Chemical Physics
QMeCha: quantum Monte Carlo package for fermions in embedding environments
Matteo Barborini, Jorge Charry, Matej Ditte et al. (+3 more)
We present the first open access version of the QMeCha (
Quantum MeCha) code, a
quantum Monte Carlo (QMC) package developed to study many-body interactions between different types of
quantum particles, with a modular and easy-to-expand structure. The present code has been built to solve the
Hamiltonian of a system that can include
nuclei and
fermions of different mass and charge, e.g. electrons and positrons, embedded in an environment of classical charges and
quantum Drude oscillators. To approximate the ground state of this many-particle operator, the code features different wavefunctions. For the fermionic particles, beyond the traditional Slater determinant, QMeCha also includes Geminal functions such as the Pfaffian, and presents different types of explicit correlation terms in the Jastrow factors. The classical point charges and
quantum Drude oscillators, described through different variational ansätze, are used to model a molecular environment capable of explicitly describing dispersion, polarization, and electrostatic effects experienced by the
nuclear and fermionic subsystem. To integrate these wavefunctions, efficient variational Monte Carlo and
diffusion Monte Carlo protocols have been developed, together with a robust wavefunction optimization procedure that features correlated sampling.
Read the full abstract ▾
All authors Matteo Barborini, Jorge Charry, Matej Ditte, Andronikos Leventis, Georgios Kafanas, Alexandre Tkatchenko
Optics
Ultrafast Reconfigurable Topological Photonic Processing Accelerator
Wenfeng Zhou, Xin Wang, Xun Zhang et al. (+12 more)
The rise of artificial intelligence has triggered exponential growth in data volume, demanding rapid and efficient processing. High-speed, energy-efficient, and parallel-scalable computing hardware is thus increasingly critical. We demonstrate a wafer-scale non-volatile topological photonic computing chip using topological modulators. Leveraging the GHz-speed electro-optic response and nonvolatility of ferroelectric lead zirconate titanate (PZT) thin films via topological photonic confinement, Our chip enables thousand-fold faster reconfiguration, zero-static-power operation, and a computational density of 266 trillion operations per second per square millimeter . This density surpasses that of silicon photonic reconfigurable computing chips by two orders of magnitude and thin-film lithium niobate platforms by four orders of magnitude. A 16-channel wavelength-space multiplexed chip delivers 1.92 TOPS throughput with 95.64% digit-recognition accuracy and 94.5% precision for solving time-varying partial differential equations. Additionally, the chip supports functional reconfiguration for high bandwidth density optical I/O. This work establishes ferroelectric topological photonics for efficient high-speed photonic tensor processing.
Read the full abstract ▾
All authors Wenfeng Zhou, Xin Wang, Xun Zhang, Yuqi Chen, Min Sun, Jingchi Li, Xiong Ni, Yahui Zhu, Qingqing Han, Jungan Wang, Chen Yang, Bin Li, Feng Qiu, Yikai Su, Yong Zhang
Instrumentation and Detectors
Design and development of optical modules for the BUTTON-30 detector
D. S. Bhattacharya, J. Bae, M. Bergevin et al. (+63 more)
BUTTON-30 is a
neutrino detector demonstrator located in the STFC Boulby underground facility in the north-east of England. The main goal of the project is to deploy and test the performance of the gadolinium-loaded water-based
liquid scintillator for
neutrino detection in an underground environment. This will pave the way for a future large-volume
neutrino observatory that can also perform remote monitoring of
nuclear reactors for nonproliferation. This paper describes the design and construction of the watertight optical modules of the experiment.
Read the full abstract ▾
All authors D. S. Bhattacharya, J. Bae, M. Bergevin, J. Boissevain, S. Boyd, K. Bridges, L. Capponi, J. Coleman, D. Costanzo, T. Cunniffe, S. A. Dazeley, M. V. Diwan, S. R. Durham, E. Ellingwood, A. Enqvist, T. Gamble, S. Gokhale, J. Gooding, C. Graham, E. Gunger, W. Hopkins, I. Jovanovic, T. Kaptanoglu, E. Kneale, L. Lebanowski, K. Lester, V. A. Li, M. Malek, C. Mauger, N. McCauley, C. Metelko, R. Mills, A. Morgan, F. Muheim, A. Murphy, M. Needham, K. Ogren, G. D. Orebi Gann, K. Y. Oyulmaz, S. M. Paling, A. F. Papatyi, G. Pinkney, J. Puputti, S. Quillin, B. Richards, R. Rosero, A. Scarff, Y. Schnellbach, P. R. Scovell, B. Seitz, L. Sexton, O. Shea, G. D. Smith, R. Svoboda, D. Swinnock, A. Tarrant, F. Thomson, J. N. Tinsley, C. Toth, A. Usón, M. Vagins, J. Webster, S. Woodford, G. Yang, M. Yeh, E. Zhemchugov
Applied Physics
Force-Based Reading and Writing of Individual Single-Atom Magnets
Yuuki Adachi, Kazuki Ueda, Yuuki Yasui et al. (+1 more)
The integration of single-atom bits enables the realization of the highest data-density
memory. Reading and writing information to these bits through mechanical interactions opens the possibility of operating the
magnetic devices with low heat generation and high density recording. To achieve this visionary goal, we demonstrate the use of
magnetic exchange force microscopy to read and write the
spin orientation of individual holmium adatoms on MgO thin films. The
spin orientation of the holmium adatom is stabilized by the strong uniaxial anisotropy of the adsorption site and can be read out by measuring the exchange forces between the
magnetic tip and the atom. The
spin orientation can be written by approaching the tip closer to the holmium adatom.We explain this writing mechanism by the
symmetry reduction of the adsorption site of the Ho adatom. These findings demonstrate the potential for information storage with minimal energy loss and pave the way for a new field of atomic-scale mechano-spintronics.
Read the full abstract ▾
All authors Yuuki Adachi, Kazuki Ueda, Yuuki Yasui, Yoshiaki Sugimoto
Optics
Exploring the role of hyperbolicity in surface enhanced Raman sensing
Mihir Kumar Sahoo, Abhay Anand V S, Nihar Ranjan Sahoo et al. (+1 more)
A plasmonic nanostructure-based substrate, serving as a surface-enhanced Raman scattering (SERS) substrate, enhances the Raman scattering of molecules. By employing an electron beam lithography followed by our recently developed nano-electroplating protocol, a gold nanorod array SERS substrate can be fabricated to detect lower molecular analyte concentrations, such as Rhodamine 6G (R6G) solution. As the critical dimensions of the nanorod array decrease, they exhibit
hyperbolic metamaterial (HMM) characteristics with anisotropic permittivity behavior. In our study, we fabricated two sets of nanorod arrays: one in the HMM regime (140 nm periodicity) and the other in the non-HMM regime (400 nm periodicity), aiming to evaluate the performance of each set based on R6G detection. The obtained results are compared and analyzed using COMSOL simulation and Raman mapping and the role of hyperbolicity is discussed.
Read the full abstract ▾
All authors Mihir Kumar Sahoo, Abhay Anand V S, Nihar Ranjan Sahoo, Anshuman Kumar
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Enhancing composition-based materials property prediction by cross-modal knowledge transfer
Ivan Rubtsov, Ivan Dudakov, Yuri Kuratov et al. (+1 more)
Crystal graph neural networks are widely applicable in modeling experimentally synthesized compounds and hypothetical materials with unknown synthesizability. In contrast, structure-agnostic predictive
algorithms allow exploring previously inaccessible domains of chemical space. Here we present a universal approach for enhancing composition-based materials property prediction by means of cross-modal knowledge transfer. Two formulations are proposed: implicit transfer involves pretraining chemical
language models on
multimodal embeddings, whereas explicit transfer suggests generating
crystal structures and implementing structure-aware predictors. The proposed approaches were benchmarked on LLM4Mat-Bench and MatBench tasks, achieving state-of-the-art performance in 25 out of 32 cases. In addition, we demonstrated how another modeling aspect of chemical
language models - interpretability - benefits from applying a game-theoretic approach, which is able to incorporate high-order feature interactions.
Read the full abstract ▾
All authors Ivan Rubtsov, Ivan Dudakov, Yuri Kuratov, Vadim Korolev
Computational Physics · Cross-listed from quant-ph
Universal Quantum Computer Simulation of 50 Qubits on Europe`s First Exascale Supercomputer Harnessing Its Heterogeneous CPU-GPU Architecture
Hans De Raedt, Jiri Kraus, Andreas Herten et al. (+5 more)
We have developed a new version of the high-performance Jülich universal
quantum computer simulator (JUQCS-50) that leverages key features of the GH200 superchips as used in the JUPITER supercomputer, enabling simulations of a 50-
qubit universal
quantum computer for the first time. JUQCS-50 achieves this through three key innovations: (1) extending usable
memory beyond GPU limits via high-bandwidth CPU-GPU interconnects and LPDDR5
memory; (2) adaptive data encoding to reduce
memory footprint with acceptable trade-offs in precision and compute effort; and (3) an on-the-fly network traffic optimizer. These advances result in a 16.6-fold speedup over the previous 48-
qubit record on the K computer
Read the full abstract ▾
All authors Hans De Raedt, Jiri Kraus, Andreas Herten, Vrinda Mehta, Mathis Bode, Markus Hrywniak, Kristel Michielsen, Thomas Lippert
Atmospheric and Oceanic Physics
Impact of Wave Interference on the Consistency Relations of Internal Gravity Waves near the Ocean Bottom
Guangyao Wang, Yue Wu, Yulin Pan et al. (+5 more)
Consistency relations of internal
gravity waves (IGWs) describe ratios of cross-spectral quantities as functions of frequency. It has been a common practice to evaluate the measured or simulated signals (e.g., time series of velocity, density, etc.) against the consistency relations, as a way to determine whether an oceanic field of interest is comprised of IGWs. One such study is carried out in Nelson et al. (JGR Oceans, 125(5), 2020, e2019JC015974), which certifies that the ocean interior field in a numerical simulation of a region southwest of Hawaii is dominated by IGWs, through evaluating the consistency relations derived from time series at a depth of 620 m. However, we find that when the same procedure is applied at greater depths (e.g., 2362 m, 3062 m, and 4987 m), a clear deviation of the simulated signal from the classical consistency relations is observed. In this paper, we identify the reason for the unexpected deviation and show that it is a general phenomenon due to interference of low vertical modes under the reflection by the ocean bottom. We further derive a new set of formulae to characterize the consistency relations of these low modes and validate these formulae using model output.
Read the full abstract ▾
All authors Guangyao Wang, Yue Wu, Yulin Pan, Kayhan Momeni, Joseph Skitka, Dimitris Menemenlis, Brian K. Arbic, William R. Peltier
Plasma Physics
First global gyrokinetic profile predictions of ITER burning plasma
A. Di Siena, C. Bourdelle, A. Bañón Navarro et al. (+11 more)
In this work, we present the first global gyrokinetic simulations of the ITER baseline scenario operating at 15 MA using GENE-Tango electrostatic and electromagnetic simulations. The modeled radial region spans close to the
magnetic axis up to rho_tor = 0.6. Our results show a pronounced density peaking, moderated by electromagnetic fluctuations. The predicted fusion gain for this scenario is Q = 12.2, aligning well with ITER's mission objectives. We further characterize the
turbulence spectra and find that electromagnetic modes, such as microtearing modes, kinetic ballooning modes, and Alfvenic ion temperature gradient modes at low binormal wave numbers, play a critical role in the core transport of this ITER scenario, necessitating high numerical resolution for accurate modeling. Local flux-tube simulations qualitatively reproduce the key features observed in the global gyrokinetic simulations but exhibit a much higher sensitivity to profile gradients, reflecting increased stiffness, likely due to the linearization of the
equilibrium profiles and safety factor. Our study also reveals that the imposed external toroidal rotation profiles have a negligible impact on turbulent transport, as their magnitudes are substantially lower than the dominant linear growth rates. Furthermore, we demonstrate that the safety factor profile is of paramount importance: scenarios featuring flat q profiles with near-zero
magnetic shear lead to the destabilization of kinetic ballooning modes in the
plasma core, significantly enhancing turbulent transport and potentially degrading confinement. Finally, although electron temperature gradient
turbulence initially appears large, sometimes exceeding ion-scale transport levels, it is ultimately quenched over long timescales by secular
evolution of zonal flows, which are weakly damped under the very low collisionality conditions expected in ITER.
Read the full abstract ▾
All authors A. Di Siena, C. Bourdelle, A. Bañón Navarro, G. Merlo, T. Görler, E. Fransson, A. Polevoi, S. H. Kim, F. Koechl, A. Loarte, E. Fable, C. Angioni, P. Mantica, F. Jenko
Atomic Physics
Isolated quantum-state networks in ultracold molecules
Tom R. Hepworth, Simon L. Cornish and Philip D. Gregory
Precise control over rotational angular momentum is at the heart of recent advances in
quantum chemistry,
quantum simulation, and
quantum computation with ultracold bialkali molecules. Each rotational state comprises a rich
manifold of hyperfine states arising from combinations of rotation and
nuclear spins; this often yields hundreds of transitions available between a given pair of rotational states, and the efficient
navigation of this complex space is a current challenge for experiments. Here, we describe a general approach based on a simple heuristic and graph theory to quickly identify optimal sets of states in ultracold bialkali molecules. We explain how to find pathways through the many available transitions to prepare the molecule in a specific state with maximum speed for any desired fidelity. We then examine networks of states where multiple couplings are present at the same time. As example applications, we first identify a closed loop of four states in the RbCs molecule where there is minimal population leakage out of the loop during simultaneous microwave coupling; we then extend the optimisation procedure to account for decoherence induced by
magnetic-field noise and obtain an optimal set of 3 states for
quantum computation applications.
Read the full abstract ▾
Optics
Far-UVC Field Emission Device at 226 nm and its Sub-Nanometer thick GaN/AlN Quantum Well Anode
D. L. Boiko, P. Demolon, J.-F. Carlin et al. (+10 more)
We report on unique features of ultra-thin GaN/AlN
quantum wells and demonstrate a new field emission device for human-safe disinfection with an external
quantum efficiency of 18% and superior reliability, as compared to far-UVC LEDs. We investigate the behavior of a Shockley-Read-
Hall recombination via Al vacancies-oxygen complexes in AlN barriers as a function of GaN well thickness and come to the conclusion that direct relaxation of confined states via mid-gap traps is prohibited and the main mechanism limiting the
quantum efficiency (QE) is the carrier escape followed by non-radiative SRH recombination in the AlN barriers. As a consequence, the QE is highly dependent on the defect density, QW width and temperature which allowed us to reach a descent emissions at 226 nm wavelength although at wall plug efficiency being low, at 0.02%. We build a complete Light-Current-Voltage model and find that present device performance is limited by the self-heating and by the Child's space charge effect, both limitations can be easily addressed with some additional engineering efforts.
Read the full abstract ▾
All authors D. L. Boiko, P. Demolon, J.-F. Carlin, E. Eriksson, A. Hoogerwerf, K. Bach Gravesen, A. Brimnes Gardner, M.-A. Dubois, P. Tønning, E. Zanchetta Ulsig, M. Marin, J. Tingsborg, N. Volet
Optics
Conventional Scintillation Statistics with Turbulence Impacted Coupled Dipole Oscillation
Shouvik Sadhukhan and C. S. Narayanamurthy
We investigate the propagation of optical fields through polymethyl methacrylate (PMMA) rods under atmospheric
turbulence conditions, employing a generalized Lorentz dipole oscillator model with nonlinear restoring forces and dipole-dipole coupling. The theoretical framework incorporates second- and third-order anharmonic terms ($\beta_i|r_i|r_i$ and $\alpha_i|r_i|^2r_i$) alongside dyadic Green's function-mediated coupling between localized dipoles. Gradient forces arising from spatially non-uniform field distributions and Lorentz force perturbations are incorporated through d'Alembert's principle, revealing an effective inertia mechanism that opposes rapid field redistribution. Modal diagonalization demonstrates that synchronized dipole oscillations can compensate
turbulence-induced wavefront distortions, with the perturbation force $\delta F_{\text{Pert}}(t) = F'_{\text{Inertia}} - F_{\text{Inertia}}$ governing the compensation efficacy. Experimental verification employs a pseudo-random phase plate (PRPP) generating Kolmogorov-spectrum
turbulence, with 200 frames recorded across four configurations: baseline,
turbulence-only, and
turbulence with one or two PMMA rods. Statistical analysis quantifies scintillation index variations. Results indicate that dipole-dipole coupling energy transitions enable partial
turbulence compensation when stronger suppression observed for longer propagation paths through increased synchronization.
Read the full abstract ▾
Optics
Graphene-enabled coherent (sub-)terahertz wave detection and thickness determination
Ronny de la Bastida, Enzo Rongione, Karuppasamy Pandian Soundarapandian et al. (+9 more)
Phase-sensitive terahertz (THz) detection enables applications ranging from astronomy to non-destructive testing. However, current THz detectors lack phase sensitivity, unless they are combined with external interferometers, or through photomixing. This implies a large footprint and sensitive dependence on
alignment. Here, we demonstrate a
graphene-enabled, on-chip, integrated (sub-)THz detector-interferometer with optical cavity and
antenna, exhibiting high sensitivity to the phase of incident THz light. We exploit this by determining the thickness of thin films placed in front of the detector-interferometer, obtaining a deep sub-wavelength thickness accuracy of a few micrometer, while we predict that an improved accuracy is within reach. This is relevant for a range of industrial application domains, including automotive, construction, and health. We furthermore achieve a record-high external responsivity - considering bias-free
graphene-based (sub-)THz detectors - of 172 mA/W and a noise-equivalent power of 26 pW$~\rm{Hz}^{-1/2}$. This performance is due to enhanced absorption at the resonant cavity mode around 89 GHz, in agreement with multi-physics simulations. These results pave the way to exploiting coherent wave detection in the (sub-)THz regime with utility in spectroscopy, next-generation wireless communication, and beyond.
Read the full abstract ▾
All authors Ronny de la Bastida, Enzo Rongione, Karuppasamy Pandian Soundarapandian, Ioannis Vangelidis, Anand Nivedan, David Saleta Reig, Kenji Watanabe, Takashi Taniguchi, Elefterios Lidorikis, Frank H. L. Koppens, Sebastián Castilla, Klaas-Jan Tielrooij
Optics
Incorporating QM/MM molecular dynamics into the few-mode quantization approach for light-matter interactions in nanophotonic structures
Ruth H. Tichauer, Maksim Lednev, Gerrit Groenhof et al. (+1 more)
In the context of light-matter interactions between organic chromophores and confined
photons of (plasmonic) nano-resonators, we introduce a general framework that couples ab initio QM/MM molecular dynamics with few-mode field quantization to simulate light-matter interactions of molecular emitters at the nanoscale. Arbitrary, lossy, and spatially inhomogeneous photonic environments are represented by a minimal set of interacting modes fitted to their spectral density, while geometry-dependent molecular properties are computed on the fly. Applications to few-molecule strong coupling show that strong coupling persists when molecular degrees of freedom and disorder are included for the chosen system consisting of a nanoparticle dimer coupled to multiple emitters. At the same time,
symmetry-protected degeneracies of two-level models are lifted. The framework further reveals how spatial field inhomogeneity and molecular disorder shape cavity-mediated energy transfer, illustrated for an HBQ-Methylene Blue donor-acceptor combination in a five-emitter system.
Read the full abstract ▾
All authors Ruth H. Tichauer, Maksim Lednev, Gerrit Groenhof, Johannes Feist
Optics
Contactless Modulation of Intralayer and Interlayer Excitons in MoS2/WSe2 heterostructures with Acoustoelectric Fields
Yueyi Sun, Dexing Liu, Jiefei Zhu et al. (+9 more)
This work presents a platform that enables surface acoustic wave (SAW) modulation of both intralayer and interlayer
excitons in MoS2/WSe2
heterostructures. Harnessing the coupled piezoelectric and strain fields of SAWs, this integrated approach allows for dynamic, precise, and fully contactless control of excitonic properties, a capability essential for the realization of next generation optoelectronic,
quantum photonic, and excitonic devices. We identify two distinct modulable interlayer
excitons in optical communication bands: IX$_{K\Gamma}$ in the O band (around 1300 nm) and IX$_{K\!-\!K}$ in the S band (around 1500 nm); these two
excitons display a robust twist-angle-independent energy splitting of 120 meV, in agreement with density functional theory (DFT) calculations. The type-II band
alignment induced by the SAW not only promotes efficient
exciton dissociation but also enables direct and tunable modulation of photoluminescence via the formation of confined piezoelectric potential wells. Furthermore, by simultaneously generating in-plane and out-of-plane SAW fields, the platform achieves selective manipulation of intralayer and interlayer
excitons, inducing quadratic Stark effects for intralayer
excitons and linear Stark effects for interlayer
excitons. These findings provide new insights into SAWexciton interactions in van der Waals
heterostructures, broaden the operational spectral range, and establish pathways toward on-chip acousto-optic and
quantum optoelectronic devices with advanced excitonic functionality.
Read the full abstract ▾
All authors Yueyi Sun, Dexing Liu, Jiefei Zhu, Siming Liu, Jiwei Chen, Yingjie Luo, Yihong Sun, Mansun Chan, Cary. Y. Yang, Taojie Zhou, Min Zhang, Changjian Zhou
Medical Physics
Structural Stress as a Predictor of the Rate and Spatial Location of Aortic Growth in Uncomplicated Type B Aortic Dissection
Yuhang Du, Yuxuan Wu, Hannah L. Cebull et al. (+10 more)
Accurate prediction of aortic expansion in uncomplicated type B aortic dissection (TBAD) can help identify patients who may benefit from timely thoracic endovascular aortic repair. This study investigates associations between biomechanical predictors derived from reduced-order fluid-structure interaction (FSI) analysis and aortic growth outcomes. Baseline and follow-up CT images from 30 patients with uncomplicated TBAD were obtained. For each patient, a reduced-order FSI analysis using the forward penalty stress computation method was performed on the baseline geometry. Aortic growth was quantified by registering baseline and follow-up surfaces using nonrigid registration. Mixed-effects linear and logistic regression analyses were performed to assess relationships between structural stress, wall shear stress (WSS), pressure and growth rate while accounting for inter-patient variability. Group comparison analyses were performed to evaluate spatial distributions of these biomechanical variables along the dissected aorta between patient groups categorized by optimal medical therapy (OMT) and aortic growth outcomes. Linear regression revealed a positive association between structural stress and aortic growth rate (p = 0.0003) and a negative association for WSS (p = 0.0227). Logistic regression yielded area under the receiver operator characteristic curve (AUCs) of 0.7414, 0.5953, 0.4991, and 0.6845 for structural stress, WSS, pressure, and aortic diameter, respectively. Group comparisons showed significant regional differences in structural stress, but not in diameter, WSS, or pressure, between groups defined by aortic growth and OMT outcomes. These results indicate that structural stress is a promising predictor of both the rate and location of aortic growth in uncomplicated TBAD, which supports its use in risk stratification models to identify patients at higher risk of TBAD progression.
Read the full abstract ▾
All authors Yuhang Du, Yuxuan Wu, Hannah L. Cebull, Bangquan Liao, Rishika Agarwal, Alan Meraz, Hai Dong, Asanish Kalyanasundaram, John N. Oshinski, Rudolph L. Gleason Jr, John A. Elefteriades, Bradley G. Leshnower, Minliang Liu
Geophysics
3D Bayesian Variational Surface Wave Tomography and Application to the Southwest China
Wenda Yang and Xin Zhang
Seismic surface wave
tomography uses surface wave information to obtain velocity structures in the subsurface. Due to data noise and nonlinearity of the problem, surface wave
tomography often has non-unique solutions. It is therefore required to quantify uncertainty of the results in order to better interpret the resulting images.
Bayesian inference is the most widely-used method for this purpose. However, the commonly-used Monte Carlo methods require huge computational cost and remains intractable in high-dimensional problems. Variational inference uses optimization to solve
Bayesian inverse problems, and therefore can be more efficient in the case of large
datasets and high-dimensional parameter spaces. Variational inference has been applied to 2-D surface wave tomographic problems. In this study, we extend the method to 3-D surface wave
tomography by directly inverting for 3-D spatial structures from frequency-dependent travel time measurements. Specifically, we apply three variational methods, mean-field automatic differential variational inference (mean-field ADVI), physically structured variational inference (PSVI) and
stochastic Stein varational gradient descent (sSVGD) to surface wave tomographic problems using both synthetic data and real data in the Southwest China. The results show that all methods can provide accurate velocity estimates, while sSVGD produces more reasonable uncertainty estimates than mean-field ADVI and PSVI because of Gaussian assumption used in the later methods. In the real data case, the variational methods provide more detailed velocity structures than those obtained using traditional methods, along with reliable uncertainty estimates. We therefore conclude that variational surface wave tomograph can be applied fruitfully to many realistic problems.
Read the full abstract ▾
Fluid Dynamics
On the role of back-propagating pressure suppression in enhancing the pressure-gain performance of quasi-2D rotating detonation engines
Tonghui Wang, Guoqing Zhang and Haocheng Wen
The total pressure gain (PG) characteristics of the quasi-2D rotating detonation engine (RDE) are numerically investigated in this study, based on an abstract check valve model and the quasi-1D assumption. The influence of back-propagating pressure suppression on PG and its underlying mechanism are examined. An abstract check valve model is established to simulate various flow channel configurations, with backflow check strength $\alpha_b$ defined, where a larger $\alpha_b$ corresponds to a stronger backflow blocking effect. The quasi-1D assumption is applied along the axial direction to simplify the radial features of the annular RDE. The quasi-2D governing equations for RDE flow are derived. Simulations are conducted for varying expansion ratios $A_e$ and values of $\alpha_b$. The results indicate that increasing $\alpha_b$ effectively suppresses back-propagating pressure and slightly improves PG; however, it cannot fully eliminate the back-propagating pressure, as the check valve itself introduces flow disturbances. Increasing $A_e$ also suppresses back-propagating pressure but significantly reduces PG. Achieving positive PG requires reducing $A_e$ below a critical value. However, this reduction is limited by $\alpha_b$; further reduction in $A_e$ leads to forward propagation of back-propagating pressure to the engine inlet, resulting in inlet blocking. Therefore, a sufficiently large $\alpha_b$ is essential for the required reduction in $A_e$. The key aerodynamic challenge for achieving positive PG lies in optimizing flow channels to suppress back-propagating pressure efficiently. Finally, a general PG criterion is proposed by normalizing the quasi-2D RDE with stoichiometric hydrogen/air mixtures. This study provides theoretical guidance for enhancing PG in RDEs.
Read the full abstract ▾
Fluid Dynamics
Meshless data-driven decompositions with RBF-based inner products
Manuel Ratz, Alessandro Parente and Miguel Alfonso Mendez
Data-driven modal decompositions are useful tools for compressing data or identifying dominant structures. Popular ones like the dynamic mode decomposition (DMD) and the proper orthogonal decomposition (POD) are defined with continuous inner products. These are usually approximated with samples of data uniform in space and time. However, not every
dataset fulfills this requirement. Numerical simulations with smoothed particle hydrodynamics or experiments with Lagrangian particle tracking velocimetry produce scattered data varying in time and space, rendering sample-based inner products impossible. In this work, we extend a previous approach that computes the modal decompositions with meshfree radial basis functions (RBFs). We regress the data and use the continuous representation of the RBFs to compute the required inner products. We choose our basis to be constant in time, greatly reducing the computational cost since the inner product of the data reduces to the inner product of the basis functions. We use this approach in the most popular decompositions, namely the POD, DMD, multi-scale POD, and the two versions of the spectral POD. For all decompositions, the RBFs give a mesh-free representation of the spatial structures. Two test cases are considered: particle image velocimetry measurements of an impinging jet and large eddy simulations of the flow past a transitional airfoil. In both cases, the RBF-based approach outperforms classical binning and better recovers relevant structures across all data densities.
Read the full abstract ▾
Instrumentation and Detectors
Development of a Hermetic Gaseous Xenon Detector for Suppressing External Radon Background
Ryuta Miyata, Koki Fujikawa, Rina Harata et al. (+3 more)
Radon-induced backgrounds, particularly from $^{222}$Rn and its beta-emitting progeny, present a critical challenge for next-generation
liquid xenon (LXe) detectors aimed at probing dark matter down to the
neutrino fog. To address this, we developed a compact hermetic gaseous xenon (GXe) detector. This device physically isolates the active volume from external radon sources by using a PTFE vessel sealed between two quartz flanges with mechanically compressed ePTFE gaskets. To quantify radon sealing performance, we implemented a dual-loop GXe circulation system and conducted a 670-hour radon-injection measurement campaign. Radon ingress into the hermetic detector was monitored using electrostatic radon detectors and photomultiplier tubes (PMTs). From these two independent measurements, the steady-state ratios of the radon concentrations inside the hermetic detector to those outside were estimated to be $ (1.1 \pm 0.1) \times 10^{-2} $ and $ (1.1 \pm 0.2) \times 10^{-2} $, corresponding to radon-leakage flows of $ (2.9 \pm 0.3) \times 10^{-11} $ and $ (2.6 \pm 0.4) \times 10^{-11} $ $ \thinspace $m$^{3}$ $ \thinspace $ $\mathrm{s}^{-1}$, respectively. An extrapolation to a 60-tonne LXe TPC such as XLZD suggests that the radon leakage could amount to $ 1.2 \times 10^{-2} $ $ \thinspace $mBq, which is negligible compared to the expected natural radon emanation inside the detector, typically 3$ \thinspace $mBq. These results demonstrate that flange-based mechanical sealing provides an effective solution for realizing radon-isolated inner detectors in large-scale LXe experiments.
Read the full abstract ▾
All authors Ryuta Miyata, Koki Fujikawa, Rina Harata, Yoshitaka Itow, Shingo Kazama, Masatoshi Kobayashi
Accelerator Physics
Wide frequency-range acceleration using second harmonic RF bucket in fixed field accelerators
Tomonori Uesugi, Yoshihiro Ishi and Yoshiharu Mori
We propose a novel acceleration scheme for fixed-field accelerators (FFAs), in which RF buckets with harmonic numbers $h = 1$ and $h = 2$ are time-sequenced to form a single, continuous acceleration path. This approach completes acceleration in two RF frequency sweeps, thereby reducing the total frequency sweep range and shortening the repetition period. The feasibility of this method is demonstrated through longitudinal simulations based on parameters of the FFA at the Institute for Integrated Radiation and
Nuclear Science, Kyoto University (KURNS). We also establish operational conditions under which the second harmonic rf bucket remains stable and practically usable.
Read the full abstract ▾
Fluid Dynamics
A Hybrid CNN-Cheby-KAN Framework for Efficient Prediction of Two-Dimensional Airfoil Pressure Distribution
Yaohong Chen, Luchi Zhang, Yiju Deng et al. (+3 more)
The accurate prediction of airfoil pressure distribution is essential for aerodynamic performance evaluation, yet traditional methods such as computational fluid dynamics (CFD) and wind tunnel testing have certain bottlenecks. This paper proposes a hybrid deep learning model combining a Convolutional Neural Network (CNN) and a Chebyshev-enhanced Kolmogorov-Arnold Network (Cheby-KAN) for efficient and accurate prediction of the two-dimensional airfoil flow field. The CNN learns 1549 types of airfoils and encodes airfoil geometries into a compact 16-dimensional feature vector, while the Cheby-KAN models complex nonlinear mappings from flight conditions and spatial coordinates to pressure values. Experiments on multiple airfoils–including RAE2822, NACA0012, e387, and mh38–under various Reynolds numbers and angles of attack demonstrate that the proposed method achieves a mean squared error (MSE) on the order of $10^{-6}$ and a coefficient of determination ($R^2$) exceeding 0.999. The model significantly outperforms traditional Multilayer Perceptrons (MLPs) in accuracy and generalizability, with acceptable computational overhead. These results indicate that the hybrid CNN-Cheby-KAN framework offers a promising data-driven approach for rapid aerodynamic prediction.
Read the full abstract ▾
All authors Yaohong Chen, Luchi Zhang, Yiju Deng, Yanze Yu, Xiang Li, Renshan Jiao
Optics
Selective sparsity-enhanced synchronization in disordered semiconductor laser networks
Li-Li Ye, Nathan Vigne, Fan-Yi Lin et al. (+2 more)
Biological networks tend to leverage selective sparsity as an economic strategy to optimize function while minimizing wiring costs. In contrast, achieving synchronization in engineered systems such as
semiconductor laser arrays is traditionally expected to require resource-intensive coupling %strong connections to overcome intrinsic frequency disorders. We demonstrate that selectively coupled sparse networks can outperform fully connected architectures, achieving near-complete synchronization with a significantly reduced coupling budget. Using an evolutionary
algorithm, we identify a “pairing opposites" principle: optimal structures specifically prioritize connections between oscillators with the largest opposite frequency detuning. This
topology neutralizes dynamical interference induced by redundant links, leading to stable synchronization. We formalize this mechanism through a thermodynamic potential framework, mapping time-delayed phase dynamics to an energy landscape where optimal sparsity prunes additional states to stabilize global phase-locking. Furthermore, we show that the optimal connectivity scales inversely with system size. This principle provides a resource-efficient blueprint for synchronizing and stabilizing diverse complex networks, from photonic arrays to neuromorphic hardware.
Read the full abstract ▾
All authors Li-Li Ye, Nathan Vigne, Fan-Yi Lin, Hui Cao, Ying-Cheng Lai
Chemical Physics · Cross-listed from quant-ph
Quantum Sensing of Copper-Phthalocyanine Electron Spins via NV Relaxometry
Boning Li, Xufan Li, Yifan Quan et al. (+2 more)
Molecular
spin systems are promising candidates for
quantum information processing and nanoscale sensing, yet their characterization at room temperature remains challenging due to fast
spin decoherence. In this work, we use $T_1$ relaxometry of shallow nitrogen-vacancy (NV) centers in diamond to probe the electron
spin ensemble of a polycrystalline copper phthalocyanine (CuPc) thin film. In addition to unequivocally identifying the NV-CuPc interaction thanks to its hyperfine spectrum, we further extract key parameters of the CuPc
spin ensemble, including its correlation time and local
lattice orientation, that cannot be measured in bulk electron resonance experiments. The analysis of our experimental results confirms that electron-electron interactions dominate the decoherence dynamics of CuPc at room temperature. Additionally, we demonstrate that the CuPc-enhanced NV relaxometry can serve as a robust method to estimate the NV depth with $\sim1$~nm precision. Our results establish NV centers as powerful probes for molecular
spin systems, providing insights into molecular
qubits,
spin bath engineering, and hybrid
quantum materials, and offering a potential pathway toward their applications such as molecular-scale
quantum processors and
spin-based
quantum networks.
Read the full abstract ▾
All authors Boning Li, Xufan Li, Yifan Quan, Avetik R Harutyunyan, Paola Cappellaro
Chemical Physics
Exploring the mechanisms of transverse relaxation of copper(II)-phthalocyanine spin qubits
Boning Li, Yifan Quan, Xufan Li et al. (+4 more)
Molecular
spin qubits are promising candidates for
quantum technologies, but their performance is limited by decoherence arising from diverse mechanisms. The complexity of the environment makes it challenging to identify the main source of noise and target it for mitigation. Here we present a systematic experimental and theoretical framework for analyzing the mechanisms of transverse relaxation in copper(II) phthalocyanine (CuPc) diluted into diamagnetic phthalocyanine hosts. Using pulsed EPR spectroscopy together with first-principles cluster correlation expansion simulations, we quantitatively separate the contributions from hyperfine-coupled
nuclear spins,
spin–
lattice relaxation, and electron–electron dipolar interactions. Our detailed modeling shows that both strongly and weakly coupled
nuclei contribute negligibly to $T_2$, while longitudinal dipolar interactions with electronic
spins, through instantaneous and spectral
diffusion, constitute the main decoherence channel even at moderate
spin densities. This conclusion is validated by direct comparison between simulated
spin-echo dynamics and experimental data. By providing a robust modeling and experimental approach, our work identifies favorable values of the electron
spin density for
quantum applications, and provides a transferable methodology for predicting ensemble coherence times. These insights will guide the design and optimization of molecular
spin qubits for scalable
quantum devices.
Read the full abstract ▾
All authors Boning Li, Yifan Quan, Xufan Li, Guoqing Wang, Robert G Griffin, Avetik R Harutyunyan, Paola Cappellaro
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
A Probabilistic U-Net Approach to Downscaling Climate Simulations
Maryam Alipourhajiagha, Pierre-Louis Lemaire, Youssef Diouane et al. (+1 more)
Climate models are limited by heavy computational costs, often producing outputs at coarse spatial resolutions, while many
climate change impact studies require finer scales. Statistical downscaling bridges this gap, and we adapt the probabilistic U-Net for this task, combining a deterministic U-Net backbone with a variational latent space to capture aleatoric uncertainty. We evaluate four training objectives, afCRPS and WMSE-MS-SSIM with three settings for downscaling precipitation and temperature from $16\times$ coarser resolution. Our main finding is that WMSE-MS-SSIM performs well for extremes under certain settings, whereas afCRPS better captures spatial variability across scales.
Read the full abstract ▾
All authors Maryam Alipourhajiagha, Pierre-Louis Lemaire, Youssef Diouane, Julie Carreau
Optics
Correcting Fabrication-Induced Curvature in Micromirror-Based Spatial Light Modulators with a Microlens Array
Munkyu Kang, Elizabeth Murray, Leyla A. Kabuli et al. (+2 more)
Computer generated holography requires high-speed spatial light modulators (SLMs) for dynamically patterning light in 3D. Piston-motion micromirror-based SLMs support high-speed ($\geq$ 10 kHz) phase modulation; however, fabricating micromirror arrays with sufficient fill factor necessary for high diffraction efficiency is challenging. In particular, the larger mirrors of high fill factor designs are susceptible to stress-induced
curvature that significantly degrades optical performance. In this work, we introduce an optical compensation method using a pitch-matched microlens array (MLA) to focus light onto just the center of each mirror. Our approach thus avoids
curvature-induced artifacts and improves optical fill factor to nearly 100$\%$, independent of the original mechanical fill factor. Through simulations and experiments on a fabricated micromirror array with bowed mirrors, we show that the Pearson correlation coefficient of the imparted phase profile is improved from 0.11 to 0.85 and the brightness of a holographically-generated single spot is enhanced by 8$\times$ with our microlens array in place. Our hybrid optical-electromechanical strategy thus provides a scalable path toward high-speed, high-fidelity wavefront control for applications such as adaptive optics,
holographic displays, and optogenetics.
Read the full abstract ▾
All authors Munkyu Kang, Elizabeth Murray, Leyla A. Kabuli, Rikky Muller, Laura Waller
Computational Physics · Cross-listed from math.NA
The isogeometric boundary element algorithm for solving the plane strain problem of an elastic matrix containing an open material surface of arbitrary shape
Rohit Satish Patil, Zhilin Han and Sofia G. Mogilevskaya
The paper presents the Isogeometric Boundary Element Method (IGABEM)
algorithm for solving the plane strain problem of an isotropic linearly elastic
matrix containing an open material surface of arbitrary shape. Theoretical developments are based on the use of the Gurtin-Murdoch model of material surfaces. The governing equations and the boundary conditions for the problem are reviewed, and analytical integral representations for the elastic fields everywhere in the material system are presented in terms of unknown traction jumps across the surface. To find the jumps, the problem is reduced to a system of singular boundary integral equations in terms of two unknown scalar components of the surface stress tensor. The system is solved numerically using the developed IGABEM
algorithm in which NURBS are used to approximate the unknowns. The main steps of the
algorithm are discussed and convergence studies are performed. The
algorithm is validated using two
benchmark problems involving the
matrix subjected to a uniform far-field load and containing a surface along (i) a straight segment and (ii) a circular arc. Numerical examples are presented to illustrate the influence of governing parameters with a focus on the influence of
curvature variation.
Read the full abstract ▾
Instrumentation and Detectors
{\alpha}/{\gamma} discrimination method for bulky BaF2 detector used in {\gamma} total absorption facility
Chong Zou, Qiwei Zhang, Guangyuan Luan et al. (+10 more)
The gamma-ray total absorption facility (GTAF) composed of 40 BaF2 detection units is designed to measure the cross section data of
neutron radiation capture reaction online, in order to comply with the experimental
nuclear data sheet.We have found that one of the most important sources of experimental background is the initial alpha particles emitted by the BaF2
crystal. Developing data analysis
algorithms to eliminate the influence of alpha particles in experimental data has become a key aspect. In this work, in order to meet the needs of data acquisition, online measurement and analysis of
neutron radiation cross section, the GTAF data acquisition system adopts a full waveform acquisition method, which results in a large number of data recorded, transmitted, and stored during experiment, which also affects the uncertainty of the cross-section data.Based on the signal waveform characteristics of the BaF2 detection unit, in order to solve the aforementioned problems, three methods, namely the ratio of fast component to total component, pulse width, and time decay constant, are used to identify and distinguish alpha particles and gamma rays. The quality factor FOM is utilized as an evaluation value and several experiments are conducted using three radioactive sources (22Na, 137Cs, 60Co) for verification.
Read the full abstract ▾
All authors Chong Zou, Qiwei Zhang, Guangyuan Luan, Hongyi Wu, Haotian Luo, Xuanbo Chen, Xiaoyu Wang, Guozhu He, Jie Ren, Hanxiong Huang, Xichao Ruan, Jie Bao, Xinghua Zhu
Computational Physics · Cross-listed from math.OC
Optimal Boundary Control of Diffusion on Graphs via Linear Programming
Harbir Antil, Rainald Löhner and Felipe Pérez
We propose a linear programming (LP) framework for steady-state
diffusion and flux optimization on
geometric networks. The state variable satisfies a discrete
diffusion law on a weighted, oriented graph, where conductances are scaled by edge lengths to preserve
geometric fidelity. Boundary potentials act as controls that drive interior fluxes according to a linear network
Laplacian. The optimization problem enforces physically meaningful sign and flux-cap constraints at all boundary edges, derived directly from a gradient bound. This yields a finite-dimensional LP whose feasible set is polyhedral, and whose boundedness and solvability follow from simple
geometric or algebraic conditions on the network data. We prove that under the absence of negative recession directions–automatically satisfied in the presence of finite box bounds, flux caps, or sign restrictions–the LP admits a global minimizer. Several sufficient conditions guaranteeing boundedness of the feasible region are identified, covering both full-rank and rank-deficient flux maps. The analysis connects classical results such as the Minkowski–Weyl decomposition, Hoffman's bound, and the fundamental
theorem of linear programming with modern network-based
diffusion modeling. Two large-scale examples illustrate the framework: (i) A typical large stadium in a major modern city, which forms a single connected component with relatively uniform corridor widths, and a (ii) A complex street network emanating from a large, historical city center, which forms a multi-component system.
Read the full abstract ▾