#nqs — Public Fediverse posts

Australia’s crumbling childcare safeguards put kids at risk. How can parents make sure they’re safe?

The real…
#NewsBeep #News #Australia #acecqa #adeleferguson #AU #australianchildren'seducationandcarequalityauthority #BlueCard #childcare #childprotection #childsafety #childsexabuse #childsexualabuse #earlychildhoodlearning #Earlylearning #Education #fourcorners #nationalqualityframework #nationalqualitystandard #nqf #nqs #workingwithchildrencheck #wwcc
https://www.newsbeep.com/au/243562/

Review on solving dynamics of quantum matter by means of neural quantum states #NQS out now:

https://arxiv.org/abs/2506.03124

#machinelearning boosts real-time simulations in #quantum many-body systems, in particular in the challenging regime of two spatial dimensions.

Review on solving dynamics of quantum matter by means of neural quantum states #NQS out now:

https://arxiv.org/abs/2506.03124

#machinelearning boosts real-time simulations in #quantum many-body systems, in particular in the challenging regime of two spatial dimensions.

Review on solving dynamics of quantum matter by means of neural quantum states #NQS out now:

https://arxiv.org/abs/2506.03124

#machinelearning boosts real-time simulations in #quantum many-body systems, in particular in the challenging regime of two spatial dimensions.

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Efficient optimization of deep neural quantum states toward machine precision

Neural quantum states have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a key challenge to train modern large-scale deep network architectures, which would be vital in utilizing the full power of the underlying artificial neural networks. In this recent preprint we take on this challenge:

https://arxiv.org/abs/2302.01941

#nqs #quantum #deepnetworks

Highly Resolved Spectral Functions of Two-Dimensional Systems with Neural Quantum States

Spectral functions are central to link experimental probes to theoretical models in condensed matter physics. However, performing exact numerical calculations for interacting quantum matter has remained a key challenge. In this recent publication, we develop a versatile approach using neural quantum states to obtain spectral properties:

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.131.046501

#quantum #machinelearning #nqs

Highly Resolved Spectral Functions of Two-Dimensional Systems with Neural Quantum States

Spectral functions are central to link experimental probes to theoretical models in condensed matter physics. However, performing exact numerical calculations for interacting quantum matter has remained a key challenge. In this recent publication, we develop a versatile approach using neural quantum states to obtain spectral properties:

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.131.046501

#quantum #machinelearning #nqs