#condensedmatter — Public Fediverse posts

https://www.europesays.com/uk/949858/ Scientists Create “Quantum Sound” Device That Works Near Absolute Zero #CondensedMatter #lasers #MaterialsScience #McGillUniversity #Nanotechnology #Physics #QuantumPhysics #Science #UK #UnitedKingdom

Scientists Create “Quantum Sound” Device That Works Near Absolute Zero

A new ultra-cold device developed at McGill University can generate controlled sound-like quantum vibrations known as phonons. The…
#NewsBeep #News #Physics #CA #Canada #CondensedMatter #Lasers #MaterialsScience #McGillUniversity #Nanotechnology #Quantumphysics #Science
https://www.newsbeep.com/ca/659611/

Scientists Create “Quantum Sound” Device That Works Near Absolute Zero

A new ultra-cold device developed at McGill University can generate controlled sound-like quantum vibrations known as phonons. The…
#NewsBeep #News #US #USA #UnitedStates #UnitedStatesOfAmerica #Physics #CondensedMatter #lasers #MaterialsScience #McGillUniversity #Nanotechnology #QuantumPhysics #Science
https://www.newsbeep.com/us/634141/

Scientists Create “Quantum Sound” Device That Works Near Absolute Zero

A new ultra-cold device developed at McGill University can generate controlled sound-like quantum vibrations known as phonons. The…
#NewsBeep #News #US #USA #UnitedStates #UnitedStatesOfAmerica #Physics #CondensedMatter #lasers #MaterialsScience #McGillUniversity #Nanotechnology #QuantumPhysics #Science
https://www.newsbeep.com/us/634141/

https://www.europesays.com/ie/477018/ Scientists Create “Quantum Sound” Device That Works Near Absolute Zero #CondensedMatter #Éire #IE #Ireland #Lasers #MaterialsScience #McGillUniversity #Nanotechnology #QuantumPhysics #Technology

New publication https://doi.org/10.1038/s41524-025-01880-3

Our work on AD-DFPT, a unification of #automaticdifferentiation with linear response for #densityfunctionaltheory is published in npj Computational Materials. We show examples for #property predition, #uncertainty propagation, the design of #materials and #machinelearning of new #dft models. #condensedmatter #dftk

New preprint https://arxiv.org/abs/2511.06957

A #perspective discussing Moreau-Yosida (MY) techniques in #densityfunctionaltheory.
MY regularisation has enabled to import tools from #convexanalysis into #dft
providing a new mathematical understanding of the most important atomistic simulation approach
and new robust algorithms for Kohn-Sham #dft.

Thanks to my co-authors from the #hylleraas centre and #oslomet for insightful discussions.

#condensedmatter #quantumchemistry #numericalanalysis #dftk

New preprint: https://arxiv.org/abs/2509.07785

We present an implementation of AD-DFPT, a unification of #automaticdifferentiation with classical #dfpt response techniques for #densityfunctionaltheory (#dft). We demonstrate its use for #property predition, #uncertainty propagation, design of new #materials as well as the #machinelearning of new #dft models.

#condensedmatter #planewave #response #physics #simulation #computation

New publication https://doi.org/10.1103/PhysRevB.111.205143

New algorithm for the #inverseproblem of Kohn-Sham #densityfunctionaltheory (#dft), i.e. to find the #potential from the #density.

Outcome of a fun collaboration of @herbst with the group of Andre Laestadius at #oslomet to derive first mathematical error bounds for this problem

#condensedmatter #planewave #numericalanalysis #convexanalysis #dftk

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"