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Created and edited by Alejandro Rosales. Dedicated to PK and Lucy, my best boy and best girl. I publish articles to this educational website in my free time so I can talk and teach about subjects I love.
Using quantum computing, the authors exploit quantum mechanics for the algorithmic complexity optimization of a support vector machine with high-dimensional... read more
A quantum convolutional neural network combines two key techniques: multi-scale entanglement renormalization ansatz MERA, which is a variational ansatz for many-body wavefunctions... read more
Entanglement renormalization is a numerical technique that locally reorganizes the Hilbert space of a quantum many-body system to reduce entanglement in its wave function. It addresses the computational challenges of real-space renormalization group RG methods, which struggle with the rapid growth of degrees of freedom during successive RG transformations. The key idea is... read more
Let \(\mathscr{N}\) denote noise, \(\mathscr{R}\) denote the recovery process, and
\(L(H)\) denote the space of linear operators on \(H\). The noise and recovery processes
can be described as quantum operations \(\mathscr{N}, \mathscr{R}: L(H) \rightarrow L(H)\),
from where the mapping can be represented as an operator-sum such as:
\(\mathscr{N}(\rho)=\sum_i E_i \rho E_i^{\dagger},\) \(\quad E_i \in L(H),\) \(\quad
\mathscr{N}=\left\{E_i\right\}\)
Given the quantum code \(C_{Q}\), a subspace of Hilbert space \(H\), there exists a
recovery... read more
The formula in the case of \(SU(2)\) is as follows. Choose a polynomial \(Q\). For each \(k \in
\mathbb{Z}_{+}\), let
\(\xi(k, t)\) be the formal power series in \(t\) that represents a unique critical point of the
function in \(\xi\).
\(F(\xi ; h, k, t)\) \(:=\frac{1}{2}(\xi-k)^2+t \cdot \frac{h}{2 \pi^2} \cdot Q(\pi \xi
/ h)\)
where, \(t\) is treated as a formal variable. \(\xi(k,t)\) undergoes \(t\)-series expansion near the minimum
\(\xi(k,0)=k\), formulated as:
\(\displaystyle{ \int_{F(\Sigma ; G)} \exp \left\{h \omega+t \cdot[\Sigma] \backslash
Q\left(u^* \phi_2\right)\right\} }\)
\(\displaystyle{ =\# Z(G) \cdot h^{3 g-3} \operatorname{vol}(G)^{2 g-2} }\)
\(\displaystyle{ \sum_{k>0}\left[\frac{1+\frac{t}{2 h} Q^{\prime \prime}(\xi(k, t))}{\xi(t,
k)^2}\right]^{g-1} }\)
such that, \(\#Z(G)=2\) for \(SU(2)\)...
read more
A Riemannian manifold is a smooth manifold \(M\) with a Riemannian metric denoted \((M,g)\). For every point
\(p\in M\) the tangent bundle of \(M\) assigns a vector space \(T_{p}M\), termed the tangent space of \(M\)
at
\(p\). The Riemanniam metric defines a positive-definite inner product:
\(g_p: T_p M \times T_p M \rightarrow \mathbb{R}\)
with a norm \(|\cdot|_p: T_p M \rightarrow \mathbb{R}\) defined as:
\(|v|_p=\sqrt{g_p(v, v)}\)
...read more
The thalamic nuclei are paired structures of the thalamus divided into three main groups: the lateral nuclear, medial nuclear, and anterior nuclear groups. The internal medullary lamina, a Y-shaped structure that splits these groups, is present on each side of the thalamus. A midline, thin thalamic nuclei, adjacent to the... read more