Physics and Society
Beyond the Wisdom of the Crowd: How Network Topology Distorts Collective Perception
Giovanni Palermo, Vittorio Loreto and Giulio Cimini
Cognitive biases are often attributed to heuristics or limited information. Yet the structure of social networks is a key, often-overlooked source of perceptual bias. When information passes through social connections, the network alone can systematically distort how individuals view society. We use a simple model in which
agents have a binary attribute (e.g., atheist or believer) and show that network
topology alone can cause misperceptions of peers' attributes. These misperceptions persist even after aggregation and challenge the idea of the "wisdom of the crowd." We derive an
estimator that predicts the size and direction of these biases from network features. We validate our findings using three large-scale opinion surveys. Our results show that network structure is a critical factor in collective perception, with major implications for reducing segregation, polarisation, and the marginalisation of minorities.
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Atmospheric and Oceanic Physics · Cross-listed from eess.SP
Assessing Ionospheric Scintillation Risk for Direct-to-Cellular Satellite Communications using Frequency-Scaled GNSS Observations
Abdollah Masoud Darya and Muhammad Mubasshir Shaikh
One of the key issues facing Direct-to-Cellular (D2C) satellite communication systems is ionospheric scintillation on the uplink and downlink, which can significantly degrade link quality. This work investigates the spatial and temporal characteristics of amplitude scintillation at D2C frequencies by scaling L-band scintillation observations from Global
Navigation Satellite Systems (GNSS) receivers to bands relevant to D2C operation, including the low-band, and 3GPP's N255 and N256. These observations are then compared to scaled
radio-occultation scintillation observations from the FORMOSAT-7/
COSMIC-2 (F7/C2) mission, which can be used in regions that do not possess ground-based scintillation monitoring stations. As a proof of concept, five years of ground-based GNSS scintillation data from Sharjah, United Arab Emirates, together with two years of F7/C2 observations over the same region, corresponding to the ascending phase of
Solar Cycle 25, are analyzed. Both space-based and ground-based observations indicate a pronounced diurnal scintillation peak between 20–22 local time, particularly during the equinoxes, with occurrence rates increasing with
solar activity. Ground-based observations also reveal a strong azimuth dependence, with most scintillation events occurring on southward satellite links. The scintillation occurrence rate at the low-band is more than twice that observed at N255 and N256, highlighting the increased robustness of higher D2C bands to ionospheric scintillation. These results demonstrate how GNSS scintillation observations can be leveraged to characterize and anticipate scintillation-induced D2C link impairments, which help in D2C system design and the implementation of scintillation mitigation strategies.
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Fluid Dynamics · Cross-listed from cond-mat.soft
Reverse segregation in dense granular flow through narrow vertical channel
Bhanjan Debnath
Controlling flow-induced segregation in a granular mixture is highly relevant to many industrial settings. To enhance mixing or promote segregation, the continuous
gravity flow of a bidisperse granular mixture through a series of narrow vertical channels with exit slots is investigated. The bidisperse mixture is composed of two different sizes of particles, but of the same density. In dense flow, segregation occurs, leading to formation of bands. The bands of large particles appear at a distance away from the walls. This finding is in contrast to that in shear-driven segregation in a dense flow where large particles segregate towards the walls. Using a phenomenological model, it has been shown that rolling and bouncing induced segregation is the dominant mechanism. When cylindrical inserts are placed to modify flow patterns, that significantly influences segregation patterns. The symmetrical placement of a cylindrical insert close to the exit slot vanishes the bands and enhances mixing. However, with two inserts placed symmetrically and close to the exit slot, the degree of segregation in the reverse direction is greatly enhanced compared to that without insert. In the former, small particles accumulate in thin regions adjacent to the walls, and large particles comprise the bulk of the domain and the flowing stream. The heap formation above the insert in a narrow channel, when the insert is close to the exit, enhances mixing in one configuration, whereas it amplifies reverse segregation in the other.
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Fluid Dynamics
Conversions between kinetic and surface energy in periodically forced multiphase turbulence
Jonathan Vahé and Fabien Thiesset
In multiphase flows, kinetic and interfacial energies coexist, and their mutual conversion can potentially influence the overall energy balance. However, in statistically steady flows these energy reservoirs remain constant, making such conversions undetectable. For them to be observed, a degree of unsteadiness must be introduced, here provided by the deliberate use of a fluctuating time-periodic input of kinetic energy into the system. The main focus of the present work is on the dynamical cycle connecting energy injection, conversion, and dissipation which we explore using {direct} numerical simulations of multiphase homogeneous isotropic
turbulence, subjected to periodic forcing. The database includes various Reynolds and Weber numbers and volume fractions in the dense regime. To interpret and replicate the observed dynamics, we reformulate the Ka-Pi-bara model of \cite{Bos2026} (an extension of the $k$–$\epsilon$ model) in terms of total energy (the sum of kinetic and surface energy), which we further enhance by adding equations for the surface energy and its destruction. This model accurately captures a key feature of
turbulence: non-
equilibrium effects, seen as the phase lag between kinetic energy and its rate of dissipation, which are found to operate also in multiphase flows. Linearizing the model highlights the various relevant time scales of the system and provides predictions of how different observables are coupled and respond to the energy input.
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Atomic Physics
Breit corrections to moderately charged ions in all-orders calculations
Andoni Skoufris and Benjamin M. Roberts
The atomic properties of heavy, moderately-charged ions are important for a wide variety of applications, including precision tests of fundamental physics and for the study and development of atomic and
nuclear clocks. In these systems it is known that relativistic effects, such as the Breit interaction and radiative
quantum electrodynamics corrections, are important for an accurate understanding of atomic properties. It is also known that inclusion of correlations alongside the Breit effect is crucial. In this work we include the Breit interaction into all-orders calculations of energy levels and fine structure intervals of ions in the Cs and Fr isoelectronic sequences. This requires modifying the electron Green's function to account for Breit within the all-orders correlation potential method, which sums dominating series of perturbation diagrams exactly using a Feynman diagram technique. We find that Breit corrections to the energies of moderately ionized ions along these sequences are very large, particularly for the f states. We also observe a significant deviation from experiment for these levels. Incorporating Breit into the all-orders correlation potential provides a significant additional contribution beyond including Breit at the second-order level alone. While this does not resolve the disagreement in the energy levels, it does substantially improve the fine-structure intervals beyond what is achieved by including Breit only at second order. Furthermore, we include the frequency-dependent Breit interaction into the Dirac-Fock procedure, and find that this does not significantly modify the energy levels at this order of approximation.
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Instrumentation and Detectors
Measurement of ionization yield of low energy ions in low pressure $\mathrm{CF}_{4}$ gas for dark matter searches
Satoshi Higashino, Wakako Toyama, Takuya Shiraishi et al. (+3 more)
Direction-sensitive direct dark matter search experiments have been conducted using gaseous detectors. In spite of the long history of the study on the energy deposition of charged particles in materials, a full agreement between the measured results and theoretical predictions, especially in a low energy scale, are yet to be achieved. It is thus important to measure the ionization yields of
recoil nuclei for the experiments with gaseous detectors using an ionization charge readout scheme. This study measured the ionization yield using a low-energy ion beam facility at Kanagawa University. The ionization yields for fluorine ions with an energy range of 5 $\sim$ 50 keV were measured using a dedicated proportional wire chamber filled with $\mathrm{CF}_{4}$ gas at 0.06 atm. The low-energy ion injection scheme into a gaseous detector was established and the ionization yield for fluorine ions was obtained to be 0.45 at 30 keV with a moderate dependence on the ion energy.
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All authors Satoshi Higashino, Wakako Toyama, Takuya Shiraishi, Yasushi Hoshino, Tatsuhiro Naka, Kentaro Miuchi
Geophysics
Data-driven sequential analysis of tipping in high-dimensional complex systems
Tomomasa Hirose and Yohei Sawada
Abrupt transitions ("tipping") in nonlinear dynamical systems are often accompanied by changes in the geometry of the attracting set, but quantifying such changes from partial and noisy observations in high-dimensional systems remains challenging. We address this problem with a sequential diagnostic framework, Data Assimilation-High dimensional Attractor's Structural Complexity (DA-HASC). First, this method reconstructs system's high-dimensional state using data assimilation from limited and noisy observations. Second, we quantify a structural complexity of the high-dimensional system dynamics from the reconstructed state by
manifold learning. Third, we capture underlying changes in the system by splitting the reconstructed timeseries into sliding windows and analyzing the changes in the temporally local attractor's structural complexity. The structural information is provided as graph
Laplacian and measured by Von Neumann
entropy in this framework. We evaluate DA-HASC on both synthetic and real-world
datasets and demonstrate that it can detect tipping under high-dimensionality and imperfect system knowledge. We further discuss how this framework behaves across different tipping mechanisms.
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Computational Physics · Cross-listed from cs.LG
Synergizing Transport-Based Generative Models and Latent Geometry for Stochastic Closure Modeling
Xinghao Dong, Huchen Yang and Jin-long Wu
Diffusion models recently developed for generative AI tasks can produce high-quality samples while still maintaining diversity among samples to promote mode coverage, providing a promising path for learning
stochastic closure models. Compared to other types of generative AI models, such as GANs and VAEs, the sampling speed is known as a key disadvantage of
diffusion models. By systematically comparing transport-based generative models on a numerical example of 2D Kolmogorov flows, we show that flow matching in a lower-dimensional latent space is suited for fast sampling of
stochastic closure models, enabling single-step sampling that is up to two orders of magnitude faster than iterative
diffusion-based approaches. To control the latent space distortion and thus ensure the physical fidelity of the sampled closure term, we compare the implicit regularization offered by a joint training scheme against two explicit regularizers: metric-preserving (MP) and geometry-aware (GA) constraints. Besides offering a faster sampling speed, both explicitly and implicitly regularized latent spaces inherit the key topological information from the lower-dimensional
manifold of the original complex dynamical system, which enables the learning of
stochastic closure models without demanding a huge amount of training data.
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Fluid Dynamics
Order of Magnitude Analysis and Data-Based Physics-Informed Symbolic Regression for Turbulent Pipe Flow
Yunus Emre Ünal, Özgür Ertunç, Ismail Ari et al. (+1 more)
Friction losses in rough pipes are often predicted using semi-empirical correlations, such as the Colebrook-White equation (Colebrook,1939), which do not fully replicate Nikuradse's rough-pipe experiments (1950). This study derives scaling relations for the viscous and turbulent contributions to the streamwise pressure drop through an order-of-magnitude analysis of the Reynolds-averaged Navier-Stokes equations and the kinetic-energy transport equations. These relations impose constraints on the local sensitivity of the pressure drop to factors such as mean velocity, roughness, viscosity, and density through exponent envelopes and serve as a physical prior for symbolic regression. By combining Nikuradse's rough-pipe and smooth-pipe data of Zagarola and Smits (1998), we aim to derive compact correlations for the friction factor that fit experimental data while adhering to the derived constraints. A modified genetic programming engine (GPTIPS2) optimizes model structure and evaluates it based on fitness, complexity, and constraint violation. This method yields interpretable expressions that accurately reproduce friction factors across various roughness levels and Reynolds numbers, validated up to $Re \sim 10^7$.
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All authors Yunus Emre Ünal, Özgür Ertunç, Ismail Ari, Ivan Otić
Fluid Dynamics
Fluid viscoelasticity controls acoustic streaming via shear waves
T. Sujith and A. K. Sen
Control of acoustic streaming can significantly impact fluid and particle transport in microfluidics. We report enhancement, suppression, and reversal of acoustic streaming inside a rectangular microchannel by controlling the fluid viscoelastic properties. Our study reveals that the streaming regimes depend on Deborah number ($De$) and viscous
diffusion number ($Dv$), expressed in terms of a Streaming Coefficient ($C_s$). We find streaming is enhanced when $C_s>1$, suppressed for $0\leq C_s\leq1$, and reversed when $C_s<0$. We explain the regimes in terms of the interplay between the Reynolds and viscoelastic stresses that collectively drive fluid motion. Remarkably, we discover the role of viscoelastic shear waves in acoustic streaming transition characterized by the ratio of acoustic attenuation length and shear wavelength. We gain deeper insight into the streaming transition by examining energy dynamics in terms of the loss and storage
moduli. Our study may find applications in acousto-microfluidics systems for particle handling and fluid pumping/mixing.
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Optics
Full-Field Metasurface Characterization with Polarization Sensitive Coherent Modulation Imaging
Xinjie Sun, Xin Liu, Zixin Cai et al. (+3 more)
Characterizing the intensity, phase, and polarization of engineered light is fundamental to understanding and applying metasurfaces. However, existing characterization frameworks are hindered by several limitations, most notably their inability to account for the polarization of the field. Here, we report polarization sensitive coherent modulation imaging (PS-CMI), a light-weight but robust, high-resolution platform for the full-field characterization of metasurface-modulated light. By supplementing the orthogonal x- and y- complex amplitude components with an additional 45{\deg}-component, this approach calculates the retardance between two orthogonal polarization components while eliminating phase offsets, thereby enabling the subsequent recovery of the complete polarization state. We demonstrate the versatility of our method by characterizing light fields produced by a United States Air Force (USAF) target, two kinds of complex polarization field, and a metalens. This compact solution addresses a critical gap in metasurface metrology and is broadly applicable to other fields requiring the mapping of complex, polarized light distributions.
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All authors Xinjie Sun, Xin Liu, Zixin Cai, Yanghui Li, Xu Liu, Xiang Hao
Fluid Dynamics
Evaporation of a freely floating droplet in an airstream: effects of temperature, humidity, and shape oscillations
Shubham Chakraborty, Someshwar Sanjay Ade, Aman John Tudu et al. (+2 more)
We present a comprehensive experimental and theoretical investigation of the evaporation dynamics of freely levitated water droplets in an upward airstream under varying temperature and relative humidity conditions, using a custom-designed wind tunnel that replicates natural rainfall scenarios. A high-speed imaging system captures the temporal
evolution of morphology, shape oscillations, and size reduction of the droplet undergoing evaporation. Our observations reveal that larger droplets exhibit persistent shape oscillations due to the interplay between inertia and surface tension in the presence of convective airflow, which significantly alters the evaporation rate compared to that of a stationary spherical droplet in quiescent air. To quantify the effects of air convection, complex morphology, and shape oscillations of the levitated droplet at different temperatures and humidity, we develop a modified evaporation model that extends the classical $d^2$-law. This model incorporates (i) a generalized Sherwood number that accounts for the variation in Reynolds number, Schmidt number, temperature, and relative humidity and (ii) a shape factor that captures the time-averaged surface area of oscillating droplets. The model is validated against experimental findings across a wide range of droplet sizes and environmental conditions, showing excellent agreement in predicting the temporal
evolution of droplet diameter and total evaporation time. Furthermore, we construct a regime map showing the variation in the lifetime of the droplet in the temperature-humidity space. The present study establishes a framework that integrates convective transport and morphological deformation, offering new insights into the microphysics of raindrop evaporation.
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All authors Shubham Chakraborty, Someshwar Sanjay Ade, Aman John Tudu, Lakshmana Dora Chandrala, Kirti Chandra Sahu
Optics
Carlo Silvestri, Aleksandar D. Rakić, Dragan Indjin et al. (+46 more)
Quantum cascade
lasers (QCLs) are unipolar
semiconductor lasers first demonstrated in 1994. Since then, they have played a central role in advancing mid-infrared and terahertz photonics, becoming among the most reliable light sources in these regions of the electromagnetic spectrum. Their importance is further reinforced by their ability to generate self-starting optical frequency combs, whose investigation is motivated both by fundamental physics and by a wide range of applications, including molecular spectroscopy and free-space optical communications. This Roadmap provides a unified overview of current advances and emerging directions in QCL research. The chapters are organized into three main sections: device design and technology; frequency combs and pulse formation; and applications of QCLs. Each chapter reviews the relevant background, summarizes the current state of the art, and identifies key challenges and future directions within its specific research area.
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All authors Carlo Silvestri, Aleksandar D. Rakić, Dragan Indjin, Ali Khalatpour, Christian Jirauschek, Aleksandar Demic, Zoran Ikonic, Paul Dean, Nikola Vuković, Jelena Radovanović, Lianhe Li, Edmund Linfield, Michael Jaidl, Karl Unterrainer, Giacomo Scalari, Jérôme Faist, Lorenzo Luigi Columbo, Massimo Brambilla, Marco Piccardo, Sukhdeep Dhillon, Mithun Roy, David Burghoff, Karl Bertling, Jari Torniainen, Xiaoqiong Qi, Thomas Taimre, Olivier Spitz, Frédéric Grillot, Marilena Giglio, Angelo Sampaolo, Pietro Patimisco, Vincenzo Spagnolo, Eva A. A. Pogna, Xiao Guo, Rainer Hillenbrand, Mengkun Liu, Michael Brünig, Adrian Cernescu, Alexander A. Govyadinov, Tecla Gabbrielli, Jacopo Pelini, Irene La Penna, Alessia Sorgi, Paolo De Natale, Davide Mazzotti, Iacopo Galli, Luigi Consolino, Francesco Cappelli, Simone Borri
Optics
Integrated Photonic Polarization Synthesizer and Analyzer
Carson G. Valdez, Anne R. Kroo, Anna J. Miller et al. (+3 more)
Polarization-resolved control and measurement of the optical field are essential for a wide range of photonic systems, including coherent communication, polarimetric sensing, and
quantum information processing. We present a photonic integrated
circuit that enables the generation and analysis of arbitrary polarization states. The device provides reconfigurable access to the full polarization degree of freedom of coherent light within a single integrated platform. We experimentally demonstrate arbitrary polarization state generation spanning the Poincare sphere, as well as Stokes vector measurement on chip. Unlike conventional Stokes measurements that rely on direct detection, polarization analysis utilizing this architecture is intrinsically non-destructive, preserving the optical signal for further optical domain processing. The devices are fabricated in a commercial foundry using CMOS-compatible processes, enabling scalable and reproducible integration. By combining polarization generation and analysis in a compact and stable photonic
circuit, this work eliminates the need for external polarization optics and provides a foundation for robust, polarization-enabled photonic integrated systems.
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All authors Carson G. Valdez, Anne R. Kroo, Anna J. Miller, Charles Roques-Carmes, David A. B. Miller, Olav Solgaard
Optics
Self-referenced, drift-tolerant dipole-resolved population inversion using degeneracy-lifted dual quasinormal modes
Jiaxin Yu, Xinyu Zhang, Guangyu Dai et al. (+3 more)
Photoluminescence intensity is widely used to infer
exciton populations, yet the detected signal inherently convolves occupancy with radiative-rate modification and collection efficiency, making quantitative inversion vulnerable to pump and system drifts. Here we realize a dual-channel self-referenced scheme enabled by two nearly degenerate quasinormal modes in a hybrid microcavity. Their shared optical path provides common-mode observables (i.e., overall spectral and intensity drift) that track global thermo-optic and pump fluctuations, while their differential-mode observables (i.e., spectral splitting and mode-contrasted emission) remain highly sensitive to local gap dielectric perturbations and dipole-dependent radiative weights. Using temperature as a control parameter in monolayer WSe$ _2 $, we exploit this common/differential-mode framework to robustly invert the relative populations of
excitons with out-of-plane ($ \perp $) and in-plane ($ \parallel $) dipole transitions without external absolute calibration. At the temperature of $\sim$50 K, we obtain $ N_\perp/N_\parallel \approx 200 $, coincident with the expected accumulation in the out-of-plane-emitting dark
manifold. This internally referenced approach provides a practical route to drift-tolerant, dipole-resolved population metrology in nanogap photonic systems.
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All authors Jiaxin Yu, Xinyu Zhang, Guangyu Dai, Shuai Xing, Minghui Yang, Fuxing Gu
Accelerator Physics · Cross-listed from cond-mat.supr-con
Power attenuation in millimeter-wave and terahertz superconducting rectangular waveguides: linear response, TLS loss, and Higgs-mode nonlinearity
Takayuki Kubo
Superconducting waveguides are a promising platform for ultralow-loss transmission in the millimeter-wave to terahertz band under cryogenic conditions, with potential applications in astronomical instrumentation and emerging
quantum technologies. We develop a framework, based on microscopic superconductivity theory, to evaluate the power-flow attenuation constant $\alpha$ of superconducting rectangular waveguides in the $100~\mathrm{GHz}$–THz range, applicable to arbitrary electronic mean free paths $\ell$ from the dirty limit $\ell\ll\xi_0$ to the clean limit $\ell\gg\xi_0$. We also derive an analytical expression for two-level-system (TLS)-induced attenuation $\alpha_{\rm TLS}$ in thin native
oxide layers within the standard TLS model. Using this framework, we perform numerical evaluations of $\alpha$ for representative materials over standard waveguide sizes from WR15 to WR1. In the high-frequency regime $f \gtrsim 0.5 \Delta/h$, low attenuation favors the clean regime $\ell\gtrsim\xi_0$, indicating that high-purity materials can achieve very low attenuation below their gap frequency. For the TLS contribution, using parameter values representative of native Nb
oxides, we find that $\alpha_{\rm TLS}$ can become relevant at sufficiently low temperatures $T/T_c\lesssim 0.1$-0.2, where quasiparticle dissipation is exponentially suppressed. Finally, we extend the discussion to the strong-excitation regime using a recently developed nonlinear-response theory within the Keldysh–Usadel framework of nonequilibrium superconductivity and show that nonlinear dissipation produces a
Higgs-mode peak in $\alpha$ near $f\simeq \Delta/h$ via a Kerr-type nonlinearity of the dissipative conductivity. This peak provides a distinct hallmark of the
Higgs mode that has been largely overlooked so far.
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Medical Physics
Radiological mapping and uncertainty quantification by a fast Microcanonical Langevin Monte Carlo sampler
Lei Pan, Jaewon Lee, Brian J. Quiter et al. (+3 more)
Radiological mapping plays a critical role in
nuclear emergency response and environmental management activities. A radiation image, representing the spatial and intensity distribution of the radioactivity, is reconstructed from the radiation data and the associated contextual information. Typical image reconstruction methods, such as Maximum Likelihood Expectation-Maximization (ML-EM), only provide point estimates of the pixel or voxel activities without associated uncertainties. Here, we apply a new Microcanonical Langevin Monte Carlo (MCLMC) sampler for radiation image reconstruction and uncertainty quantification. The MCLMC sampler properties are first tested with synthetic radiation images. Methods to obtain the radiation distribution estimate and the associated uncertainty from the samples drawn by MCLMC are discussed. Given sufficient measurement statistics, the radiation distribution estimate obtained from MCLMC results closely resembles the ground truth with less risk of over- or under-fitting compared to ML-EM. When MCLMC is run in parallel on a GPU, the samples can converge to the posterior distribution in about 10 seconds for an image with $10^3$–$10^4$ pixels, which is significantly faster than other comparable Markov Chain Monte Carlo (MCMC) samplers. We also tested MCLMC on a
dataset from a real distributed source radiological mapping campaign, and the reconstructed results agree well with the expected activity map. The fast MCLMC sampler therefore enables improved imaging accuracy and
prompt uncertainty quantification for reconstructed radiation images, which can better inform decision-making in response to radiological events.
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All authors Lei Pan, Jaewon Lee, Brian J. Quiter, Jakob Robnik, Uroš Seljak, Jayson R. Vavrek
History and Philosophy of Physics · Cross-listed from quant-ph
Retrieving the Baby: Reichenbach's Principle, Bell Locality, and Selection Bias
Huw Price
In his late piece 'La nouvelle cuisine' (Bell 1990), John Bell describes the steps from an intuitive, informal principle of locality to a mathematical rule called Factorizability. This rule stipulates that when possible past causes are held fixed, the joint probabilities of outcomes of spacelike separated measurements, conditional on measurement settings, be the product of the local conditional probabilities individually. Bell shows that Factorizability conflicts with predictions of QM, predictions since confirmed in many experiments. However, Bell warns his readers that the steps leading to Factorizability should 'be viewed with the utmost suspicion'. He says that 'it is precisely in cleaning up intuitive ideas for mathematics that one is likely to throw the baby out with the bathwater' (1990, 239). Bell's suspicions were well-founded, for he himself misses an important baby. Here we retrieve and identify it: it is selection bias. We explain how failure of Factorizability may be regarded as a selection artefact, requiring no violation of locality in the intuitive, conceptual sense with which Bell begins his analysis. The argument begins with a central principle of causal discovery, Reichenbach's Principle of Common Cause (PCC). It is well known that correlations due to selection bias are not subject to PCC. Several writers have proposed that EPR-Bell correlations are also an exception to PCC, but it has not been noticed that they fall under this well-known exclusion. The point is relevant not only to the status of Bell nonlocality, but also for statistics and causal modeling. For these fields, the news is that selection effects play a ubiquitous role in
quantum phenomena, in a form akin to
collider bias.
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Fluid Dynamics
Ground effect on Undulation and pumping near surfaces
Sunghwan Jung
Locomotion and fluid pumping near surfaces are ubiquitous in nature, ranging from the slow crawling of snails to the rapid flight of bats. This study categorizes these behaviors based on the Undulation number ($\text{Un}$) and Reynolds number ($Re$). We contrast low $Re$ undulatory propulsion ($\text{Un} > 1$), exemplified by freshwater snails, with high $Re$ flapping propulsion ($\text{Un} < 1$), seen in bats and bees. For snails, we derive lubrication models showing that pumping and swimming speeds scale with $(a/h_0)^2$, a result validated by robotic experiments which also reveal the detrimental effects of surface deformation (high Capillary/Bond ratio). Conversely, for high $Re$ fliers, we examine the ground effect's role in lift enhancement. Biological data from bats (R. ferrumequinum) reveal a 2.5-fold increase in lift coefficient during surface-skimming drinking flights, attributed to aerodynamic squeezing effects. Finally, we analyze honeybee fanning, demonstrating how a "jet-
vortex" mechanism utilizes ground effect to transport pheromones efficiently against
diffusion. These findings provide a unified framework for understanding fluid-structure interactions near boundaries in biological systems.
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