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Since 1960, the Journal of Mathematical Physics (JMP) has published some of the best papers from outstanding mathematicians and physicists. JMP was the first journal in the field of mathematical physics and publishes research that connects the application of mathematics to problems in physics, as well as illustrates the development of mathematical methods for such applications and for the formulation of physical theories.

The Journal of Mathematical Physics  (JMP) features content in all areas of mathematical physics. Specifically, the articles focus on areas of research that illustrate the application of mathematics to problems in physics, the development of mathematical methods for such applications, and for the formulation of physical theories. The mathematics featured in the articles are written so that theoretical physicists can understand them. JMP also publishes review articles on mathematical subjects relevant to physics as well as special issues that combine manuscripts on a topic of current interest to the mathematical physics community.

JMP welcomes original research of the highest quality in all active areas of mathematical physics, including the following:

• Partial Differential Equations
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• Quantum Mechanics - General and Nonrelativistic
• Quantum Information and Computation
• Relativistic Quantum Mechanics, Quantum Field Theory, Quantum Gravity, and String Theory
• General Relativity and Gravitation
• Dynamical Systems
• Classical Mechanics and Classical Fields
• Statistical Physics
• Methods of Mathematical Physics

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• 2021 : 24th Annual Conference on Quantum Information Processing; Great Lakes Mathematical Physics Meeting (GLaMP); XX International Congress on Mathematical Physics; Learning from Insulators: New Trends in the Study of Conductivity of Metals (Workshop)
• 2019 : Young Researchers Integrability School and Workshop; Mathematical Physics at The Crossings (Celebrating the 65th Birthday of George Hagedorn); Great Lakes Mathematical Physics Meeting (GLaMP 2019); Mathematical Results in Quantum Theory (QMath14); Quantissima in the Serenissima III
• 2018 : Arizona School of Analysis and Mathematical Physics; Workshop on probabilistic approaches to quantum spin systems; 7th Summer School on Current Topics in Mathematical Physics; XIX International Congress on Mathematical Physics; School on Mathematics of Non-equilibrium Statistical Mechanics, on the occasion of the sixtieth birthday of Claude-Alain Pillet
• 2017 : Spectral Days 2017; ESI-EMS-IAMP - Mathematical Relativity Summer School “Between Geometry and Relativity”; International Conference on Clifford Algebras and Their Applications in Mathematical Physics (ICCA11)
• 2016 : QMATH 13; Young Researcher Symposium "Methods of Modern Mathematical Physics" (Barry Simon Birthday Conference); Frontiers in Mathematical Physics (Barry Simon Birthday Conference); Stochastic and Analytic Methods in Mathematical Physics
• 2015 : The Erwin Schrödinger International Institute for Mathematical Physics Thematic Program on Quantum Many-Body Systems, Random Matrices, and Disorder; ICMP Satellite meeting: Operator Algebras and Quantum Physics; ICMP 2015; Summer-school on current topics in mathematical-physics; Mathematical Approach to Topological Phase in Spintronics

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The international standard serial number (ISSN) for  Journal of  Mathematical  Physics  is 0022-2488 for the printed edition and the electronic ISSN (E-ISSN) is 1089-7658 for the online edition.

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Focus  26 January 2021

Applied physics and mathematics

This page aims to highlight the most interesting papers published in Nature Communications in the interdisciplinary areas where diverse approaches at the boundaries of physics, mathematics, materials science and engineering take place to create new research opportunities.

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Featured articles

Programming mechanics in knitted materials, stitch by stitch

Knitted fabrics are prized for their stretchability, breathability, and long-wearability in everyday life. This study combines experiments and simulations to present a micromechanical approach to understanding the origin of the anisotropic elasticity of four canonical patterns of knitted fabrics.

• Krishma Singal
• Michael S. Dimitriyev
• Elisabetta A. Matsumoto

TacticAI: an AI assistant for football tactics

In modern football games, data-driven analysis serves as a key driver in determining tactics. Wang, Veličković, Hennes et al. develop a geometric deep learning algorithm, named TacticAI, to solve high-dimensional learning tasks over corner kicks and suggest tactics favoured over existing ones 90% of the time.

• Petar Veličković

Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction

For reservoir computing, improving prediction accuracy while maintaining low computing complexity remains a challenge. Inspired by the Granger causality, Li et al. design a data-driven and model-free framework by integrating the inference process and the inferred results on high-order structures.

Dynamical order and many-body correlations in zebrafish show that three is a crowd

Active matter systems, such as zebrafish groups, demonstrate similar collective dynamics to assemblies of particles, or interacting agents. The authors show that majority of dynamics patterns seen in large zebrafish groups are exhibited by a minimal group of three fish.

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Local prediction-learning in high-dimensional spaces enables neural networks to plan

The task of planning a sequence of actions, and dynamically adjusting the plan in dependence of unforeseen circumstances, remains challenging for artificial intelligence frameworks. The authors introduce a learning approach inspired by cognitive functions, that demonstrates high flexibility and generalization capability in planning tasks, suitable for on-chip learning.

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Large exchange-driven intrinsic circular dichroism of a chiral 2D hybrid perovskite

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Emerging opportunities and challenges for the future of reservoir computing

Reservoir Computing has shown advantageous performance in signal processing and learning tasks due to compact design and ability for fast training. Here, the authors discuss the parallel progress of mathematical theory, algorithm design and experimental realizations of Reservoir Computers, and identify emerging opportunities as well as existing challenges for their large-scale industrial adoption.

Low-frequency vibrational density of states of ordinary and ultra-stable glasses

Power-law scaling of low-frequency vibrational density of states is widely observed in glassy materials, yet the value of scaling exponents remains controversial. Here, Xu et al. identify two scaling exponents by separating stable from unstable glass to reconcile the debate in the literature.

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Elasticity-controlled jamming criticality in soft composite solids

Soft composite solids are building blocks for many functional and biological materials, yet it remains challenging to predict their mechanical properties. Zhao et al. propose a criticality framework to connect the mechanics to the critical behaviour near the shear-jamming transition of the dispersed inclusions.

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Predicting the evolution of dynamical systems remains challenging, requiring high computational effort or effective reduction of the system into a low-dimensional space. Here, the authors present a data-driven approach for predicting the evolution of systems exhibiting spatiotemporal dynamics in response to external input signals.

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Learning stochastic dynamics and predicting emergent behavior using transformers

Learning the dynamics governing a simulation or experiment usually requires coarse graining or projection, as the number of transition rates typically grows exponentially with system size. The authors show that transformers, neural networks introduced initially for natural language processing, can be used to parameterize the dynamics of large systems without coarse graining.

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Anticipating regime shifts by mixing early warning signals from different nodes

Early warning signals for rapid regime shifts in complex networks are of importance for ecology, climate and epidemics, where heterogeneities in network nodes and connectivity make construction of early warning signals challenging. The authors propose a method for selecting an optimal set of nodes from which a reliable early warning signal can be obtained.

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Sequential stacking link prediction algorithms for temporal networks

Link prediction in temporal networks is relevant for many real-world systems, however, current approaches are usually characterized by high computational costs. The authors propose a temporal link prediction framework based on the sequential stacking of static network features, for improved computational speed, appropriate for temporal networks with completely unobserved or partially observed target layers.

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A magnetic multi-layer soft robot for on-demand targeted adhesion

Magnetic soft robots offer a non-invasive way to deliver bioadhesives to targeted lesion sites to accelerate the healing. Authors present a magnetic multi-layer soft robot that is capable of performing navigated locomotion on biological tissues and on-demand multi-target adhesion at different sites.

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Reconfigurable droplet networks

Earlier methods for droplet network stabilization require extremely precise control and manipulation with considerable energy consumption, making them difficult to implement. Here, the authors present 2D interfacial networks, formed by irreversible interfacial interactions between polymer chains dissolved in one liquid and ligands dissolved in a second immiscible liquid at random points along the chains.

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• Shaowei Shi

β -Variational autoencoders and transformers for reduced-order modelling of fluid flows

Reduced-order models provide better understanding for complex spatio-temporal dynamics of fluid flows with high numbers of degrees of freedom and non-linear interactions. The authors propose a variational autoencoder and transformer framework for learning the temporal dynamics of the nonlinear reduced-order models relevant for fluid dynamics, weather forecasting, and biomedical engineering.

• Alberto Solera-Rico
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Chiral active particles are sensitive reporters to environmental geometry

There hasn’t been much experimental attention to the interaction of chiral active particles with complex environments. Chan et al. propose an interesting granular particle system based on natural plant seeds to examine the transport of chiral active matter in complex surroundings.

• Chung Wing Chan

Flow-induced periodic chiral structures in an achiral nematic liquid crystal

Under strong surface or geometric constraints, achiral nematic liquid crystals can form chiral structures. Using pressure driven flow, Zhang et al. show a pathway to mirror symmetry breaking that does not require such constraints and that occurs in nematic lyotropic chromonic liquid crystals.

• Weiqiang Wang
• Irmgard Bischofberger

A retrofit sensing strategy for soft fluidic robots

In existing soft robotic sensing strategies, additional components and design changes are often required to sense the environment. Zou et al. introduce a retrofit self-sensing strategy for soft pneumatic actuators, utilizing internal pressure variations arising from interactions.

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Unconventionally fast transport through sliding dynamics of rodlike particles in macromolecular networks

Transport of rodlike particles in macromolecular networks is relevant to various biological processes and technological applications, where thin rods have been mainly in focus. Here the authors investigate diffusion dynamics of thick rods in confinement media of macromolecular networks, and uncover dependence of translational diffusion upon rod length.

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Epidemic graph diagrams as analytics for epidemic control in the data-rich era

Approaches for assessing epidemic risks meet challenges when dealing with high-resolution data available nowadays, that includes behaviors, disease progression, and interventions. The authors propose an analytical framework to compute the epidemic threshold for arbitrary models of diseases, interventions, and hosts contact patterns.

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DomiRank Centrality reveals structural fragility of complex networks via node dominance

Identification of nodes that play a crucial role in the complex network functionality is of high relevance for supply, transportation, and epidemic spreading networks. The authors propose a metric to evaluate nodal dominance based on competition dynamics that integrate local and global topological information, revealing fragile structures in complex networks.

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Learning low-rank latent mesoscale structures in networks

Network structures can be examined at different scales, and subnetworks in the form of motifs can provide insights into global network properties. The authors propose an approach to decompose a network into a set of latent motifs, which can be used for network comparison, network denoising, and edge inference.

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Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics

Brain-inspired spiking neural networks have shown their capability for effective learning, however current models may not consider realistic heterogeneities present in the brain. The authors propose a neuron model with temporal dendritic heterogeneity for improved neuromorphic computing applications.

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The D -Mercator method for the multidimensional hyperbolic embedding of real networks

Embedding of complex networks in the latent geometry allows for a better understanding of their features. The authors propose a framework for mapping complex networks into high-dimensional hyperbolic space to capture their intrinsic dimensionality, navigability and community structure.

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Learning few-shot imitation as cultural transmission

The modelling of human-like behaviours is one of the challenges in the field of Artificial Intelligence. Inspired by experimental studies of cultural evolution, the authors propose a reinforcement learning approach to generate agents capable of real-time  third-person imitation.

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Augmenting interpretable models with large language models during training

Prediction and interpretation tasks may be challenging in high-stakes applications, such as medical decision-making, or systems with compute-limited hardware. The authors introduce an augmented framework for leveraging the knowledge learned by Large Language Models to build interpretable models which are both accurate and efficient.

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A colloidal viewpoint on the sausage catastrophe and the finite sphere packing problem

Packing a finite number of spheres in a compact cluster does not always result in the densest packing. Here, the authors provide a physical realization of the finite sphere packing problem by enclosing colloids in a flaccid lipid vesicle and mapping out a state diagram that displays linear, planar, and cluster conformations of spheres, as well as bistable states that alternate between cluster-plate and plate-linear conformations.

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Spatiotemporal dynamics of traffic bottlenecks yields an early signal of heavy congestions

Heavy traffic jams are difficult to predict due to the complexity of traffic dynamics. The authors propose a framework to unveil identifiable early signals and predict the eventual outcome of traffic bottlenecks, which may be useful for designing effective methods preventing traffic jams.

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Optimal free-surface pumping by an undulating carpet

Pumping fluids at small scales near fluid-fluid interfaces remains challenging. Pandey et al. present a pump that drives interfacial flow by traveling waves on a deformable boundary.

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• Sunghwan Jung

Functional Janus structured liquids and aerogels

A combination of functional nanoparticles and liquid streaming can be used to generate structures for the fabrication of soft functional materials. In this study, authors demonstrate the creation of Janus-structured liquids with anisotropic and programmable distributions of nanoparticles by utilizing interfacial assembly and jamming of nanoparticles at the liquid-liquid interface.

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• Seyyed Alireza Hashemi
• Mohammad Arjmand

Constructing temporal networks with bursty activity patterns

Many real-world systems are characterized by bursty dynamics with interchanging periods of intense activity and quiescence. The authors propose a method to construct temporal networks that match a given activity pattern, and apply it to empirical bursty patterns.

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• Joshua B. Plotkin

Environmental memory boosts group formation of clueless individuals

Indirect coordination among individuals through the environment typically requires some basic levels of communication and information processing. Dias et al. introduce a coordination mechanism that emerges in a population of clueless individuals, facilitated by environmental memory, culminating in group formation.

• Cristóvão S. Dias
• Manish Trivedi
• Giorgio Volpe

A generalized Knudsen theory for gas transport with specular and diffuse reflections

Knudsen theory and Smoluchowski model perform poorly for ballistic gas transport. Qian et al. propose a generalized Knudsen theory to describe gas nanoflow, reconciling both extreme specular reflection and complete diffuse reflection.

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Electroconvective viscous fingering in a single polyelectrolyte fluid on a charge selective surface

When a low-viscosity fluid displaces into a higher viscosity fluid, the liquid-liquid interface becomes unstable causing finger-like patterns. These patterns are usually observed in two fluids, but here Kim et al. describes the development of fingers in a single polyelectrolyte fluid adjacent to a charge-selective interface under the influence of a potential gradient.

• Jeonghwan Kim
• Joonhyeon Kim
• Rhokyun Kwak

Three-degrees-of-freedom orientation manipulation of small untethered robots with a single anisotropic soft magnet

Existing magnetic actuation systems using a single permanent magnet can only achieve 2-DoF orientation manipulation. Wang et al. propose a magnetic actuation method that uses a single anisotropic soft magnet instead of a permanent magnet to enable full 3-DoF orientation manipulation of small, untethered robots.

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Simultaneous and independent topological control of identical microparticles in non-periodic energy landscapes

External fields can control the motion of colloidal particles inducing different trajectories depending on for instance the particle size. The authors here use nonperiodic energy landscapes and topological protection to transport a collection of identical colloidal particles simultaneously and independently.

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• Farzaneh Farrokhzad
• Daniel de las Heras

Non-reciprocity across scales in active mixtures

Non-reciprocal interactions (NRI) are ubiquitous in active systems, but, in the presence of NRI, it is difficult to predict which microscopic systems correspond to a given macroscopic description. Dinelli et al. relate microscopic and macroscopic dynamics of active mixtures and show that non-reciprocity strongly depends on the scale of description.

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• Jérémy O’Byrne
• Julien Tailleur

Spontaneous shock waves in pulse-stimulated flocks of Quincke rollers

Dielectric colloids suspended in a weak electrolyte and energized by a static electric field called Quincke rollers are the model system to study active matter. Zhang et al. report the formation of spontaneous shockwaves in the colloidal Quincke rollers under the temporal activity modulations.

• Andreas Glatz
• Alexey Snezhko

Bioinspired soft robots for deep-sea exploration

High pressure and low temperature are the greatest challenges faced by scientists to explore deep oceans, which remain largely unknow to us today. Li et al. review these challenges and give insight into designing soft robots, inspired by deep-sea creatures, that enable resilient operations in harsh conditions.

• Tuck-Whye Wong

The nature and nurture of network evolution

Degree distributions are often used as informative descriptions of complex networks, however previous studies mainly focused on characterizing the tail of the distribution. The authors propose an evolutionary model that integrates the weight and degree of a node, which allows to better capture degree and degree ratio distributions of real networks and replicate their evolution processes.

• Petter Holme
• Xiangyi Meng

Grasping extreme aerodynamics on a low-dimensional manifold

In adverse weather, small-scale modern aircraft can encounter severe turbulence in urban canyons and mountainous areas hindering stable flight. The authors use machine learning to reveal the low-dimensional manifold that captures the extreme aerodynamics of gust-airfoil interactions.

• Kunihiko Taira

A nanoscale view of the origin of boiling and its dynamics

Boiling, despite being a well-known phenomenon still lacks an understanding of its multiscale and non-equilibrium nature. Using the stochastic mesoscale model based on fluctuating hydrodynamics and diffuse interface approach Gallo et al. describe the process of boiling from nucleation to macroscopic bubble dynamics.

• Mirko Gallo
• Francesco Magaletti
• Carlo Massimo Casciola

Golden section criterion to achieve droplet trampoline effect on metal-based superhydrophobic surface

The relation between the rebound behavior of droplets and surface structure is crucial to regulating the surface dynamic wettability based on structure design. Zhao et al. explore droplet rebound numbers when the droplet impacts laser-ablated microstructures with different structure spaces and report that droplets can consecutively rebound 17 times.

• Shengteng Zhao

Minimum entropy production by microswimmers with internal dissipation

What is the physical limit on entropy production in a suspension of active microswimmers? In answer to this question, the authors derive a general theorem that provides an exact lower bound on the total, external and internal dissipation by a microswimmer and apply it to optimize swimmer shapes.

• Abdallah Daddi-Moussa-Ider
• Ramin Golestanian
• Andrej Vilfan

Liquid–liquid phase separation within fibrillar networks

Liquid–liquid phase separation is known in cell biology as an underlying mechanism of intracellular organization. The authors study a complex interplay between phase separation, network mechanics, and condensate capillarity, providing explanation for the phenomena in complex environments like the cellular interior.

• Jason X. Liu
• Mikko P. Haataja
• Rodney D. Priestley

Hyper-cores promote localization and efficient seeding in higher-order processes

Networks with higher-order interactions provide better description of social and biological systems, however tools to analyze their function still need to be developed. The authors introduce here a decomposition of network in hyper-cores, that gives better understanding of spreading processes and can be applied to fingerprint real-world datasets.

• Marco Mancastroppa
• Iacopo Iacopini
• Alain Barrat

Predicting discrete-time bifurcations with deep learning

Critical transitions and qualitative changes of dynamics in cardiac, ecological, and economical systems, can be characterized by discrete-time bifurcations. The authors propose a deep learning framework that provides early warning signals for critical transitions in discrete-time experimental data.

• Thomas M. Bury
• Daniel Dylewsky

Versatile bubble maneuvering on photopyroelectric slippery surfaces

Light-induced bubble maneuvering remains challenging in terms of response and functional adaptability due to the single driving mechanism including the Marangoni effect or asymmetrical deformation. Using a photopyroelectric slippery surface (PESS), Liu et al. demonstrate the splitting, merging, and detachment of underwater bubbles with high flexibility and precision.

• Haiyang Zhan
• Zichao Yuan

Electro-capillary peeling of thin films

Current methods for thin film peeling suffer from limitations because of complicated preparations and the limitations of applied films. Li et al. present a peeling method for the thin film’s detachment that is achieved by driving liquid to percolate and spread into the bonding layer under electric fields.

• Xianfu Huang

Reactive wetting enabled anchoring of non-wettable iron oxide in liquid metal for miniature soft robot

Interfacial non-wettability between biocompatible iron oxide and liquid metal caused by the substantial mismatch in surface energy remains an issue. Here, the authors introduce a silver intermediate layer to reduce compositional mismatch and improve the wetting ability between iron oxide and liquid metal.

• Yifeng Shen
• Dongdong Jin

Microrobots powered by concentration polarization electrophoresis (CPEP)

Concentration polarization electroosmosis (CPEO) has recently been found to produce similar flow patterns around spheres in an AC electric field as induced charge electroosmosis. Katzmeier and Simmel study the flow around the asymmetric particle dimers caused by CPEO and design a microrobot that can be steered with a joystick and facilitates the transport of cargo particles.

• Florian Katzmeier
• Friedrich C. Simmel

Model-free tracking control of complex dynamical trajectories with machine learning

In nonlinear tracking control, relevant to robotic applications, the knowledge on the system model may be not available and there is current need in model-free approaches to track a desired trajectory, regular or chaotic. The authors introduce here a framework that employs machine learning to control a two-arm robotic manipulator using only partially observed states.

• Zheng-Meng Zhai
• Mohammadamin Moradi
• Ying-Cheng Lai

Capturing dynamical correlations using implicit neural representations

Analysis of experimental data in condensed matter is often challenging due to system complexity and slow character of physical simulations. The authors propose a framework that combines machine learning with theoretical calculations to enable real-time analysis for electron, neutron, and x-ray spectroscopies.

• Sathya R. Chitturi
• Joshua J. Turner

Multimaterial fiber as a physical simulator of a capillary instability

Capillary breakup in multimaterial fibers is explored for the self-assembly of optoelectronic systems. However, its insights primarily stem from numerical simulations, qualitative at best. The authors formulate an analytical model of such breakup, obtaining a window in the governing parameters where the generally chaotic breakup becomes predictable and thus engineerable.

• Camila Faccini de Lima
• Alexander Gumennik

On the visual analytic intelligence of neural networks

Visual oddity tasks delve into the visual analytic intelligence of humans, which remained challenging for artificial neural networks. The authors propose here a model with biologically inspired neural dynamics and synthetic saccadic eye movements with improved efficiency and accuracy in solving the visual oddity tasks.

• Stanisław Woźniak
• Hlynur Jónsson
• Evangelos Eleftheriou

Efficient optimization with higher-order Ising machines

Combinatorial optimization problems can be solved on parallel hardware called Ising machines. Most studies have focused on the use of second-order Ising machines. Compared to second-order Ising machines, the authors show that higher-order Ising machines realized with coupled-oscillator networks can be more resource-efficient and provide superior solutions for constraint satisfaction problems.

• Connor Bybee
• Denis Kleyko
• Friedrich T. Sommer

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The Role of Physics and Mathematics in Influencing Science Students’ Performance

• Conference paper
• First Online: 16 April 2019
• Cite this conference paper

• Munirah Rossdy 4 ,
• Roseline Michael 4 ,
• Janvin Janteng 4 &
• Shirley Arvilla Andrew 5  

438 Accesses

1 Citations

Physics and Mathematics are two closely related fields in the world of Science. Although they are closely related, these two fields have distinct identities. The distinction between these two fields has influenced the learning process in Science programmes at institutions of higher education. The main objective of this study is to identify the relationship between the two disciplines and how their influence affects students’ overall performance. In order to learn Physics, students need basic knowledge of Mathematics. The dependence on Mathematics to understand Physics and its interrelationship have been identified since secondary school level. This is because mathematical concepts that students acquire can be applied in Physics such as functions, derivatives, equations and other aspects with a similar concept. The role of Physics and Mathematics courses is evaluated to determine whether both subjects affect students’ achievement for the Science programme. Data were acquired from 45 students undertaking Part 3 Diploma in Science (AS120) at UiTM Cawangan Sabah. These students took up Physics and Mathematics in the first and second semesters. The instruments used in this study included students’ grades in Physics and Mathematics as well as their Cumulative Grade Point Average (CGPA). The data were analysed using Statistical Package for the Social Sciences (SPSS) version 22.0 software, while a regression analysis was used to identify the relationship between Physics, Mathematics and students’ performance (CGPA). From the findings, it can be established that there is a highly positive relationship between Physics and Mathematics with students’ CGPA. It shows that students’ achievement in both fields will be early predictors to determine their CGPA. Moreover, Mathematics also provides a positive relationship with the learning of Physics, and it appears that students’ performance in Mathematics can predict their Physics’ result.

• Science programme
• Physics and Mathematics
• Relationship
• Students’ performance
• Regression analysis

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Ahmed, I., Mohamed, N., & Fahar, H. (2012). Relating grades of maths and science courses with students’ performance in a multi-disciplinary engineering program- a gender inclusive case study. Procedia – Social and Behavioral Sciences, 46 , 3989–3992.

Article   Google Scholar  

Ahmed, I., Mohamed, N., & Fahar, H. (2015). The role of physics and mathematics courses in influencing students’ performance in engineering programs . In QScience Proceeding (Engineering Leaders Conference 2014). Retrieved November 4, 2015, from https://doi.org/10.5339/qproc.2015.elc2014.61 .

Awodun, A. O., & Ojo, O. A. (2013). Mathematics skills as predictors of physics students’ performance in senior secondary schools. International Journal of Science and Research, 2 (7), 391–394.

Google Scholar  

Baskan, Z., Alev, N., & Karal, I. S. (2010). Physics and mathematics teachers’ ideas about topics that could be related or integrated. Procedia – Social and Behavioral Sciences, 2 , 1558–1562.

Dehipawala, S., Shekoyan, V., & Yao, H. (2014). Using mathematics review to enhance problem solving skills in general physics classes , Proceedings of 2014 Zone 1 Conference of the American Society for Engineering Education (ASEE Zone 1) . Bridgeport: IEEE.

Book   Google Scholar  

Izaak, H. W. (2015). The correlation study of interest at physics and knowledge of mathematics basics concepts towards the ability to solve physics problems with 7th grade students at Junior High School in Ambon Maluku Province, Indonesia. Education Research International, 2015 (2015), 396750.

Kauffman, L. H., & Ul-Haq, R. (2015). The mysterious connection between mathematics and physics. Progress in Biophysics and Molecular Biology, 119 , 453–459.

Michelsen, C. (2015). Mathematical modeling is also physics-interdisciplinary teaching between mathematics and physics in Danish upper secondary education (Vol. 50). Denmark: Physics Education Issue 4, article id. 489 (2015).

Noemi, M. B. (2013). Factors influencing the academic performance in physics of DMMMSU-MLUC laboratory high school fourth year students S.Y. 2011–2012. International Scientific Research Journal, 5 (2), 34–44.

Redish, E. F. (2006). Problem solving and the use of math in physics courses . Paper presented at the conference World View on Physics in 2005: Focusing on Change, Delhi, August 21–26, 2005.

Simpson, J., & Fernandez, E. (2014). Student performance in first year, mathematics, and physics courses: Implications for success in the study of electrical and computer engineering . Frontiers in Education Conference (FIE), 2014 IEEE. Madrid.

Tan, U. -X., Zhu, Y., Lee, C. H., Toh, T. L., Sze, G. K., Tay, S., & Kin, L. P. (2017). Preliminary study of integrated physics and mathematics bridging course (pp. 1146–1151). IEEE Global Engineering Education Conference (EDUCON).

Vinitsky-Pinsky, L., & Galili, I. (2014). The need to clarify the relationship between physics and mathematics in science curriculum: Cultural knowledge as possible framework. Procedia – Social and Behavioral Sciences, 116 , 611–616.

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Munirah Rossdy, Roseline Michael & Janvin Janteng

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Rossdy, M., Michael, R., Janteng, J., Andrew, S.A. (2019). The Role of Physics and Mathematics in Influencing Science Students’ Performance. In: Mat Noor, A., Mohd Zakuan, Z., Muhamad Noor, S. (eds) Proceedings of the Second International Conference on the Future of ASEAN (ICoFA) 2017 - Volume 1. Springer, Singapore. https://doi.org/10.1007/978-981-10-8730-1_40

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• Rodrigo Arrieta Candia Numerical methods for PDEs, Numerical Analysis, Scientific Computing, Computational Electromagnetism
• Joel Been Nonlinear Waves, Inverse Scattering Transform, Fractional Calculus
• Andrey Bryutkin Mathematics of Data, Statistics, Physical Applied Mathematics
• Diego Chavez
• Mo Chen Optimization, Scientific Computing
• David Darrow Applied Math, Fluid Dynamics
• Davis Evans Hydrodynamic Quantum Analogs
• Andrey Khesin Quantum Computing
• Ivan Motorin Cluster Algebras, Resolution of Singularities, Representation Theory, Integrable Systems
• George Stepaniants Statistical Learning of Differential Equations, Optimal Transport in Biology
• Harry Walden

*Only a partial list of graduate students