Papers

Detection claims surrounding life beyond Earth often attract intense attention because the question of whether we are alone in the cosmos carries unusually high scientific, social, philosophical, and theological stakes. This chapter compares two high uncertainty life-detection claims, the 2020 phosphine detection claim on Venus and the 1976 Viking life-detection experiments on Mars, to examine how evidence, interpretation, and public narratives interact when results are ambiguous. We trace how each case unfolded through critique, reanalysis, and shifting assessments, and how institutional choices shaped subsequent research pathways, from long term monitoring and renewed Venus exploration to a Mars strategy centred on habitability rather than direct life-detection. Drawing lessons across both cases, we propose best practices for scientists, institutions, the wider scientific community, and science communicators, with emphasis on open science, constructive follow-up, cognitive bias awareness, and careful framing so that initial detections are not framed as final conclusions. We argue that managing future life-detections is less about eliminating uncertainty than about building transparent verification pathways that protect credibility as follow-up evidence refines the picture.

We revisit the conditions for perfect electromagnetic absorption in a homogeneous lossy layer on a reflecting substrate. Using phasor diagram analysis, we demonstrate a fundamental physical similarity between the high-refractive-index limit (classic Dallenbach quarter-wavelength absorbers) and the epsilon-near-zero regime (half-wavelength resonances). In both extremes, perfect absorption relies on long cyclic multipath propagation and gradual amplitude decay. Crucially, we uncover that in the intermediate regime near $n = 1$, this picture changes fundamentally: the trapping efficiency drastically increases, and backscattering is eliminated almost instantaneously within a single round-trip. Using temporal coupled-mode theory, we prove that this low-contrast state minimizes the system's quality factor to a global minimum of $Q \approx 0.69$. This critically damped state mirrors universal highly damped stabilization principles found in acoustics and mechanics, driving anomalous spectral broadening and enabling nearly instantaneous dissipation of ultrashort pulses without time-domain ringing.

Any viable interpretation of quantum theory needs to account for the Born rule, from which the theory gets its probabilistic empirical predictions. In this paper, we give an overview of possible approaches to this problem in the context of the Many Worlds interpretation. We argue that, for structural reasons, none of them can possibly succeed. More precisely, we argue that the Many Worlds interpretation must obtain the Born rule by proceeding either axiomatically, deductively, or inductively, and that all three of these approaches run into general, fundamental obstructions.

Unmanned Autonomous Systems (UASs) can remotely sense targets across large-scale areas but may be vulnerable to threats in contested environments. Current approaches consider efficiency through UAS path planning, but missions prioritizing robustness (i.e., the capacity to withstand disruptions) and resilience (i.e., the ability to recover from disruptions) are rarely considered despite their ability to increase mission success. This paper presents robust and resilient strategies for route planning for a fleet of UASs in a heterogeneous threat landscape. By integrating components of robustness and resilience in route planning through allowing the UASs to overlap in the waypoint locations and dynamic mission adaptation, the probability of mission success of complete area coverage can be increased. The results show that a robustness-focused strategy shows significant improvement in probability of mission success over an efficiency-based strategy, and that a resilience-based strategy outperforms both the efficiency- and robustness- based strategies. The specified methodologies provide promising future directions of research to explicitly incorporate robustness and resilience into UAS mission planning.

Technologies for artificially controlling chemical reaction systems, such as optogenetics, are rapidly advancing, making it increasingly important to understand reaction dynamics under time-dependent control. When the modulation of reaction rates is periodic in time, the Floquet formalism provides a systematic framework. We develop a Floquet theory for classical stochastic processes that enables the calculation of the current and its counting statistics under such periodic modulation. In particular, we formulate the theory in terms of a counting field and derive general expressions for the first cumulant and the corresponding current. The current is expressed using the effective Floquet generator and the kicked state, and we further obtain general asymptotic expressions for the current in both the high- and low-frequency regimes. As a concrete example to test our analytical expressions, we then apply the results to discrete Floquet driving – a non-perturbative, stepwise protocol. The setup is motivated by a biochemical system known as cyclic adenosine monophosphate (cAMP) production, which is an enzymatic reaction activated and inhibited by G-proteins. This is formulated as a discretely driven Michaelis–Menten-type reaction model, in which the catalytic activity is switched on and off abruptly in time, and we obtain analytical expressions and numerical results showing how periodic switching of reaction rates generates a long-time product current. In particular, in the high-frequency limit, we show that the effect of the periodic driving can be interpreted through an effective modification of the chemical reaction rates. These results provide a basis for Floquet analysis of periodically driven chemical reactions.

Laser-plasma accelerators have been the subject of extensive research in recent years. The electron beams they generate exhibit a broad energy spread. To conveniently characterize beams from laser wakefield acceleration (LWFA), electron spectrometers employing scintillating screens coupled with CCD cameras are typically used. In this work, we calibrate a series of DRZ phosphor screens and measure the spectra of the light they emit. The calibration was performed using the radio-frequency linear electron accelerator at Tsinghua University, which provided monoenergetic electron beams with peak energy of approximately 30 MeV.

This study investigates the coupled effects of an insoluble surfactant and a radial electric field on the stability of a viscous liquid film flowing down a vertical fiber. Starting from the governing equations in two dimensions, a reduced model in one dimension is derived using the long wave approximation to describe the coupled evolution of the interface and surfactant transport. Linear stability analysis identifies two distinct unstable modes: the Rayleigh-Plateau mode, which dominates at lower values of the Marangoni number $Ma$, and the Marangoni mode, which becomes dominant at higher values of $Ma$. The influence of the radial electric field is determined by the position of the outer electrode $\beta$. When $\beta<\mathrm{e}$, the electric field enhances both instabilities and narrows the stable interval in $Ma$ between the two modes. When $\beta>\mathrm{e}$, the electric field suppresses both modes and can completely eliminate the unstable region associated with the Marangoni mode even at a relatively small electric Weber number $E_b$. Continuation of the traveling wave solutions further shows that, when $\beta<\mathrm{e}$, the magnitude of the relative interfacial motion $I_{RP}$, generally increases with $E_b$. By contrast, the intensity of Marangoni convection $I_{M}$ varies only weakly at smaller values of $E_b$ and increases appreciably only when the electric field becomes sufficiently strong. Analysis of the stream function and the relative interfacial velocity reveals that the electric stress primarily intensifies the recirculation beneath the wave crest and reshapes the spatial distribution of the relative interfacial velocity.

Forecasting the outcomes of transition-metal-catalyzed reactions is notoriously complex due to the interplay of diverse physical and chemical variables. A persistent computational bottleneck has been effectively merging broad electronic descriptors with the localized, three-dimensional geometry of the reactive site. To bridge this representation gap, we present ChemFusion, a hybrid neural network that fuses conventional electronic features with explicit 3D atomic coordinates. Using a cross-attention mechanism, the model enables global electronic states to dynamically attend to specific spatial constraints within un-pooled molecular point clouds. When benchmarked against a diverse library of cross-couplings, this approach delivers exceptional predictive performance, decisively surpassing traditional single-modality frameworks. Importantly, extracting the attention matrices reveals that the architecture autonomously learns to identify and penalize restrictive steric hindrances. This provides a physically grounded interpretability, demonstrating that spatially aware networks can navigate complex reaction sterics that standard statistical models typically miss.

We consider economic theory from the perspective of a total automation economy, one with no human involvement in production either in manufacturing or in management. One can naturally ask whether a total automation economy is fundamentally a centrally planned economy or, alternatively, whether efficiency demands decentralization into local decisions by competing agents – agentic production. A soviet economist, Leonid Kantorovich, developed linear programming as a method companies or governments can use to optimize production. Ironically, he is also generally credited with showing that the most efficient production is achieved through decentralization – a free market economy with competing agents. Here we review Kantorovich's dualization in detail. We take the objective of the economy to be maximizing production weighted by (human) market price. A fundamental issue is whether an automated pursuit of this objective might have alignment vulnerabilities as the economy evolves. Another question is whether dualization provides insight into the utility of agentic AI systems (multi-agent AI systems) generally.

We report the progress achieved on the development of a two-dimensional Optical Parallel-Plate Avalanche Counter (OPPAC) prototype for heavy-ion tracking. The device consists of two uniform thin parallel plates of 10 x 10 cm2 effective area, separated by a gap of 3 mm. The gap is filled with Tetrafluoromethane (CF4) at low pressure (up to 50 Torr). By applying a voltage difference between parallel plates, a uniform electric field is established within the gap. Electroluminescence emission is produced during the electron avalanche triggered by a charged particle that crosses the gas gap. The light is detected by an optical readout comprising four arrays of collimated Silicon Photomultipliers (SiPMs) deployed around the gas gap. The position of the particles is reconstructed by processing the light signals collected by all the SiPMs by computing the center of gravity of the light distribution within the SiPM arrays. The SiPM signals are read out and processed by a data acquisition (DAQ) system based on the General Electronics for TPC (GET). Preliminary results from a test with an alpha-particle source and a 100 MeV/u 40Ca beam demonstrate a sub-millimetre intrinsic position resolution sigma_det = 0.7 mm) while preserving good linearity over the entire detector active area.

Large language models (LLMs) can plan tool-mediated scientific work, but scientific instruments remain difficult to connect to such agents: vendor APIs may load only inside acquisition host processes, facilities may prohibit cloud-hosted agents, and natural-language interfaces can emit physically unreasonable arguments. We present a method for connecting local LLMs to scientific instruments through the Model Context Protocol (MCP). It combines: (1) a schema-bound tool surface that validates requests against physical bounds before adapter dispatch; (2) a vendor-neutral, host-process adapter pattern separating language-side reasoning from instrument-side execution; (3) a persistent lifecycle for long-running live-processing jobs; and (4) MCP-prompt-registered skills that compose typed tools into reusable multi-step protocols. Our open-source reference server exposes 30 typed tools, 5 live-job types, and 6 skills through a physics-plausible simulator implementing the same protocol surface. Validation is software-only: all 120 hardware-independent tests pass deterministically, while 15 local-LLM integration tests pass 12-15 of 15 across runs because of model nondeterminism. A preliminary single-run probe across five open tool-calling LLMs indicates that the schema-bound interface can be driven locally by small open-weight models without cloud dependency; it is not a benchmark and has no confidence intervals. The method provides a bounded, testable, and reproducible foundation for closed-loop agentic instrumentation research.

The electric charges that make up charge distributions and currents in classical electromagnetism (EM) are point charge electrons with a fixed finite charge. This means that a truly continuous charge distribution or current cannot be formed because that would require infinitesimal charges. If the number of electrons in any distribution is very large, the distributions can be approximately continuous, and can be used in many applications, but the discrete character of the distributions has a major effect on other physical effects. We consider two of those effects in this paper. Does a point charge have infinite self-energy, and does a moving current loop have an electric dipole moment?

Motivated by the interactions of the GCR protons with the Martian atmosphere and regolith in the absence and presence of hydrogen, a series of GEANT4 simulations are employed in this study to reveal the influence of hydrogen on the energy spectra of secondary and albedo neutrons together with the associated gamma rays at the Martian surface. Following irradiation of the Martian atmosphere with a planar vertical PAMELA proton beam, the attenuation of the primary proton spectrum through the atmosphere and the range and energy deposition of protons within the regolith are first obtained. The depth profile of the generated neutrons and gamma rays, along with the kinetic energy spectra of the atmospherically produced neutrons and gammas reaching the surface, is then acquired in the absence and presence of 0.11 wt.% hydrogen by voxelizing the regolith into 100 cells of 2-cm thickness. Finally, a surface detector is placed atop the regolith, and the atmospherically produced neutron and gamma spectra are compared with the total neutron and gamma spectra recorded at the surface detector to assess the relative contribution of the atmosphere and the regolith to the overall radiation field reaching the Martian surface. The energy spectra of the albedo neutrons are also obtained in terms of thermal, epithermal, and fast neutrons. The GEANT4 simulations show that the Martian regolith, rather than the atmosphere alone, constitutes the dominant source of the neutron and gamma population arriving at the surface, and that the presence of 0.11 wt.% hydrogen is observable in each energy regime of the albedo neutrons at the Martian surface, while proton transport and the overall neutron and gamma production depth profile remain comparatively insensitive to hydrogen, thereby indicating the elemental variation of the Martian regolith.

Hot-wall fuel-droplet impingement affects liquid redistribution, secondary droplet formation, and droplet evaporation in diesel-relevant spray-wall systems. This study investigates the spreading and breakup of single n-hexadecane droplets, used as a single-component diesel surrogate, on a heated stainless-steel wall at 300-500 {\deg}C over a Weber number (We) range of 5.77-208.61. High-speed backlit images were recorded during experiments and used to classify deposition, rebound, ejection, fragmentation, and splashing regimes, and to measure spreading-factor histories. The measured spreading histories were compared with a lamella-rim model to evaluate its predictive capability before droplet breakup and to infer the lamella state at experimentally observed breakup instants. The 300 {\deg}C cases did not enter the Leidenfrost regime under the present impact conditions and therefore serve as a non-Leidenfrost reference, deviating from the model predictions. For Leidenfrost cases at 350-500 {\deg}C, the model captures the pre-breakup spreading trajectory, including higher-We cases that later undergo breakup. Wall temperature has a limited influence on the early spreading stage but more strongly affects later breakup timing after lamella thinning, especially in the intermediate-We regime. At high We, breakup becomes increasingly inertia-dominated. Model-inferred lamella thicknesses evaluated at experimentally observed breakup instants are mainly concentrated between 0.010 and 0.017 of the initial droplet diameter. These results suggest that model-inferred lamella thickness can complement conventional Weber-number and temperature-based regime maps by providing local-state information for breakup timing in hot-wall fuel-droplet impingement models.

In this study, we characterize the permittivity of various commercially available materials commonly used in 3D printing over the millimeter-wave frequency range of 70-110 GHz. The open-waveguide extraction method is employed to efficiently determine the permittivity of these 3D-printed materials, and key strategies for improving its accuracy are discussed. This methodology can be readily applied to the characterization of similar materials and extended to higher frequency ranges. The resulting permittivity data are expected to support advances in 6G and beyond wireless communication technologies, in which 3D-printed materials and millimeter-wave frequencies are anticipated to play an increasingly important role in the development of novel antennas and metasurfaces.

China emits the most methane of any country worldwide, but there are large uncertainties in recent emissions trends, sources, and the potential impacts of policy actions. This study focuses on a period when the government initiated ambitious methane control efforts, linking sectoral policies with atmospheric evidence on sectoral, sub-national, and seasonal emissions during 2019–2024. We quantify daily methane emissions from China using a regional atmospheric inverse model with TROPOMI satellite observations. Our results reveal an average methane emissions increase rate of 0.3 Tg yr$^{-2}$ in Eastern & Central China, likely a milder trend than in the 2010s. Coal industry methane emissions intensity declined for the first time (-3.2% yr$^{-1}$) despite rising production, possibly associated with diverse policy instruments, mandates, and incentives. We further highlight two emerging challenges for future mitigation: leaks from expanding urban gas use amid the energy transition and rising agricultural emission yet with substantial uncertainty in estimates. Lastly, declining emissions intensity of coal mines points to the future role of targeted mandates and incentives in encouraging methane reduction for other sectors.

We develop the Cloud 3-Dimensional Imager Retrieval (C3DIR), a deep learning model that estimates 3-D cloud properties for multiple passive satellite imagers trained to match retrievals from the Earth Cloud Aerosol and Radiation Explorer(EarthCARE) ACM-CAP product. This work is aimed towards moving AI/ML 3-D cloud algorithms closer towards operational use. C3DIR predicts the occurrence water content of ice, cloud liquid, and rain along the imager line-of-sight and uses a voxel-level collocation approach to account for the misaligned viewing geometries of passive imagers and active profiling instruments. This precise collocation methodology allows for constructing vertical profiles using voxels contained by multiple imager pixels to facilitate comparisons with active profiling instruments. Qualitative case studies show that C3DIR can accurately depict multiple distinct overlapping cloud layers, albeit with some smoothing. Quantitative evaluations illustrate that C3DIR overall excels at hydrometeor detection which intuitively tends to be a function of water content. However, detection of voxels classified as liquid cloud remains difficult due to the their small geometric thickness, finer horizontal scale, and frequent tendency to be obscured or embedded within ice clouds. In general, water content estimation is reasonably accurate, yielding the best results in ice clouds but uncertainties remain for liquid and rain water content. Column-integrated water paths are in tighter agreement with EarthCARE. Comparisons with the algorithms underpinning current NOAA operational products highlight several areas where C3DIR may offer improvement. Overall, these results demonstrate the potential for C3DIR to provide flexible 3-D output depicting vertically resolved cloud structure which can offer broader utility for aviation applications, numerical weather modeling, and climate research.

We demonstrate a two-dimensional Sisyphus laser cooling method that increases the number of strontium monohydroxide (SrOH) molecules loaded into a magneto-optical trap by a factor of 12. Subsequent loading into an optical dipole trap (ODT) achieves $2.2 (3)\times10^4$ ultracold SrOH molecules with a peak density of $\sim2(1)\times10^{10}~\mathrm{cm^{-3}}$. The lifetime of molecules in the ODT is limited by two-body collisions characterized by a measured collision rate constant $\beta \sim 4\times10^{-10}~\mathrm{cm^3/s}$. The cooling method developed here is generally applicable to all known cases of direct molecular laser cooling, including symmetric and asymmetric top molecules. Increases in trapped molecule number will directly improve the search for ultralight dark matter, position polyatomic molecules as a platform for probing CP-violating new particles with masses $\gg$10 TeV, and facilitate a broad range of further research in quantum science.

Non-uniform flow dynamics in bedrock-bound channel morphologies play a critical role in landscape evolution because these reaches are locations along river long profiles where active bedrock incision occurs. Field observations indicate that plunging flows, characterized by velocity inversions within bedrock-bound constriction-pool-widening (CPW) channel morphologies, drive incision at the local scale. These flows generate high shear stresses that promote sediment transport and contribute to the development and maintenance of CPW morphology. Previous studies of plunging flows have relied on coarse-scale field observations and labor-intensive laboratory experiments to investigate their dynamics. Here, we use eddy-resolving computational fluid dynamics models to examine plunging-flow behavior, building on experimental evidence that lateral channel constriction induces plunging flows. Using large-eddy simulations (LES) of laboratory-scale flows, we found that the optimal constriction for generating plunging flows is approximately 35% under lower-flow conditions but increases to 50% at higher flows because of changes in inlet velocity and flow depth. At higher discharge rates, channel constriction further amplifies the plunging effect, producing substantial shear stresses near the point of velocity inversion. Increasing constriction also leads to greater velocity variance and more intermittent pulsing of plunging flows, both of which are likely to enhance incision potential. These findings highlight the need to refine bedrock incision models to better represent the dynamic and complex nature of plunging flows, moving beyond the simplified steady-flow assumptions that underpin most landscape evolution models.

Optical microcavities are widely used to control the emission of organic semiconductors, but their ability to reshape the molecular pathways that precede emission remains largely unexplored. Here we show that embedding a ZnPc:TPBi blend in a planar Fabry-Pérot microcavity suppresses the formation of non-radiative exciplexes and removes bimolecular annihilation at high excitation densities, increasing the photoluminescence quantum yield by more than forty-fold under continuous-wave excitation. This enhancement is far larger than expected from the weak Purcell effect. Instead, transient spectroscopy, power-dependent photoluminescence and kinetic modelling point to a cavity-induced rebalancing of excited-state populations: long-range Förster energy transfer from ZnPc monomers to emissive aggregates is enhanced, allowing it to outcompete charge transfer to dark exciplexes. Electromagnetic calculations predict FRET enhancements of up to ~400-fold at relevant distances, consistent with the observed suppression of exciplex-mediated losses. Our results show that optical cavities can control not only how molecules emit, but also which excited states they form, opening a route to improved efficiency and reduced roll-off in organic optoelectronic and photonic devices.

Magmatic anhydrite has long been regarded as diagnostic of oxidized intermediate-felsic magmas in porphyry Cu deposits. Here we report the world first occurrence of mantle-derived magmatic anhydrite in ultramafic rock from a magmatic platinum group elements sulfide deposit. The formation age of the clinopyroxenite and hornblnedite hosting this anhydrite is 408.8 Ma, shortly after the Palaeozoic Oxygenation Event (POE). The anhydrite coexists igneous carbonate mineral and systematics Ca-O-C-Fe-S isotopes indicate oxidation of the mantle source by recycled oxidized surface-derived carbonates due to POE. After the POE, the more oxidized supra-subduction mantle is coupled with the emergence of magmatic sulfide deposits in orogenic belt during Late Paleozoic (410-270 Ma) and the rapidly increased frequency of porphyry Cu deposits worldwide. Our results further suggest that high-Mg basaltic magma, typically considered to be parent magma of magmatic sulfide deposits in orogenic belt, can evolve into PGE-enriched porphyry Cu deposit systems. This requires sufficiently high oxygen fugacity in magma after POE to retain sulfur predominantly as sulfate and thereby suppress sulfide saturation after olivine differentiation. Our findings link atmospheric oxygenation to deep Earth redox evolution and suggest that secular changes in Earth's redox state fundamentally influenced the evolution of key strategic metal sulfide deposits.

One should not assume that reconstructing an electronic observable with a smaller set of measurement settings will cut the number of repetitions in proportion. Each setting is simply a basis change and qubit readout, but the savings are not guaranteed to be commensurate. Take two electrons of opposite spin in two spatial orbitals: the orbital degree of freedom of each electron acts as a logical qubit and rotations are independent in the spin sectors. From the observable's one- and two-qubit coefficients we derive an exact floor for the setting count and a decomposition to meet it in no more than three settings. With fewer settings, the minimum error in the two-qubit correlation coefficients is set by the singular values left out. A case in point is an exchange with equal nonzero couplings on the three Pauli axes. This demands three orbital settings yet only one joint measurement. We offer a Clifford circuit for four physical qubits to effect the necessary mapping of Pauli products under conjugation. In the case of a one-parameter family of logical singlet-triplet mixtures, the orbital-to-Clifford shot cost ratio is three at maximum mixing and trends toward 3/2 near the logical singlet. Where spin sectors may be mixed, isotropic exchange needs one orbital setting. For spin-conserving Hamiltonians with $N$ spatial orbitals encoded via Jordan-Wigner, the $X$-rank, the binary rank of the $X$ parts of its strings, of any commuting Pauli string family is no more than $2(N-1)$. Searches with the Robust Adaptive Nature-inspired Global Explorer (RANGE) reach this limit for CH$_4$, with the rank of the Hamiltonian support vouching for the maximality of the search values. And for all nonidentity Pauli strings on $n$ qubits, semidefinite witnesses from the Lovász theta number give a lower bound on the Clifford setting count that agrees with the integer cover and counting bounds at $2^n+1$.

Quantum estimates of molecular energy require repeated state preparation and measurement. We bound the minimum repetition count for given measurements and processing rules from above with a practical schedule and from below with independently verified inequalities. For an H$_4$ chain at H-H distances of 0.90 and 1.80 Åwith 2 per cent uniform noise in the ground state, entangling Clifford measurements, which map Pauli products onto one another, cut leading-order repetitions by at least 65.9 and 61.0 per cent, respectively, relative to any schedule using only single-qubit Pauli measurements and Hamiltonian terms. With 69 unaltered measurement settings, each a basis change followed by qubit readout, processing further observables saves at least 12.04 and 6.70 per cent. For four lanthanide and actinide Hamiltonians with depolarized Hartree-Fock covariances, reducing the sum of absolute Hamiltonian coefficients does not proportionally reduce sampling. The bounds cover linear unbiased estimates from independent batches at small error.

Hong-Ou-Mandel (HOM) interferometry enables delay estimation at the quantum precision limit but is traditionally constrained to path differences within the coherence time of the interfering photons. Here, we demonstrate single-measurement path-delay sensing at the measurement Cramer-Rao bound using spectrally resolved HOM interference, thereby removing the conventional dynamic-range limitation imposed by the photon coherence window, with no scanning required for calibration. By extracting delay information from the spectral interference fringes of spectrally entangled photon pairs, we retain near-optimal sensitivity over an operational range exceeding the photon coherence time by over two orders of magnitude. Using one million detected photon pairs, we achieve a time-delay precision of 20 attosecond (6 nm), while real-time operation (at 1 Hz) yields 330 attosecond (100 nm) precision. Because the estimator relies on fringe periodicity rather than absolute coincidence rates, the method is intrinsically robust to photon losses and variations in interference visibility, eliminating the need for recalibration. As a practical demonstration, we measure the thickness of a 300 um transmissive target with nanometer-scale precision. These results mark a significant step towards deploying quantum-limited measurements in real-world sensing applications using HOM interferometry.

Motivated by programmable tweezer arrays, we develop an exactly solvable shape-space theory for near-equilateral atomic trimers. The Higgs oscillator on Kendall's shape sphere gives a nonresonant spectral lattice whose fixed-angular-momentum relative-stationary minimizers are supported on two adjacent admissible sites. These symmetry-selected doublets are separated from higher relative-stationary branches by a finite branch gap. With phase-coherent shape-mode driving and Rydberg-mediated conditional phases, they furnish a candidate route to geometric qubits and entangling operations.

I rivisit the history of the first matter-antimatter collider built in Italy in 1960 and carried to success through an inter-European collaboration with France, underlying the foundational role of the Austrian born theoretical physicist Bruno Touschek. Touschek's life path through Europe before and after World War II is briefly recalled. The role of CERN in jump-starting this international collaboration between the Frascati National Laboratories in Italy and the Orsay Linear Accelerator Laboratory in France, is highlighted through historical documents, and contributions from interviews with the main protagonists of Touschek's game-changing proposal.

This work proposes a compact and hardware-efficient frequency- and radiation-pattern-reconfigurable antenna (FPRA) for passive multi-target direction-of-arrival (DOA) estimation using a single receive RF chain. The antenna consists of a sectorized circular patch loaded with 16 PIN diodes. By switching the diode states, the current-concentration boundary on the patch is shifted, enabling reconfiguration of both the operating frequency and radiation pattern. With a single receive RF chain, the proposed antenna achieves beam scanning from -40 degrees to 40 degrees and provides multiple operating frequencies across the S- and C-bands. Based on these reconfigurable observation states, radiation-pattern switching is used to emulate the spatial sampling of a conventional antenna array, while multi-frequency observations introduce phase diversity to reduce the correlation among echoes from multiple passive targets illuminated by the same transmitter. Experimental results demonstrate that the combined virtual spatial sampling and frequency diversity enable passive multi-target DOA estimation without a conventional antenna array or multiple receive RF chains. The proposed FPRA offers a compact and hardware-efficient sensing solution for future integrated sensing and communication (ISAC) systems.

We investigate the existence and dynamics of two-dimensional solitary waves in a quantum droplet environment described by the extended Gross-Pitaevskii equation featuring logarithmic mean-field and Lee-Huang-Yang interactions. In the modulationally stable regime of the background, we employ suitable multiscale asymptotic methods to derive effective nonlinear integrable models corresponding to the Kadomtsev-Petviashvili and Davey-Stewartson equations. Based on these reduced models, we construct approximate analytical solutions describing line solitons, algebraically localized lump solitons, ring solitons, and exponentially localized dromions embedded on the droplet background. The dynamical robustness of these solutions is monitored through numerical simulations. Line, lump and ring solitons stay closest to the theoretical predictions, although progressively deviate due to the emergence of small-amplitude radiation, while dromions depart from their analytical waveform the most, although they roughly maintain their shape. Our results unveil unprecedented multidimensional soliton solutions in models featuring the competition of mean-field and quantum fluctuations and as such are amenable to current ultracold atom experiments.

Strategy learning governs the evolution of collective cooperation in multi-agent systems. Although evolutionary outcomes depend strongly on the information available to agents during strategy learning, most studies treat both the source and amount of that information as fixed over time. In reality, however, individuals are continually exposed to external information that varies over time. Here we develop a general framework for evolutionary dynamics with temporal information, which uses temporal networks to characterize dynamic changes in information available for strategy learning, with time-varying connections determining each agent's information state. Across synthetic and empirical networks, we find that temporal information consistently promotes cooperation relative to their static counterparts. We further demonstrate that this advantage becomes more pronounced as temporal networks become sparser. This pattern arises because sparsification amplifies information heterogeneity among agents, creating unequal access to learning information that can facilitate the spread of cooperative strategies, in sharp contrast to static information formulations where heterogeneity often suppresses cooperation. Guided by this insight, we develop an interpretable algorithm that substantially enhances cooperation across diverse networks by generating learning networks with tunable heterogeneity. Our results identify temporal information as a realistic and broadly applicable mechanism for promoting collective cooperation.

The region near the interface between cortical bone and the medullary cavity (the endosteal surface) is of particular interest for the early detection of osteoporosis. This region is typically the first to exhibit signs of unbalanced remodeling (enlarged pores and increased surface roughness). In this study, we analyze ultrasound reflection at the endosteal surface to introduce a novel potential biomarker of cortical bone health based on specularity. Our hypothesis is that increased pore size and surface roughness enhance ultrasound scattering, thereby reducing specular reflection. We reconstruct maps of specularity by combining a signal processing technique initially designed to enhance specular reflectors in soft tissues with a beamforming technique that accounts for refraction at bone soft tissue interfaces. Specularity values (between 0 and 1) quantify the similarity between received signals and signals from an ideal specular reflector. Using numerical simulations and ex vivo measurements with a 2.5 MHz phased array we highlight a strong relationship between specularity and bone microstructure, as assessed by high-resolution micro-computed tomography. Among 12 regions of interest (ROI) in the femoral bone of three donors, 8 ROIs without large pores showed high specularity (>0.5) in over 50% of pixels, in contrast to 4 ROIs with signs of extensive remodeling. Both pore volume fraction and pore size were strongly associated with specularity. In simple linear regression analyses, each parameter individually explained 84% of the variability in specularity. These findings suggest that specularity reflects bone microstructure and may potentially serve as a sensitive marker for identifying cortical bone degradation near the endosteal surface.