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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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Work and Energy for Variable Forces01:10

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When an object is acted upon by a variable force, the amount of work done and the change in energy of the object can be more complex to calculate compared to when a constant force is applied. Work is the product of force and displacement, while energy is the capacity of a system to do work. When a constant force is applied to an object, the work done can be calculated as the product of the force and the distance moved in the direction of the force. However, when a variable force is applied, the...
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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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Ampere-Maxwell's Law: Problem-Solving01:17

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
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Energy Associated With a Charge Distribution01:21

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The work done to bring a charge through a distance r is given by the potential difference between the initial and the final position. To assemble a collection of point charges, the total work done can be expressed in terms of the product of each pair of charges divided by their separation distance, defined with respect to a suitable origin. Solving this expression gives the energy stored in a point charge distribution.
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Force and Potential Energy in One Dimension01:13

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Force can be calculated from the expression for potential energy, which is a function of position. The component of a conservative force, in a particular direction, equals the negative of the derivative of the corresponding potential energy with respect to the displacement in that direction. For regions where potential energy changes rapidly with displacement, the work done and force is maximum. Also, when force is applied along the positive coordinate axis, the potential energy decreases with...
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Deep Learning-Based Segmentation of Cryo-Electron Tomograms
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Loop-free tensor networks for high-energy physics.

Simone Montangero1,2,3, Enrique Rico4,5, Pietro Silvi6

  • 1Dipartimento di Fisica e Astronomia 'G. Galilei', Università di Padova, Padova 35131, Italy.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|December 20, 2021
PubMed
Summary
This summary is machine-generated.

Tensor network methods offer powerful computational tools originating from quantum physics. This review focuses on their application to high-energy physics, particularly lattice gauge theories, overcoming limitations of traditional Monte Carlo simulations.

Keywords:
lattice gauge theorymany-body quantum systemstensor networks

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Area of Science:

  • Condensed matter physics
  • Quantum information science
  • High-energy physics
  • Quantum chemistry
  • Artificial intelligence

Background:

  • Tensor network methods are a powerful theoretical and numerical paradigm.
  • These methods originate from condensed matter physics and quantum information science.
  • They are increasingly used across diverse research fields.

Purpose of the Study:

  • Introduce tensor network methods.
  • Specialize in loop-free tensor network applications.
  • Focus on high-energy physics problems, especially lattice gauge theories.

Main Methods:

  • Application of loop-free tensor network methods.
  • Studying lattice gauge theories.
  • Addressing regimes hindered by the Monte Carlo sign problem.

Main Results:

  • Tensor networks provide a viable approach for lattice gauge theories.
  • They overcome limitations faced by Monte Carlo methods due to the sign problem.
  • Demonstrates the utility of tensor networks in high-energy physics.

Conclusions:

  • Tensor network methods are versatile tools with broad applicability.
  • Loop-free tensor networks are particularly effective for lattice gauge theories.
  • This approach advances research in quantum technologies for particle physics.