Articles tagged with Computational Physics
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.
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.
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.
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.
KAUST researchers have developed a new method to simulate viscous liquids up to 15 times faster than the current state of the art. This breakthrough enables faster simulations for industrial processes, medical devices, computer graphics, and visual simulations.
A new AI program identified four variables for a swinging double-pendulum, but the remaining two variables remain a mystery. The AI successfully predicted physical phenomena in other systems, such as air dancers and lava lamps, with varying numbers of variables.
Scientists at Kyoto University propose a novel approach using holograms to approximate the universe's expansion in de Sitter space. The model uses conformal field theory and a positive integer for the cosmological constant, enabling the identification of the first example of two-dimensional CFT.
A Polish-Japanese team demonstrates a salutary delay in the reaction of crystal atoms to an avalanche of photons, using X-ray laser pulses. This discovery enables the observation of an undisturbed structure of matter by using sufficiently short laser pulses.
Scientists at Chung-Ang University have pioneered a novel method for controlling microdroplet motion on solid surfaces using near-infrared light. This approach allows for more precise control than traditional thermal techniques and opens up new possibilities for applications in microfluidics, drug delivery, and self-cleaning surfaces.
Researchers use computational detective work to verify the existence of a 3D quantum spin liquid in cerium zirconium pyrochlore, overcoming decades-long challenge. The material exhibits fractionalized spin excitations, where electrons do not arrange their spins in relation to neighbors.
Physicists from Cracow have developed a new measurement technique to track phenomena lasting attoseconds, using X-ray chronoscopy. This approach potentially makes it possible to infer events in the world of attophysics even at current XFEL technology.
Researchers from the University of Seville have conducted a groundbreaking experiment demonstrating quantum contextuality without loopholes. The study uses atomic ions to show that certain probabilities have a limit, contradicting previous findings.
Researchers used simulations to compare Einstein's theory and modified gravity, finding that 'dark gravity' may be equally good at explaining data from binary neutron star collisions. This could lead to the discovery of new phenomena detectable by next-generation gravitational interferometers.
Scientists have designed logic operations using liquid crystals, enabling potential applications in robotics and sensing. The technique uses topological defects to carry information, offering a new approach to computing.
Researchers at ETH Zurich have developed a new approach to modeling nonlinear dynamical systems using experimental data. By identifying key structures rather than detailed dynamics, the algorithm reduces calculation time from hours to just minutes.
Researchers at TU Darmstadt and Universitat Politècnica de València used HPC resources to develop a new symmetry-based turbulence theory, resolving the closure problem of turbulence. This approach allows for reduced computational grid size and direct access to mean values like air pressure and speed.
A team of researchers from Ritsumeikan University developed an unprecedented stream cipher using chaos theory to create highly secure cryptographic systems. The new system is resistant to statistical attacks and eavesdropping, even against quantum computers, making it a promising solution for post-quantum era cryptosystems.
Cornell researchers have successfully trained various physical systems, including mechanical, optical, and electrical systems, to perform machine learning tasks. The developed training algorithm enables diverse systems to be chained together for efficient processing.
Researchers at PPPL develop an algorithm to solve the complex equation describing free electron motion in tokamaks, enabling accurate simulations and better control of plasma. This breakthrough provides a rigorous mathematical proof and expands the capabilities of the Computational Sciences Department.
The ATIQ project aims to develop reliable, user-friendly quantum computing demonstrators based on ion trap technology within 30 months. The consortium will optimize hardware for applications in chemistry and finance, paving the way for new approaches in credit risk assessment.
A new machine learning-based algorithm can predict stable material compounds much faster than traditional methods, opening up new avenues for research and discovery. The researchers identified several thousand potential new compounds using the computer, offering a promising breakthrough in materials science.
The WVU-led Dolly Sods GPU cluster enables researchers to accelerate computational research in fields like drug development, interstellar phenomena, and biometrics. The cluster will facilitate the analysis of massive datasets and enable real-time processing of signals from satellites in space.
A team of researchers has developed a simple and efficient method of quantum encryption using single photons, which can detect any attempt to hack the message. The breakthrough brings us closer to securing our data against quantum computers' potential attacks.
New research reveals that sinking tectonic plates are significantly weakened as they enter the mantle, but not broken apart entirely. The study's computer model shows a 'tectonic snake' shape, with stresses pinching the plate along weak points.
Researchers have developed a new method that uses deep neural networks to predict extreme heat waves with unprecedented accuracy, up to two weeks before they occur. This breakthrough has significant implications for risk management, planning, and warning systems, which will greatly improve public safety and support public policies.
Researchers find that triangular-patterned materials can exhibit a mashup of three different phases, with each phase overlapping and competing for dominance. As temperature increases, the material becomes more ordered due to the breaking down of these competing electron arrangements.
Researchers have identified a complex alloy system that can be strengthened and made more ductile using quantum-mechanical modeling. This breakthrough may lead to more efficient engines, lowering fuel consumption and greenhouse gas emissions in the aviation industry.
The PHAse Space MApping experiment, a complex plasma physics research project at WVU, aims to study the motion of ions and electrons in plasmas. The facility can measure three-dimensional motion at very small scales and is capable of performing detailed measurements.
Researchers at the University of Virginia and Penn State are developing a new hardware platform called FerroCoDE that can generate solutions for complex problems more efficiently. The platform uses analog computing to exploit the spatial-temporal properties of oscillators and their synchrony.
Using observations, lab experiments, theory, and computation, researchers have developed a simple theory to explain the form and growth of apples' cusp-like features. The team found that mechanical instability and underlying fruit anatomy play joint roles in giving rise to multiple cusps in fruits.
The 2021 Fall Meeting of the APS Division of Nuclear Physics presents cutting-edge research on nuclear astrophysics, quantum technology, and rare isotopes. Researchers will discuss breakthroughs such as the most precise measurement of neutron lifetime and novel experiments measuring neutron skin in calcium.
Researchers develop a new method to perform logic operations more efficiently and reliably using magnonics. Nanostructured antiferromagnetic wires are well-suited for this purpose, enabling quick and low-energy computation.
The NSF has renewed the Physics of Living Systems graduate research network at Rice for five years, connecting students and educators across institutions to share resources and data. The award will fund local expenses and training programs, as well as efforts to grow faculty and student numbers in the field.
Researchers have identified two possible Mott-insulating pictures in magnetic superexchange couplings of Sr2IrO4, shedding light on the mechanism for superconductivity in doped La2CuO4. The study used different theories to analyze the magnetic interactions in the strong-to-intermediate coupling regime.
A new experimental method tracks the motion of fibers instead of particles to reveal previously hidden information about turbulent flows. The researchers developed an innovative solution using rigid fibers, which allowed them to measure the speed and direction of flow at two points a fixed distance apart.
A City University of Hong Kong physicist has observed the first unpaired singular Weyl magnetic monopole in a specific kind of single crystalline solid, defying the Nielsen-Ninomiya no-go theorem. The discovery opens up new avenues for understanding bulk topological properties and potential applications in spintronics.
Physicists have developed a new method to identify and address imperfections in materials for quantum computing. The technique, terahertz scanning near-field optical microscopy, has been used to optimize fabrication protocols and reduce decoherence.
Researchers at Washington University found that neurons in the primary visual cortex exhibit 'drift' over time, changing their responses to the same stimulus even without learning or experience. This discovery challenges the notion of stable neural activity in sensory cortices.
Researchers at North Carolina State University developed a new method to calculate thermodynamic properties using partition function zeros on quantum computers. By calculating the zeros of the partition function, they can determine free energy, entropy, and other properties without necessitating huge numbers of quantum computations.
Researchers have modelled how drugs are delivered to the respiratory tract via an inhaler to better treat lung diseases. Finer drug particles of around one micron are better able to travel further into the lungs.
SUTD researchers created a novel modeling technique to reduce risk of permanent device damage in resistive memory devices. The new toolkit can predict current accurately, improving prediction accuracy by around ten times.
A team from the University of Bristol's QETLabs developed an algorithm that uses machine learning to reverse engineer Hamiltonian models and formulate approximate models for quantum systems. This breakthrough enables the automated characterization of new devices, such as quantum sensors.
Active matter systems, which can move under their own power, have been found to spontaneously order without higher-level instructions. Researchers developed a theory that predicts certain types of active matter will enter
The Argonne team has created a machine learning algorithm that approximates how the present detector would respond to the greatly increased data expected with the LHC upgrade. This algorithm simulates detector responses and reconstructs objects from physical processes, enabling faster and more accurate analysis of particle collisions.
Scientists have revealed that gallium melt lacks stable crystalline domains and molecule-like Ga2 dimers, offering a fresh perspective on melt formation processes. Experimental data from neutron diffraction provided critical evidence to support this finding.
Researchers have found a new obstacle to effective accelerator beam pulses by forming 'electrostatic solitary waves' that reduce neutralization. Widening the filament injecting electrons into the beam can improve neutralization rates.
Computational statistical mechanics was born from numerical models of fluids developed in the 1950s, initially as a pet project by physicists. These Monte Carlo and Molecular Dynamics simulations were later confirmed through clever applications of importance sampling, proving reliable evidence for describing matter.
Researchers have made strides in medical imaging, computer modeling, and control strategies to optimize Deep Brain Stimulation (DBS) therapy in individual patients. The review highlights the interactive nature of factors influencing DBS effects and paves the way for truly patient-specific optimization.
Researchers observed four colliding galaxies and found a lag between dark matter and its associated galaxy, suggesting that dark matter interacts with forces other than gravity. This discovery could be the first evidence for rich physics in the dark sector, helping scientists better understand dark matter's nature.
A team of researchers has developed novel self-assembling materials, known as 'Soft Lego', which can form complex crystal structures with specific properties. These materials have potential applications in photonics and light guides, offering a new approach to the construction of materials at the macroscopic scale.
Researchers explore how membranes influence self-assembly and structure formation in cells, revealing that membranes promote self-assembly and reproduce structures similar to those found in nature.
Kai Germaschewski, a UNH assistant professor, received a $750,000 grant to develop more refined models of fusion plasmas. His work aims to enhance understanding of the state of plasma and its effects in high-temperature experiments.
Tetrahedral dice pack 76% of container space, surpassing sphere packing, and single molecules can calculate thousands of times faster than PCs.
Researchers at Washington University in St. Louis used a network of interconnected pendulums to demonstrate that introducing disorder can lead to order and synchronization in chaotic systems. The findings have potential applications in understanding neuronal activity and may help explain previously unexplained observations.