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Fresnel Equations

The Fresnel Equations describe the reflection and transmission of light when it encounters an interface between two different media. These equations are fundamental in optics and are used to determine the proportions of light that are reflected and refracted at the boundary. The equations depend on the angle of incidence and the refractive indices of the two media involved.

For unpolarized light, the reflection and transmission coefficients can be derived for both parallel (p-polarized) and perpendicular (s-polarized) components of light. They are given by:

  • For s-polarized light (perpendicular to the plane of incidence):
Rs=∣n1cos⁡θi−n2cos⁡θtn1cos⁡θi+n2cos⁡θt∣2R_s = \left| \frac{n_1 \cos \theta_i - n_2 \cos \theta_t}{n_1 \cos \theta_i + n_2 \cos \theta_t} \right|^2Rs​=​n1​cosθi​+n2​cosθt​n1​cosθi​−n2​cosθt​​​2 Ts=∣2n1cos⁡θin1cos⁡θi+n2cos⁡θt∣2T_s = \left| \frac{2 n_1 \cos \theta_i}{n_1 \cos \theta_i + n_2 \cos \theta_t} \right|^2Ts​=​n1​cosθi​+n2​cosθt​2n1​cosθi​​​2
  • For p-polarized light (parallel to the plane of incidence):
R_p = \left| \frac{n_2 \cos \theta_i - n_1 \cos \theta_t}{n_2 \cos \theta_i + n_1 \cos \theta_t}

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Hamiltonian Energy

The Hamiltonian energy, often denoted as HHH, is a fundamental concept in classical mechanics, quantum mechanics, and statistical mechanics. It represents the total energy of a system, encompassing both kinetic energy and potential energy. Mathematically, the Hamiltonian is typically expressed as:

H(q,p,t)=T(q,p)+V(q)H(q, p, t) = T(q, p) + V(q)H(q,p,t)=T(q,p)+V(q)

where TTT is the kinetic energy, VVV is the potential energy, qqq represents the generalized coordinates, and ppp represents the generalized momenta. In quantum mechanics, the Hamiltonian operator plays a crucial role in the Schrödinger equation, governing the time evolution of quantum states. The Hamiltonian formalism provides powerful tools for analyzing the dynamics of systems, particularly in terms of symmetries and conservation laws, making it a cornerstone of theoretical physics.

Graphene Oxide Reduction

Graphene oxide reduction is a chemical process that transforms graphene oxide (GO) into reduced graphene oxide (rGO), enhancing its electrical conductivity, mechanical strength, and chemical stability. This transformation involves removing oxygen-containing functional groups, such as hydroxyls and epoxides, typically through chemical or thermal reduction methods. Common reducing agents include hydrazine, sodium borohydride, and even thermal treatment at high temperatures. The effectiveness of the reduction can be quantified by measuring the electrical conductivity increase or changes in the material's structural properties. As a result, rGO demonstrates improved properties for various applications, including energy storage, composite materials, and sensors. Understanding the reduction mechanisms is crucial for optimizing these properties and tailoring rGO for specific uses.

Landau Damping

Landau Damping is a phenomenon in plasma physics and kinetic theory that describes the damping of oscillations in a plasma due to the interaction between particles and waves. It occurs when the velocity distribution of particles in a plasma leads to a net energy transfer from the wave to the particles, resulting in a decay of the wave's amplitude. This effect is particularly significant when the wave frequency is close to the particle's natural oscillation frequency, allowing faster particles to gain energy from the wave while slower particles lose energy.

Mathematically, Landau Damping can be understood through the linearized Vlasov equation, which describes the evolution of the distribution function of particles in phase space. The key condition for Landau Damping is that the wave vector kkk and the frequency ω\omegaω satisfy the dispersion relation, where the imaginary part of the frequency is negative, indicating a damping effect:

ω(k)=ωr(k)−iγ(k)\omega(k) = \omega_r(k) - i\gamma(k)ω(k)=ωr​(k)−iγ(k)

where ωr(k)\omega_r(k)ωr​(k) is the real part (the oscillatory behavior) and γ(k)>0\gamma(k) > 0γ(k)>0 represents the damping term. This phenomenon is crucial for understanding wave propagation in plasmas and has implications for various applications, including fusion research and space physics.

Lindahl Equilibrium

Lindahl Equilibrium ist ein Konzept aus der Wohlfahrtsökonomie, das die Finanzierung öffentlicher Güter behandelt. Es beschreibt einen Zustand, in dem die individuellen Zahlungsbereitschaften der Konsumenten für ein öffentliches Gut mit den Kosten seiner Bereitstellung übereinstimmen. In diesem Gleichgewicht zahlen die Konsumenten unterschiedlich hohe Preise für das gleiche Gut, basierend auf ihrem persönlichen Nutzen. Dies führt zu einer effizienten Allokation von Ressourcen, da jeder Bürger nur für den Teil des Gutes zahlt, den er tatsächlich schätzt. Mathematisch lässt sich das Lindahl-Gleichgewicht durch die Gleichung

∑i=1npi=C\sum_{i=1}^{n} p_i = Ci=1∑n​pi​=C

darstellen, wobei pip_ipi​ die individuelle Zahlungsbereitschaft und CCC die Gesamtkosten des Gutes ist. Das Lindahl-Gleichgewicht stellt sicher, dass die Summe der Zahlungsbereitschaften aller Individuen den Gesamtkosten des öffentlichen Gutes entspricht.

Recombinant Protein Expression

Recombinant protein expression is a biotechnological process used to produce proteins by inserting a gene of interest into a host organism, typically bacteria, yeast, or mammalian cells. This gene encodes the desired protein, which is then expressed using the host's cellular machinery. The process involves several key steps: cloning the gene into a vector, transforming the host cells with this vector, and finally inducing protein expression under specific conditions.

Once the protein is expressed, it can be purified from the host cells using various techniques such as affinity chromatography. This method is crucial for producing proteins for research, therapeutic use, and industrial applications. Recombinant proteins can include enzymes, hormones, antibodies, and more, making this technique a cornerstone of modern biotechnology.

Fermat Theorem

Fermat's Last Theorem states that there are no three positive integers aaa, bbb, and ccc that can satisfy the equation an+bn=cna^n + b^n = c^nan+bn=cn for any integer value of nnn greater than 2. This theorem was proposed by Pierre de Fermat in 1637, famously claiming that he had a proof that was too large to fit in the margin of his book. The theorem remained unproven for over 350 years, becoming one of the most famous unsolved problems in mathematics. It was finally proven by Andrew Wiles in 1994, using techniques from algebraic geometry and number theory, specifically the modularity theorem. The proof is notable not only for its complexity but also for the deep connections it established between various fields of mathematics.