Articles tagged with Computational Physics
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
A new project aims to develop robust logical quantum bits for scalable and fault-tolerant quantum computing. The snaQCs2025 project combines innovative simulation and integration methods to compensate for error susceptibility of physical qubits, bringing quantum computing closer to practical use.
The American Physical Society's Global Physics Summit will convene over 14,000 physicists worldwide for groundbreaking research presentations. The event will feature both in-person and online experiences, including scientific sessions, exhibits, and networking events.
Researchers have discovered a linear relationship between reactivity and the reciprocal of uranium concentration in thermal-spectrum molten salt reactors. This finding has significant implications for criticality calculations, fuel loading prediction, and reactivity measurement.
Theoretical physicists at MIT propose that under certain conditions, magnetic material’s electrons could form quasiparticles called “anyons” that can flow together without friction. If confirmed, it would introduce a new form of superconductivity persisting in the presence of magnetism.
Researchers at University of Jyväskylä discovered fundamental design principles for greater stability in metallene interfaces. They found that smooth, well-aligned geometries provide strong resistance to defects and mechanical strain.
Researchers developed a comprehensive model of luminous black hole accretion, including radiation flows and interactions with surrounding gas. Their simulations reproduce consistent behaviors across various black hole systems, providing insight into extreme nonlinear processes.
The German Research Foundation has awarded a €10 million grant to the Collaborative Research Centre 211 'Strong-Interaction Matter under Extreme Conditions' for its third phase, extending funding for another 3.5 years.
Researchers at Waseda University have demonstrated a transformative approach for realizing skyrmion logic based on fluidic principles, utilizing the flow behavior of many skyrmions to simplify device operations. This breakthrough enables the development of nanofluidic logic gates with reduced complexity and improved stability.
The 'Otus' supercomputer provides a solution to pressing challenges through its massive parallel computing capacity, allowing researchers to simulate complex processes, identify patterns, and make predictions about future developments. The system also promotes sustainability with indirect free cooling and renewable energy sources.
TorchSim, a PyTorch-based simulation engine, delivers acceleration for MLIPs by unifying molecular dynamics and gradient-based learning. The platform provides speed, flexibility, and ease of integration with emerging machine learning atomistic models.
Stefano Baroni, a renowned physicist, has been awarded the 2026 Aneesur Rahman Prize for his pioneering work in first-principles methods and open-source software development. His research has significantly advanced our understanding of material properties and paved the way for cutting-edge technologies.
Engineers at the University of Delaware have developed a novel method to detect and control magnetic waves using electric signals, enabling computers to run faster and with greater energy efficiency. This breakthrough could lead to computer chips that integrate magnetic and electric components directly.
A new study from UBC Okanagan has mathematically proven that the fundamental nature of reality operates in a way that no computer could simulate. The researchers demonstrate that a complete and consistent description of everything requires non-algorithmic understanding, which is beyond algorithmic computation.
Researchers at TU Wien have developed a new computational method that accurately calculates van der Waals forces between large molecules, resolving decades-long discrepancies. The improved method corrects errors in existing approaches and enables reliable predictions for biological systems and renewable energy technologies.
The study reveals that certain rectangular shapes allow chloroplasts to achieve both efficient light capture at high density and enough space for shifting during strong light avoidance. The natural geometry of Elodea cells matches the predicted optimal shapes well, with a balance between packing and flexibility.
A new mathematical framework, STIV, can predict larger-scale effects like proteins unfolding and crystals forming without costly simulations or experiments. The framework solves a 40-year-old problem in phase-field modeling, allowing for the design of smarter medicines and materials.
A new project aims to develop a computationally efficient model that accurately predicts how additive manufacturing process parameters influence the solidification microstructure of binary alloy solidification. This will enable optimization of additively manufactured parts with confidence in critical industries.
Researchers at University of Tsukuba predicted the intensity of 21-cm radio signal in different dark matter models using numerical simulations. The results imply hydrogen gas produced a characteristic signal that could reveal dark matter mass and velocity if detected globally.
Researchers used 3D modeling, field experiments to confirm how Rapa Nui people moved iconic moai statues. The team found that the statues were likely walked in a zig-zag motion along carefully designed roads using rope, with a physics-backed explanation.
The new emulator Effort.jl allows researchers to analyze complex data sets faster and more efficiently than ever before. It uses state-of-the-art numerical methods and clever preprocessing strategies to achieve exceptional computational performance, making it possible to explore cosmic scenarios without waiting hours for each simulation.
Researchers from the Institute of Industrial Science, The University of Tokyo, have developed a mathematical theory that can be used to design optimization strategies for dynamical networks, such as those comprising living organisms. They found that tools from information theory provided a way to simplify nonlinear optimization problem...
Researchers created the largest qubit array with 6,100 neutral-atom qubits trapped in a grid by lasers, demonstrating improved accuracy and scalability. The team successfully maintained superposition for over 13 seconds and manipulated individual qubits with high accuracy.
University of Michigan researchers have made significant progress in developing a more accurate simulation approach for density functional theory, a widely used method in fundamental chemistry and materials science studies. The new approach has improved the calculation of exchange-correlation functionals, which describe how electrons i...
Researchers will generate maps showing the intensity and extent of an earthquake, helping to identify regions with a higher probability of infrastructure damage. The simulation will recreate a hypothetical scenario of an 8.1 magnitude earthquake in Mexico's Michoacán state.
The SAGEST Predictive Simulation Center will develop simulation tools to give scientists confidence in exploring extreme physical conditions. The center, led by UVA's Xinfeng Gao, will use high-fidelity and low-fidelity solvers to balance accuracy and efficiency in predictions.
A sophisticated neutron flux diagnostic system will gather knowledge of plasma and power released in nuclear reactions at ITER. The High Resolution Neutron Spectrometer (HRNS) measures both neutron number and energies, providing information on fuel composition, ion temperature, and combustion quality.
Researchers have developed a motion-compensation method that allows single-pixel imaging to capture sharp images of complex dynamic scenes. The new approach improves image quality and video smoothness in various scenarios, including surveillance and medical diagnostics.
Researchers from TUM and Google Quantum AI realize Floquet topologically ordered state, a phase predicted but never observed, using 58 superconducting qubit quantum processor. They probe the system's underlying topological properties and witness dynamical 'transmutation' of exotic particles.
A newly detected black hole merger has provided the clearest evidence yet of how black holes work, confirming fundamental predictions by Albert Einstein and Stephen Hawking. The observations reveal insights into the properties of black holes and the nature of space-time, hinting at how quantum physics and general relativity fit together.
A new hybrid software approach, sys-sage, facilitates collaboration between quantum and high-performance computing systems. The system can optimize task allocation and mapping to the best resources in each topology.
The study reveals that when physical constraints are removed, human mobility follows a power-law pattern, decreasing steadily with distance. The researchers found this pattern across five orders of magnitude, from 10 meters to hundreds of kilometers.
Researchers at the University of California, Riverside, have made a breakthrough in building larger and more reliable quantum computers by linking multiple quantum chips. The team found that even imperfect links between quantum chips can produce a functioning fault-tolerant quantum system.
Researchers use numerical relativity to probe the universe's biggest questions, including the Big Bang, cosmic inflation, and multiverse theories. The method allows for exploration of extreme situations beyond current mathematical limits.
The book explores foundational and advanced principles of modeling concurrent control systems using Petri nets, focusing on building reliable, verifiable systems where concurrency plays a central role.
Studies compare three helmet materials (ABS, fiberglass, and aluminum alloys) for reducing traumatic brain injury risk in elite athletes. ABS is sufficient for training and recreational sports, while fiberglass or aluminum alloys are recommended for elite athletes due to their unique benefits.
Researchers have developed a world-first method to simulate specific types of error-corrected quantum computations, a significant leap forward in the quest for robust quantum technologies. The new algorithm tackles a long-standing challenge in quantum research and enables accurate simulation using conventional computers.
The SPINNING project has successfully demonstrated a robust and energy-efficient alternative to established quantum computing hardware platforms. The developed spin qubits in diamond outperform comparable commercially available superconducting systems in terms of longer operation times and lower error rates.
Researchers from OIST develop new quantum AI method for image recognition based on boson sampling, achieving highly accurate results without complex training. The approach uses a linear optical network and preserves information, outperforming classical methods in various datasets.
Researchers from the University of Utah have developed an 'optical neural engine' that encodes partial differential equations in light and feeds them into a device to accelerate machine learning. The optical approach accelerates the process and requires less energy compared to electronic methods.
Researchers developed a machine learning framework that can predict how materials respond to electric fields up to a million atoms, accelerating simulations beyond quantum mechanical methods. This allows for accurate, large-scale simulations of material responses to various external stimuli.
Researchers successfully simulated fundamental interactions using Google's quantum processor, demonstrating the potential of quantum computing in particle physics and quantum materials. The study provides new insights into gauge theories and the behavior of particles, with implications for understanding space and time.
The University of Texas at Arlington's nursing and physics team has developed a system to study alpha radiation, improving the effectiveness of radiation therapy. The team's research was recognized with the Best in Physics award at the American Association of Physicists in Medicine's annual meeting.
Researchers develop new method to simulate Pockels effect, a key phenomenon in optoelectronics, using Density Functional Theory and finite differences. The approach enables accurate modeling of barium titanate's behavior, paving the way for more efficient devices.
A University of Texas-led team has discovered a shortcut to design leak-proof magnetic confinement systems in stellarator reactors, addressing a 70-year-old challenge. This breakthrough enables engineers to simulate the system more efficiently without sacrificing accuracy, paving the way for the development of reliable fusion energy.
Researchers have unveiled the secrets of deconfined quantum critical points (DQCPs), breaking away from conventional physics and offering a fresh perspective on quantum matter. The study reveals anomalous logarithmic behaviors and identifies a critical threshold value, suggesting DQCPs can resemble continuous phase transitions.
A Lehigh University team developed a novel machine learning method to predict abnormal grain growth in materials, enabling the creation of stronger, more reliable materials. The model successfully predicted abnormal grain growth in 86% of cases, with predictions made up to 20% of the material's lifetime.
Researchers developed a new viscoelastic model of enzymes, elucidating the intertwined effects of elastic forces and friction forces on enzyme function. This breakthrough allows proteins to be perceived as soft robots or programmable active matter, revolutionizing our understanding of enzymatic catalysis.
The Flatiron Institute's Center for Computational Astrophysics is now supporting MESA's ongoing maintenance and development after its creator Bill Paxton steps down. The center has hired Philip Mocz as a full-time software engineer to ensure MESA's continued growth and impact in stellar physics.
Researchers developed a new liquid-crystal-based platform to handle hundreds of optical modes in compact two-dimensional setups, overcoming optical losses. This breakthrough enables the scalability of quantum simulations and all-optical AI systems.
Scientists from South Africa and China successfully established the world's longest intercontinental ultra-secure quantum satellite link spanning 12,900 km. This achievement demonstrates South Africa's potential to develop a thriving quantum ecosystem.
Physicists at the University of Cologne have successfully observed Crossed Andreev Reflection in TI nanowires, a crucial step toward engineering Majorana-based qubits. This breakthrough enables reliable control over superconducting correlations in topological insulator nanowires.
The Global Physics Summit will feature nearly 1,200 sessions and 14,000 presentations on various topics, including astrophysics, climate science, medicine, and quantum information. Registered journalists and public information officers will receive daily emails with meeting information.
Researchers at AWS and Caltech developed a new cat qubit chip, called Ocelot, to suppress errors in quantum computers. The chip uses superconducting circuits to create stable qubits resistant to bit-flip errors.
Researchers used Quantum Approximate Optimization Algorithm (QAOA) to cluster jets in high-energy particle collisions, achieving performance comparable to classical algorithms. The study demonstrates the potential of quantum computing in improving jet clustering for practical applications.
Researchers find that intense laser pulses cause tunnel ionization, generating photocarriers and altering the lattice energy surface, leading to ultrafast melting of wide-gap ceramic materials like MgO. The study demonstrates a universal microscopic mechanism for laser-induced phase transitions.
Discounted hotel rates available at select hotels near the Anaheim Convention Center. The Global Physics Summit will feature nearly 14,000 individual presentations on new research in various fields.
Researchers at Tampere University developed a new method to detect congestive heart failure using inter-beat intervals measured by smartwatches and heart rate monitors. The accuracy of the method was found to be 90% in distinguishing patients with congestive heart failure from healthy control subjects.
Dental implant surgeries require optimal mechanical stress levels for successful bone healing and long-term implant success. Researchers are developing a hybrid biomechanical model using machine learning to provide precise, patient-specific predictions of mechanical stress.
Researchers at Lancaster University have developed a new method to detect Alzheimer's disease by analyzing changes in brain oxygenation dynamics and neuronal function. The study found that individuals with Alzheimer's disease exhibit altered respiratory frequency, which may be an early indicator of the condition.
Researchers found that some materials can store and recall sequences under specific conditions, defying mathematical predictions. This phenomenon relies on 'frustrated' hysterons, which are key to forming and recovering a sequence with asymmetric driving.