In 2011, with a probing tip functionalized with a CO molecule, internal details of molecular wavefunctions, the nodal structures, was experimentally observed and mapped in real space using scanning tunneling microscopy (STM). Together with the charge density contours of atomic and molecular wavefunctions directly observed and mapped by STM in the 2000s, wavefunctions are proven to be an observable physical field. A fact is, STM is a non-destructive imaging method, and the measurement process does not disturb the wavefunctions under observation. For many decades, wavefunction has been imagined as an abstract complex subject, not directly observable. The new developments showed that wavefunction is an observable, like electrical and magnetic fields. Those new developments enable a realistic interpretation of quantum mechanics, as advocated by Planck, Einstein, Schrödinger and de Broglie; and enable a significant simplification in teaching and learning quantum mechanics. 

(The original title was **Experimental Observation and Mapping of Atomic and Molecular Wavefunctions: Consequences on the Fundamental Understanding of Quantum Mechanics**). 


Wavefunction Is an Observable Physical Field

**Author(s):** Bluet, A; Osiurak, F; Claidière, N; Reynaud, E. INTRODUCTION: Our technologies have never ceased to evolve, allowing our lineage to expand its habitat all over the Earth, and even to explore space. This phenomenon, called cumulative technological culture (CTC), has been studied extensively, notably using mathematical and computational models. One main factor that has received extensive attention is demography, and more precisely population size. However, the cognitive capacities needed for the emergence and maintenance of CTC remain largely unknown. In the literature, the focus is put on the distinctive ability of humans to imitate, with an emphasis on our unique social skills underlying it, namely theory of mind (ToM). A recent alternative view, called the technical-reasoning hypothesis, proposes that our unique ability to understand the physical world (i.e., technical reasoning; TR) might also play a critical role in CTC. Here, we propose a simple model that focuses on micro-societies experiments. Classically, we observe three forms of social learning in this literature: reverse-engineering (RE) where only the technology is present; observation (OBS) where a receiver witnesses a demonstration of the building of the technology by a sender; and communication (COM) with verbal interaction between a receiver and a sender. Thus, our model will implement these three social learning. Our model is composed of a simple environment with only one technology transmitted between generations of individuals. These individuals have two cognitive skills: ToM and TR, and can learn using the aforementioned different social-learning conditions. Their goal is to improve as much as possible the technology. Afterwards, we extend this model to include multiple chains of transmission in order to assess the effect of population size on CTC. OBJECTIVES: To model the transmission of technical information between two individuals in a micro-society. Mainly, we intend to investigate the role of ToM and TR in the social-learning conditions found in the micro-society literature. Another goal of this model is to replicate and solidify the results of said literature. Finally, we intend to test our model on a population scale. This allows us to test the different hypotheses of the impact of population size on CTC. APPROACH: In our model, we assume an environment composed of a single technology. We further assume that this technology can be decomposed into components, called traits. For example, if the technology represents a vehicle, traits represent the wheels, the seating, the steering wheel, etc. In each generation, an individual appears in the environment. This individual has a set of knowledge (named cog) for each technology’s trait, and two cognitive skills, namely TR and ToM. First, the individual learns from previous generations using one of three social-learning forms (RE, OBS, COM) to improve its cogs. This learning phase depends on its cognitive skills (TR and ToM; depending on the social-learning form). Afterwards, the individual tries to improve the technology by refining its traits. Refining the technology’s trait equals increasing its quality. Subsequently, the individual might have an opportunity to innovate, which is equivalent to adding a new trait to the technology in our model. This opportunity comes with a fixed probability, and the individual needs to cease it either by having a good enough technology or by being himself a quite advanced individual compared to its environment. Finally, the individual disappears from the environment and is replaced by a new one. This process is repeated for N generations (N = 1000 if not stated otherwise), thus creating transmission chains. In the extension of our model, we run multiple transmission chains at the same time. Each chain has its technology and individual, the latter of which can learn from conspecifics in other transmission chains. This emulates a fully connected population of individuals. It is important to note that we assume that innovations are transmission through social learning, meaning that an individual will bring back through learning the innovation from another transmission chain. RESULTS: In our model, all three social learning forms yield CTC in the form of exponential growth of technology’s quality. However, both RE and OBS produce lower technology quality than COM, the former both having very similar behaviours and results, which agrees with classical results of the literature on transmission chains, where RE has the lowest technology quality, closely followed by OBS and then well ahead COM. When comparing model of COM with and without ToM, we see little difference between the two, demonstrating a limited impact of ToM. Further analyses indicate that ToM has an impact only during the first generations, indicating that its effect may be to accelerate the acquisition of an optimal technology. When we add multiple transmission chains, we observe an effect of population size on CTC. This effect is weaker the greater the population size, hinting at a higher impact of adding individuals for a smaller population size. Further analysis showed that our model is driven by the frequency of innovation, thus explaining this result. Indeed, adding individuals is equal to adding potential innovators. However, we observe that once population size reaches a certain threshold, adding more individuals does not bring more innovation because there are already enough innovators. DISCUSSION: Our model results are in accordance with the transmission-chain literature, where communication conditions often outperform non-communication ones. This both strengthen the result of said literature and validate our model. Furthermore, we observe exponential growth of technology’s quality, something that is also observed in our cultural evolutionary history (Lehman, 1947). We posit that this exponential growth is due to a snowball effect: an increase in technology’s quality is accompanied by an increase in the understanding of this technology, thus increasing in return the capacity of the individual to increase the technology’s quality and so on. This snowball effect occurs because TR supports both the transmission of information and the modification of the technology. This effect of both the understanding and the technology’s quality improving together is something that we have already shown in a recent study using transmission chains, where an increase in the speed at which a wheel rolls down an axis is correlated to the increase in the understanding of how mass repartition affects this movement. Our results show that ToM has little to no impact on CTC. This seems surprising because ToM can only impact learning positively in our model. However, further analysis showed that ToM has an impact early on in our model, acting as a catalyst for the first burst of increases in technology’s quality. In this regard, we consider the impact of ToM as a launching pad for the snowball effect described earlier, being neither necessary nor sufficient for the emergence of a CTC. When applied to the scale of a population, our model shows interesting and well-known results. Indeed, a larger population size has been extensively linked to an increase in CTC and this effect has also been linked to the frequency of innovation. These are encouraging results, and in the future, we intend to further extend our model to implement other aspects of demography that have been shown to have an impact on CTC, such as population structure and dissemination of knowledge.

Impact of technical reasoning, theory of mind and population size on cumulative technological culture: insights from a model of micro-societies

Helium-filled High Altitude Balloons (HABs) have been used by St. Catherine University all women’s research team to investigate the near-space environment. Due to low pressure, the balloons expand until they burst at approximately 32 km. Cosmic ray showers colliding with atmospheric particles are significant in the region where these HABs are flown. One of the constituents of the collision process is neutrons. A personal neutron dosimeter (PND) can be used to quantify neutrons through the appearance of bubbles as a result of neutron reactions with a liquid substrate. Over the years, flights have been flown consisting of a PND, heater circuit, Geiger – Mueller tubes, GPS, and a GoPro camera. Data analysis shows a correlation between the altitude of the neutrons in comparison to other shower-generated particles. The particle peak occurs between 15-25 km – correlating to the charged particle maximum known as the Regener-Pfotzer maximum.

Personal Neutron Dosimeter Measuring Cosmic Rays in Stratospheric Ballooning Missions.

The radio sky is accessible at low cost with the RadioJOVE Project, a dual-dipole with receiver that is used by educators, students, and amateur radio astronomers to detect solar flares and radio bursts from Jupiter. In 2019, a short course on radio astronomy was designed by four undergraduates at Saint Anselm College as part of Access Academy, an afterschool program for immigrant, refugee, and underrepresented high school students in Manchester, New Hampshire, through the Meelia Center for Community Engagement. The project has been revived with a new undergraduate instructor for Access Academy and the course developed to go beyond construction of the telescope to data analysis. We will provide an update on the Saint Anselm RadioJOVE featuring new solar flare detections made by high school students and plans to incorporate RadioJOVE 2.0, a spectrograph that will facilitate more sophisticated science.

Discovering Solar Flares with High School Students

We present a citizen science campaign, Dark Energy Explorers, aiming to improve the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). HETDEX will collect at least one million galaxies that are 9 - 11 billion light-years away, yielding one of the largest maps of the universe. We created Dark Energy Explorers on Zooniverse, the world’s largest citizen science platform to help us classify these astronomical objects. With Dark Energy Explorers we train participants, of any background, to be able to distinguish different galaxies by swiping left or right on their smartphone. Initial analysis has shown that citizen science is an efficient and effective tool for classification most accurately done by the human eye. Since launching in late February 2021, we have reached 3.5 million classifications by 8,000 volunteers in 80 countries! Dark Energy Explorers has proven to be a uniquely powerful tool for science advancement and increasing accessibility to science worldwide.

Dark Energy Explorers: Using Citizen Science to Enhance the Hobby-Eberly-Telescope-Dark-Energy-Experiment

We present a very simple derivation of the commonly used approximate formula [1]:&nbsp;D = A * sin ((d/365.25) * 2*PI), where D is solar declination, A = 23.44 deg is Earth's axial tilt (obliquity of the ecliptic), and d is the number of days after Equinox. &nbsp;&nbsp;We used the heliocentric cartesian frame of reference with XY plane coplanar to the ecliptic. We analytically calculated the scalar product of the unit vector pointing from the Sun to the Earth and the other unit vector pointing from the Earth to Polaris. &nbsp;This product is equal to the cosine of the angle complementary to the solar declination D. &nbsp;&nbsp;We also demonstrated how we can find the geographic latitude using hands-on observation of the shadow of a yardstick at local geographic noon. The geographic latitude is found with the accuracy of about 1.5 degree (or 100 nautical miles along meridian). &nbsp;&nbsp;&nbsp;&nbsp;Reference:&nbsp;1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;https://www.pveducation.org/pvcdrom/properties-of-sunlight/declination-angle&nbsp;

The Approximate Formula for Solar Declination and Its Experimental Validation

Space exploration is a naturally interesting topic to many people. With the advances in spacecraft propulsion methods, it is possible for humans to study distant celestial bodies. Students can investigate the benefits and challenges of both human and non-human travel to space through different means. In this study, we investigated ways to help students understand space exploration. Two activities, Migration to Mars and Solar Sails, were designed for an undergraduate astronomy course taught online during the COVID pandemic. Students completed the activities in groups of four. One activity per group was submitted to the course management software followed by a quiz that students answered individually. Quiz responses were coded to check students’ understanding of the activities and the extent to which they were able to describe information relevant to space exploration. Students generally understood the value of uncrewed missions and the fact that solar sails use sustainable energy.

Students’ Understanding of Factors Related to Space Exploration

Knowledge transfer from micromechanics of granular media failure to geohazard forecasting and mitigation has been slow. But in the face of a rapidly expanding data infrastructure on the motion of individual grains for laboratory samples – and ground motion data at the field scale – opportunities to accelerate this knowledge transfer are emerging. In particular, such data assets coupled with data-driven approaches enable a re-examination of granular failure with ‘new eyes’. To this end, effective strategies that can jump scales from bench to field are urgently needed. Here we demonstrate one strategy that focusses on the study of deformation patterns in the precursory failure regime using kinematic data. Unlike previous studies which focus on regions of high strains, here we probe the development and evolution of near- undeforming regions through the lens of explosive percolation. We find a common dynamical signature in which undeforming regions, which are initially transient in the precursory failure regime, become persistent from the time of imminent failure. We demonstrate the robustness of these findings for data on individual grain motions in a classical laboratory test and ground motion in two real landslides at vastly different scales.

Dynamics of undeforming regions in the lead up to failure: jumping scales from lab to field

In this paper, an assembly of disordered packings is considered as a suitable set of packing cells of ordered spheres. In consequence, any of its parameters can be obtained by averaging the values of the set. Namely, the density of a packing of ordered spheres is described by two variables: the angle of the base, and the angle of the inclined edge of the associated parallelepiped. Then, the density of a packing of disordered spheres is obtained by averaging the angle of the base, and the subsequent averaging of the other angle, according to the kind of strain induced by the experiment. The average packing yields the density limits of loose sphere assemblies achieved by a process of fluidization and sedimentation in air, in water, and in viscous liquid at zero gravitational force. It also models the close sphere assemblies shaped by gentle tapping, vertical shaking, horizontal and multidirectional vibrations. The theory allows to elucidate the mechanism of each of the limits, as, for example, the metastable columns of spheres in the loosest packing, as well as the random close packing, and crystallization. The limits obtained coincide very well with the published experimental, numerical and theoretical data.

An average model for disordered sphere packings

The question of how soft granular matter, or dense amorphous systems, re-arrange their micro-structure under isotropic compression and decompression, at different strain rates, will be answered by particle simulations of frictionless model systems in a periodic three-dimensional cuboid. Starting compression below jamming, the systems experience the well-known jamming transition, with characteristic evolutions of the state variables elastic energy, elastic stress, coordination number, and elastic moduli. For large strain rates, kinetic energy comes into play and the evolution is more dynamic. In contrast, at extremely slow deformation, the system relaxes to hyper-elastic states, with well-defined elastic moduli, in static equilibrium between irreversible (plastic) re-arrangement events, discrete in time. Small, finite strains explore those reversible (elastic) states, before larger strains push the system into new states, by irreversible, sudden re-arrangements of the microstructure.

How does static granular matter re-arrange for different isotropic strain rate?

We experimentally investigate the effect of the grain shape on the flow of granular material. The grain shape is modified to highlight the effect of grain circularity on granular flow in a 2D rotating drum. Using a laser cutter, we create particles with decreasing circularity. We observe that the effect of grain shape depends on the rotation speed of the drum. For high rotation speed, granular flow is influenced by the packing’s dilatancy whereas, at low rotation speed, packing fraction seems to influence flowing dynamics. We link these two measurements to grain shape in order to explain its effect on granular flow.

Effect of grain shape on the dynamics of granular materials in 2D rotating drum

The rhombic sphere packing can be used to model granular soils in a very simple way. According to the angle of assemblage, the packing is dilatant or contractive. Correspondingly, the overall stresses are transmitted as chains of forces or oblique forces of contact. The connection of the soil stress-strain behaviour and the packing void ratio is achieved by mapping both of the plots. The mapping shows that dense soils are dilatant and loose soils are contractive, separated by the critical state. It also shows that the bifurcation point and the peak strength are features of dense soils. The line of strain localization is analysed in the elastic regime, and its inclination is found maximizing the intensity of the mobilized stress ratio. The stresses within the shear band are obtained by assuming a partially coaxial packing rotated for reaching the full plastic state. The equilibrium of the overall stress at the line of discontinuity leads to the relationship between the peak friction angle and the coefficient of lateral pressure at rest. As long as these parameters are independently obtained from each other, they allow the validation of the theory.

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Wavefunction Is an Observable Physical Field

Impact of technical reasoning, theory of mind and population size on cumulative technological culture: insights from a model of micro-societies

Personal Neutron Dosimeter Measuring Cosmic Rays in Stratospheric Ballooning Missions.

Discovering Solar Flares with High School Students

Dark Energy Explorers: Using Citizen Science to Enhance the Hobby-Eberly-Telescope-Dark-Energy-Experiment

The Approximate Formula for Solar Declination and Its Experimental Validation

Students’ Understanding of Factors Related to Space Exploration

Dynamics of undeforming regions in the lead up to failure: jumping scales from lab to field

An average model for disordered sphere packings

How does static granular matter re-arrange for different isotropic strain rate?

Effect of grain shape on the dynamics of granular materials in 2D rotating drum

A sphere packing model for shear bands in dense soils

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