Articles tagged with Computational Physics
Researchers create an analog system that can learn complex tasks like XOR relationships and nonlinear regression, using local learning rules without centralized processor. The system is fast, low-power, and scalable, offering a unique opportunity for studying emergent learning.
Research using a novel microscopic technique reveals that gold nanoparticles' lethality to cancer cells is more complex than previously thought. Smaller nanoparticles can regenerate and divide after initial stress, while larger star-shaped particles cause oxidative stress leading to programmed cell death.
Scientists at uOttawa have developed Fourier Quantum Process Tomography (FQPT) to validate quantum circuit performance. The technique allows for high-accuracy characterization with minimal measurements, enabling significant advancements in quantum computing.
Researchers developed a computational method to estimate sudden cardiac death risk using one-minute heart rate measurements at rest. The new method provides a significantly better estimate than previous analyses, identifying differences in heart rate intervals between high-risk and healthy patients.
Dr. Alice Walker will investigate the design of fluorescent protein sensors using computer simulations, which may aid in tracking diseases and monitoring treatment effectiveness in living cells and organisms. The five-year $690,816 grant also supports undergraduate research opportunities for WSU students.
Researchers at Lancaster University and Radboud University Nijmegen have discovered a novel pathway to modulate and amplify spin waves at the nanoscale, paving the way for dissipation-free quantum information technologies. The study's findings could lead to the development of fast and energy-efficient computing devices.
A recent study combines experimental data with state-of-the-art calculations to reveal new details on the origins of proton spin. The research shows that gluons, which hold protons together, contribute significantly to the proton's spin, contradicting earlier findings.
An international research team uses wavefunction matching to overcome computational challenges in ab initio methods for nuclear physics. By transforming realistic high-fidelity interactions into easily computable ones, they can perform accurate calculations that match real-world data on nuclear properties.
Researchers introduce mathematical equations revealing minimum and maximum predicted energy cost of computational processes with randomness, offering insights into computing energy-cost bounds. The framework offers a way to calculate lower bounds on the energy cost of unpredictable finish situations.
Using the Hubbard model, researchers successfully re-created key features of cuprate superconductivity, which has puzzled scientists for decades. The breakthrough demonstrates the worth of simple models in understanding complex physics.
Researchers created a digital twin model that predicts and controls complex systems, achieving higher accuracy than traditional methods. The algorithm is compact, energy-efficient, and easy to implement, making it suitable for self-driving vehicles and other dynamic systems.
Researchers at the University of Arizona and Sandia National Laboratories have developed a new class of synthetic materials that enable giant nonlinear interactions between phonons. This breakthrough could lead to smaller, more efficient wireless devices, such as smartphones or other data transmitters.
A new study using the James Webb Space Telescope found that the universe's early galaxies developed and matured much faster than previously believed. Almost 20% of disc galaxies observed had bar formations, indicating a more settled stage in galaxy evolution.
Zhite Yu has been awarded the 2024 J.J. and Noriko Sakurai Dissertation Award in Theoretical Particle Physics for his novel and outstanding doctoral thesis work. He studied the proton's interior using electron-scattering processes and proposed two new methods to overcome limitations, which can provide more information about partonic st...
Researchers from Lehigh University have developed a material that promises over 190% quantum efficiency in solar cells, exceeding the theoretical limit for silicon-based materials. The material's 'intermediate band states' enable efficient absorption of sunlight and production of charge carriers.
Researchers visualize chiral interface state at atomic scale for the first time, allowing on-demand creation of conducting channels. The technique has promise for building tunable networks of electron channels and advancing quantum computing.
Researchers from the University of Tokyo have developed a physics-based predictive tool that quickly identifies stable intercalated materials for advanced electronics and energy storage devices. By analyzing over 9,000 compounds, the tool uses straightforward principles from undergraduate chemistry to predict host-guest stability.
Scientists create high-throughput automation to calculate surface properties of crystalline materials using established laws of physics. This accelerates the search for relevant materials for applications in energy conversion, production, and storage.
Researchers at Chalmers University of Technology developed a computational model to measure entropy production on the nanoscale in laser-excited crystalline materials. The model reveals that phonons, lattice vibrations, can produce entropy similar to bacteria in water.
Astronomers have charted the largest-ever volume of the universe with a new map of active supermassive black holes, logging 1.3 million quasars in space and time. This map allows scientists to study dark matter and the universe's expansion by comparing distant quasars and their host galaxies.
The Rensselaer Polytechnic Institute researcher is working with the Tachyon Project to create surrogate machine learning models that can simulate and analyze particle physics data in real-time. This project aims to improve scientific discovery and workflow performance for scientists at Fermilab and ALCF.
Researchers at MIT have observed a rare electronic state in which electrons become fractions of their total charge without the need for external magnetic fields. This effect, known as the fractional quantum anomalous Hall effect, has significant implications for the development of topological quantum computing.
Researchers at Waseda University studied the behavior of chiral skyrmions in chiral flower-like obstacles and found that they exhibit active matter-like behaviors. The system can be used to develop a topological sorting device, which may create ordered results from disordered motion.
A new study by the Hebrew University introduces a flux-based statistical theory that predicts chaotic outcomes in non-hierarchical three-body systems. The theory offers a more efficient approach to analyzing complex systems, enabling deeper exploration and understanding of chaotic phenomena.
Researchers at Penn State have created a new fusion of materials that exhibits chiral topological superconductivity, a property required for topological quantum computation. The combination of magnetic materials and iron chalcogenide could enable the development of robust quantum computers with unique properties.
Researchers can manipulate microbial social evolution by controlling environmental flow patterns, promoting cooperation and discouraging cheating. This approach holds promise for addressing challenges like infection, antibiotic resistance, and wastewater treatment.
Scientists have successfully discovered the mechanism of trion generation using a tip-enhanced cavity-spectroscopy system. This approach enables nanoscale control and investigation of trion emission properties.
Researchers have successfully induced and controlled polarization states within metals using flexoelectric fields. This method has the potential to mitigate power losses attributed to semiconductors and extend battery lifespan in electronic devices.
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.