Traditional Search-Based Software Engineering (SBSE) assumes global search and full Pareto exploration are essential. We offer the following negative result based on a study of over 100 Software Engineering (SE) optimization tasks: "zooming" into promising regions is far more effective than Pareto and global exploration under constrained evaluation budgets. Our minimal greedy zoom method, EZR, runs three orders of magnitude faster than Pareto and global Bayesian methods, achieving higher statistical ranks and winning or tying in 84-89\% of datasets on equal budget. Even at one-fifth the evaluation budget, EZR wins or ties in 79-81\% of datasets. Surprisingly, despite never explicitly seeking a frontier, EZR matches or outperforms Pareto methods on their own coverage metrics (IGD, HV) at equal budgets. The explanation for this widespread failure is structural: across the datasets studied, Pareto-optimal solutions form a tiny, tight island concentrated in a compact region of decision space. Methods that wander waste their budgets outside this island. Beyond efficiency, zooming yields small, interpretable models, thus addressing concerns about black-box AI. By replacing global wanderi
Security often receives insufficient developer attention because it does not directly generate visible value, leading to underinvestment in practice. We evaluate a countermeasure by team-level incentives tied to measurable security improvements over time. Our semi-automated mechanism aggregates static analysis findings from Bearer, Detekt, and mobsfscan, computes security issue density, and rewards teams based on the relative improvement ratio across sprints, enabling repeatable, scriptable reporting at scale. In a controlled course experiment with 84 students across 14 teams, we compared a security-incentivized condition, in which bonus points were linked to security scanner results, against a control condition with an otherwise identical grading scheme. The treatment group achieved significantly lower security issue density overall (beta regression: $β= -0.396, p = 0.0342$), indicating improved measurable security under incentivization. After controlling for platform, we observed a marked front-end/back-end disparity, with back-ends showing fewer issues and higher improvement ratios under incentives, highlighting heterogeneous effects across stack layers. Notably, these gains wer
Agent-to-Agent (A2A) networks enable autonomous AI agents to collaborate by sharing reusable problem-solving instructions. However, how these decentralized ecosystems operate in practice remains largely unexplored. We present the first large-scale empirical study of EvoMap, a prominent A2A collaboration network. By analyzing over 1.5M assets and 128K agents, we show how design choices that prioritize scalable growth introduce trade-offs in reusability, evolution, and auditability. First, EvoMap's credit economy rewards agents for publishing valuable assets. Although this design encourages participation at scale, rewards are tied primarily to publication rather than adoption. This leads agents to mass-produce assets to accumulate credits. As a result, 98% of assets are never reused, while rewards become highly concentrated among a small fraction of agents. Second, EvoMap employs an algorithm (referred to as GDI) to score and rank the quality of these shared assets. We demonstrate that this scoring system is flawed: rather than measuring objective performance, an asset's rank is heavily dictated by unverified, self-reported metadata (e.g., claimed lines of code modified). This allows
We report proof-of-concept measurements of the magnetocaloric effect (MCE) in ultrahigh magnetic fields up to 120 T for the classical spin-ice compound Ho$_{2}$Ti$_{2}$O$_{7}$. Radio-frequency resistivity measurements using an Au$_{16}$Ge$_{84}$ thin-film thermometer enable us to detect a rapid change in the sample temperature associated with a crystal-field level crossing in the high-field region in addition to a giant MCE at low fields. We discuss a possible delay in the temperature response and outline prospects for more precise MCE measurements in destructive pulsed fields.
Extratropical storms shape midlatitude weather and vary due to the slowly evolving climate and the rapid changes in synoptic conditions. While the influence of each factor has been studied extensively, their relative importance remains unclear. Here, we quantify the climate's relative importance in mean storm activity and individual storm development using 84 years of ERA-5 data and convolutional neural networks. We find that the constructed model predicts over 90% of the variability in the mean storm activity. However, a similar model predicts about a third of the variability in individual storm properties, such as maximum intensity, showing their variability is dominated by synoptic conditions. Isolating the impact of present-day climate change on individual storms shows it contributes to about 0.1% for storm-intensity variability, whereas its contribution to storms' heat-anomaly variability is over three times greater, highlighting that focusing on variables directly tied to global warming offers a clearer attribution pathway.
Recent studies on CoNi-based multi-principal element alloys (MPEAs) have demonstrated high strength and ductility, attributed to the formation of stable L12 nanoscale precipitates. However, the fundamental mechanisms behind such impressive properties in these complex alloys are not well understood. In this work, we investigate the effects of Ti and Al concentrations on the formation of L12 precipitates in (CoNiFe)84(Al8Ti8), (CoNiFe)86(Al7Ti7), (CoNiFe)88(Al6Ti6), and (CoNiFe)94(Al4Ti2) MPEAs using hybrid molecular dynamics/Monte Carlo (MD/MC) simulations and a MEAM interatomic potential for the CoNiFeTiAl system. Additionally, we study the effect of L12 precipitation on the mechanical properties and stacking fault energy (SFE) of these MPEAs using MD. Our hybrid MD/MC simulations show that the (CoNiFe)86(Al7Ti7) alloy exhibits the highest amount of L12 nanoprecipitates. We find that L12 precipitation increases the SFE, with higher Al and Ti contents leading to greater increases. Tensile simulations reveal that L12 precipitates enhance yield strength, with alloys exhibiting higher precipitation showing increased flow stress. We also investigate dislocation-nanoprecipitate interacti
We present the first detection of electrons with kinetic energy in the 100 eV range with transition-edge sensors (TESs). This has been achieved with a $(100\times 100)$ $μ$m$^2$ Ti-Au bilayer TES, with a critical temperature of about 84 mK. The electrons are produced directly in the cryostat by an innovative cold source based on field emission from vertically-aligned multiwall carbon nanotubes. We obtain a Gaussian energy resolution between 0.8 and 1.8 eV for fully-absorbed electrons in the $(90-101)$ eV energy range, which is found to be compatible with the resolution of this same device for photons in the same energy range. This work opens new possibilities for high-precision energy measurements of low-energy electrons.
State-of-the-art Ni/Ti supermirror neutron optics have limited reflected intensity and a restricted neutron energy range due to the interface width. Incorporating low-neutron-absorbing 11B4C enhances reflectivity and allows for thinner layers to be deposited, with which more efficient supermirrors with higher m-values can be realized. However, incorporating 11B4C reduces the optical contrast, limiting the attainable reflectivity at low scattering vectors, making this approach infeasible. This study explores various approaches to optimize the material design of 11B4C-containing Ni/Ti supermirrors to maintain high reflectivity at low scattering vectors and achieve low interface widths at large scattering vectors. The scattering length density contrast versus interface width is investigated for multilayer periods of 30 Å, 48 Å, and 84 Å, for designs involving pure Ni/Ti multilayers, multilayers with 11B4C co-deposited in Ni and Ti layers, multilayers with 11B4C co-deposited only in Ni layers, and multilayers with 11B4C as thin interlayers between Ni and Ti layers. Our results suggest that a depth-graded hybrid material design by incorporating 11B4C inside the Ni and Ti layers, below a
We present a new end-to-end pipeline for Mock Observations of X-ray Halos and Analysis (MOXHA) for hydrodynamic simulations of massive halos, and use it to investigate X-ray scaling relations and hydrostatic mass bias in the Simba cosmological hydrodynamic simulation for halos with $M_{500}\sim 10^{13-15}M_\odot$. MOXHA ties together existing yT-based software packages and adds new functionality to provide an end-to-end pipeline for generating mock X-ray halo data from large-scale or zoom simulation boxes. We compare MOXHA-derived halo properties in Simba to their emission-weighted counterparts, and forecast the systematic mass bias in mock Athena observations. Overall, we find inferred hydrostatic masses are biased low compared to true Simba values. For simple mass-weighting, we find $b_\text{MW} = 0.15^{+0.15}_{-0.14}$ ($16-84\%$ range), while emission-weighting increases this to $b_\text{LW}=0.30^{+0.19}_{-0.10}$. The larger bias versus mass-weighted values we attribute to the spectroscopic and emission-weighted temperatures being biased systematically lower than mass-weighted temperatures. The full MOXHA pipeline recovers the emission-weighted hydrostatic masses at $R_{500}$ re
Researchers have finally resolved a key problem in a 100-year-old theory of color, showing that the qualities we perceive in colors are intrinsic to the mathematics of color space itself。 The discovery sharpens our understanding of human vision and could lead to more precise color technologies and visualizations
Scientists working at CERN’s Large Hadron Collider may be seeing the strongest hints yet of physics beyond the Standard Model — the decades-old theory that explains the fundamental particles and forces of the universe。 By studying incredibly rare particle transformations called “penguin decays,” researchers found behavior that doesn’t fully match t
A stunning spiral galaxy called Messier 88 is racing through the crowded Virgo Cluster on a journey that will dramatically reshape its future。 At its heart lies a supermassive black hole about 100 million times the mass of the Sun, while its graceful spiral arms sparkle with young star clusters and dark clouds of dust。 But as M88 plunges deeper int
NASA’s PExT terminal has shown that spacecraft can seamlessly communicate through multiple government and commercial networks, a major step beyond traditional single-network systems。 The mission is now expanding to test new capabilities that could help create a more flexible, reliable communications infrastructure for future space missions
A lightweight new X-ray telescope could finally give scientists something they’ve never had before: a complete chemical map of the Moon。 Researchers used detailed mission simulations to show that a compact telescope orbiting the Moon could identify key elements across the entire lunar surface, helping reveal how the Moon formed and evolved
Astronomers have finally cracked the mystery behind a strange class of repeating cosmic signals that has baffled scientists for years。 Using Australia’s ASKAP radio telescope, researchers traced the bursts to a rare stellar duo in which a dense white dwarf is relentlessly siphoning material from a nearby red dwarf companion。 As the stolen matter sp
NASA’s futuristic X-59 jet is about to face its biggest challenge yet: breaking the sound barrier for the first time。 After a successful series of test flights that pushed the aircraft to near-supersonic speeds, engineers are preparing to fly it faster than Mach 1 and eventually up to Mach 1。6 at 60,000 feet