Tootfinder

B\"ottcher-Wenzel inequality for weighted Frobenius norms and its application to quantum physics
Aina Mayumi, Gen Kimura, Hiromichi Ohno, Dariusz Chru\'sci\'nski
https://arxiv.org/abs/2403.04199

Böttcher-Wenzel inequality for weighted Frobenius norms and its application to quantum physics
By employing a weighted Frobenius norm with a positive matrix $ω$, we introduce natural generalizations of the famous Böttcher-Wenzel (BW) inequality. Specifically, we explore six types of bounds, labeled (i) through (vi), on the norms of the commutator $[A,B]:= AB - BA$, based on the combination of the weighted Frobenius norm $\|A\|_ω:= \sqrt{{\rm tr}(A^\ast A ω)}$ and the usual Frobenius norm $\|A\| := \sqrt{{\rm tr}(A^\ast A)}$. While the tight bound for the case (vi)…

This https://arxiv.org/abs/2403.02937 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum Algorithms in a Superposition of Spacetimes
Quantum computers are expected to revolutionize our ability to process information. The advancement from classical to quantum computing is a product of our advancement from classical to quantum physics -- the more our understanding of the universe grows, so does our ability to use it for computation. A natural question that arises is, what will physics allow in the future? Can more advanced theories of physics increase our computational power, beyond quantum computing? An active field of rese…

This https://arxiv.org/abs/2405.00316 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Enhance Planning with Physics-informed Safety Controllor for End-to-end Autonomous Driving
Recent years have seen a growing research interest in applications of Deep Neural Networks (DNN) on autonomous vehicle technology. The trend started with perception and prediction a few years ago and it is gradually being applied to motion planning tasks. Despite the performance of networks improve over time, DNN planners inherit the natural drawbacks of Deep Learning. Learning-based planners have limitations in achieving perfect accuracy on the training dataset and network performance can be a…

Thomas K. Gaisser, a Pioneer of Particle Astrophysics
Francis Halzen, Paolo Lipari
https://arxiv.org/abs/2403.03207 https://arxiv.org/pdf/2403.03207
arXiv:2403.03207v1 Announce Type: new
Abstract: We describe the pioneering contributions of Thomas K. Gaisser to the birth and development of particle astrophysics, a new field of research at the intersection of cosmic ray physics, astronomy, astrophysics, and particle physics that has emerged in the last few decades. We will especially focus on his studies of natural beams of neutrinos: those generated by the interactions of cosmic rays in the Earth's atmosphere and those emitted by astrophysical sources. Tom actively participated in the discovery of these cosmic neutrinos as well. His contributions also extend to gamma-ray astronomy, the study of the cosmic ray spectra and composition, and the modeling of cosmic ray interactions in the atmosphere and in astrophysical environments. Tom invariably focused his research on the theoretical and phenomenological problems of greatest interest at the time, producing frameworks that transparently interpreted often complex data. These studies have been very influential and have shaped the development of the field.

B\"ottcher-Wenzel inequality for weighted Frobenius norms and its application to quantum physics
Aina Mayumi, Gen Kimura, Hiromichi Ohno, Dariusz Chru\'sci\'nski
https://arxiv.org/abs/2403.04199

Böttcher-Wenzel inequality for weighted Frobenius norms and its application to quantum physics
By employing a weighted Frobenius norm with a positive matrix $ω$, we introduce natural generalizations of the famous Böttcher-Wenzel (BW) inequality. Specifically, we explore six types of bounds, labeled (i) through (vi), on the norms of the commutator $[A,B]:= AB - BA$, based on the combination of the weighted Frobenius norm $\|A\|_ω:= \sqrt{{\rm tr}(A^\ast A ω)}$ and the usual Frobenius norm $\|A\| := \sqrt{{\rm tr}(A^\ast A)}$. While the tight bound for the case (vi)…

Gauss-Newton Natural Gradient Descent for Physics-Informed Computational Fluid Dynamics
Anas Jnini, Flavio Vella, Marius Zeinhofer
https://arxiv.org/abs/2402.10680

Gauss-Newton Natural Gradient Descent for Physics-Informed Computational Fluid Dynamics
We propose Gauss-Newton's method in function space for the solution of the Navier-Stokes equations in the physics-informed neural network (PINN) framework. Upon discretization, this yields a natural gradient method that provably mimics the function space dynamics. Our computational results demonstrate close to single-precision accuracy measured in relative $L^2$ norm on a number of benchmark problems. To the best of our knowledge, this constitutes the first contribution in the PINN literature t…

A Transient Thermal Model for Power Electronics Systems
Neelakantan Padmanabhan
https://arxiv.org/abs/2403.03268 https://arxiv.org/pd…

A Transient Thermal Model for Power Electronics Systems
An equation based reduced order model applicable to generalized heat equation and thermal simulations of power electronics systems developed in commercial CFD tools, is presented in this work. The model considers the physics of heat transfer between multiple objects in different mediums and presents a set of equations that can be applied to a wide range of heat transfer scenarios including conduction, natural and forced convection problems. A few case studies including heat transfer in a power …

Enhance Planning with Physics-informed Safety Controllor for End-to-end Autonomous Driving
Hang Zhou, Haichao Liu, Hongliang Lu, Dan Xu, Jun Ma, Yiding Ji
https://arxiv.org/abs/2405.00316

Enhance Planning with Physics-informed Safety Controllor for End-to-end Autonomous Driving
Recent years have seen a growing research interest in applications of Deep Neural Networks (DNN) on autonomous vehicle technology. The trend started with perception and prediction a few years ago and it is gradually being applied to motion planning tasks. Despite the performance of networks improve over time, DNN planners inherit the natural drawbacks of Deep Learning. Learning-based planners have limitations in achieving perfect accuracy on the training dataset and network performance can be a…

This https://arxiv.org/abs/2211.04359 has been replaced.
link: https://scholar.google.com/scholar?q=a

Large Eddy Simulations of Turbulent Pipe Flows At Moderate-To-High Reynolds Numbers
Wall-bounded turbulence is relevant for many engineering and natural science applications, yet there are still aspects of its underlying physics that are not fully understood, particularly at high Reynolds numbers. In this study, we investigate fully-developed turbulent pipe flows at moderate-to-high friction velocity Reynolds numbers ($361 \leq Re_τ \leq 2,000$), corresponding to bulk velocity-based Reynolds numbers of $11,700 \leq Re_{b} \leq 82,500$, using wall-modeled Large Eddy Simulation…

Using Text Embeddings for Deductive Qualitative Research at Scale in Physics Education
Tor Ole B. Odden, Halvor Tyseng, Jonas Timmann Mjaaland, Markus Fleten Kreutzer, Anders Malthe-S{\o}renssen
https://arxiv.org/abs/2402.18087

Using Text Embeddings for Deductive Qualitative Research at Scale in Physics Education
We propose a technique for performing deductive qualitative data analysis at scale on text-based data. Using a natural language processing technique known as text embeddings, we create vector-based representations of texts in a high-dimensional meaning space within which it is possible to quantify differences as vector distances. To apply the technique, we build off prior work that used topic modeling via Latent Dirichlet Allocation to thematically analyze 18 years of the Physics Education Rese…

Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems
Simon Stock, Davood Babazadeh, Christian Becker, Spyros Chatzivasileiadis
https://arxiv.org/abs/2403.13602

Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems
While the uncertainty in generation and demand increases, accurately estimating the dynamic characteristics of power systems becomes crucial for employing the appropriate control actions to maintain their stability. In our previous work, we have shown that Bayesian Physics-informed Neural Networks (BPINNs) outperform conventional system identification methods in identifying the power system dynamic behavior under measurement noise. This paper takes the next natural step and addresses the more s…

Nonlinear Defect Theory of Thermalization in Complex Multimoded Systems
Emily KabatWave Transport in Complex Systems Lab, Department of Physics, Wesleyan University, Middletown, USA, Alba Y. RamosInstitute for Modeling and Innovative Technology, IMIT, Physics Department, Natural and Exact Science Faculty, Northeastern University of Argentina, Corrientes, Argentina, Lucas J. Fern\'andez-Alc\'azarInstitute for Modeling and Innovative Technology, IMIT, Physics Department, Natural …

Nonlinear Defect Theory of Thermalization in Complex Multimoded Systems
We show that a single nonlinear defect can thermalize an initial excitation towards a Rayleigh-Jeans (RJ) state in complex multimoded systems. The thermalization can be hindered by disorder-induced localization phenomena which drive the system into a metastable RJ state. It involves only a (quasi-)isolated set of prethermal modes and can differ dramatically from the thermal RJ. We develop a one-parameter scaling theory that predicts the density of prethermal modes and we derive the modal relaxa…

A Transient Thermal Model for Power Electronics Systems
Neelakantan Padmanabhan
https://arxiv.org/abs/2403.03268 https://arxiv.org/pd…

A Transient Thermal Model for Power Electronics Systems
An equation based reduced order model applicable to generalized heat equation and thermal simulations of power electronics systems developed in commercial CFD tools, is presented in this work. The model considers the physics of heat transfer between multiple objects in different mediums and presents a set of equations that can be applied to a wide range of heat transfer scenarios including conduction, natural and forced convection problems. A few case studies including heat transfer in a power …

Reconfigurable nonreciprocal heat transport with natural bulk materials
Min Lei, Peng Jin, Liujun Xu, Jiping Huang
https://arxiv.org/abs/2405.00002 https:/…

Reconfigurable nonreciprocal heat transport with natural bulk materials
Non-reciprocity is increasingly scrutinised in contemporary physics and engineering, especially in the realm of heat transport. This concept opens up novel avenues for directional heat transport and thermal regulation. Nonetheless, the development of non-reciprocal thermal metamaterials confronts three primary challenges: a constrained operational temperature range and structural scale, considerable energy dissipation, and the limitation of non-reciprocal effects due to external parameters that…

Fascinating... Hunga Tonga had a (small) net _cooling_ effect on the climate, despite the big dollop of water vapour it injected into the stratosphere:
#climatology #GlobalWarming #ClimateChange #2023_climate_anomalies

A Novel Proton Decay Signature at DUNE, JUNO, and Hyper-K
Florian Domingo, Herbi K. Dreiner, Dominik K\"ohler, Saurabh Nangia, Apoorva Shah
https://arxiv.org/abs/2403.18502 <…

A Novel Proton Decay Signature at DUNE, JUNO, and Hyper-K
Proton decay, although unobserved so far, is a natural expectation when attempting to explain the baryon asymmetry of the universe. $p\to K^+\barν$ or $p\to K^+\tildeχ_1^0$, with $\tildeχ_1^0$ a light exotic neutral particle, represent possible decay channels achievable in models of physics beyond the Standard Model, such as the MSSM with trilinear R-parity-violating terms, or the Standard Model extended by a heavy neutral lepton. Among the decay products of these modes, the neutral fermions…

This https://arxiv.org/abs/2403.04199 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Böttcher-Wenzel inequality for weighted Frobenius norms and its application to quantum physics
By employing a weighted Frobenius norm with a positive matrix $ω$, we introduce natural generalizations of the famous Böttcher-Wenzel (BW) inequality. Based on the combination of the weighted Frobenius norm $\|A\|_ω:= \sqrt{{\rm tr}(A^\ast A ω)}$ and the standard Frobenius norm $\|A\| := \sqrt{{\rm tr}(A^\ast A)}$, there are exactly five possible generalizations, labeled (i) through (v), for the bounds on the norms of the commutator $[A,B]:= AB - BA$. In this paper, we e…

Synchronization dynamics of phase oscillators on power grid models
Max Potratzki (Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany), Timo Br\"ohl (Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany, Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany), Thorsten Rings (Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany, Helmholtz Institute for Radiation and Nuclear P…

Synchronization dynamics of phase oscillators on power grid models
We investigate topological and spectral properties of models of European and US-American power grids and of paradigmatic network models as well as their implications for the synchronization dynamics of phase oscillators with heterogeneous natural frequencies. We employ the complex-valued order parameter --~a widely-used indicator for phase ordering~-- to assess the synchronization dynamics and observe the order parameter to exhibit either constant or periodic or non-periodic, possibly chaotic t…

This https://arxiv.org/abs/2312.15632 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Searching for Two-Neutrino and Neutrinoless Double Beta Decay of $^{134}$Xe with the PandaX-4T Experiment
$^{134}$Xe is a candidate isotope for neutrinoless double beta decay~($0νββ$) search. In addition, the two-neutrino case ($2νββ$) allowed by the Standard Model of particle physics has not yet been observed. Utilizing the 10.4% of $^{134}$Xe in the natural xenon in the PandaX-4T detector and its first 94.9-day exposure, we have established the most stringent constraints on $2νββ$ and $0νββ$ of $^{134}$Xe half-lives, with limits of $2.8\times10^{22}$ yr and $3.0\times10^{23}$ yr at 90…

This https://arxiv.org/abs/2311.12713 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Alpha Zero for Physics: Application of Symbolic Regression with Alpha Zero to find the analytical methods in physics
Machine learning with neural networks is now becoming a more and more powerful tool for various tasks, such as natural language processing, image recognition, winning the game, and even for the issues of physics. Although there are many studies on the application of machine learning to numerical calculation and assistance of experiments, the methods of applying machine learning to find the analytical method are poorly studied. In this paper, we propose the frameworks of developing analytical me…

Physics-Transfer Learning for Material Strength Screening
Yingjie Zhao, Zian Zhang, Zhiping Xu
https://arxiv.org/abs/2403.07526 https://

Physics-Transfer Learning for Material Strength Screening
The strength of materials, like many problems in the natural sciences, spans multiple length and time scales, and the solution has to balance accuracy and performance. Peierls stress is one of the central concepts in crystal plasticity that measures the strength through the resistance of a dislocation to plastic flow. The determination of Peierls stress involves a multiscale nature depending on both elastic lattice responses and the energy landscape of crystal slips. Material screening by stren…

This https://arxiv.org/abs/2401.00428 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Training towards significance with the decorrelated event classifier transformer neural network
Experimental particle physics uses machine learning for many of tasks, where one application is to classify signal and background events. The classification can be used to bin an analysis region to enhance the expected significance for a mass resonance search. In natural language processing, one of the leading neural network architectures is the transformer. In this work, an event classifier transformer is proposed to bin an analysis region, in which the network is trained with special techniqu…

This https://arxiv.org/abs/2403.16793 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Fidelity of Wormhole Teleportation in Finite-qubit Systems
The rapid development of quantum science and technology is leading us into an era where quantum many-body systems can be comprehended through quantum simulations. Holographic duality, which states gravity and spacetime can emerge from strongly interacting systems, then offers a natural avenue for the experimental study of gravity physics without delving into experimentally infeasible high energies. A prominent example is the simulation of traversable wormholes through the wormhole teleportation…

This https://arxiv.org/abs/2311.07684 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Gravitational neutrino reheating
Despite having important cosmological implications, the reheating phase is believed to play a crucial role in cosmology and particle physics model building. Conventionally, the model of reheating with an arbitrary coupling of inflaton to massless fields naturally lacks precise prediction and hence difficult to verify through observation. In this paper, we propose a simple and natural reheating mechanism where the particle physics model, namely the Type-I seesaw is shown to play a major role in …

Physics-Transfer Learning for Material Strength Screening
Yingjie Zhao, Zian Zhang, Zhiping Xu
https://arxiv.org/abs/2403.07526 https://

Physics-Transfer Learning for Material Strength Screening
The strength of materials, like many problems in the natural sciences, spans multiple length and time scales, and the solution has to balance accuracy and performance. Peierls stress is one of the central concepts in crystal plasticity that measures the strength through the resistance of a dislocation to plastic flow. The determination of Peierls stress involves a multiscale nature depending on both elastic lattice responses and the energy landscape of crystal slips. Material screening by stren…

Matter and cosmogenesis in Kant's Theory of the Heavens
Garance Benoit (UP1 UFR10)
https://arxiv.org/abs/2403.11710 https://arxiv…

Matter and cosmogenesis in Kant's Theory of the Heavens
In 1755, Kant published his General Natural History and Theory of the Heavens, in which he presented his hypothesis on the formation of the solar system, known as the primitive nebula hypothesis. This original theory of the heavens was written in dialogue with the conceptions of celestial matter of his time. On the one hand, Kant recognized Descartes' cosmological enterprise as a decisive mechanistic requirement for the intelligence of physics, but his vortices of matter fell into disrepute: Ne…

This https://arxiv.org/abs/2403.03207 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Thomas K. Gaisser, a Pioneer of Particle Astrophysics
We describe the pioneering contributions of Thomas K. Gaisser to the birth and development of particle astrophysics, a new field of research at the intersection of cosmic ray physics, astronomy, astrophysics, and particle physics that has emerged in the last few decades. We will especially focus on his studies of natural beams of neutrinos: those generated by the interactions of cosmic rays in the Earth's atmosphere and those emitted by astrophysical sources. Tom actively participated in the di…

An entertaining resonance experiment with just two spring scales
Yajun Wei
https://arxiv.org/abs/2402.07904 https://arxiv.org/pdf/240…

An entertaining resonance experiment with just two spring scales
Resonance is a topic included in most introductory physics courses. Any mechanical system experiences resonance if it is driven by a periodic force with a frequency that matches its natural frequency. There are plenty of simple demonstrations of the resonance phenomena of mechanical systems which can be set up using readily available items . This work presents a very simple approach to demonstrate the phenomena using just two spring scales. The experiment presented here performs a "frequency sw…

Scattering Singularity in Topological Dielectric Photonic Crystals
Langlang Xiong, Xunya Jiang, Guangwei Hu
https://arxiv.org/abs/2403.11613 https://

Scattering Singularity in Topological Dielectric Photonic Crystals
The exploration of topology in natural materials and metamaterials has garnered significant attention. Notably, the one-dimensional (1D) and two-dimensional (2D) Su-Schrieffer-Heeger (SSH) model, assessed through tight-binding approximations, has been extensively investigated in both quantum and classical systems, encompassing general and higher-order topology. Despite these advancements, a comprehensive examination of these models from the perspective of wave physics, particularly the scatteri…

An entertaining resonance experiment with just two spring scales
Yajun Wei
https://arxiv.org/abs/2402.07904 https://arxiv.org/pdf/240…

An entertaining resonance experiment with just two spring scales
Resonance is a topic included in most introductory physics courses. Any mechanical system experiences resonance if it is driven by a periodic force with a frequency that matches its natural frequency. There are plenty of simple demonstrations of the resonance phenomena of mechanical systems which can be set up using readily available items . This work presents a very simple approach to demonstrate the phenomena using just two spring scales. The experiment presented here performs a "frequency sw…