exchange quantum information. Previously, quantum coupling between mechanical degrees of freedom and microwave radiation has been shown. Now, Verhagen et al . demonstrate an optomechanical system, cooled by radiation pressure, that works as a quantum interface between a mechanical oscillator and optical photons, offering the advantage that standard optical fibres can be used to extract the quantum information. Optical laser fields have been widely used to achieve quantum control over the motional and internal degrees of freedom of atoms and ions 1 , 2 , molecules and atomic gases. A route to controlling the quantum states of macroscopic mechanical oscillators in a similar fashion is to exploit the parametric coupling between optical and mechanical degrees of freedom through radiation pressure in suitably engineered optical cavities 3 , 4 , 5 , 6 . If the optomechanical coupling is ‘quantum coherent’—that is, if the coherent coupling rate exceeds both the optical and the mechanical decoherence rate—quantum states are transferred from the optical field to the mechanical oscillator and vice versa. This transfer allows control of the mechanical oscillator state using the wide range of available quantum optical techniques. So far, however, quantum-coherent coupling of micromechanical oscillators has only been achieved using microwave fields at millikelvin temperatures 7 , 8 . Optical experiments have not attained this regime owing to the large mechanical decoherence rates 9 and the difficulty of overcoming optical dissipation 10 . Here we achieve quantum-coherent coupling between optical photons and a micromechanical oscillator. Simultaneously, coupling to the cold photon bath cools the mechanical oscillator to an average occupancy of 1.7 ± 0.1 motional quanta. Excitation with weak classical light pulses reveals the exchange of energy between the optical light field and the micromechanical oscillator in the time domain at the level of less than one quantum on average. This optomechanical system establishes an efficient quantum interface between mechanical oscillators and optical photons, which can provide decoherence-free transport of quantum states through optical fibres. Our results offer a route towards the use of mechanical oscillators as quantum transducers or in microwave-to-optical quantum links 11 , 12 , 13 , 14 , 15 .

Machine learning algorithms have become essential tools in modern physics experiments, enabling the precise and efficient analysis of large-scale experimental data. The Compressed Baryonic Matter (CBM) experiment at the Facility for Antiproton and Ion Research (FAIR) demands innovative methods for processing the vast data volumes generated at high collision rates of up to 10 MHz. This study presents a deep-learning-based approach to enhance the signal/background (S/B) ratio for Λ particles within the Kalman Filter (KF) Particle Finder framework. Using the Artificial Neural Networks for First Level Event Selection (ANN4FLES) package of CBM, a multi-layer perceptron model was designed and trained on simulated data to classify Λ particle candidates as signal or background. The model achieved over 98% classification accuracy, enabling significant reductions in background—in particular, a strong suppression of the combinatorial background that lacks physical meaning—while preserving almost the whole Λ particle signal. This approach improved the S/B ratio by a factor of 10.97, demonstrating the potential of deep learning to complement existing particle reconstruction techniques and contribute to the advancement of data analysis methods in heavy-ion physics.

\"Explains how to use the scientific method to conduct several science experiments about the properties of matter. Includes ideas for science fair projects\"--Provided by publisher.

All optical detectors to date annihilate photons upon detection, thus excluding repeated measurements. Here, we demonstrate a robust photon detection scheme that does not rely on absorption. Instead, an incoming photon is reflected from an optical resonator containing a single atom prepared in a superposition of two states. The reflection toggles the superposition phase, which is then measured to trace the photon. Characterizing the device with faint laser pulses, a single-photon detection efficiency of 74% and a survival probability of 66% are achieved. The efficiency can be further increased by observing the photon repeatedly. The large single-photon nonlinearity of the experiment should enable the development of photonic quantum gates and the preparation of exotic quantum states of light.

\"Make a simple refrigerator like pottery-maker Mohammed Bah Abba did that does not use electricity, or create little models of people out of ice like sculptor Nâele Azevedo. This title gives readers both an understanding of the different states of matter and the skills to investigate great discoveries and works. Exciting and easy-to-understand experiments encourage budding scientists, inventors, engineers, and artists to stand on the shoulders of the curious and creative people who came before them.\"-- Provided by publisher.

Fast and efficient algorithms optimized for high performance computers are crucial for the real-time analysis of data in heavy-ion physics experiments. Furthermore, the application of neural networks and other machine learning techniques has become more popular in physics experiments over the last years. For that reason, a fast neural network package called ANN4FLES is developed in C++, which will be optimized to be used on a high performance computer farm for the future Compressed Baryonic Matter (CBM) experiment at the Facility for Antiproton and Ion Research (FAIR, Darmstadt, Germany). This paper describes the first application of ANN4FLES used in the reconstruction chain of the CBM experiment to replace the existing particle competition between Ks-mesons and Λ-hyperons in the KF Particle Finder by a neural network based approach. The raw classification performance of the neural network reaches over 98% on the testing set. Furthermore, it is shown that the background noise was reduced by the neural network-based competition and therefore improved the quality of the physics analysis.