Results 61 to 70 of about 2,534,683 (266)

Wick’s Theorem for Matrix Product States [PDF]

open access: yesPhysical Review Letters, 2013
Matrix-product states and their continuous analogues are variational classes of states that capture quantum many-body systems or quantum fields with low entanglement; they are at the basis of the density-matrix renormalization group method and continuous variants thereof.
Hubener R., Mari A., Eisert J.
openaire   +6 more sources

Reciprocal control of viral infection and phosphoinositide dynamics

open access: yesFEBS Letters, EarlyView.
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley   +1 more source

Unsupervised Generative Modeling Using Matrix Product States

open access: yesPhysical Review X, 2018
Generative modeling, which learns joint probability distribution from data and generates samples according to it, is an important task in machine learning and artificial intelligence.
Zhao-Yu Han   +4 more
doaj   +1 more source

Matrix product approximations to conformal field theories

open access: yesNuclear Physics B, 2017
We establish rigorous error bounds for approximating correlation functions of conformal field theories (CFTs) by certain finite-dimensional tensor networks. For chiral CFTs, the approximation takes the form of a matrix product state.
Robert König, Volkher B. Scholz
doaj   +1 more source

Tangent-space methods for truncating uniform MPS

open access: yesSciPost Physics Core, 2021
A central primitive in quantum tensor network simulations is the problem of approximating a matrix product state with one of a lower bond dimension.
Bram Vanhecke, Maarten Van Damme, Jutho Haegeman, Laurens Vanderstraeten, Frank Verstraete
doaj   +1 more source

Continuum limits of Matrix Product States

open access: yes, 2018
We determine which translationally invariant matrix product states have a continuum limit, that is, which can be considered as discretized versions of states defined in the continuum.
Cirac, J. Ignacio   +3 more
core   +1 more source

Spatiotemporal and quantitative analyses of phosphoinositides – fluorescent probe—and mass spectrometry‐based approaches

open access: yesFEBS Letters, EarlyView.
Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho   +3 more
wiley   +1 more source

An upstream open reading frame regulates expression of the mitochondrial protein Slm35 and mitophagy flux

open access: yesFEBS Letters, EarlyView.
This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva   +5 more
wiley   +1 more source

Structural instability impairs function of the UDP‐xylose synthase 1 Ile181Asn variant associated with short‐stature genetic syndrome in humans

open access: yesFEBS Letters, EarlyView.
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li   +2 more
wiley   +1 more source

Compressing deep neural networks by matrix product operators

open access: yesPhysical Review Research, 2020
A deep neural network is a parametrization of a multilayer mapping of signals in terms of many alternatively arranged linear and nonlinear transformations.
Ze-Feng Gao   +6 more
doaj   +1 more source

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