Chemical Physics
Advanced Characterization Methods for Crystals of an Extraordinary Material
Vivekananda Bal, Jackie M. Wolfrum, Paul W. Barone et al. (+4 more)
Physicochemical characterization of materials is central to the field of science and engineering and is essential to design new/engineered materials with specific properties. Assays available for small-molecules, e.g., XRD, NMR, LC-MS, can't be applied to macromolecules easily. Thus, it is extremely challenging to characterize complex materials such as adeno-associated virus capsids (MW 5.8MDa). Capsid
crystals produced in hanging-drop are characterized in-situ using cross-polarized light and ex-situ using scanning electron microscopy, energy dispersive X-ray, and transmission electron microscopy. Cross-polarized light can be used to identify capsid
crystals within a heterogenous-system of kosmotropic/chaotropic-salt
crystals, fibers, dense solid-phase, opaques
crystals. Despite highly-conserved structures,
crystal birefringence suggests that capsids possess serotype-specific structural differences. SEM demonstrated that
crystal-growth occurs by random 2D-nucleation followed by kink-site attachment and/or spread by more 2D-
nuclei and proteinaceous assemblies tend to form semi-crystalline solids appearing as dense/opaque materials. EDX shows that C, O, and N are present in ratio of 2.33+-0.222:1:0.583+-0.019 for serotypes 5, 8, and 9 and can be an alternative to
protein sequencing-based virus identification. Biological macromolecular assemblies are found to facilitate plural-scattering responsible for Kikuchi-diffraction pattern even for thin-
crystals (~300nm). For an optimal spot-diffraction,
crystals must possess at least one dimension consisting of at most 8 layers of capsids.
Read the full abstract ▾
All authors Vivekananda Bal, Jackie M. Wolfrum, Paul W. Barone, Stacy L. Springs, Anthony J. Sinskey, Robert M. Kotin, Richard D. Braatz
Instrumentation and Detectors
Studies of ultrafast dynamics in substrate-free nanoparticles at ELI using Timepix3 optical camera
Dmitrij Ševaev, Andrei Nomerotski, Peter Švihra et al. (+7 more)
We present a novel application of the Timepix3 optical camera (Tpx3Cam) for investigating ultrafast dynamics in substrate-free nanoparticles at the Extreme Light Infrastructure European Research Infrastructure Consortium (ELI ERIC). The camera, integrated into an ion imaging system based on a micro-channel plate (MCP) and a fast P47 scintillator, enables individual time-stamping of incoming ions with nanosecond timing precision and high spatial resolution. The detector successfully captured
laser-induced ion events originating from free nanoparticles disintegrated by intense
laser pulses. Owing to the broad size distribution of the nanoparticles (10-500 nm) and the variation in
laser intensities within the interaction volume, the detected events range in occupancy from near-zero to extremely high, approaching the readout limits of the detector. By combining time-of-flight and velocity map imaging (VMI) techniques, detailed post-processing and analysis were performed. The results presented here focus on the performance of Tpx3Cam under high-occupancy conditions, which are of particular relevance to this study. These conditions approach the limitations imposed by the camera readout capabilities and challenge the effectiveness of standard post-processing
algorithms. We investigated these limitations and associated trade-offs, and we present improved methods and
algorithms designed to extract the most informative features from the data.
Read the full abstract ▾
All authors Dmitrij Ševaev, Andrei Nomerotski, Peter Švihra, Keshav Sishodia, Andreas Hult Roos, Martin Albrecht, Sivarama Krishnan, Jakob Andreasson, Maria Krikunova, Eva Klimešová
Accelerator Physics
Short-Pulse High-Power THz Generation Using Optical Klystron FELs: Simulation Results
Najmeh Mirian
The generation of high-power radiation in the terahertz (THz) regime using free-electron
lasers (FELs) is challenging due to strong diffraction and pronounced slippage effects. These constraints often limit the achievable pulse duration and peak power in conventional single-pass THz FEL configurations. In this work, we investigate an unseeded optical klystron (OK) FEL concept tailored for the THz regime. Using time-dependent three-dimensional simulations for resonant wavelengths of 10, 30, and 100 {\mu}m, we demonstrate that this approach enables the generation of coherent ultrashort THz pulses with durations of a sub picoseconds (FWHM) and peak powers in the multi-hundred- megawatt range at wavelengths 10 and 30 {\mu}m. To address the slippage challenge, we propose and numerically demonstrate a novel chicane-embedded optical delay scheme, which restores phase
alignment between the radiation and microbunched electrons. Simulations confirm that careful tuning of the dispersive strengths allows staged amplification, preserving beam quality and reaching multi-megawatt output power. These results highlight the potential of THz-tailored optical klystrons to generate compact, short, and high-intensity THz pulses, and lay the groundwork for future experimental studies and facility implementation
Read the full abstract ▾
Accelerator Physics
SPARTA: Python-Based Automated Spectral Parameter Analysis and Assessment System for Resonance Tracking
Kerem Semiz
Accurately determining resonance frequencies and quality factors (Q) is crucial in accelerator physics and radiofrequency engineering, as these factors have direct impacts on system design, operational stability, and research results. The methods currently employed to facilitate resonance analysis are mostly manual, requiring operators and physicists to estimate resonant parameters and examine scattering parameter (S-parameter) data from vector network analyzers (VNAs). The current techniques therefore become laborious, operator-dependent and challenging to replicate when applied to large
datasets or across multiple analyses. Despite the importance of these tasks for high-volume research organizations such as CERN where S-parameter measurements are regularly taken for cavity and beam diagnostic research, the currently widespread measures are outdated. In order to automate the laborious resonance characterization process, this paper presents SPARTA (Spectral Parameter Analysis for Resonance Tracking and Assessment), a data analysis software framework based on Python. SPARTA has integrated data ingestion, preprocessing, resonance detection, quality factor estimation, visualization and persistent cloud storage into a reproducible and scalable workflow. SPARTA was developed with the scientific libraries NumPy, SciPy and scikit-rf for accurate and efficient numerical processing, Flask and Dash for interactive and lightweight visualization, and SQLite for easy database management. The three main contributions of this work are outlined as follows: Firstly, this paper presents a methodological framework for resonance detection and assessment based on established RF theory. The second section describes the system architecture and implementation of SPARTA, highlighting data handling, computation and visualization. Finally this paper discusses the results and advantages of automated analysis.
Read the full abstract ▾
Physics and Society · Cross-listed from nlin.AO
Phase locking and multistability in the topological Kuramoto model on cell complexes
Iva Bačić, Michael T. Schaub, Jürgen Kurths et al. (+1 more)
Higher-order interactions fundamentally shape collective dynamics in oscillator networks. The topological Kuramoto model captures these effects by extending synchronization models to include interactions between
cells of arbitrary dimension within simplicial and
cell complexes. We introduce the topological nonlinear Kirchhoff conditions to characterize all phase-locked states of the topological Kuramoto model. These states are organized by winding numbers associated with generalized independent cycles, which quantify how phases wind around these cycles. Using rings, Platonic solids, and regular simplices as illustrative examples, we uncover a universal rule: boundaries must have at least five elements for multistability to arise. We further find that independent winding numbers associated with lower- and higher-dimensional boundaries generate cascades of multistability across dimensions. These results show how the
topology and boundary structure of
cell complexes influence phase locking and multistability, and provide a general framework for collective dynamics on
cell complexes.
Read the full abstract ▾
All authors Iva Bačić, Michael T. Schaub, Jürgen Kurths, Dirk Witthaut
Optics · Cross-listed from quant-ph
Implementation of multiparticle quantum speed limits on observables
Rui-Heng Miao, Zhao-Di Liu, Chen-Xi Ning et al. (+4 more)
The energy-time uncertainty relation limits the maximum speed of
quantum system
evolution and is crucial for determining whether
quantum tasks can be accelerated. However, multiparticle
quantum speed limits have not been experimentally explored. In this work, we experimentally verify that both multiparticles and
entanglement can accelerate the
quantum speed on observables in two-particle systems based on ultrahigh precision control of
quantum evolution time. Furthermore, we experimentally prove that the initial
quantum state plays a critical role in the
quantum speed limits of the entangled systems. In addition, we experimentally demonstrate that the upper bound and lower bound of the
quantum speed are workable even in a nonunitary Markovian open system with two
photons. The results obtained based on two-
photon experiments have been shown to be generalizable to more particles. Our work facilitates the characterization of the dynamic transient properties of complex
quantum systems and the control of the
quantum speed of large-scale
quantum systems.
Read the full abstract ▾
All authors Rui-Heng Miao, Zhao-Di Liu, Chen-Xi Ning, Yu-Cong Hu, Hao Zhang, Chuan-Feng Li, Guang-Can Guo
Biological Physics
First experimental measurements of biophotons from Astrocytes and Glioblastoma cell cultures
L. De Paolis, E. Pace, C. Mazzanti et al. (+10 more)
Biophotons are non-thermal and non-bioluminescent ultraweak
photon emissions, first hypothesised by Gurwitsch in 1924 as a regulatory mechanism in
cell division, and then experimentally observed in living organisms. Today, two main hypotheses explain their origin:
stochastic decay of excited molecules and coherent electromagnetic fields produced in biochemical processes. Recent interest focuses on the role of biophotons in cellular communication and disease monitoring. This study presents the first campaign of biophoton emission measurements from cultured astrocytes and glioblastoma
cells, conducted at Fondazione Pisana per la Scienza (FPS) using two ultra-sensitive setups developed by the collaboration at the National Laboratories of Frascati (LNF-INFN) and at the University of Rome II - Tor Vergata. The statistical analyses of the data collected revealed a clear separation between cellular signals and dark noise, confirming the high sensitivity of the apparatuses. The
Diffusion Entropy Analysis (DEA) was applied to the data to uncover dynamic patterns, revealing anomalous
diffusion and long-range
memory effects potentially related to intercellular signalling and cellular communication. These findings support the hypothesis that biophoton emissions encode rich information beyond intensity, reflecting metabolic and pathological states. The differences that emerged from the application of
Diffusion Entropy Analysis to the biophotonic signals of Astrocytes and Glioblastoma are highlighted and discussed in the paper. This work lays the foundation for future studies on neuronal cultures and proposes biophoton dynamics as a promising tool for non-invasive diagnostics and cellular communication research.
Read the full abstract ▾
All authors L. De Paolis, E. Pace, C. Mazzanti, M. Morelli, F. Di Lorenzo, L. Tonello, C. Curceanu, A. Clozza, M. Grandi, I. Davoli, A. Gemignani, P. Grigolini, M. Benfatto
Optics
Mapping complex optical light field distributions with single fluorescent molecules
Daniel Marx, Ivan Gligonov, David Malsbenden et al. (+3 more)
Single fluorescent molecules, behaving as ideal electric dipole emitters, are powerful nanoscopic probes of complex optical fields. Here, this property is exploited to precisely map the polarization and vectorial structure of tightly focused
laser beams, utilizing both linear and circular polarization states. The resulting three-dimensional fluorescence excitation maps strikingly reveal the intrinsic
chiral and non-
chiral structure of the light field, in perfect quantitative agreement with a full vectorial wave-optical model. This precise correspondence not only enables the reliable determination of absolute molecular orientations but also allows for the accurate characterization of the field's properties. These results fundamentally advance our understanding of light-matter interaction at the single-molecule level and open new avenues for characterizing complex light fields, with broad applications in super-resolution microscopy and nanophotonics.
Read the full abstract ▾
All authors Daniel Marx, Ivan Gligonov, David Malsbenden, Dominik Wöll, Oleksii Nevskyi, Jörg Enderlein
Biological Physics
Models of topological barriers and molecular motors of bacterial DNA
Marc Joyeux
Bacterial genomes are partitioned into kilobases long domains that are topologically independent from each other, meaning that change of DNA superhelicity in one domain does not propagate to neighbours. This is made possible by
proteins like the LacI repressor, which behave like topological barriers and block the
diffusion of torsion along the DNA. Other
proteins, like DNA gyrases and RNA polymerases, called molecular motors, use the energy released by the hydrolysis of ATP to apply forces and/or torques to the DNA and modify its superhelicity. Here, we report on simulation work aimed at enlightening the interplay between DNA supercoiling, topological barriers, and molecular motors. To this end, we developed a coarse-grained
Hamiltonian model of topological barriers and a model of molecular motors and investigated their properties through Brownian dynamics simulations. We discuss their influence on the contact map of a model nucleoid and the steady state values of twist and writhe in the DNA. These coarse-grained models, which are able to predict the dynamics of plectonemes depending on the position of topological barriers and molecular motors, should prove helpful to back up experimental efforts, like the development of Chromosome Conformation Capture techniques, and decipher the organisational mechanisms of bacterial chromosomes.
Read the full abstract ▾
Applied Physics
Multi-Channel Amplitude-Phase Asymmetric-Encrypted Janus Acoustic Meta-Holograms
Haohan Zeng, Zhenyu He, Tianxiang Zhang et al. (+12 more)
Encrypted optical and acoustic meta-holograms only focus on the encrypted hologram in a single channel, viz. modulating spatial amplitude to project a
holographic image. In this research, the unique concept of multi-channel amplitude-phase asymmetric-encrypted Janus acoustic meta-holograms is proposed, demonstrating remarkable capabilities of generating, encrypting, and decrypting both amplitude and phase
holographic images on both sides of a metascreen. The flexible and decoupled manipulation mechanism for the amplitude-phase of the bidirectional acoustic waves used in our concept offers multiple possibilities to apply various encryption methods. In this work, our system enables single-input, two-faced four-channel asymmetric encryption, which substantially increase the communication capacity of conventional acoustic holograms, and establish a security framework based on mathematical problem, proving its security. Our work can lead to concrete applications including, but not limited to, multi-channel acoustic field communications and acoustic illusion and cloaking in non-transparent media.
Read the full abstract ▾
All authors Haohan Zeng, Zhenyu He, Tianxiang Zhang, Xiao Guo, Xinghao Hu, Youyu Mo, Tingting Li, Feilong Mao, Haiyan Fan, Xudong Fan, Weiwei Kan, Yifan Zhu, Hui Zhang, Guodong Yin, Badreddine Assouar
Physics and Society
Binary Option Market Manipulation by Influencing Belief Dynamics
Henry Waldhausen and Christopher Griffin
Using techniques from information geometry, we construct a semi-
Hamiltonian system modelling trader beliefs in a binary asset
market and study the impact of inequality or asymmetry in beliefs, information, and power on price dynamics. We show that in a
market with no inequality and $N$ completely symmetric traders, the resulting dynamics evolve on a $2N + 1$ dimensional
manifold consisting of a $2N-2$ dimensional centre
manifold, a $2$ dimensional stable
manifold and a $1$ dimensional slow
manifold. Introducing asymmetry into the traders has the potential to decrease the dimension of the centre
manifold, which we prove using a parameter analysis. Using the belief model, we also study the impact of inter-
agent communication, exogenous information and asymmetric purchasing power on price dynamics, showing that
market bubbles can emerge when powerful traders produce outsize influence in the
market, thus impacting other traders' beliefs as well as the price. This process is exacerbated when back-channel communication is permitted. The impact of areas of high
curvature in belief space is also discussed.
Read the full abstract ▾
Atomic Physics
All-optical bubble trap for ultracold atoms in microgravity
Romain Veyron, Clément Métayer, Jean-Baptiste Gérent et al. (+5 more)
In this paper, we present an all-optical method to produce shell-shaped traps for ultracold atoms in microgravity. Our scheme exploits optical double dressing of the ground state to create a short range strongly repulsive central potential barrier. Combined with a long range attractive central potential, this barrier forms the shell trap. We demonstrate that a pure spherical bubble, reaching the quasi 2D regime for standard atom numbers, could be formed from two crossed beams with a
parabolic profile. An analytical study shows that the relevant characteristics of the trap depend on the ratio of the ground and excited state polarisabilities and the lifetime of the excited state. As a
benchmark, we provide quantitative analysis of a realistic configuration for rubidium ensembles, leading to a 250 Hz transverse confinement for a 35 $\mu$m radius bubble and a trap residual scattering rate of less than 10 s$^{-1}$.
Read the full abstract ▾
All authors Romain Veyron, Clément Métayer, Jean-Baptiste Gérent, Ruiyang Huang, Eliott Beraud, Barry M. Garraway, Simon Bernon, Baptiste Battelier
Fluid Dynamics
Spectrum of the Curl of Vorticity as a Precursor to Dissipation in 3D Taylor–Green Turbulence
Satori Tsuzuki
Predicting when a three-dimensional turbulent flow reaches its dissipation peak is essential for both theory and adaptive
algorithms in simulations and experiments. Using direct numerical simulations (DNSs) of the Taylor–Green
vortex (TGV) at resolutions of $256^3$–$1024^3$, we introduce and test a small-scale weighted diagnostic: the spectrum of $|\nabla \times \boldsymbol{\omega}|^2$ (with $\boldsymbol{\omega}=\nabla \times \mathbf{u}$), which, for incompressible flow, is equivalent to a $k^4$-weighted energy spectrum. We show that the peak wavenumber of this spectrum, $k_{{\rm peak}}[\,|\nabla \times \boldsymbol{\omega}|^2\,]$, advances rapidly to intermediate-small scales and then levels off before the dissipation rate $\varepsilon(t)=\sum_k 2\nu k^2 E(k)$ reaches its maximum. Across all resolutions, we observe robust temporal ordering $t_k<t_\varepsilon<t_\Pi$, where $t_k$ marks the onset of the rapid rise of $k_{{\rm peak}}[\,|\nabla \times \boldsymbol{\omega}|^2\,]$, $t_\varepsilon$ is the time of the maximal $\varepsilon(t)$, and $t_\Pi$ is when the cumulative flux $|\Pi(K)|$ attains its largest peak scale. This early-warning signal correlates with the morphological transition to filament-dominated structures visible in $Q$-criterion isosurfaces and is consistent with integral-scale trends ($L_{{\rm int}},\lambda,\eta$). The diagnostic is simple to compute from standard DNS data and highlights the incipient formation of high-
curvature structures, where viscosity acts most strongly.
Read the full abstract ▾
Biological Physics · Cross-listed from nlin.AO
Division Strategies Determine Growth and Viability of Growing-Dividing Autocatalytic Systems
Parth Pratim Pandey and Sanjay Jain
We present a
geometric framework to study the growth-division dynamics of
cells and protocells, and demonstrate that self-reproduction emerges only when a system's growth dynamics and division strategy are mutually compatible. Using several commonly used models (the linear Hinshelwood cycle and non-linear coarse-grained models of protocells and bacteria), we show that, depending on the chosen division mechanism, the same chemical system can exhibit either (i) balanced exponential growth, (ii) balanced nonexponential growth, or (iii) system death (where the system either diverges to infinity or collapses to zero over successive generations). In particular, we show that cellular trajectories in an N-dimensional phase space (where N is the number of distinct chemical species) shuttle between two N-1 dimensional surfaces - a division surface and a birth surface - and that the relationship between these surfaces and the growth trajectories determine something as fundamental as cellular homeostasis and self-reproduction. Geometrically visualizing bacterial growth and division uncovers, for the first time, the type of division processes that sustain or destroy cellular homeostasis in autocatalytic chemical systems, thereby offering strategies to stabilize or destabilize growing-dividing systems. This reveals that, in addition to autocatalysis of growth, division mechanisms are not passive bystanders but active determinants of a growing-dividing system's long-term fate. Our work thus provides a framework for further exploration of growing dividing systems that will aid in the design of self-reproducing synthetic
cells.
Read the full abstract ▾
Applied Physics
Artificial Synapse based on ULTRARAM Memory Device for Neuromorphic Applications
Abhishek Kumar, Peter D. Hodgson, Manus Hayne et al. (+1 more)
The
memory demands of large-scale deep neural networks (DNNs) require synaptic weight values to be stored and updated in off-chip
memory like dynamic random-access
memory, which reduces energy efficiency and increases training time. Monolithic crossbar or pseudo-crossbar arrays using analog non-volatile
memories, which can store and update weights on-chip, present an opportunity to efficiently accelerate DNN training. In this article, we present on-chip training and inference of a neural network using an ULTRARAM
memory device-based synaptic array and complementary metal-
oxide-
semiconductor (CMOS) peripheral
circuits. ULTRARAM is a promising emerging
memory exhibiting high endurance (>10^7 P/E cycles), ultra-high retention (>1000 years), and ultra-low switching energy per unit area. A physics-based compact model of ULTRARAM
memory device has been proposed to capture the real-time trapping/de-trapping of charges in the floating gate (FG) and utilized for the synapse simulations. A
circuit-level macro-model is employed to evaluate and
benchmark the on-chip learning performance in terms of area, latency, energy, and accuracy of an ULTRARAM synaptic core. In comparison to CMOS-based design, it demonstrates an overall improvement in area and energy by 1.8x and 1.52x, respectively, with 91% of training accuracy.
Read the full abstract ▾
All authors Abhishek Kumar, Peter D. Hodgson, Manus Hayne, Avirup Dasgupta
Biological Physics
Objective clustering protocol for single-molecule data: A lifetime vs. intensity study
Michael Lovemore, Joshua Botha, Bertus van Heerden et al. (+1 more)
Single-molecule spectroscopy (SMS) is an exceptionally sensitive technique, but its inherently limited
photon budget produces noisy data that can readily lead to subjective analyses, fitting errors, and reduced statistical power, obscuring true subpopulations and their dynamics. Here, we present an unbiased, objective method to cluster two-dimensional single-molecule data and demonstrate it on fluorescence lifetime–intensity correlations. The clustering method is based on Gaussian mixture modeling, with the optimal number of clusters determined through {information criteria (the Akaike and
Bayesian information criteria and integrated completed likelihood) and supplemented by cluster quality metrics such as average cluster tightness and the fraction of points outside confidence ellipses, which guide the selection of statistically robust and physically meaningful clusters. The protocol was benchmarked on simulated
datasets spanning clean, smeared, and noisy overlap-limited regimes, and applied to experimental data from Alexa Fluor 647 and QD 605. This approach reliably recovers relevant subpopulations even in the presence of noise and overlapping distributions, providing an objective framework for analyzing single-molecule heterogeneity, with limitations arising primarily under severe
geometric overlap or extreme state-occupancy imbalance where distinct populations are no longer separable.
Read the full abstract ▾
All authors Michael Lovemore, Joshua Botha, Bertus van Heerden, Tjaart Kruger
Plasma Physics
Deposition rate and energy to substrate in chopped and standard HiPIMS: identifying optimal pulse parameters
Mina Farahani, Jiří Čapek and Tomáš Kozák
High-Power Impulse Magnetron Sputtering (HiPIMS) delivers higher ionisation of the target material at the expense of lower deposition rates than conventional magnetron sputtering. A fine optimisation of the deposition conditions is crucial for specific applications. Chopped or multi-pulse HiPIMS (segmenting pulses into shorter micropulses) has been proposed to enhance the degree of ionisation of the film-forming flux fraction while maintaining the deposition rate. This study investigates how micropulse length and the delay time between segments influence energy flux, deposition rate, and the ionised flux fraction in both chopped and standard HiPIMS. These quantities are evaluated by passive thermal probe, biasable QCM and mass spectrometer measurements at the substrate position. Deposition-averaged and pulse-averaged power is kept constant for all conditions to facilitate meaningful comparison. Results indicate that chopping the HiPIMS pulse consistently leads to higher energy flux and total deposition rate compared to standard HiPIMS at the same total pulse length, primarily due to increased ion flux. In chopped HiPIMS, increasing the delay time between micropulses beyond 30 us simultaneously improved the deposition rate and the ionised flux fraction. In comparison, standard HiPIMS, operated at higher frequencies and shorter pulse lengths, demonstrated similar performance with even higher total energy fluxes, but this can be attributed to a higher fraction of process-gas ions in the flux to the substrate, rather than to an increased ionised flux fraction of the film-forming species.
Read the full abstract ▾
Optics
Broadband spectral mapping of photo-induced second-harmonic generation in silicon nitride microresonators
Ji Zhou, Marco Clementi, Samantha Sbarra et al. (+2 more)
By employing a pump-probe technique for enhanced spectral mapping of the dynamics in nonlinear frequency conversion, we demonstrate that photo-induced second-harmonic generation (SHG) in silicon nitride (Si3N4) microresonators can persist when transitioning from the preferred doubly resonant condition–where the resonances of the optical harmonics are required to be matched–to a highly detuned state where the generated second harmonic is significantly shifted away from its corresponding resonance. This results in an unconventionally broad conversion bandwidth. Other intriguing phenomena, such as detuning-dependent all-optical poling and nonlinear multi-mode interaction, are also presented for the first time with direct experimental evidence. Our findings provide new insights into the physics of photo-induced second-order (\chi^{(2)}) nonlinearity, highlighting its potential applications for nonlinear \chi^{(2)} photonics in integrated Si3N4 platform
Read the full abstract ▾
All authors Ji Zhou, Marco Clementi, Samantha Sbarra, Ozan Yakar, Camille-Sophie Brès
Chemical Physics
Enhancing NMR Shielding Predictions of Atoms-in-Molecules Machine Learning Models with Neighborhood-Informed Representations
Surajit Das and Raghunathan Ramakrishnan
Accurate prediction of
nuclear magnetic resonance (NMR) shielding with machine learning (ML) models remains a central challenge for data-driven spectroscopy. We present atomic variants of the Coulomb
matrix (aCM) and bag-of-bonds (aBoB) descriptors, and extend them using radial basis functions (RBFs) to yield smooth, per-atom representations (aCM-RBF, aBoB-RBF). Local structural information is incorporated by augmenting each atomic descriptor with contributions from the n nearest neighbors, resulting in the family of descriptors, aCM-RBF(n) and aBoB-RBF(n). For 13C shielding prediction on the QM9NMR
dataset (831,925 shielding values across 130,831 molecules), aBoB-RBF(4) achieves an out-of-sample mean error of 1.69 ppm, outperforming models reported in previous studies. While explicit three-body descriptors further reduce errors at a higher cost, aBoB-RBF(4) offers the best balance of accuracy and efficiency. Benchmarking on external
datasets comprising larger molecules (GDBm, Drug12/Drug40, and pyrimidinone derivatives) confirms the robustness and transferability of aBoB-RBF(4), establishing it as a practical tool for ML-based NMR shielding prediction.
Read the full abstract ▾
Applied Physics
Field Free Spin-Orbit Torque Controlled Synapse and Stochastic Neuron Devices for Spintronic Boltzmann Neural Networks
Aijaz H. Lone, Meng Tang, Camelia Florica et al. (+4 more)
Spintronics offers a promising approach to energy efficient neuromorphic computing by integrating the functionalities of synapses and
neurons within a single platform. A major challenge, however, is achieving field-free
spin orbit torque SOT control over both synaptic and neuronal devices using an industry-adopted spintronic materials stack. In this study, we present field-free SOT spintronic synapses utilizing a CoFeB
ferromagnetic thin film system, where asymmetrical device design and specifically added lateral notches in the CoFeB thin film facilitate effective domain wall DW nucleation, movement, and pinning and depinning. This method yields multiple analog, nonvolatile resistance states with enhanced linearity and
symmetry, resulting in programmable and stable synaptic weights. We provide a systematic measurement approach to improve the linearity and
symmetry of the synapses. Additionally, we demonstrate nanoscale
magnetic tunnel junctions MTJs that function as SOT-driven
stochastic neurons, exhibiting current-tunable, Boltzmann-like probabilistic switching behavior, which provides an intrinsic in-hardware Gibbs sampling capability. By integrating these synapses and
neurons into a Boltzmann machine complemented by a classifier layer, we achieve recognition accuracies greater than 98 percent on the MNIST
dataset and 86 percent on Fashion MNIST. This work establishes a framework for field free synaptic and neuronal devices, setting the stage for practical, materials-compatible, and all spintronic neuromorphic computing hardware.
Read the full abstract ▾
All authors Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Xixiang Zhang, Gianluca Setti
Biological Physics
A fluorescence microscopy platform for time-resolved studies of spin-correlated radical pairs in biological systems
Noboru Ikeya and Jonathan R. Woodward
The importance of
spin-correlated radical pairs in biology is increasingly recognized, with roles in biological effects of weak
magnetic fields and emerging
quantum spin-based biomedical applications. Fluorescence microscopy offers sufficient sensitivity to study
magnetic field effects on radical pair reactions in living
cells, but conventional techniques cannot directly resolve their dynamics because most biologically relevant radical pairs are non-emissive. To overcome this challenge, we introduce two novel microscopy techniques: single color pump-probe (PP) and pump-field-probe (PFP) fluorescence. Here, we describe their working principles, provide their mathematical formulation, and validate both techniques through theoretical analysis and experiments on well-established flavin-based
magnetic field sensitive reactions. These approaches offer a sensitive and broadly applicable platform for quantifying and visualizing the
quantum spin dynamics of radical pair chemical reactions in biological systems.
Read the full abstract ▾
Fluid Dynamics
Transient almost-invariant sets reveal convective heat transfer patterns in plane-layer Rayleigh-Bénard convection
Aleksandar Badza, Gary Froyland, Roshan J. Samuel et al. (+1 more)
Horizontally extended plane-layer convection flows are characterized by characteristic patterns of turbulent heat transfer due to the convective fluid motion consisting of a nearly-regular ridge network where hot fluid rises and cold fluid sinks. Here, we analyse this transport behavior by the so-called inflated generator framework, which identifies quasi-stationary families of almost-invariant sets, derived from leading inflated generator eigenvectors. We demonstrate the effectiveness of this data-driven analysis framework in three-dimensional turbulent flow, by extracting transient characteristic heat transfer patterns as families of almost-invariant sets subject to a transient
evolution, which contribute least to the convective heat transfer.
Read the full abstract ▾
All authors Aleksandar Badza, Gary Froyland, Roshan J. Samuel, Jörg Schumacher
Computational Physics · Cross-listed from stat.ML
Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes
Nicholas H. Nelsen, Houman Owhadi, Andrew M. Stuart et al. (+2 more)
Methods for solving scientific computing and inference problems, such as kernel- and neural network-based approaches for partial differential equations (PDEs), inverse problems, and supervised learning tasks, depend crucially on the choice of hyperparameters. Specifically, the efficacy of such methods, and in particular their accuracy, stability, and generalization properties, strongly depends on the choice of hyperparameters. While bilevel optimization offers a principled framework for hyperparameter tuning, its nested optimization structure can be computationally demanding, especially in PDE-constrained contexts. In this paper, we propose an efficient strategy for hyperparameter optimization within the bilevel framework by employing a Gauss-Newton linearization of the inner optimization step. Our approach provides closed-form updates, eliminating the need for repeated costly PDE solves. As a result, each iteration of the outer loop reduces to a single linearized PDE solve, followed by explicit gradient-based hyperparameter updates. We demonstrate the effectiveness of the proposed method through Gaussian process models applied to nonlinear PDEs and to PDE inverse problems. Extensive numerical experiments highlight substantial improvements in accuracy and robustness compared to conventional random hyperparameter initialization. In particular, experiments with additive kernels and neural network-parameterized deep kernels demonstrate the method's scalability and effectiveness for high-dimensional hyperparameter optimization.
Read the full abstract ▾
All authors Nicholas H. Nelsen, Houman Owhadi, Andrew M. Stuart, Xianjin Yang, Zongren Zou
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Co-evaporated Formamidinium tin triiodide with suppressed p-type self-doping
Junhyoung Park, Andrea Olivati, Mirko Prato et al. (+2 more)
Co-evaporation of formamidinium tin triiodide (FASnI3) precursors, without any additives or reducing
agents, leads to the growth of a highly crystalline thin film which shows a bandgap around 1.31 eV, closely matching the theoretical value predicted from the ideal single
crystal structure of FASnI3. The polycrystalline thin film presents a lower tendency of Sn2+ to Sn4+ oxidation and highly reduced tendency to self-doping, demonstrating, overall, an improved resistance to defects formation. These findings suggest solvent-free co-evaporation processes as a promising route for high quality Sn-based perovskite polycrystalline thin films.
Read the full abstract ▾
All authors Junhyoung Park, Andrea Olivati, Mirko Prato, Min Kim, Annamaria Petrozza
Applied Physics · Cross-listed from cond-mat.soft
Memory behavior of a randomly driven model glass
Roni Chatterjee, Smarajit Karmakar, Muhittin Mungan et al. (+1 more)
We investigate by atomistic simulations the
memory behavior a model glass subjected to random driving protocols. The training consists of a random walk of forward and/or backward shearing sequences bounded by a maximal shear strain of absolute value {\gamma}T . We show that such a
stochastic training protocol is able to record the training amplitude. Different read-out protocols are also tested and are shown to be able to retrieve the training amplitude. We then emphasize the ten- sorial character of the
memory encoded in the glass sample and then characterize the anisotropic mechanical behavior of the trained samples.
Read the full abstract ▾
All authors Roni Chatterjee, Smarajit Karmakar, Muhittin Mungan, Damien Vandembroucq
Physics and Society
Evolution of social behaviors in noisy environments
Guocheng Wang, Qi Su, Long Wang et al. (+1 more)
Evolutionary game theory offers a general framework to study how behaviors evolve by social learning in a population. This body of theory can accommodate a range of social dilemmas, or games, as well as real-world complexities such as spatial structure or behaviors conditioned on reputations. Nonetheless, this approach typically assumes a deterministic payoff structure for social interactions. Here, we extend evolutionary game theory to account for random changes in the social environment, so that mutual cooperation may bring different rewards today than it brings tomorrow, for example. Even when such environmental noise is unbiased, we find it can have a qualitative impact on the behaviors that evolve in a population. Noisy payoffs can permit the stable co-existence of cooperators and defectors in the prisoner's dilemma, for example, as well as bistability in snowdrift games and stable limit cycles in rock-paper-scissors games – dynamical phenomena that cannot occur in the absence of noise. We conclude by discussing the relevance of our framework to scenarios where the nature of social interactions is subject to external perturbations.
Read the full abstract ▾
All authors Guocheng Wang, Qi Su, Long Wang, Joshua B. Plotkin
Space Physics · Cross-listed from astro-ph.SR
Empirical Optimization of the Source-Surface Height in the PFSS extrapolation
Munehito Shoda, Kyogo Tokoro, Daikou Shiota et al. (+1 more)
The potential field source surface (PFSS) method is a widely used
magnetic field extrapolation technique in the space weather community. The only free parameter in the PFSS method is the source-surface height ($R_{\rm SS}$), beyond which all field lines are open. Although $R_{\rm SS}$ is known to vary with
solar activity, there is no consensus on how to determine it for a given surface
magnetic field distribution. In this study, we investigate the nature of $R_{\rm SS}$ using a long-period (2006-2023) data, covering two
solar minima and one maximum. We adopt ADAPT-GONG magnetograms and determine $R_{\rm SS}$ by matching the open flux estimated from observations at 1 au with that calculated using the PFSS method. Our analysis reveals that $R_{\rm SS}$ increases slightly after the
solar minima and around the
solar maximum, and that it can be characterized by both the mean unsigned photospheric
magnetic field strength and the dipolarity parameter $f_{\rm dip}$, defined as $f_{\rm dip} = B_{\rm dip}^2/(B_{\rm dip}^2 + B_{\rm quad}^2 + B_{\rm oct}^2)$, with $B_{\rm dip}$, $B_{\rm quad}$, and $B_{\rm oct}$ denoting the magnitudes of dipolar, quadrupolar, and octupolar components of photospheric radial
magnetic field, respectively. Our results suggest that $R_{\rm SS}$ does not exhibit a simple monotonic dependence on the
solar activity and must be determined by properly considering both surface
magnetic field strength and global field structure.
Read the full abstract ▾
All authors Munehito Shoda, Kyogo Tokoro, Daikou Shiota, Shinsuke Imada
Accelerator Physics
Prediction of Spallation Induced Transmutation Rates For Long Lived Fission Products via Proton Accelerator
Grigor Tukharyan, William Reed Kendrick, Areg Danagoulian et al. (+1 more)
Long lived fission products represent a major challenge in
nuclear waste management due to persistent radiotoxicity over very long timescales. This study focuses on six of these fission products: Se-79, Zr-93, Tc-99, Sn-126, I-127, Cs-135. This study investigates the feasibility of spallation driven transmutation, in which a high energy
proton beam strikes a heavy spallation target to generate
neutrons that induce transmutation in the fission products surrounding the target. Lead and depleted uranium are identified as the principal spallation target candidates, reflecting contrasting trade offs in
neutron yield, secondary reactions, and heat generation. Simulations assess nuclide specific behavior under reactor scale inventories and practical
geometric constraints. Results demonstrate that technetium, iodine, and selenium are strong candidates for transmutation using this pathway, while tin shows partial resistance but benefits from thermal flux. By contrast, zirconium is
neutron transparent and inefficient to transmute, and cesium suffers from low net reduction due to competition with lighter isotopes. Cost effectiveness is highly isotope dependent: technetium is most favorable, whereas cesium and zirconium remain expensive. These findings highlight the advantages and limitations of spallation driven systems and motivate strategies with optimized target-blanket designs.
Read the full abstract ▾
All authors Grigor Tukharyan, William Reed Kendrick, Areg Danagoulian, Benoit Forget
Fluid Dynamics
Viscosity and dynamic surface tension measurement: A guideline for appropriate measurement
Vivek Kumar, JSM Quintero, Aleksey Baldygin et al. (+3 more)
Dynamic surface tension measurements play a critical role in interfacial activities for
liquids with varying viscosities. Understanding the rate at which the interface attains the
equilibrium, for surface tension measurements, after the formation of a new interface is of significant interest. Although surface tension is independent of viscosity, the time required for a new surface to form (
equilibrium/relaxation time) is influenced by viscosity. The measured surface tension value is accurate only once these viscous effects have subsided. Therefore, the relaxation time represents the minimum surface age value achievable during the measurement process. We experimentally established the minimum surface age needed to measure the dynamic and static surface tension of a fluid with a specific viscosity using three widely used methods: the Pendant drop method, the Wilhelmy plate method, and the Bubble pressure method. We propose a guideline with a phase plot that helps to choose the most suitable method and the youngest achievable surface age for an accurate measurement, independent of viscous effects. This guideline enables users in diverse applications such as 3D printed clothing, spray paint, coating, etc., to accurately measure dynamic and static surface tension without being influenced by viscosity effects.
Read the full abstract ▾
All authors Vivek Kumar, JSM Quintero, Aleksey Baldygin, Paul Molina, Thomas Willers, Prashant R. Waghmare
Optics
On-chip room-temperature CW lasing from a III-V nanowire integrated with a Si photonic crystal platform
Masato Takiguchi, Takuro Fujii, Hisashi Sumikura et al. (+3 more)
We report the demonstration of continuous-wave (CW) lasing at room temperature from a III-V
semiconductor nanowire integrated into a Si photonic
crystal (PhC) cavity. Conventional hybrid nanowire
lasers [M. Takiguchi. et.al., APL Photonics, 2, 046106 (2017)], which typically feature circular nanowire-cross-sections, suffer from a weak optical confinement, preventing CW lasing under ambient conditions. To overcome this limitation, we fabricated nanowires with rectangular cross-sections via dry etching and integrated them into the air trenches of Si PhC cavities formed using atomic force microscope tips. This configuration forms a hybrid photonic
crystal cavity with an improved optical confinement. As a result, we achieved room-temperature CW oscillation from a single nanowire, representing a significant step toward on-chip nanophotonic light sources. This unique in-plane integration of the nanolaser in the same plane as the Si slab rather than on top of the substrate will contribute to the development of compact, scalable, and CMOS-compatible photonic
circuits.
Read the full abstract ▾
All authors Masato Takiguchi, Takuro Fujii, Hisashi Sumikura, Akihiko Shinya, Shinji Matsuo, Masaya Notomi