Fundamental Interactions Research Articles

Endosymbiont and gut bacterial communities of the brown-banded cockroach, Supella longipalpa.

The brown-banded cockroach (Supella longipalpa) is a widespread nuisance and public health pest. Like the German cockroach (Blattella germanica), this species is adapted to the indoor biome and completes the entirety of its life cycle in human-built structures. Recently, understanding the contributions of commensal and symbiotic microbes to the biology of cockroach pests, as well as the applications of targeting these microbes for pest control, have garnered significant scientific interest. However, relative to B. germanica, the biology of S. longipalpa, including its microbial associations, is understudied. Therefore, the goal of the present study was to quantitatively examine and characterize both the endosymbiont and gut bacterial communities of S. longipalpa for the first time. To do so, bacterial 16S rRNA gene amplicon sequencing was conducted on DNA extracts from whole adult females and males, early instar nymphs, and late instar nymphs. The results demonstrate that the gut microbiome is dominated by two genera of bacteria known to have beneficial probiotic effects in other organisms, namely Lactobacillus and Akkermansia. Furthermore, our data show a significant effect of nymphal development on diversity and variation in the gut microbiome. Lastly, we reveal significant negative correlations between the two intracellular endosymbionts, Blattabacterium and Wolbachia, as well as between Blattabacterium and the gut microbiome, suggesting that Blattabacterium endosymbionts could directly or indirectly influence the composition of other bacterial populations. These findings have implications for understanding the adaptation of S. longipalpa to the indoor biome, its divergence from other indoor cockroach pest species such as B. germanica, the development of novel control approaches that target the microbiome, and fundamental insect-microbe interactions more broadly.

Optically Controlled Nano-Transducers Based on Cleaved Superlattices for Monitoring Gigahertz Surface Acoustic Vibrations.

Surface acoustic waves (SAWs) convey energy at subwavelength depths along surfaces. Using interdigital transducers (IDTs) and opto-acousto-optic transducers (OAOTs), researchers have harnessed coherent SAWs with nanosecond periods and micrometer localization depth for various applications. These applications include the sensing of small amount of materials deposited on surfaces, assessing surface roughness and defects, signal processing, light manipulation, charge carrier and exciton transportation, and the study of fundamental interactions with thermal phonons, photons, magnons, and more. However, the utilization of cutting-edge OAOTs produced through surface nanopatterning techniques has set the upper limit for coherent SAW frequencies below 100 GHz, constrained by factors such as the quality and pitch of the surface nanopattern, not to mention the electronic bandwidth limitations of the IDTs. In this context, unconventional optically controlled nanotransducers based on cleaved superlattices (SLs) are here presented as an alternative solution. To demonstrate their viability, we conducted proof-of-concept experiments using ultrafast lasers in a pump-probe configuration on SLs made of alternating AlxGa1-xAs and AlyGa1-yAs layers with approximately 70 nm periodicity and cleaved along their growth direction to produce a periodic nanostructured surface. The acoustic vibrations, generated and detected by laser beams incident on the cleaved surface, span a range from 40 to 70 GHz, corresponding to the generalized surface Rayleigh mode and bulk modes within the dispersion relation. This exploration shows that, in addition to SAWs, cleaved SLs offer the potential to observe surface-skimming longitudinal and transverse acoustic waves at GHz frequencies. This proof-of-concept demonstration below 100 GHz in nanoacoustics using such an unconventional platform might be useful for realizing sub-THz to THz coherent surface acoustic vibrations in the future, as SLs can be epitaxially grown with atomic-scale layer width and quality.

Aharonov-Bohm effect for confined matter in lattice gauge theories

Gauge theories arise in physical systems displaying space-time local symmetries. They provide a powerful description of important realms of physics ranging from fundamental interactions to statistical mechanics, condensed matter, and, more recently, quantum computation. As such, a remarkably deep understanding has been achieved in the field. With the advent of quantum technology, lower energy analogs, capable of capturing important features of the original quantum field theories through quantum simulation, have been intensively studied. Here, we propose a specific scheme implementing an quantum simulation of lattice gauge theories constrained to mesoscopic spatial scales. To this end, we study the dynamics of mesons residing in a ring-shaped lattice of mesoscopic size pierced by an effective magnetic field. In particular, we find a type of Aharonov-Bohm effect that goes beyond the particlelike effect, reflecting the features of the confining gauge potential. The coherence properties of the meson are quantified by the persistent current and by specific features of the correlation functions. When the magnetic field is quenched, Aharonov-Bohm oscillations and correlations start a specific matter-wave current dynamics. Published by the American Physical Society 2024

SIMULATeQCD: A simple multi-GPU lattice code for QCD calculations

The rise of exascale supercomputers has fueled competition among GPU vendors, driving lattice QCD developers to write code that supports multiple APIs. Moreover, new developments in algorithms and physics research require frequent updates to existing software. These challenges have to be balanced against constantly changing personnel. At the same time, there is a wide range of applications for HISQ fermions in QCD studies. This situation encourages the development of software featuring a HISQ action that is flexible, high-performing, open source, easy to use, and easy to adapt. In this technical paper, we explain the design strategy, provide implementation details, list available algorithms and modules, and show key performance indicators for SIMULATeQCD, a simple multi-GPU lattice code for large-scale QCD calculations, mainly developed and used by the HotQCD collaboration. The code is publicly available on GitHub. Program summaryProgram Title: SIMULATeQCDCPC Library link to program files:https://doi.org/10.17632/ytgycy9nc3.1Developer's repository link:https://github.com/LatticeQCD/SIMULATeQCDLicensing provisions: MITProgramming language: C++, CUDA, HIPNature of problem: Quantum chromodynamics (QCD) is the fundamental theory behind the strong force, one of the four fundamental forces in nature. It describes interactions, mediated by gluons, between quarks, the elementary particles that build up protons, neutrons and other hadrons. One of its unique features is asymptotic freedom: with increasing energy, the interaction strength or coupling between quarks and gluons weakens, which enables studying QCD with peturbation theory. At lower energy scales, however, the strong coupling between quarks and gluons causes perturbation theory to break down, and other tools, such as lattice QCD, need to be employed to obtain QCD predictions.Solution method: Lattice QCD is a technique to solve QCD non-perturbatively by discretizing space and time onto a four-dimensional grid. The QCD path integral is thereby rendered finite dimensional and can be evaluated numerically via Monte Carlo methods. In this paper, we present SIMULATeQCD, a C++ code to perform lattice QCD calculations on multiple GPUs, supporting multiple APIs. SIMULATeQCD implements various Monte Carlo sampling methods ranging from sampling of purely gluonic configurations to fully dynamical quark simulations with the Highly Improved Staggered Quark (HISQ) discretization. Modules for measuring various physical observables on these samples are also available.

Design and Control of the Magnetically Actuated Micro/Nanorobot Swarm toward Biomedical Applications.

Recently, magnetically actuated micro/nanorobots hold extensive promises in biomedical applications due to their advantages of noninvasiveness, fuel-free operation, and programmable nature. While effectively promised in various fields such as targeted delivery, most past investigations are mainly displayed in magnetic control of individual micro/nanorobots. Facing practical medical use, the micro/nanorobots are required for the development of swarm control in a closed-loop control manner. This review outlines the recent developments in magnetic micro/nanorobot swarms, including their actuating fundamentals, designs, controls, and biomedical applications. The fundamental principles and interactions involved in the formation of magnetic micro/nanorobot swarms are discussed first. The recent advances in the design of artificial and biohybrid micro/nanorobot swarms, along with the control devices and methods used for swarm manipulation, are presented. Furthermore, biomedical applications that have the potential to achieve clinical application are introduced, such as imaging-guided therapy, targeted delivery, embolization, and biofilm eradication. By addressing the potential challenges discussed toward the end of this review, magnetic micro/nanorobot swarms hold promise for clinical treatments in the future.

A global survey of prokaryotic genomes reveals the eco-evolutionary pressures driving horizontal gene transfer

Horizontal gene transfer, the exchange of genetic material through means other than reproduction, is a fundamental force in prokaryotic genome evolution. Genomic persistence of horizontally transferred genes has been shown to be influenced by both ecological and evolutionary factors. However, there is limited availability of ecological information about species other than the habitats from which they were isolated, which has prevented a deeper exploration of ecological contributions to horizontal gene transfer. Here we focus on transfers detected through comparison of individual gene trees to the species tree, assessing the distribution of gene-exchanging prokaryotes across over a million environmental sequencing samples. By analysing detected horizontal gene transfer events, we show distinct functional profiles for recent versus old events. Although most genes transferred are part of the accessory genome, genes transferred earlier in evolution tend to be more ubiquitous within present-day species. We find that co-occurring, interacting and high-abundance species tend to exchange more genes. Finally, we show that host-associated specialist species are most likely to exchange genes with other host-associated specialist species, whereas species found across different habitats have similar gene exchange rates irrespective of their preferred habitat. Our study covers an unprecedented scale of integrated horizontal gene transfer and environmental information, highlighting broad eco-evolutionary trends.

Embodying Deeply Held Values in Education: Seeking a More Equitable World for Both Humans and Non-Humans

Highlights In this article, we contend that the bedrock of an equitable world lies in the profound recognition of love as the fundamental force permeating the cosmos. We believe that love is built into the essence of who we are. We posit that genuine progress toward an equitable world is elusive unless we place love, both for one another and for the natural world, at the core of our educational endeavors.

Upper limit of the solar wind protons backscattering efficiency from Comet 67P/Churyumov-Gerasimenko

Context. Solar wind ions backscattering is a fundamental plasma-surface interaction process that may occur on all celestial bodies exposed to the solar wind and lacking a significant atmosphere or magnetosphere. Yet, observations have been limited to the regolith-covered Moon and Phobos, one of the Martian moons. Aims. We aim to expand our knowledge of the process to include comets by investigating the backscattering of solar wind protons from the surface of comet 67P/Churyumov-Gerasimenko. Methods. We used one of the ion spectrometers on board ESA’s Rosetta spacecraft to search for evidence of backscattered solar wind protons from the cometary surface. The signal of interest was expected to be very weak and several statistical treatments of the data were essential to eliminate any influence from background noise and instrumental effects. Due to limited knowledge of the signal location within the observed parameter space, we conducted a statistical analysis to identify the most probable conditions for detecting the signal. Results. No significant solar wind backscattered protons were ever observed by the instrument. The statement applies to the large spectrum of observation conditions. An upper limit of the backscattered proton flux is given, as well as an upper limit of the backscattering efficiency of 9 × 10−4. Conclusions. The surface of comet 67P/Churyumov-Gerasimenko distinguishes itself as a notably weak reflector of solar wind protons, with its backscattering efficiency, at most, as large as the lowest observed backscattering efficiency from the lunar regolith.

PROBING THE NUCLEAR STRUCTURE OF EXOTIC 33Mg ISOTOPE

Research on the nuclear structure of exotic isotopes, such as 33Mg, is an exciting and cuttingedge field of nuclear physics. Exotic isotopes are typically those that are far from the stable region of the nuclear chart and often exhibit unique properties that can help us better understand the fundamental forces and structure of atomic nuclei. In this paper the largescale shell model calculations are performed within the model spaces SDPFMU, to study the positive- and negative-parity energy levels and electromagnetic transitions in the exotic 33Mg isotope. Core-polarization effects on reduced transition probability are introduced through first order perturbation theory, which allows for higher energy configurations through excitations of nucleons from core orbits to that outside model space up to . The corepolarization effects have been improved the agreement of B(E2) with their corresponding experimental data, and have ignorable effect on B(M1)

Mechanism of high Li-ion conductivity in poly(vinylene carbonate)-poly(ethylene oxide) cross-linked network based electrolyte revealed by solid-state NMR

Solid polymer electrolytes (SPEs) have become increasingly important in advanced lithium-ion batteries (LIBs) due to their improved safety and mechanical properties compared to organic liquid electrolytes. Cross-linked polymers have the potential to further improve the mechanical property without trading off Li-ion conductivity. In this study, focusing on a recently developed cross-linked SPE, i.e., the one based on poly(vinylene carbonate)-poly(ethylene oxide) cross-linked network (PVCN), we used solid-state nuclear magnetic resonance (NMR) techniques to investigate the fundamental interaction between the chain segments and Li ions, as well as the lithium-ion motion. By utilizing homonuclear/heteronuclear correlation, CP (cross-polarization) kinetics, and spin–lattice relaxation experiments, etc., we revealed the structural characteristics and their relations to lithium-ion mobilities. It is found that the network formation prevents poly(ethylene oxide) chains from crystallization, which could create sufficient space for segmental tumbling and Li-ion conduction. As such, the mechanical property is greatly improved with even higher Li-ion mobilities compared to the poly(vinylene carbonate) or poly(ethylene oxide) based SPE analogues.

Storm Impacts on Mineral Mass Accumulation Rates of Coastal Marshes

AbstractCoastal marsh survival may be compromised by sea‐level rise, limited sediment supply, and subsidence. Storms represent a fundamental forcing for sediment accumulation in starving marshes because they resuspend bottom material in channels and tidal flats and transport it to the marsh surface. However, it is unrealistic to simulate at high resolution all storms that occurred in the past decades to obtain reliable sediment accumulation rates. Similarly, it is difficult to cover all possible combinations of water levels and wind conditions in fictional scenarios. Thus, we developed a new method that derives long‐term deposition rates from short‐term deposition generated by a finite number of storms. Twelve storms with different intensity and frequency were selected in Terrebonne Bay, Louisiana, USA and simulated with the 2D Delft3D‐FLOW model coupled with the Simulating Waves Nearshore (SWAN) module. Storm impact was analyzed in terms of geomorphic work, namely the product of deposition and frequency. To derive the long‐term inorganic mass accumulation rates, the new method generates every possible combination of the 12 chosen storms and uses a linear model to fit modeled inorganic deposition with measured inorganic mass accumulation rates. The linear model with the best fit (highest R2) was used to derive a map of inorganic mass accumulation rates. Results show that a storm with 1.7 ± 1.6 years return period provides the largest geomorphic work, suggesting that the most impactful storms are those that balance intensity with frequency. Model results show higher accumulation rates in marshes facing open areas where waves can develop and resuspend sediments. This method has the advantage of considering only a few real scenarios and can be applied in any marsh‐bay system.

Tuning the adsorption of H2O, H2 and O2 molecules on diamond surfaces by B-doping

In this study, the fundamental interactions between the low Miller index (001), (110) and (111) B-doped diamond surfaces and H2O, H2 and O2 molecules, which are commonly present during growth, in ambient air and involved in electrochemical reactions, are investigated by means of ab initio simulations. The results are presented in close comparison with previous studies on undoped diamond surfaces to reveal the impact of B doping. It is demonstrated that the B dopant is preferably incorporated on the topmost carbon layer and enhances the adsorption of H2O by forming a dative bond with O. On the contrary in some cases, it seems to weaken the adsorption of O2, compared to the undoped diamond. Moreover, a noticeable displacement of the surface atoms attached to the fragment of the dissociated H2O and O2 molecules was observed, which can be associated to early stages of wear at the atomistic level. B doping was also found to reduce the energy barriers for water dissociation in most cases, with this effect being most pronounced in the C(111) surfaces. These qualitative and quantitative results aim to provide useful insights for the development of improved protective coatings and electrochemical devices.

Measuring gravity with milligram levitated masses.

Gravity differs from all other known fundamental forces because it is best described as a curvature of space-time. For that reason, it remains resistant to unifications with quantum theory. Gravitational interaction is fundamentally weak and becomes prominent only at macroscopic scales. This means, we do not know what happens to gravity in the microscopic regime where quantum effects dominate and whether quantum coherent effects of gravity become apparent. Levitated mechanical systems of mesoscopic size offer a probe of gravity, while still allowing quantum control over their motional state. This regime opens the possibility of table-top testing of quantum superposition and entanglement in gravitating systems. Here, we show gravitational coupling between a levitated submillimeter-scale magnetic particle inside a type I superconducting trap and kilogram source masses, placed approximately half a meter away. Our results extend gravity measurements to low gravitational forces of attonewton and underline the importance of levitated mechanical sensors.

Fundamental insights and molecular interactions in pancreatic cancer: Pathways to therapeutic approaches

The gastrointestinal tract can be affected by a number of diseases that pancreatic cancer (PC) is a malignant manifestation of them. The prognosis of PC patients is unfavorable and because of their diagnosis at advanced stage, the treatment of this tumor is problematic. Owing to low survival rate, there is much interest towards understanding the molecular profile of PC in an attempt in developing more effective therapeutics. The conventional therapeutics for PC include surgery, chemotherapy and radiotherapy as well as emerging immunotherapy. However, PC is still incurable and more effort should be performed. The molecular landscape of PC is an underlying factor involved in increase in progression of tumor cells. In the presence review, the newest advances in understanding the molecular and biological events in PC are discussed. The dysregulation of molecular pathways including AMPK, MAPK, STAT3, Wnt/β-catenin and non-coding RNA transcripts has been suggested as a factor in development of tumorigenesis in PC. Moreover, cell death mechanisms such as apoptosis, autophagy, ferroptosis and necroptosis demonstrate abnormal levels. The EMT and glycolysis in PC cells enhance to ensure their metastasis and proliferation. Furthermore, such abnormal changes have been used to develop corresponding pharmacological and nanotechnological therapeutics for PC.

Neutrality in plant-herbivore interactions.

Understanding the distribution of herbivore damage among leaves and individual plants is a central goal of plant-herbivore biology. Commonly observed unequal patterns of herbivore damage have conventionally been attributed to the heterogeneity in plant quality or herbivore behaviour or distribution. Meanwhile, the potential role of stochastic processes in structuring plant-herbivore interactions has been overlooked. Here, we show that based on simple first principle expectations from metabolic theory, random sampling of different sizes of herbivores from a regional pool is sufficient to explain patterns of variation in herbivore damage. This is despite making the neutral assumption that herbivory is caused by randomly feeding herbivores on identical and passive plants. We then compared its predictions against 765 datasets of herbivory on 496 species across 116° of latitude from the Herbivory Variability Network. Using only one free parameter, the estimated attack rate, our neutral model approximates the observed frequency distribution of herbivore damage among plants and especially among leaves very well. Our results suggest that neutral stochastic processes play a large and underappreciated role in natural variation in herbivory and may explain the low predictability of herbivory patterns. We argue that such prominence warrants its consideration as a powerful force in plant-herbivore interactions.

Modified Friedmann equations and fractal Black Hole thermodynamics

The general relativity unification and quantum theory is a significant open problem in theoretical physics. This problem arises from the fact that these two fundamental theories, which describe gravity and the behavior of particles at the microscopic level, respectively, are currently incompatible. The unification of these theories is crucial for a complete comprehension of the fundamental forces and the nature of the universe. In this regard, the quantum properties of a Black Hole result in fundamental importance. By analyzing such properties in quantum field theory, in the first step, the gravity enters as a classical background. In semi-classical approximation, Black Holes will emit Hawking radiation with an almost thermal spectrum, while Black Hole’s entropy is proportional to the Black Hole’s horizon. Besides, Hawking’s temperature and Black Hole entropy should follow the first law of Black Hole thermodynamics. Also, Jacobson [Thermodynamics of spacetime: The Einstein equation of state, Phys. Rev. Lett. 75 (1995) 1260, doi:10.1103/PhysRevLett.75.1260] showed shown that there is a connection between Black Hole thermodynamics and Einstein’s equation that opens the root of a potential thermodynamic nature of gravity. This issue opened a new impressive research framework in which the Einstein field equation can be expressed as a form of the first law of thermodynamics and vice versa. In this study, it is assumed that the universe has a fractal structure. Accordingly, modified Friedmann’s equations and the Black Holes thermodynamics in a fractal universe have been examined. The fractal framework shows what features and changes occur in the description of the universe, particularly in studying the thermodynamics of a Black Hole. However, the paper strategy is organized as follows: in the beginning, we consider the first thermodynamic law in a fractal universe. Then, we investigate the Friedmann equation of the fractal universe in the form of the entropy balance, this means [Formula: see text], where [Formula: see text] and [Formula: see text] are the thermal energy and horizon temperature. We consider the entropy [Formula: see text] have two terms; (1) obeys the usual area law and (2) the entropy production term due to the non-equilibrium thermodynamics of a fractal universe. Therefore, in a fractal universe, a term with non-equilibrium thermodynamics of spacetime may be needed. Also, we study the generalized second law of thermodynamics in a fractal universe. When the temperature of the apparent horizon and the temperature of the matter fields inside the horizon are equal, i.e. [Formula: see text], the second law of generalized thermodynamics can be obtained according to the state parameter range equation, which is consistent with the recent observations. Finally, in Sec. 6, based on the mathematical calculations, we study the various cosmological parameters such as the Hubble parameter, scale factor, deceleration parameter and equation of state parameter.

Cholesterols Induced Distinctive Entry of the Graphene Nanosheet into the Cell Membrane.

Graphene nanosheets are highly valued in the biomedical field due to their potential applications in drug delivery, biological imaging, and biosensors. Their biological effects on mammalian cells may be influenced by cholesterols, which are crucial components in cell membranes that take part in many vital processes. Therefore, it is particularly important to investigate the effect of cholesterols on the transport mechanism of graphene nanosheets in the cell membrane as well as the final stable configuration of graphene, which may have an impact on cytotoxicity. In this paper, the molecular details of a graphene nanosheet interacting with a 1,2-dipalmitoyl-sn-glycero-3-phosphorylcholine (DPPC) membrane with cholesterols were studied using molecular dynamics simulations. Results showed that the structure of the graphene nanosheet transits from the cut-in state in a pure DPPC membrane to being sandwiched between two DPPC leaflets when cholesterols reach a certain concentration. The underlying mechanism showed that cholesterols are preferentially adsorbed on the graphene nanosheet, which causes a larger disturbance to the nearby DPPC tails and thus guides the graphene nanosheet into the core of lipid bilayers to form a sandwiched structure. Our results are helpful for understanding the fundamental interaction mechanism between the graphene nanosheet and cell membrane and to explore the potential applications of the graphene nanosheet in biomedical sciences.

Institute for Artificial Intelligence and Fundamental Interactions (IAIFI): Infusing physics intelligence into artificial intelligence

AbstractThe NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI, pronounced /aI‐faI/) is one of the inaugural NSF AI research institutes (https://iaifi.org). The IAIFI is enabling physics discoveries and advancing foundational AI through the development of novel AI approaches that incorporate first principles from fundamental physics. By combining state‐of‐the‐art research with early career talent and a growing AI + physics community in the Boston area and beyond, the IAIFI is enabling researchers to develop AI technologies to tackle some of the most challenging problems in physics, and transfer these technologies to the broader AI community. Since trustworthy AI is as important for physics discovery as it is for other applications of AI in society, IAIFI researchers are applying physics principles to develop more robust AI tools and to illuminate existing AI technologies. To cultivate human intelligence, the IAIFI promotes training, education, and public engagement at the intersection of physics and AI. In these ways, the IAIFI is fusing deep learning with deep thinking to gain a deeper understanding of our universe and AI.

Energy management of electric vehicle using a new strategy based on slap swarm optimization and differential flatness control

Optimal energy management of electric vehicles using slap swarm optimization and differential flatness control has been proposed. A battery–supercapacitor power system is adopted. Each source is connected in parallel to the DC-bus using DC–DC bidirectional converters and supplies a synchronous reluctance motor (SynRM) based drive. The proposed EMS fundamental forces lie in using a combination of complementary proprieties of two approaches, a Slap Swarm optimization Algorithm and Differential Flatness (DF). With a fast optimization mechanism, the Slap Swarm optimization algorithm allows adapting in real-time conditions the DF gains to optimize the system performances. On its side, DF uses predefined trajectories respecting the physical proprieties of the system, which is a powerful tool to guarantee the dynamic constraints of the sources when ensuring desired robust control proprieties. To check the feasibility and performance of the suggested EMS, comprehensive processor-in-the-loop co-simulations of the electric vehicle were carried out using the C2000 launchxl-f28379d DSP board. The main goal of the proposed EMS is to guarantee the DC-bus stabilization, reducing the DC-bus voltage ripples (Δv = 5 V) and the voltage overshoots 15 V (3.2%), respect the source dynamics, and satisfy the SynRM motor power demand. Furthermore, the algorithm minimizes induced harmonics by the drive (10.49%), reducing the battery current ripple by 17.15A, thereby enhancing the battery lifecycle.

Nonextensive statistics and the entropy on the horizon

We explore the application of nonextensive Bose statistics to describe the behavior of an ideal gas near the horizon of black holes, presenting a compelling case for its efficacy as an effective theory for interacting bosons. The central focus is on the careful selection of a nonextensive parameter, a critical aspect that enables the derivation of the correct entropy on the black hole horizon. Remarkably, this approach aligns with the well-established Bekenstein–Hawking entropy, showcasing the utility of nonextensive Bose statistics in capturing the thermodynamic properties of particles near black hole horizons. The study contributes to our understanding of fundamental interactions in extreme gravitational environments and provides a novel perspective on the statistical mechanics of black hole thermodynamics.