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Related Concept Videos

Inertia Tensor01:24

Inertia Tensor

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The concept of the inertia tensor is employed to depict the mass distribution and rotational inertia of a solid or rigid object. This tensor is expressed through a three-by-three matrix. Each component within this matrix corresponds to varying moments of inertia about specific axes.
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Network Covalent Solids02:18

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Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Trial and Error and Algorithm01:12

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A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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Thermal expansion and Thermal stress: Problem Solving01:27

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San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
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Thermal strain is a concept that arises when we consider how temperature changes affect structures. Unlike the conventional assumption that structures remain constant under load, real-world scenarios often involve temperature fluctuations that can significantly impact these structures. Consider a homogeneous rod with a uniform cross-section resting freely on a flat horizontal surface. If the rod's temperature increases, the rod elongates. This elongation is proportional to the temperature...
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Characterization of Thermal Transport in One-dimensional Solid Materials
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Tensor Network Annealing Algorithm for Two-Dimensional Thermal States.

A Kshetrimayum1,2, M Rizzi2, J Eisert1,3

  • 1Dahlem Center for Complex Quantum Systems, Physics Department, Freie Universität Berlin, 14195 Berlin, Germany.

Physical Review Letters
|March 9, 2019
PubMed
Summary
This summary is machine-generated.

We developed a new tensor network algorithm to simulate two-dimensional quantum systems at finite temperatures. This method accurately models thermal states, aiding experimental studies and quantum simulations.

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Area of Science:

  • Condensed Matter Physics
  • Quantum Information Science

Background:

  • Tensor network methods are crucial for strongly correlated matter.
  • Simulating 2D quantum systems at finite temperatures is challenging.

Purpose of the Study:

  • To introduce a novel tensor network algorithm for simulating 2D quantum lattice systems at finite temperatures.
  • To enable simulations in the thermodynamic limit.

Main Methods:

  • Development of projected entangled pair states and operators.
  • Algorithm mimics cooling from infinite to finite temperature.

Main Results:

  • Successfully simulated the finite-temperature phase transition of the 2D Ising model, showing excellent agreement with exact solutions.
  • Studied the finite-temperature Bose-Hubbard model for two and three bosonic modes per site.

Conclusions:

  • The new algorithm provides a powerful tool for studying 2D quantum systems at finite temperatures.
  • Supports experimental research on 2D materials and benchmarks quantum simulators.