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.
Physicists at Leipzig University have developed a neural network that uses active colloidal particles for artificial intelligence. The system reduces noise and increases efficiency in calculations by utilizing past states of the reservoir.
A Swiss-Polish team has found the answer to why previous attempts to use magnesium hydride for efficient hydrogen storage failed. The researchers developed a new model that predicts local, thermodynamically stable clusters are formed in magnesium during hydrogen injection, reducing hydrogen ion mobility.
Researchers at Maynooth University and the University of Chicago discovered that molecular processes can perform complex calculations rivaling simple neural networks. The study used phase transitions to recognize subtle chemical combinations and build different structures in response.
Researchers identify surface signature that is unique to higher-order topological insulators, allowing for experimental confirmation of their existence. By analyzing spin-dependent surface behaviors, they found a transparent layer separating the material's interior from its surface.
Researchers analyze tidal disruption events (TDEs) to estimate the properties of supermassive black holes and stars. The CN22 model, proposed by Syracuse University researchers, provides a new way forward for understanding TDEs and their implications for galaxy evolution.
A new method allows for the estimation of exercise thresholds based on dynamical correlation properties of heart rate variability, optimizing athlete training and injury prevention. This method utilizes heartbeat interval measurements from sports watches and heart rate monitors, providing a reliable alternative to current methods.
A new unified model confirms that some long-lasting gamma-ray bursts are created in the aftermath of cosmic mergers that spawn an infant black hole surrounded by a giant disk of natal material. The findings explain recently observed long GRBs that astronomers couldn't link to collapsing stars.
Scientists have developed a new, efficient ethanol catalyst made from copper nanoparticles, which is cheaper than platinum and could increase the potential of ethanol fuel cells. The catalyst was created through laser melting and shows great promise for improving ethanol oxidation.
Researchers have carried out the largest ever computer simulations to investigate the Universe's evolution, taking into account ordinary matter and dark energy. The FLAMINGO simulations provide a detailed picture of virtual galaxies and galaxy clusters, allowing for comparisons with observations from new high-powered telescopes.
Research explains why X-ray diffraction images 'darken' at high intensities, offering new perspective for ultra-short laser pulse production. Different atoms respond differently to ultrafast X-ray pulses, potentially improving atomic structure reconstruction and generating even shorter pulses.
The High Performance Data Facility Hub will provide researchers with unprecedented data management resources, accelerating scientific discovery through seamless access to large and complex datasets. The hub will be led by Jefferson Lab and partner with Lawrence Berkeley National Laboratory.
Researchers at the University of Cambridge have shown that simulating models of hypothetical time travel can solve experimental problems in quantum metrology. By manipulating entanglement, they can retroactively change past actions to improve outcomes in the present. The simulation has a 75% chance of failure but provides valuable insi...
Researchers from FAU's College of Engineering and Computer Science employ a computer-vision deep learning technique to analyze wall-bounded turbulent flows. They successfully identify the sources of extreme events in a data-driven manner, providing new insights into non-linear relationships in fluid dynamics simulations.
Researchers at MIT have developed a novel superconducting qubit architecture that can perform operations between qubits with high accuracy, exceeding 99.9% for two-qubit gates and 99.99% for single-qubit gates. The new design utilizes fluxonium qubits, which have longer lifespans than traditional transmon qubits.
Researchers at the University of Waterloo have created a robust method to control individual qubits made of barium, a crucial step towards building functional quantum computers. The new optical system uses laser light and precision engineering to target and control individual atoms with unprecedented accuracy.
Researchers have identified a mechanism explaining the characteristic properties of strange metals, which operate outside normal rules of electricity. The theory combines two properties: electron entanglement and nonuniform atomic arrangement, resulting in electrical resistance.
Scientists studied fluid dynamics to understand interfacial tension, a force affecting mixing of liquids. Their numerical simulation revealed a non-monotonic relationship between flow strength and hydrodynamic instability, overturning conventional wisdom.
A team at Osaka University has simulated photon-photon collisions to produce electron-positron pairs, paving the way for experimental confirmation of quantum physics theories. The simulation uses ultra-intense laser pulses and demonstrates the feasibility of creating matter solely from light.
A team of scientists studied the impact of radiation on DNA, revealing that damaged areas are separated by a critical distance before breaking. The study found an exponential increase in DNA breakage time with distance, providing crucial information for effective DNA repair processes.
Researchers created a self-supervised AI model called GedankenNet that learns physics laws and thought experiments to reconstruct microscopic images. The model successfully reconstructed human tissue samples and Pap smears from holograms without relying on real-world experiments or data.
A newly developed P-VAE framework could speed up computational imaging by reducing the number of measurements required, making it suitable for applications such as scientific discovery and medical imaging. Researchers applied P-VAE to LED microscopy and computed tomography, achieving improved reconstruction with sparse measurements.
Researchers from Japan have solved a long-standing puzzle of porous soft materials, revealing the importance of elastic heterogeneity in tuning molecular adsorption/desorption properties. The study provides physicochemical insight into the origin of elastic heterogeneity within MOFs, with applications to imparting targeted properties.
The Vlasiator model demonstrated that two central theories on plasma eruptions in near-Earth space are simultaneously valid: magnetic reconnection and kinetic instabilities. This finding helps understand how these events occur and improves the predictability of space weather.
A team at the University of Washington has made a breakthrough in quantum computing by detecting signatures of 'fractional quantum anomalous Hall' (FQAH) states in semiconductor materials. This discovery marks a significant step towards building stable qubits and potentially developing fault-tolerant quantum computers.
Princeton researchers used data from NASA's Parker Solar Probe to determine that a catastrophic event, such as a high-speed collision or gaseous explosion, likely created the Geminids meteoroid stream. This is in contrast to most meteor showers, which originate from comets emitting tails of ice and dust.
Researchers developed a new technique called zero noise extrapolation (ZNE) that allows noisy quantum computers to produce accurate results for specific calculations. This breakthrough could enable the use of quantum computing for cutting-edge physics problems and improve classical algorithms.
A group of scientists from the JIHT, HSE and MIPT have developed a novel solution: OpenDust, a fast, open-source code that performs calculations ten times faster than existing analogues. The algorithm uses multiple GPUs simultaneously to accelerate computations.
A research group led by NCKU professor I-Non Chiu conducted the first cosmological study on galaxy clusters identified by eROSITA, analyzing 550 galaxy clusters. The results suggest that Dark Energy occupies up to 76% of the total energy density in the Universe.
The CHEP2023 conference will address computing, networking, and software issues for leading data-intensive science experiments. Key trends and solutions in computing as it applies to research in nuclear and high energy physics will be discussed.
Researchers from Osaka University developed an AI algorithm called FINDE that discovers and preserves the underlying conservation laws of real-world dynamical systems, not just superficial dynamics. FINDE allows for more accurate computer simulations and can reveal additional information about a system's structure.
Researchers developed a nano-excitonic transistor that controls excitons to process massive amounts of data at the speed of light with minimal heat energy loss. This technology has potential applications in optical computing and realizing an era of data explosion driven by AI.
Researchers have derived a formula predicting the effects of environmental noise on quantum computing. By incorporating redundancy in quantum messages, scientists can now quantify how much redundancy is needed to protect against dephasing noise.
The POSTECH team developed a multifunctional tip-enhanced spectroscopy that dynamically controls the physical properties of quasiparticles in 2D materials. This technology increases interlayer excitons' luminous efficiency by 9,000 times and modulates their energy.
A new mathematical model predicts turbulence and heat transport in fusion plasmas with high accuracy, approximately 1,500 times faster than conventional large-scale nonlinear calculations. This breakthrough accelerates fusion research and expands the range of applicability.
Researchers have developed a new simulation method to study polarons in 2D materials, which could lead to breakthroughs in OLED TVs and hydrogen fuel production. The study uses quantum mechanical theory and computation to determine the fundamental properties of polarons in 2D materials.
The team has developed a coupled dipole method-based photonic dispersion solver (CDPDS) online, enabling fast computation and accessibility to general users. The CDPDS provides band dispersions and topological phases of one-dimensional and two-dimensional photonic crystals, making it suitable for rapid simulations and modeling.
A new mathematical theory developed by Peter Wolynes and David Logan predicts the nature of motions in a chlorophyll molecule when it absorbs energy from sunlight. The findings suggest that there are exceptions where simple motions persist for long times, influencing processes like photosynthesis.
A new study by Tulane University demonstrates that even a single atom can act as a reservoir for computing, processing information optically. The researchers proposed a non-linear single-atom computer where input and output are encoded in light, enabling flexible computation with any desired outcome.
A new pumping strategy has been developed to slash energy costs of fluid transport by up to 22%. By switching pumps on and off, turbulent flows can be reduced, resulting in more efficient fluid transport. This approach could bring significant economic and environmental benefits, particularly for the transition to green energy.
A new study uses Fourier analysis to understand how deep neural networks learn complex physics. By analyzing the equation of a fully trained model, researchers were able to identify crucial information about how the network learns and generalizes. This breakthrough could accelerate the use of scientific deep learning in climate science.
A new Swedish quantum computer is being made available to the industry, accompanied by a test bed and a quantum helpdesk. The test bed will allow companies and researchers to solve problems using quantum technology at a significantly lower cost than existing commercial options.
Physicists at MIT and Caltech developed a new benchmarking protocol to characterize the fidelity of quantum analog simulators, enabling high precision characterization. The protocol analyzes random fluctuations in atomic-scale systems, revealing universal patterns that can be used to gauge the accuracy of these devices.
Researchers demonstrated high-visibility quantum interference between two independent semiconductor quantum dots, an important step toward scalable quantum networks. The observed interference visibility is up to 93%, paving the way for solid-state quantum networks with distances over 300 km.
Researchers used auto-encoder technique to analyze 150 XRD patterns of magnetic alloys, identifying clusters and fine-tuning alloys by detecting relevant peaks. The approach enables accelerated development of high-efficiency materials with low environmental impact.
A Polish-German-Italian team developed a new simulation tool called XSPIN to simulate X-ray-induced demagnetisation in multilayer materials. The tool allows for control over laser pulse parameters, such as energy and duration, to achieve specified spatial and temporal scales.
A team of quantum engineers at UNSW Sydney has developed a method to reset a quantum computer using a fast digital voltmeter to watch the temperature of an electron, reducing preparation errors from 20% to 1%. This innovation represents a modern twist on Maxwell's demon, a thought experiment that dates back to 1867.
A Collaborative Research Centre investigates animal navigation using the Earth's magnetic field. The study focuses on vertebrates, including birds and fish, aiming to protect endangered migratory species.
Researchers discover circular polycatenanes with properties similar to DNA rings, showcasing a connection between local and global properties. These structures have unique elastic properties and can be used in designing new materials and micro-sensors.
Researchers have developed a continuum theory of micro-hairs, allowing for the study of collective movements and fluid flows. The theory reveals that even random movement is unstable and leads to synchronisation, while perfect unison is also unstable, resulting in specific patterns of movement.
A team of researchers from Japan Advanced Institute of Science and Technology developed an analytical tool to investigate the ordering of fluorine in lead titanium oxyfluoride. They used first-principles calculation to analyze experimental results and determined the element substitution positions, finding that fluorine atoms predominan...
The study reveals that the distribution of local interface displacements exhibits non-zero skewness due to pinned segments lagging behind the rest. The researchers also found that scaling properties of interface segments depend on whether they are lagging or moving ahead of the average displacement.
Researchers have successfully demonstrated large numbers of interacting qubits maintaining coherence for an unprecedentedly long time, in a programmable solid state superconducting processor. This breakthrough could accelerate computing processes and enable applications such as quantum sensing and metrology.
A breakthrough computer model from Chalmers University of Technology reveals the properties of an atomic nucleus, providing insights into the strong force that governs neutron star behavior. The model predicts a surprisingly thin neutron skin, which could lead to increased understanding of heavy element creation in neutron stars.
Researchers from the Max Born Institute found that magnesium ions reduce ultrafast fluctuations in water's hydration shell, slowing solvation dynamics. The study reveals a short-range effect of individual ion pairs on dilute aqueous systems.
Physicists at the University of Basel have developed a computational shortcut for neural networks, allowing for faster calculation of optimal solutions without training. This breakthrough provides insight into neural network functioning and could help detect unknown phase transitions in materials and quantum systems.
A joint research team has proposed a method for densely storing data using a sharp probe, enabling polarization switching with minimal force. The result shows a significant increase in storage capacity, reaching up to 1 terabit per square centimeter.
Physicists used machine learning to compress a complex quantum problem into four equations, capturing the physics of electrons on a lattice with high accuracy. The approach could revolutionize how scientists investigate systems containing many interacting electrons and potentially aid in designing materials with sought-after properties.
Researchers at the University of Oldenburg and Fraunhofer IWES collaborate on a new project to develop more accurate wind flow simulations using artificial intelligence. The goal is to reduce computing times and enhance precision, ultimately accelerating innovation in wind turbine design.
Scientists reconstruct evolution of complex multicellular organisms using genomic data and computational models, revealing gradual changes that began early in evolution. The research reveals distinct paths taken by animal and fungal lineages, shedding light on their shared eukaryotic supergroup.
Physicists have created a way to simulate quantum entanglement between interacting particles using neural networks and fictitious 'ghost' electrons. This approach enables accurate predictions of molecule behavior, which could lead to breakthroughs in pharmaceutical development and material design.