The spectral characteristics of dextran, labeled with fluorescein, depend upon pH. We have loaded the lysosomes of mouse peritoneal macrophages with this fluorescence probe and used it to measure the intralysosomal pH under various conditions. The pH of the medium has no effect on the intralysosomal pH. Weakly basic substances in the medium cause a concentration-dependent increase in the intralysosomal pH. However, the concentration of base necessary to produce a significant change in the intralysosomal pH varies over a wide range for different bases. The active form of the base is the neutral, unprotonated form. Although most of these weak bases cause an increase in the volume of the lysosomes, increase in lysosomal volume itself causes only a minor perturbation of the intralysosomal pH. This was demonstrated in cells whose lysosomes were loaded with sucrose, and in cells vacuolated as a demonstrated in cells whose lysosomes were loaded with sucrose, and in cells vacuolated as a consequence of exposure to concanavalin A. The results of these studies are interpreted in terms of energy-dependent lysosomal acidification and leakage of protons out of the lysosomes in the form of protonated weak bases.
Simon Richard Goorney, Emre Aslan, Aleksandrs Baskakovs
et al.
As quantum technologies (QT) move from foundational research toward industrial and societal deployment, national strategies have become critical instruments for shaping the future of this emerging field. In this study, we conduct the first large-scale, data-driven analysis of 62 national quantum strategic documents (QSDs) from 20 countries. Using AI-based natural language processing (topic modeling), we identify 12 topics present in the text, ranging from technical development areas to transversal aspects such as workforce development and governance. Temporal analysis reveals a distinct shift in policy discourse toward applications of QT and commercialisation, and relatively away from basic science. Our findings highlight the increasing diversification of the QT field, and contribute to the growing area of quantum policy studies. We advocate for more AI and data-driven analyses of the quantum ecosystem, to work toward a scalable framework for understanding the technological and societal challenges of the second quantum revolution.
In a network, the vertices with similar characteristics construct communities. The vertices in a community are well-connected. Detecting the communities in a network is a challenging and important problem in the theory of complex networks. One approach to solving this problem uses the classical random walks on graphs. In quantum computing, quantum walks are the quantum mechanical counterparts of classical random walks. In this article, we employ a variant of Szegedy's quantum walk to develop a procedure for discovering the communities in networks. The limiting probability distribution of quantum walks assists us in determining the inclusion of a vertex in a community. We apply our community detection procedure to a variety of graphs and social networks, including the relaxed caveman graph, $l$-partition graph, Karate club graph, and the dolphin's social network, among others.
This paper presents a comprehensive review of the Social Laser Theory (SLT) as a natural extension of the broader framework of Quantum-Like Modeling (QLM). While QLM applies the mathematical formalism of quantum theory . such as Hilbert space representations, interference, and non-commutative observables - to model context-dependent and non-classical phenomena in cognition, decision-making, and social behavior, SLT advances this approach by integrating concepts from quantum field theory. The theory conceptualizes social systems as ensembles of social atoms capable of absorbing and emitting quantized units of social energy. Under conditions analogous to population inversion in physical lasers, external informational stimuli (e.g., media signals or mobilizing rhetoric) can trigger coherence across the population, resulting in large-scale, synchronized collective actions such as protests or ideological shifts. SLT thus provides a formal framework for understanding the amplification and coherence of social energy leading to abrupt phase-like transitions in collective behavior. Beyond its metaphorical appeal, the theory proposes measurable quantities and predictive parameters that may support empirical diagnostics of sociopolitical dynamics. By bridging micro-level psychological processes with macro-level sociological phenomena, SLT extends QLM into the domain of complex social systems, offering a mathematically grounded paradigm for interpreting rapid transformations in contemporary societies.
We propose a kinetic model to describe the dynamical evolution of wealth and knowledge in national and global markets, starting from a microscopic description of individual interactions. The model is built upon interaction rules that account for a strong interdependence between the microscopic variables, influencing agents' trading and saving propensities, knowledge acquisition, and the stochastic market effects. We begin with a domestic market scenario and extend the framework to international trade, incorporating the possibility of individual transfers between different countries. The dynamics of the system are described through Boltzmann-type equations, which allow for a detailed study of the evolution of the agent distribution in each country. In this context, we study the evolution of macroscopic quantities of the system, focusing on the number density of individuals, and the mean wealth and knowledge of each population, and we discuss these results in relation to existing models in the literature. Finally, under a quasi-invariant trading limit, we derive simplified Fokker-Planck type equations that reveal some emergent behaviors of the system, including the formation of Pareto tails in the long-term wealth and knowledge distributions.
Founded in 2007, the Foothill College Physics Show has served nearly a quarter of a million attendees in the two decades that have followed. This demo show features both performances for the public and field trips for students from local Title 1 schools. The college's students play an important role, acting as both on-stage talent, leading tours of the college, and helping build equipment. From a small beginning, it now hosts over twenty-five thousand attendees a year, and is an important part of the college's outreach efforts.
Collective synchronization in complex systems arises from the interplay between topology and dynamics, yet how to design and control such patterns in higher-order networks remains unclear. Here we show that a Dirac spectral programming framework enables programmable topological cluster synchronization on directed hypergraphs. By encoding tail-head hyperedges into a topological Dirac operator and introducing a tunable mass term, we obtain a spectrum whose isolated eigenvalues correspond to distinct synchronization clusters defined jointly on nodes and hyperedges. Selecting a target eigenvalue allows the system to self-organize toward the associated cluster state without modifying the underlying hypergraph structure. Simulations on directed-hypergraph block models and empirical systems--including higher-order contact networks and the ABIDE functional brain network--confirm that spectral selection alone determines the accessible synchronization patterns. Our results establish a general and interpretable route for controlling collective dynamics in directed higher-order systems.
Gerliz M. Gutiérrez-Finol, Aman Ullah, María González-Béjar
et al.
As scientists living through a climate emergency, we have a responsibility to lead by example, or to at least be consistent with our understanding of the problem. This common goal of reducing the carbon footprint of our work can be approached through a variety of strategies. For theoreticians, this includes not only optimizing algorithms and improving computational efficiency but also adopting a frugal approach to modeling. Here we present and critically illustrate this principle. First, we compare two models of very different level of sophistication which nevertheless yield the same qualitative agreement with an experiment involving electric manipulation of molecular spin qubits while presenting a difference in cost of $>4$ orders of magnitude. As a second stage, an already minimalistic model of the potential use of single-ion magnets to implement a network of probabilistic p-bits, programmed in two different programming languages, is shown to present a difference in cost of a factor of $\simeq 50$. In both examples, the computationally expensive version of the model was the one that was published. As a community, we still have a lot of room for improvement in this direction.
Sanjay Vishwakarma, Vishal Sharathchandra Bajpe, Ryan Mandelbaum
et al.
Quantum computing is an emerging technology whose positive and negative impacts on society are not yet fully known. As government, individuals, institutions, and corporations fund and develop this technology, they must ensure that they anticipate its impacts, prepare for its consequences, and steer its development in such a way that it enables the most good and prevents the most harm. However, individual stakeholders are not equipped to fully anticipate these consequences on their own it requires a diverse community that is well-informed about quantum computing and its impacts. Collaborations and community-building across domains incorporating a variety of viewpoints, especially those from stakeholders most likely to be harmed, are fundamental pillars of developing and deploying quantum computing responsibly. This paper reviews responsible quantum computing proposals and literature, highlights the challenges in implementing these, and presents strategies developed at IBM aimed at building a diverse community of users and stakeholders to support the responsible development of this technology.
The study of Opinion Dynamics, which explores how individual opinions and beliefs evolve and how societal consensus is formed, has been examined across social science, physics, and mathematics. Historically based on statistical physics models like the Ising model, recent research integrates quantum information theory concepts, such as Graph States, Stabilizer States, and Toric Codes. These quantum approaches offer fresh perspectives for analyzing complex relationships and interactions in opinion formation, such as modeling local interactions, using topological features for error resistance, and applying quantum mechanics for deeper insights into opinion polarization and entanglement. However, these applications face challenges in complexity, interpretation, and empirical validation. Quantum concepts are abstract and not easily translated into social science contexts, and direct observation of social opinion processes differs significantly from quantum experiments, leading to a gap between theoretical models and real-world applicability. Despite its potential, the practical use of the Toric Code Hamiltonian in Opinion Dynamics requires further exploration and research.
María T. Soto-Sanfiel, Chin-Wen Chong, José I. Latorre
An interpretive phenomenological approach is adopted to investigate scientists' attitudes and practices related to hype in science communication. Twenty-four active quantum physicists participated in 5 focus groups. Through a semi-structured questionnaire, their use of hype, attitudes, behaviours, and perspectives on hype in science communication were observed. The main results show that scientists primarily attribute hype generation to themselves, major corporations, and marketing departments. They see hype as crucial for research funding and use it strategically, despite concerns. Scientists view hype as coercive, compromising their work's integrity, leading to mostly negative feelings about it, except for collaborator-generated hype. A dissonance exists between scientists' involvement in hype, their opinions, and the negative emotions it triggers. They manage this by attributing responsibility to the academic system, downplaying their practices. This reveals hype in science communication as a calculated, persuasive tactic by academic stakeholders, aligning with a neoliberal view of science. Implications extend to science communication, media studies, regulation, and academia.
The rapid advancement of technology underscores the critical importance of robustness in complex network systems. This paper presents a framework for investigating the structural robustness of interconnected network models. This paper presents a framework for investigating the structural robustness of interconnected network models. In this context, we define functional nodes within interconnected networks as those belonging to clusters of size greater than or equal to $s$ in the local network, while maintaining at least $M$ significant dependency links. This model presents precise analytical expressions for the cascading failure process, the proportion of functional nodes in the stable state, and a methodology for calculating the critical threshold. The findings reveal an abrupt phase transition behavior in the system following the initial failure. Additionally, we observe that the system necessitates higher internal connection densities to avert collapse, especially when more effective support links are required. These results are validated through simulations using both Poisson and power-law network models, which align closely with the theoretical outcomes. The method proposed in this study can assist decision-makers in designing more resilient reality-dependent systems and formulating optimal protection strategies.
The possibility of direct air capture of CO$_2$ in Antarctica is discussed. Because the concentration of H$_2$O in the atmosphere during the Antarctic winter is extremely low, an installation for direct air capture could employ a physisorption-based process, allowing, in principle, a very short adsorption/desorption cycle time. The lower required binding allows more options for materials for the sorbent. With a shorter cycle time, more resource could be spent on structuring the sorbent to improve energy efficiency, for example by improving its mass efficiency if desorption is driven thermally.