Peer Revenue An exchange of ideas

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Physics

physics Watch Physics

Monday 27 April

Optics

Sub-acoustic resolution photoacoustic imaging through scattering layers using speckle correlations

Benjamin Keenlyside, Arnon A.B., Dylan Marques et al. (+2 more)

Optical scattering presents a major obstacle to high resolution imaging in biological tissue and other turbid media. Conventional photoacoustic imaging can partially overcome this obstacle, enabling imaging of optical absorption in the multiple-scattering regime, but its resolution remains limited by acoustic diffraction. In this work we explore a strategy to overcome this limit by exploiting correlations in the illumination patterns produced by coherent scattered light. Combining controlled speckle translations with photoacoustic signal detection, this method enables the recovery of optical resolution images within acoustically selected regions, while overcoming the strict decorrelation range limitations of other speckle correlation techniques. In proof-of-concept experiments, we demonstrate imaging of objects hidden behind an opaque diffuser at sub-acoustic diffraction limited (<11um) resolution, over a >5mm^2 field of view much larger than the effective speckle decorrelation range. These results suggest that speckle correlation based photoacoustic imaging may offer a route to high resolution imaging of optical absorption under scattering conditions where conventional optical or photoacoustic techniques are fundamentally limited.
Read the full abstract

All authors Benjamin Keenlyside, Arnon A.B., Dylan Marques, Ivo Vellekoop, James Guggenheim

Computational Physics · Cross-listed from quant-ph

A Novel Hierarchy of Quantum Kernel Networks on Smoothed Particle Hydrodynamics

Yudong Li, Wenkui Shi, Chunfa Wang et al. (+3 more)

This study proposed the hierarchy of quantum kernel networks by combing multi quantum networks with smoothed particle hydrodynamics (SPH). The Lagrangian quantum network model was further developed based on an improved quantum multilayer perceptron (QMLP). A sequential hybrid quantum-classical framework was constructed to ensure robust particle gradient-based optimization and mitigate barren plateaus for computational particle dynamics. This approach combines smoothing kernels with quantum learning, establishing a novel quantum intelligent particle paradigm. The framework was validated through some benchmarks on multifarious quantum neural networks, static multi-level vortex reconstructions and transient scalar advective transports. Numerical results show that while elementary quantum circuits struggle with generalization in unstructured domains, the hybrid crossed-QMLP matches the fitting accuracy of classical SPH in quantum optimized space. Despite current limitations in computational efficiency and hardware implementation, this work paves the way for a new investigation on quantum-particle approach by mapping unstructured Lagrangian particle topologies into integrated quantum networks.
Read the full abstract

All authors Yudong Li, Wenkui Shi, Chunfa Wang, Zhihao Qian, Zhiqiang Feng, Moubin Liu

Applied Physics

Pressure sensing by electro-mechanical coupling in compliant dielectric membranes polarized by a bias voltage

Bart Van Damme, Alexandre Brun d'Arre, Patrick Danner et al. (+2 more)

Among smart materials, piezoelectric materials occupy a very prominent position for sensing and actuation functions. Combined with simple or more advanced shunts, they are also proposed in various vibration mitigation schemes. However, the selection of available piezoelectric materials is mainly limited to ceramics (with an elastic modulus in the order of 10 Gpa (e.g. PZT ceramics) and a few polymer materials, with elastic modulus in the range of 1 Gpa (e.g. PVDF). In both cases, the high mechanical impedance and, consequently, the small dynamic strains limit the application of these materials to stiff structures. In this contribution, we discuss using a bias voltage to polarize dielectric materials and thereby compensate for the lack of spontaneous polarization observed in piezoelectrics. This enables access to materials with a wider range of elastic properties, such as soft elastomers, e.g. poly(dimethylsiloxane). As an example, we present a practical implementation of a silicone rubber membrane used as a highly compliant dynamic pressure sensor. For such nearly-incompressible materials, the capacitance change during dynamic deformation of the membranes is sufficiently large to generate a measurable dynamic voltage change over the membrane.
Read the full abstract

All authors Bart Van Damme, Alexandre Brun d'Arre, Patrick Danner, Dorina Opris, Andrea Bergamini

Fluid Dynamics

Synchronized molecular dynamics method for thin-layer flows of complex fluids

Shugo Yasuda, Kotaro Oda, Fumito Muragaki et al. (+3 more)

We propose a multiscale computational method for thin-layer flows of complex fluids, termed the synchronized molecular dynamics (SMD) method, which directly couples local molecular dynamics (MD) simulations with a macroscopic lubrication description. In thin layers, the flow can be decomposed into cross-sectional dynamics that are strongly influenced by interfacial effects, and streamwise transport along the channel. The SMD method exploits this separation of scales by sparsely distributing local MD cells along the channel and synchronizing them through macroscopic conservation laws. In this framework, the macroscopic continuity equation is enforced by iteratively updating the external forces applied to each MD cell, thereby allowing the cross-sectional velocity profiles and the streamwise pressure distribution to be obtained without prescribing constitutive relations or boundary conditions. The method is validated for pressure-driven and wall-driven flows of Lennard–Jones fluids in a wedge-shaped channel, demonstrating excellent agreement with a modified Reynolds equation that accounts for boundary slip. The SMD method is further applied to polymeric lubrication flows modeled by the Kremer–Grest chain model. At large pressure differences, the present approach naturally captures pronounced shear-thinning behavior coupled with microscopic polymer conformation dynamics. The results demonstrate that the SMD method provides an efficient and physically consistent framework for the multiscale simulation of complex fluid thin-layer flows.
Read the full abstract

All authors Shugo Yasuda, Kotaro Oda, Fumito Muragaki, Yuta Taketa, Masashi Iwayama, Tomohide Ina

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Characterizing Fill Factor Limitations in Perovskite-Silicon Tandem Solar Cells

Yueming Wang, Nan Sun, Chris Dreessen et al. (+4 more)

Perovskite-silicon tandem technology has exceeded the single junction theoretical efficiency limit. However, there is still distance to the thermodynamic limit mainly caused by the fill factor. This work presents a methodology to illustrate the mechanisms of FF loss in perovskite-Si monolithic tandem solar cells. Apart from the series resistance related loss characterized by electroluminescence, another loss factor is from the photoshunt, a phenomenon in which the parallel resistance apparently reduces under illumination in perovskite solar cells due to the moderate charge transport layer mobility. In addoition, the two-diode property of the Si cell can also influence the FF of tandem devices. The photoshunt can be hidden when the bottom cell is over illuminated, which explains highly efficient tandem solar cells are usually bottom cell limited. This work outlines strategies that overcoming the photoshunt issue can move the perovskite top cell closer to low FF losses in tandem solar cells.
Read the full abstract

All authors Yueming Wang, Nan Sun, Chris Dreessen, Gaosheng Huang, Alexander Eberst, Kaining Ding, Thomas Kirchartz

Fluid Dynamics

Beyond Stokes drift – Lagrangian transport in evolving gravity waves

Tatsuo Izawa, Giulio Foggi Rota, Alessandro Chiarini et al. (+1 more)

Finite-amplitude gravity waves at the air-water interface induce net fluid and particle transport, known as Stokes drift. While this mechanism is well understood for steady waves, transport under unsteady, evolving conditions remains poorly characterized. Here, we investigate Lagrangian transport in freely decaying waves using high-resolution two-phase simulations and a perturbative analytical model. Wave decay modifies the classical Lagrangian drift by introducing both first- and second-order corrections in the wave amplitude expansion, and generates a net vertical transport, governed by the balance between inertia and viscosity. These effects alter particle trajectories and enhance anisotropic mixing, with implications for interpreting field observations and modelling surface transport processes.
Read the full abstract

All authors Tatsuo Izawa, Giulio Foggi Rota, Alessandro Chiarini, Marco Edoardo Rosti

Data Analysis and Statistics · Cross-listed from econ.GN

A phase transition in monetary function explains expansion without inflation

Ran Huang

Large monetary expansions do not necessarily generate consumer-price inflation, challenging scalar views of "money supply." Here we propose that monetary function is phase-dependent: newly issued base money can occupy distinct functional compartments with different coupling to prices. Starting from an accounting framework that separates reproduction, consumption, and reservation, we operationalize a measurable order parameter, phi=RB/MB, the reserve-share fraction of the monetary base. Using Japan's monthly record (1971-2026), we identify a compositional phase transition after 2013 from a cash-dominated to a reserve-dominated regime, quantitatively captured by a Landau-type order-parameter transition. Phase-conditional local projections using unexpected (residual) base-growth shocks show that, in Japan, unexpected base expansions are absorbed primarily as reserve balances-phi rises significantly-rather than entering the consumption-goods transaction sector; consequently, the core CPI inflation response is strongly attenuated and can even reverse sign. This demonstrates that increases in monetary supply do not necessarily cause inflation: the key is the "phase" in which incremental money accumulates (reservoir versus circulation). We further define function-specific efficiencies for reservation absorption and CPI transmission and provide an operational distinction between circulation-driven and reservation-dominant inflation regimes.
Read the full abstract

Optics

Non-Hermitian Synthetic Phase Shifter: Topologically-Protected Phase Control via Tunable Losses

Kevin Zelaya, Jonathan Friedman, Hector Rubio et al. (+2 more)

Phase shifters are fundamental reconfigurable components in photonic circuits. In conjunction with passive elements, they control light flow and serve as foundational building blocks for diverse applications, including communication, sensing, analog signal processing, and quantum control. Conventional phase shifters achieve phase control by modulating the refractive index through various physical mechanisms such as thermo-optic or electro-optic effects. However, despite expectations that such index-based approaches would integrate seamlessly, they, in practice, restrict circuit size, bandwidth, and scalability and thus become bottlenecks to large-scale photonic integration. Here, we introduce an alternative phase-control approach based on optical loss modulation. We demonstrate a synthetic phase shifter that uses two independently controlled loss-modulation stages combined with multipath interference to achieve full-cycle phase tunability while maintaining constant amplitude. We develop a theoretical framework based on conserved topological charges to demonstrate how synthetic phase control can be achieved via non-Hermitian effects, enabling robust topologically-protected phase control. By shifting the paradigm from index control to loss modulation, the proposed synthetic phase shifter could pave the way for scalable integrated photonic systems that support applications from communications and sensing to photonic classical and quantum information processing.
Read the full abstract

All authors Kevin Zelaya, Jonathan Friedman, Hector Rubio, Stefan Preble, Mohammad-Ali Miri

Optics

Molecular-optomechanical phonon laser

Bin Yin, Jie Wang, Qian Zhang et al. (+3 more)

Molecular cavity optomechanics (COM) leverages ultrastrong interactions between confined optical fields and high-frequency molecular vibration, providing a unique platform for exploring high-frequency phonon dynamics. In this work, we theoretically propose the use of a hybrid molecular COM system for realizing an ultra-low-threshold mid-infrared (MIR) phonon laser. Despite an optical quality factor of only $Q_a=100$, an ultra-low threshold power of $\mathrm{P}_{\mathrm{th}} = 17.5~\mathrm{nW}$ is achieved, enabled by giant single-photon optomechanical coupling and molecular collective effect. Moreover, the mechanical gain and threshold power can be further tuned by adjusting the distance between mirrors of the Fabry-Pérot cavity. Our findings establish the first direct connection between molecular COM and MIR phonon lasers, with potential applications in MIR acoustics and biomedical imaging.
Read the full abstract

All authors Bin Yin, Jie Wang, Qian Zhang, Deng Wang, Tian-Xiang Lu, Hui Jing

Instrumentation and Detectors

Charge readout electronics for the DUNE horizontal drift far detector: design and performance in ProtoDUNE-HD

DUNE Collaboration: S. Abbaslu, F. Abd Alrahman, A. Abed Abud et al. (+1367 more)

DUNE (Deep Underground Neutrino Experiment) is a long-baseline neutrino oscillation experiment currently under construction, whose far detectors will be the largest liquid argon time projection chambers ever built. This detector design calls for custom-built cryogenic front-end electronics to meet its performance requirements. This paper describes the charge readout electronics that will be used in the DUNE horizontal drift (HD) far detector and presents performance results using data from the ProtoDUNE-HD detector, a 770 ton liquid argon time projection chamber operated at the CERN Neutrino Platform in 2024 that served as the final prototype of the DUNE HD design.
Read the full abstract

All authors DUNE Collaboration: S. Abbaslu, F. Abd Alrahman, A. Abed Abud, R. Acciarri, L. P. Accorsi, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, K. Adhikari, C. Adriano, K. Agudelo-Jaramillo, F. Akbar, F. Alemanno, N. S. Alex, L. Aliaga Soplin, A. Alqaisi, M. Alrashed, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, R. Amarinei, P. Amedo, E. P. M. Amorim, J. Anderson, D. A. Andrade, C. Andreopoulos, M. Andreotti, M. P. Andrews, F. Andrianala, S. Andringa, F. Anjarazafy, S. Ansarifard, D. Antic, A. Antonakis, A. Aranda-Fernandez, T. Araya-Santander, L. Arellano, E. Arrieta Diaz, M. A. Arroyave, M. Artero Pons, J. Asaadi, M. Ascencio, A. Ashkenazi, L. Asquith, E. Atkin, D. Auguste, A. Aurisano, V. Aushev, D. Autiero, D. Ávila Gómez, M. B. Azam, F. Azfar, J. J. Back, Y. Bae, I. Bagaturia, L. Bagby, H. Bagdu, S. Balasubramanian, A. Balboni, P. Baldi, W. Baldini, E. Baldo, J. Baldonedo, B. Baller, B. Bambah, F. Barao, D. Barbu, G. Barenboim, P. Barham Alzás, G. J. Barker, W. Barkhouse, E. Barlas Yucel, G. Barr, W. Barrett, D. Barrow, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, M. Bassani, D. Basu, L. Bathe-Peters, J. G. Batista Sigolo, J.B.R. Battat, F. Battisti, J. Bautista, F. Bay, J. L. L. Bazo Alba, J. F. Beacom, E. Bechetoille, A. Beever, B. Behera, E. Belchior, B. Bell, G. Bell, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, C. Benitez Montiel, D. Benjamin, K. Benslama, F. Bento Neves, J. Berger, S. Berkman, J. Bermudez, J. Bernal, P. Bernardini, A. Bersani, E. Bertholet, E. Bertolini, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, Y. Bezawada, A. T. Bezerra, A. Bhat, V. Bhatnagar, M. Bhattacharjee, S. Bhattacharjee, M. Bhattacharya, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, K. Biery, B. Bilki, A. Binau, M. Bishai, P. Bishop, A. Blake, A. Blanchet, F. D. Blaszczyk, G. C. Blazey, E. Blucher, A. Bodek, B. Bogart, J. Boissevain, T. Bolton, L. Bomben, M. Bonesini, C. Bonilla-Diaz, A. Booth, F. Boran, C. Borden, R. Borges Merlo, D. Borodulina, N. Bostan, G. Botogoske, B. Bottino, R. Bouet, J. Boza, B. Brahma, D. Brailsford, F. Bramati, A. Branca, A. Brandt, J. Bremer, S. J. Brice, S. Brickner, V. Brio, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. B. Brunetti, N. Buchanan, H. Budd, J. Buergi, A. Bundock, D. Burgardt, S. Butchart, G. Caceres V., R. Calabrese, R. Calabrese, J. Calcutt, L. Calivers, S. Calvez, E. Calvo, A. Caminata, A. F. Camino, W. Campanelli, A. Campani, A. Campos Benitez, N. Canci, J. Capó, I. Caracas, D. Caratelli, D. Carber, G. Carini, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, N. Carrara, L. Carroll, A. Carter, J. Carvalho Roberto, E. Casarejos, D. Casazza, J. F. Castaño Forero, F. A. Castaño, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, C. Cerna, A. Cervelli, A. Cervera Villanueva, J. Chakrani, M. Chalifour, A. Chappell, A. Chatterjee, B. Chauhan, C. Chavez Barajas, H. Chen, M. Chen, W. C. Chen, Y. Chen, Z. Chen, D. Cherdack, S. S. Chhibra, C. Chi, F. Chiapponi, R. Chirco, N. Chitirasreemadam, K. Cho, S. Choate, G. Choi, D. Chokheli, P. S. Chong, O. Chow, B. Chowdhury, D. Christian, E. Church, M. F. Cicala, M. Cicerchia, V. Cicero, R. Ciolini, P. Clarke, G. Cline, A. G. Cocco, J. A. B. Coelho, A. Cohen, J. Collazo, J. Collot, H. Combs, J. M. Conrad, L. Conti, T. Contreras, M. Convery, K. Conway, S. Copello, P. Cova, C. Cox, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, G. Crone, R. Cross, T. Cruz, A. Cudd, C. Cuesta, Y. Cui, F. Curciarello, D. Cussans, O. Dalager, W. Dallaway, R. D'Amico, H. da Motta, Z. A. Dar, R. Darby, L. Da Silva Peres, Q. David, G. S. Davies, S. Davini, J. Dawson, R. De Aguiar, K. H. De Barros, P. Debbins, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, P. De Jong, P. Del Amo Sanchez, G. De Lauretis, A. Delbart, M. Delgado, A. Dell'Acqua, G. Delle Monache, N. Delmonte, P. De Lurgio, G. De Matteis, J. R. T. de Mello Neto, A. P. A. De Mendonca, D. M. DeMuth, S. Dennis, C. Densham, P. Denton, G. W. Deptuch, V. De Romeri, J. P. Detje, J. Devine, K. Dhanmeher, R. Dharmapalan, M. Dias, A. Diaz, J. S. Díaz, F. Díaz, F. Di Capua, A. Di Domenico, S. Di Domizio, S. Di Falco, D. Di Ferdinando, L. Di Giulio, P. Ding, L. Di Noto, E. Diociaiuti, G. Di Sciascio, C. Distefano, R. Di Stefano, R. Diurba, M. Diwan, Z. Djurcic, S. Dolan, M. Dolce, M. J. Dolinski, D. Domenici, S. Dominguez, S. Donati, S. Doran, D. Douglas, T.A. Doyle, F. Drielsma, D. J. Drobner, D. Duchesneau, K. Duffy, K. Dugas, P. Dunne, S. Durando, B. Dutta, D. A. Dwyer, A. S. Dyshkant, S. Dytman, M. Eads, A. Earle, S. Edayath, D. Edmunds, J. Eisch, S. Elias, J. Ellis, W. Emark, P. Englezos, A. Ereditato, D. T. Ergonul, T. Erjavec, C. O. Escobar, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, C. Fang, M. Fani', F. Fanomezana, D. Faragher, C. Farnese, Y. Farzan, J. Felix, Y. Feng, M. Ferreira da Silva, E. Fialova, L. Fields, P. Filip, A. Filkins, F. Filthaut, G. Fiorillo, M. Fiorini, N. F. Fiuza De Barros, S. Fogarty, W. Foreman, B. Fossing, J. Fowler, J. Franc, K. Francis, D. Franco, J. Franklin, J. Freeman, J. Fried, A. Friedland, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, R. Gaba, A. Gabrielli, A. M Gago, F. Galizzi, H. Gallagher, M. Galli, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, R. Gan, R. Gandhi, S. Ganguly, F. Gao, S. Gao, A. Garcia, D. Garcia-Gamez, M. Á. García-Peris, V. Garcia Pol, S. Gardiner, P. Gauzzi, G. Ge, N. Geffroy, B. Gelli, S. Gent, A. Ghosh, T. Giammaria, D. Gibin, I. Gil-Botella, A. Gioiosa, S. Giovannella, A. K. Giri, V. Giusti, D. Gnani, O. Gogota, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. S. Gomez Fajardo, D. Gonzalez-Diaz, J. Gonzalez-Santome, M. C. Goodman, S. Goswami, C. Gotti, J. Goudeau, C. Grace, E. Gramellini, R. Gran, P. Granger, C. Grant, D. R. Gratieri, G. Grauso, P. Green, S. Greenberg, W. C. Griffith, A. Gruber, K. Grzelak, L. Gu, W. Gu, V. Guarino, M. Guarise, R. Guenette, M. Guerzoni, D. Guffanti, A. Guglielmi, F. Y. Guo, A. Gupta, V. Gupta, G. Gurung, D. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, R. Hafeji, L. Hagaman, A. Hahn, J. Hakenmüller, A. Hambardzumyan, T. Hamernik, P. Hamilton, J. Hancock, M. Handley, F. Happacher, B. Harris, D. A. Harris, L. Harris, A. L. Hart, J. Hartnell, T. Hartnett, T. Hasegawa, C. M. Hasnip, K. Hassinin, R. Hatcher, S. Hawkins, J. Hays, M. He, A. Heavey, K. M. Heeger, A. Heindel, J. Heise, K. Heller, P. Hellmuth, L. Henderson, A. Hergenhan, J. Hernández, M. A. Hernandez Morquecho, K. Herner, V. Hewes, A. Higuera, K. Hildebrandt, A. Himmel, E. Hinkle, L.R. Hirsch, J. Ho, J. Hoefken Zink, J. Hoff, A. Holin, C. Hong, S. Horiuchi, G. A. Horton-Smith, R. Hosokawa, T. Houdy, B. Howard, I. Hristova, M. S. Hronek, Y. Hua, J. Huang, R.G. Huang, X. Huang, Z. Hulcher, A. Hussain, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, F. Imamoglu, G. Ingratta, A. Ioannisian, M. Ismerio Oliveira, C.M. Jackson, A. Jacobi, V. Jain, C. James, E. James, W. Jang, B. Jargowsky, D. Jena, I. Jentz, C. Jiang, J. Jiang, A. Jipa, J. H. Jo, F. R. Joaquim, A. M. Johnson, W. Johnson, C. Jollet, M. Joshi, N. Jovancevic, M. Judah, C. K. Jung, K. Y. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. C. Kaboth, I. Kadenko, O. Kalikulov, D. Kalra, M. Kandemir, S. Kar, C. Karagianni, G. Karagiorgi, G. Karaman, A. Karcher, Y. Karyotakis, S. P. Kasetti, L. Kashur, A. Kauther, N. Kazaryan, L. Ke, E. Kearns, P.T. Keener, A. Kelly, K.J. Kelly, R. Keloth, O. Kemularia, J. Kerby, Y. Kermaidic, W. Ketchum, S. H. Kettell, N. Khan, A. Khvedelidze, D. Kim, J. Kim, M. J. Kim, S. Kim, B. King, M. King, M. Kirby, A. Kish, J. Klein, J. Kleykamp, T. Kobilarcik, L. Koch, K. Koehler, L. W. Koerner, D. H. Koh, K. Kong, M. Kordosky, V. A. Kostelecký, I. Kotler, M. Kramer, F. Krennrich, T. Kroupova, S. Kubota, M. Kubu, V. A. Kudryavtsev, G. Kufatty, A. Kumar, J. Kumar, M. Kumar, P. Kumar, S. Kumaran, J. Kunzmann, V. Kus, T. Kutter, J. Kvasnicka, T. Labree, M. Lachat, T. Lackey, I. Lalău, A. Lambert, B. J. Land, C. E. Lane, N. Lane, K. Lang, M. Langstaff, F. Lanni, S. Lanzi, J. Larkin, P. Lasorak, D. Last, G. Laurenti, E. Lavaut, W. Lavrijsen, H. Lay, I. Lazanu, R. LaZur, M. Lazzaroni, S. Leardini, J. Learned, G. Lehmann Miotto, R. Lehnert, M. Leitner, H. Lemoine, D. Leon Silverio, L. M. Lepin, J.D. Lewis, J.-Y Li, S. W. Li, Y. Li, R. C. R. Lima, R. Lima, C. S. Lin, D. Lindebaum, S. Linden, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, M. Lkhagvadorj, S. Lockwitz, I. Lomidze, J.Lopez, I. López de Rego, N. López-March, A. Lopez Moreno, J. M. LoSecco, A. Lozano Sanchez, X.-G. Lu, K.B. Luk, X. Luo, G. Lupi, E. Luppi, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, A. Madorsky, S. Magill, C. Magueur, K. Mahn, A. Maio, N. Majeed, K. Majumdar, A. Malige, S. Mameli, M. Man, R. C. Mandujano, J. Maneira, S. Manly, K. Manolopoulos, M. Manrique Plata, S. Manthey Corchado, L. Manzanillas-Velez, E. Mao, M. Marchan, A. Marchionni, D. Marfatia, C. Mariani, J. Maricic, R. Marie, F. Marinho, A. D. Marino, T. Markiewicz, F. Das Chagas Marques, M. Marshak, C. M. Marshall, J. Marshall, J. Martin, M. Martin, L. Martina, J. Martín-Albo, D.A. Martinez Caicedo, M. Martinez-Casales, F. Martínez López, S. Martynenko, V. Mascagna, A. Mastbaum, M. Masud, F. Matichard, G. Matteucci, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, T. McAskill, N. McConkey, B. McConnell, K. S. McFarland, C. McGivern, C. McGrew, A. McNab, C. McNulty, J. Mead, L. Meazza, V. C. N. Meddage, A. Medhi, M. Mehmood, B. Mehta, P. Mehta, F. Mei, P. Melas, L. Mellet, T. C. D. Melo, O. Mena, D. P. Méndez, A. Menegolli, G. Meng, A. Mengarelli, A. C. E. A. Mercuri, A. Meregaglia, G. Merino, M. D. Messier, S. Metallo, W. Metcalf, M. Mewes, H. Meyer, T. Miao, J. Micallef, A. Miccoli, G. Michna, R. Milincic, F. Miller, G. Miller, W. Miller, A. Minotti, L. Miralles Verge, C. Mironov, S. Miscetti, P. Mishra, S. R. Mishra, D. Mladenov, I. Mocioiu, A. Mogan, P. S. Mohan, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, D. Montanino, L. M. Montaño Zetina, M. Mooney, A. F. Moor, M. Moore, Z. Moore, B. Moreira, D. Moreno, G. Moreno-Granados, O. Moreno-Palacios, L. Morescalchi, A. Morita, E. Motuk, C. A. Moura, W. Mu, L. Mualem, J. Mueller, M. Muether, A. Muir, Y. Mukhamejanov, A. Mukhamejanova, E. Muldoon, M. Mulhearn, D. Munford, L. J. Munteanu, H. Muramatsu, J. Muraz, M. Murphy, T. Murphy, A. Mytilinaki, J. Nachtman, Y. Nagai, S. Nagu, H. Nam, D. Naples, S. Narita, J. Nava, D. Navas-Nicolás, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, A. Nehm, J. K. Nelson, O. Neogi, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, D. Newmark, L. Nguyen, R. Nichol, F. J. Nicolas-Arnaldos, A. Nielsen, A. Nikolica, J. Nikolov, E. Niner, X. Ning, K. Nishimura, A. Norman, A. Norrick, F. Noto, P. Novella, A. Nowak, J. A. Nowak, M. Oberling, J. P. Ochoa-Ricoux, S. Oh, S.B. Oh, A. Olivier, T. Olson, Y. Onel, Y. Onishchuk, A. Oranday, G. P. Orebi Gann, A. I. R. Orimogunje, M. Osbiston, J. E. Ossa Sanchez, L. O'Sullivan, L. Otiniano Ormachea, L. Pagani, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, B. Pan, S. Pan, M. Panareo, P. Panda, V. Pandey, W. Panduro Vazquez, E. Pantic, V. Paolone, A. Papadopoulou, R. Papaleo, D. Papoulias, S. Paramesvaran, J. Park, J. Park, Y. Park, S. Parke, S. Parsa, M. Parvu, D. Pasciuto, S. Pascoli, L. Pasqualini, G. Patel, J. L. Paton, C. Patrick, L. Patrizii, R. B. Patterson, T. Patzak, A. Paudel, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, A. Peake, V. Pec, E. Pedreschi, S. J. M. Peeters, L. Pelegrina-Gutiérrez, W. Pellico, E. Pennacchio, A. Penzo, O. L. G. Peres, Y. F. Perez Gonzalez, L. Pérez-Molina, C. Pernas, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, M. Pfaff, V. Pia, G. M. Piacentino, L. Pickering, G. Piemonti, L. Pierini, F. Pietropaolo, M. Pimenta Sampaio, V.L.Pimentel, G. Pinaroli, S. Pincha, J. Pinchault, K. Pitts, P. Plesniak, K. Pletcher, K. Plows, C. Pollack, F. Polleri, T. Pollmann, F. Pompa, X. Pons, N. Poonthottathil, F. Poppi, J. Porter, L. G. Porto Paixão, M. Pozzato, R. Pradhan, L. Prais, T. Prakash, M. Prest, F. Psihas, D. Pugnere, D. Pullia, X. Qian, J. Quelin-Lechevranton, J. L. Raaf, V. Radeka, J. Rademacker, F. Raffaelli, A. Rafique, U. Rahaman, A. Rahe, S. Rajagopalan, M. Rajaoalisoa, I. Rakhno, L. Rakotondravohitra, M. A. Ralaikoto, L. Ralte, L. Ralte, M. A. Ramirez Delgado, B. Ramson, S. S. Randriamanampisoa, A. Rappoldi, G. Raselli, T. Rath, P. Ratoff, R. Raut, R. Ray, H. Razafinime, R. F. Razakamiandra, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, E. Renner, S. Repetto, S. Rescia, F. Resnati, J. V. Restrepo Laverde, C. Reynolds, S. Riboldi, C. Riccio, G. Riccobene, J. S. Ricol, M. Rigan, A. Rikalo, A. Ritchie-Yates, D. Rivera, A. Rivetti, A. Robert, E. Robles, A. Roche, M. Roda, D. Rodas Rodríguez, M. J. O. Rodrigues, J. Rodriguez Rondon, S. Rosauro-Alcaraz, P. Rosier, D. Ross, M. Rossella, M. Ross-Lonergan, N. Roy, P. Roy, C. Royon, C. Rubbia, D. Rudik, A. Ruggeri, G. Ruiz Ferreira, K. Rushiya, B. Russell, E. Sabater Andres, S. Sacerdoti, N. Saduyev, D. Sagar, S. Saha, S. K. Sahoo, N. Sahu, S. Sakhiyev, P. Sala, N. Sallin, G. Salmoria, S. Samanta, M. C. Sanchez, A. Sánchez-Castillo, P. Sanchez-Lucas, D. A. Sanders, S. Sanfilippo, G. Santoni, D. Santoro, N. Saoulidou, P. Sapienza, I. Sarcevic, I. Sarra, C. Sauer, L. Sauer, G. Savage, V. Savinov, A. Scanu, A. Scaramelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D.W. Schmitz, A. W. Schneider, K. Scholberg, A. Schroeder, A. Schukraft, B. Schuld, S. Schwartz, A. Segade, H. Segal, E. Segreto, A. Selyunin, D. Senadheera, C. R. Senise, J. Sensenig, S.H. Seo, D. Seppela, M. H. Shaevitz, P. Shanahan, P. Sharma, R. Kumar, S. Sharma Poudel, K. Shaw, T. Shaw, J. Shen, C. Shepherd-Themistocleous, J. Shi, W. Shi, S. Shin, S. Shivakoti, A. Shmakov, I. Shoemaker, D. Shooltz, R. Shrock, M. Siden, J. Silber, L. Simard, J. Sinclair, G. Sinev, Jaydip Singh, J. Singh, L. Singh, P. Singh, V. Singh, S. Singh Chauhan, R. Sipos, C. Sironneau, G. Sirri, K. Siyeon, K. Skarpaas, J. Smedley, J. Smith, R. S. Smith-Jones, J. Smolik, M. Smy, M. Snape, E. L. Snider, P. Snopok, M. Soares Nunes, H. Sobel, M. Soderberg, H. Sogarwal, C. J. Solano Salinas, S. Söldner-Rembold, N. Solomey, V. Solovov, W. E. Sondheim, T. Sonius, M. Sorbara, M. Sorel, J. Soto-Oton, A. Sousa, K. Soustruznik, D. Souza Correia, F. Spinella, J. Spitz, N. J. C. Spooner, D. Stalder, M. Stancari, L. Stanco, J. Steenis, R. Stein, H. M. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, T. Stokes, T. Strauss, L. Strigari, A. Stuart, W. Su, A. Surdo, L. Suter, A. Sutton, Y. Suvorov, R. Svoboda, S. K. Swain, C. Sweeney, B. Szczerbinska, A. M. Szelc, A. Sztuc, A. Taffara, N. Talukdar, J. Tamara, H. A. Tanaka, S. Tang, N. Taniuchi, A. M. Tapia Casanova, A. Tapper, S. Tariq, E. Tatar, R. Tayloe, A. M. Teklu, K. Tellez Giron Flores, J. Tena Vidal, P. Tennessen, M. Tenti, K. Terao, F. Terranova, S. Teruel, G. Testera, A. Thea, S. Thomas, A. Thompson, C. Thorpe, M. Timalsina, S. C. Timm, E. Tiras, V. Tishchenko, S. Tiwari, N. Todorović, L. Tomassetti, A. Tonazzo, L. Tong, D. Torbunov, D. Torres Muñoz, M. Torti, M. Tortola, Y. Torun, N. Tosi, D. Totani, M. Toups, C. Touramanis, V. Trabattoni, D. Tran, J. Trevor, E. Triller, S. Trilov, D. Trotta, W. H. Trzaska, Y. Tsai, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Z. Tu, S. Tufanli, C. Tunnell, S. Turnberg, J. Turner, M. Tuzi, M. Tzanov, M. A. Uchida, J. Ureña González, J. Urheim, T. Usher, H. Utaegbulam, S. Uzunyan, M. R. Vagins, P. Vahle, G. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. F. Valle, R. Van Berg, D. V. Forero, P. Van Gemmeren, A. Vannozzi, M. Van Nuland-Troost, F. Varanini, N. Vaughan, K. Vaziri, A. Vázquez-Ramos, J. Vega, J. Vences, S. Ventura, A. Verdugo, M. Verzocchi, J. Vesic, K. Vetter, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, E. Villa, S. Viola, B. Viren, G. V. Stenico, R. Vizarreta, A. P. Vizcaya Hernandez, S. Vlachos, G. Vorobyev, Q. Vuong, A. V. Waldron, L. Walker, H. Wallace, M. Wallach, J. Walsh, T. Walton, L. Wan, B. Wang, J. Wang, L. Wang, M.H.L.S. Wang, X. Wang, Y. Wang, Y. Wang, D. Warner, L. Warsame, M.O. Wascko, D. Waters, A. Watson, K. Wawrowska, A. Weber, C. M. Weber, M. Weber, H. Wei, A. Weinstein, S. Westerdale, M. Wetstein, Q. Weyrich, K. Whalen, A.J. White, L. H. Whitehead, D. Whittington, F. Wieler, J. Wilhelmi, M. J. Wilking, A. Wilkinson, C. Wilkinson, R. J. Wilson, P. Winter, J. Wolcott, J. Wolfs, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, M. Wright, M. Wrobel, S. Wu, Z. Wu, J. Wyenberg, B. M. Wynne, Y. Xiao, Z. Xie, D. Xing, B. Yaeggy, A. Yahaya, N. Yahlali, E. Yandel, G. Yang, J. Yang, T. Yang, A. Yankelevich, L. Yates, U. Yevarouskaya, K. Yonehara, T. Young, B. Yu, H. Yu, J. Yu, K. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. P. Zeller, J. Zennamo, J. Zettlemoyer, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, L. Zhao, M. Zhao, K. Zhu, E. D. Zimmerman, S. Zucchelli, A. Zummo, V. Zutshi, R. Zwaska

Fluid Dynamics

Intermittency-Driven Turbulence Cascade Memory Extends the Markov-Einstein Coherence Length Beyond the Canonical Estimate

Y. Sungtaek Ju

Using direct numerical simulation of forced isotropic turbulence at $\text{Re}_\lambda \approx 1300$ and $\approx 433$, together with two independent Markov-by-construction null surrogates, we measure the Markov–Einstein coherence length of the turbulent energy cascade to be $\Delta r \approx 3.2$-$3.6$ in log-scale cascade coordinates, approximately three times the canonical estimate $\Delta r \approx 1$. Stratifying the gap-scan test by local dissipation intensity and by increment amplitude reveals that intermittent events carry $\Delta r \approx 3$-$4$, while at mid-inertial-range scales the quiescent cascade recovers $\Delta r \approx 1.0$-$1.4$, consistent with the canonical value. Near the dissipation range this pattern reverses: bulk dynamics carry more memory than extreme events, consistent with the spectral bottleneck. The excess memory is internal to the inertial range and Reynolds-number-independent over $\text{Re}_\lambda \approx 433$-$1300$. These findings indicate that the Markov approximation underlying the cascade Fokker-Planck equation and fluctuation-theorem analyses is substantially more restrictive than previously assumed, and that a non-Markovian correction, informed by the amplitude-dependent memory structure identified here, is needed for the intermittent component of the cascade.
Read the full abstract

Instrumentation and Detectors

Systematic Investigation of Acceptor Removal in HPK LGADs with Modified Gain Layers

Yua Murayama, Mahiro Kobayashi, Tomoka Imamura et al. (+7 more)

Low-Gain Avalanche Diodes (LGADs) are fast silicon sensors with internal charge multiplication and are key candidates for precision timing layers in future high-energy hadron colliders. Their operation in harsh radiation environments, however, is limited by acceptor removal in the gain layer, which reduces the active acceptor concentration and degrades the internal electric field required for avalanche multiplication. Improving the radiation tolerance of the gain layer is therefore essential for future 4D tracking applications. In this work, we investigated several LGAD prototypes produced in collaboration with Hamamatsu Photonics K.K. (HPK), featuring modified gain-layer designs, including oxygen-modified, carbon-implanted, and boron–phosphorus compensated structures. The sensors were studied after proton and reactor-neutron irradiation. Radiation tolerance was characterized using the acceptor-removal coefficient extracted from IV measurements and the operation voltage required to recover the timing performance after irradiation. The results show that carbon implantation is the only approach among those studied here that provides a clear improvement in radiation tolerance. In contrast, neither oxygen-related modification, including the Partially Activated Boron (PAB) approach, nor gain-layer compensation alone yields a significant improvement, and the compensated carbon-implanted structure shows no clear advantage over the carbon-only case. In addition, the acceptor-removal coefficient is found to depend on the irradiation particle type and energy.
Read the full abstract

All authors Yua Murayama, Mahiro Kobayashi, Tomoka Imamura, Koji Nakamura, Issei Horikoshi, Koji Sato, Masato Terada, Minoru Hirose, Tatsuya Masubuchi, Sayuka Kita

Computational Physics

Learning subgrid interfacial area in two-phase flows with regime-dependent inductive biases

Anirban Bhattacharjee, Luis H. Hatashita and Suhas S. Jain

The reliability of machine learning in multiscale physical systems depends on how physical structure is embedded into the learning process. We investigate this in the context of turbulent multiphase flows, focusing on the prediction of subgrid interfacial area density, a key quantity governing interphase transport that remains unresolved in large-eddy simulations. In this work, we develop and evaluate two machine learning subgrid closure models to predict the three-dimensional subgrid interfacial area density: a purely data-driven 3D encoder-decoder network, and a physics-constrained variant regularized by a fractal geometric prior. Across a range of Weber numbers, the physics-based model improves predictive accuracy, reduces error variance, and suppresses nonphysical artifacts relative to purely data-driven approaches. We also show that these gains are regime-dependent: the embedded inductive bias enhances generalization in corrugation-dominated regimes where its underlying assumptions hold, but becomes ineffective in fragmentation-dominated regimes characterized by topology change and droplet breakup. These results reveal a broader principle for scientific machine learning: the utility of physics-informed models depends not only on the presence of inductive bias, but on its alignment with the governing physical regime. This suggests a path toward regime-aware learning frameworks for modeling of complex multiscale systems.
Read the full abstract

Biological Physics

An in situ self-adaptive hydrogel coating enables seamless neural interfaces via okra mucilage polysaccharide and {\alpha}-helical peptide amphiphiles co-assembly

Tenglong Luo, Yiqing Guo, Shanshan Su et al. (+10 more)

Long-term stability of neural interfaces is frequently compromised by mechanical mismatch and chronic neuroinflammation, often leading to electrode detachment and signal failure. While hydrogel coatings offer a solution, conventional designs typically rely on exogenous conductive fillers that can sacrifice mechanical flexibility or induce toxicity. Here, we report on a soft neural interface based on the supramolecular co-assembly of a renewable natural polysaccharide, okra mucilage polysaccharide (OMP), and an {\alpha}-helical peptide amphiphiles (APA). The resulting OMP-APA hydrogel (OP gel) exhibits environment-responsive enhancements in bioadhesion and charge-transport capability triggered by physiological pH and electrical stimulation. These properties arise from intrinsic, stimulus-responsive alterations in fibre architecture and orientation, eliminating the need for conductive fillers. Leveraging interfacial liquid-liquid phase separation, we demonstrate the in situ coating of ultra-thin OP-gel coating onto carbon fibre electrodes (CFE). The OP-gel-coated electrodes (OP-CFE) significantly mitigate foreign body responses and glial scarring, enabling stable, high-quality neural recordings in a mouse cortical in vivo model. Our findings provide a versatile strategy for constructing seamless, multifunctional bio-interfaces through supramolecular co-assembly, with broad implications for advancing neural prosthetics and neuroscience research.
Read the full abstract

All authors Tenglong Luo, Yiqing Guo, Shanshan Su, Qiaoyu Yang, Wen Deng, Zhangfeng Huang, Zhiquan Yu, Dawen Yu, Yubin Ke, Hua Yang, Jiecong Wang, Dewen Zhang, Yuanhao Wu

Fluid Dynamics

Multi-scale Dynamic Wake Modeling and Prediction of Floating Offshore Wind Turbines via Physics-Informed Neural Networks and Fourier Neural Operators

Guodan Dong, Jianhua Qin and Chang Xu

Multi-scale dynamic wake modeling and prediction are essential for the real-time control and optimization of floating offshore wind turbines (FOWTs). In this study, wakes of FOWTs under coupled surge and pitch motions across a range of Strouhal numbers (St), which can induce wake meandering, are modeled via two novel deep-learning frameworks: physics-informed neural networks (PINNs) and Fourier neural operators (FNOs). The high-fidelity dataset is obtained from large-eddy simulations with the actuator line model (LES-AL). The results demonstrate that the dominant large-scale dynamic structures, such as meandering, can be well modeled by both frameworks; however, FNOs exhibit significant advantages over the PINN model in terms of efficiency (8-fold computational speedup and 40-fold faster convergence), long-term predictive capability, and multi-scale coherent structural fidelity. Furthermore, the wakes predicted by the PINN model exhibit a smoothing effect that limits the resolution of high-frequency coherent structures and underestimates turbulent fluctuations in both the wake center and half-width. Spectral analysis reveals that FNOs resolve the primary meandering frequency (where Stp denotes the frequency induced by the coupled surge and pitch motions), its corresponding higher-order harmonics (2Stp, 3Stp), and the energy cascade. In contrast, the energy cascade in the PINN predictions dissipates more rapidly in the high-frequency regime (St > 1.0). Additionally, the pre-multiplied power spectral density indicates that the energy contained in meandering and the corresponding harmonic frequencies modeled by PINNs is relatively low compared to that in CFD and FNOs. These findings suggest that FNOs are promising for the high-fidelity, real-time modeling of FOWT wakes.
Read the full abstract

Instrumentation and Detectors

Development and Performance Study of Vertical GaN $\alpha$-Particle Detector with High Energy Resolution

Minjie Ye, Yuzi Yang, Jiangtao Wei et al. (+11 more)

High-energy-resolution GaN $\alpha$-particle detectors have significant potential for space radiation, nuclear instrumentation, and harsh-environment applications. However, existing GaN $\alpha$-particle detectors still face several key challenges, including reducing the dead-layer thickness, suppressing leakage current under high reverse bias, improving energy resolution, and clarifying the physical mechanism underlying the low-energy tail phenomenon. This study presents a vertical homoepitaxial GaN $\alpha$-particle detector integrating a 20-nm ultrathin dead layer and a guard-ring structure. The detector exhibits an ultralow leakage current of 2.195 nA at -200 V and an intrinsic energy resolution of 2.69% with a charge collection efficiency (CCE) of 95.9% at -260 V. More importantly, this work demonstrates for the first time through Geant4 simulations that depletion-width nonuniformity is the dominant source of partial energy leakage, leading to an extended low-energy tail in the energy spectrum. We establish a depletion-width nonuniformity model and observe good agreement between simulation and experiment. This finding provides practical guidance for the design and optimization of high-performance GaN-based radiation detectors.
Read the full abstract

All authors Minjie Ye, Yuzi Yang, Jiangtao Wei, Weilong Qin, Hao Hong, Dong Han, Jianping Ni, Zhiyi Liu, Po-Chung Huang, Cheng-Chang Yu, Chao-Yi Fang, Entsai Lin, Zewen Liu, Shaomin Chen

Accelerator Physics

High Harmonic Radiation from a Low-K Biharmonic Planar Undulator

Sihong Liu and Bocheng Jiang

High harmonic generation by an undulator is a key issue for extending the photon energy range of synchrotron light sources. In this work, we propose a biharmonic planar undulator operating in the low-K regime (K<1) to enhance high-harmonic radiation. By superimposing a 1/3 subharmonic undulator field onto a short-period superconducting undulator, a biharmonic undulator is formed. The on-axis intensities of the 5th and 7th harmonics are significantly enhanced, corresponding to radiation near the 2nd harmonic of the short-period superconducting undulator. The results are confirmed by both theoretical analysis and numerical simulations using SPECTRA. It shows that the biharmonic configuration effectively overcomes the limitations of low-K undulators for high harmonic generation. In this study, reasonable undulator parameters are selected with full consideration of technical challenges. The simulation indicates that an unprecedented photon flux in the 16-22 keV energy range can be achieved with a 3.5 GeV beam, offering a promising approach for high brightness, short-wavelength synchrotron radiation.
Read the full abstract

Sunday 26 April

Computational Physics

Crystal Fractional Graph Neural Network for Energy Prediction of High-Entropy Alloys

Takanori Kotama and Yang Huang

High-entropy alloys (HEAs) have attracted growing attention for their exceptional mechanical and thermal properties arising from complex atomic configurations. In this paper, we propose crystal fractional graph neural network for predicting the energy of high-entropy alloys by explicitly integrating both local atomic environments and global compositional information. The model consists of three components: a crystal graph neural network, which employs graph attention network layers to learn local interactions among 16 on-site atoms within the crystal lattice; fractional neural network, a fully connected network that embeds the global fraction of constituent elements; and feature fusion neural network, which fuses the outputs of the two submodels to predict the total crystal energy. We train the model on a dataset of 1,049 crystal structures and validate it on 198 quaternary structures, optimizing all hyperparameters via Optuna. Our results show that our model achieves an RMSE comparable to first-principles calculations and maintains high accuracy even for low-energy configurations. However, the model exhibits limitations in handling large crystal cells, which we aim to address in future work to extend its applicability to more complex systems.
Read the full abstract

Medical Physics · Cross-listed from eess.IV

A Coupled Fourth Order Telegraph Diffusion Framework Using Grayscale Indicators for Image Despeckling

Manish Kumar and Rajendra K. Ray

Speckle noise severely limits the quality of images acquired from coherent imaging systems such as Synthetic Aperture Radar (SAR) and medical ultrasound. Traditional second-order PDE-based despeckling approaches, although popular, often introduce staircase artifacts and blur fine details. To overcome these limitations, we present a nonlinear, fourth-order coupled hyperbolic-parabolic PDE model that effectively reduces noise while preserving the structure. The framework consists of two evolution equations: one governing fourth-order diffusion for effective speckle reduction and smooth intensity transitions, and another refining an edge indicator to protect textures and structural features. The diffusion coefficient is adaptively constructed using both the image intensity variable u and a grayscale-based indicator function, ensuring structure-aware denoising while avoiding blocky artifacts and preserving fine details. We also prove the existence of a weak solution to the proposed model by applying Schauder fixed-point theorem. A finite-difference scheme with Gauss Seidel iteration is employed for efficient implementation. We compare the proposed model with the existing coupled second-order PDE model (HPCPDE) and the fourth-order telegraph diffusion model (TDFM). The results show that our model consistently outperforms these approaches. Experiments on standard grayscale images, real SAR and ultrasound data, as well as speckle-corrupted color images, demonstrate that the proposed method achieves superior performance over conventional PDE-based techniques in terms of PSNR, MSSIM, and Speckle Index.
Read the full abstract

Fluid Dynamics · Cross-listed from math.NA

Mode-realigned pointwise interpolation (MRPWI) for efficient POD-Galerkin parametric reduced-order models

Lei Du and Shengqi Zhang

As a cornerstone of reduced-order modeling, the POD-Galerkin framework has garnered widespread attention and remains one of the most widely adopted approaches. Constructing POD-Galerkin PROMs involves integrating this framework with advanced interpolation techniques to obtain POD modes at target (unseen) parameters. While Grassmann manifold interpolation (GMI) serves as an accurate baseline, mode-realigned pointwise interpolation (MRPWI) is proposed to develop highly efficient PROMs that maintain comparable accuracy. Notably, the MRPWI employs a two-step mode realignment procedure, consisting of sign alignment and rotation alignment, to effectively synchronize the POD modes. Demonstration and evaluation of the constructed POD-Galerkin PROMs are conducted by examining flow over a cylinder. These models exhibit high fidelity in comparison to direct numerical simulation and standard POD-Galerkin ROMs. PROMs constructed via MRPWI achieve accuracy comparable to those using GMI, while providing significantly higher computational efficiency.
Read the full abstract

Classical Physics

The Inverse Cube Force Law

John C. Baez

Newton's Principia is famous for its investigations of the inverse square force law for gravity. But in this book Newton also did something that remained little-known until fairly recently. He figured out what kind of central force exerted upon a particle can rescale its angular velocity by a constant factor without affecting its radial motion. This turns out to be a force obeying an inverse cube law! Here we discuss this and some other interesting features of the inverse cube force law.
Read the full abstract

General Physics

Higgs and Yukawa Structure in a Clifford Algebra Model with Three Generations and $S_3$ Family Symmetry

Niels Gresnigt

We construct the Higgs and Yukawa sectors as a structural completion of an algebraic three-generation model based on the complex Clifford algebra $\mathbb{C}\ell(10)$ with an intrinsic $S_3$ family symmetry. This addresses a common limitation of algebraic frameworks, in which Standard Model fermion multiplets and gauge symmetries may be described naturally, while the Higgs and Yukawa sectors remain less developed or absent. In the present framework, three algebraically distinguished fermion sectors are permuted by $S_3$, while the Standard Model gauge generators remain generation-independent. Higgs components are realised as right-action operators mapping weak-doublet fermion sectors into the corresponding weak-singlet sectors, and Yukawa coefficients are extracted using a Hilbert–Schmidt trace pairing. This yields two first-generation Higgs doublets with electroweak quantum numbers $(1,2,-1)$ and $(1,2,+1)$ under $SU(3)_C \times SU(2)_L \times U(1)_Y$, together with a Type-II-like separation between down-type and up-type Yukawa channels. Acting with the order-three family generator then generates a family-resolved Higgs sector organised into cyclic $S_3$ orbits. In the cyclically averaged Higgs limit, the Type-II-like Yukawa selection rule is preserved, while the generation-space Yukawa matrix is fixed algebraically and is non-diagonal in the algebraic generation basis. Under the usual implementation of electroweak symmetry breaking, the neutral Higgs couplings are aligned with the corresponding mass matrices, so tree-level flavour-changing neutral currents are not expected in this limit. The result is a constrained algebraic starting point for future $S_3$-breaking flavour phenomenology.
Read the full abstract

Fluid Dynamics

Improved global stability bounds for two-dimensional plane Poiseuille flow

Vicente Iligaray, Danilo Aballay and Federico Fuentes

This work provides new lower bounds on the global (nonlinear) stability limit of pressure-driven two-dimensional plane Poiseuille flow, improving on the energy stability limit, $Re_E$, originally computed by Orr in 1907. Using a computer we carefully construct quartic Lyapunov functionals of the velocity perturbations about the laminar profile, which certify the nonlinear stability of the flow to arbitrary perturbations. The formulation combines a decomposition of the velocity into finitely many energy eigenmodes, referred to as a 'mode set', and an infinite-dimensional 'tail', together with explicit bounds that recast the Lyapunov inequality conditions as semidefinite programs, whose feasibility is tested. Over the streamwise lengths considered, the certified stability limit exceeds the classical energy bound. In particular, at the critical energy-stable streamwise length, where $Re_E\approx 87.59$, the flow is found to be globally stable up to $Re \approx 106.8$ (representing a $22\%$ improvement). Various modestly-sized mode sets, capable of capturing sufficient features of the nonlinear dynamics of energy growth and subsequent decay, are proposed and found to be successful in producing improved bounds, with the simplest one involving only five modes.
Read the full abstract

Plasma Physics

Efficient Generation of Neutrons Based on Ultrashort Laser-driven Direct Acceleration in Microwire-Array Targets

Kaiyuan Feng, Debin Zou, Bo Cui et al. (+17 more)

We report on an experimental demonstration of efficient neutron generation based on direct laser acceleration in microwire-array targets irradiated by ultrashort (tens of femtoseconds) laser pulses. The optimal array period was identified, at which the maximum proton energy and the number of protons with energies exceeding $1~\mathrm{MeV}$ were significantly increased. Using a $1~\mathrm{PW}$, $\sim25~\mathrm{fs}$ laser at a moderate intensity of $\sim10^{20}~\mathrm{W/cm^2}$, a high neutron yield of up to $(8.33\pm0.84)\times10^{6}~\mathrm{n/sr/J}$ was detected from the LiD converter via $^7\mathrm{Li}(p,n)$ and $\mathrm{D}(p,n+p)$ nuclear reactions. Self-consistent integrated simulations reproduced the experimental results and predicted that with a Be converter, a forward pulsed neutron source with an unprecedented yield per joule of $3.67\times10^{7}~\mathrm{n/sr/J}$ can be obtained under identical laser conditions. This type of neutron source is favorable for applications that require a high repetition rate utilizing compact and economical laser systems.
Read the full abstract

All authors Kaiyuan Feng, Debin Zou, Bo Cui, Shukai He, Yingzi Dai, Wei Qi, Jinlong Luo, Jie Feng, Xinyan Li, Zehao Chen, Lixiang Hu, Chengyu Qin, Guobo Zhang, Hui Zhang, Zhigang Deng, Xiaohu Yang, Fuqiu Shao, Liangliang Ji, Weiming Zhou, Tongpu Yu

Chemical Physics

Spectral structure and controlled energy linearization of Feshbach effective Hamiltonians in a molecular quantum quench

Georgii V. D'yakonov

We establish spectral conditions under which a first-order energy linearization of a projected Feshbach Hamiltonian is controlled. When the support of the induced self-energy spectral measure lies entirely above or below the target energy window, the self-energy curvature and linearization remainder have fixed sign in the semidefinite (Löwner) order. The remainder then decreases monotonically under model-space enlargement by complete complementary-space spectral subspaces, and the minimax linearization energy is determined by the endpoint norms. Far-separated asymptotics and the near-boundary divergence caused by an approaching pole are obtained explicitly. The theory is validated by a numerically exact sudden-quench calculation for the two-electron system $HT$ -> $^3HeH^+$: all 56 nontrivially coupled basis-geometry cases have support separated above the target window, while seven cc-pVTZ cases are exactly decoupled by construction and serve as numerical control cases. The same remainder controls the projected resolvent and, through source dressing, the full prepared-state response, with resolvent amplification governing the near-pole sensitivity. These results provide a practical criterion for controlled downfolding in molecular electronic structure and for final-state analyses in neutrino-mass experiments.
Read the full abstract

Computational Physics · Cross-listed from math.NA

A positivity preserving and entropy stable nodal discontinuous Galerkin scheme for ideal MHD

Yue Wu and Chi-Wang Shu

Numerically solving magnetohydrodynamic (MHD) equations faces many challenges: avoiding divergence error, maintaining positivity, and satisfying entropy conditions. Among discontinuous Galerkin (DG) schemes, there has been a modal version that is locally divergence-free and positivity preserving and a nodal version that is semi-discretely entropy stable. In this work, we develop a DG scheme that combines the advantages of these two and solves all the three challenges. The key ingredients that bring these two schemes together are an HLL numerical flux with entropy stable signal speed estimates and a locally divergence-free projection. To handle problems with strong shocks, the essentially oscillation-free damping is applied. Various numerical experiments verify the accuracy and robustness of our method.
Read the full abstract

Optics

Syncopated Bessel beams

Irán Ramos-Prieto, Ulises Ruíz, Israel Julián-Macías et al. (+3 more)

We introduce the syncopated Bessel beam, a new class of exact solutions to the paraxial equation obtained by means of a sinusoidal modulation of the azimuthal phase at the source. This modulation imposes a phase rhythm that deliberately breaks the azimuthal symmetry, analogous to musical syncopation, and triggers a topological transformation that deflects the propagation trajectory and shifts the beam's center of symmetry off the optical axis, while preserving its self-scaling invariance that can be explained by the Madelung-Bohm formalism. An exact analytical framework, supported by experimental validation, reveals the intrinsic structural robustness and preservation of topological properties through propagation.
Read the full abstract

All authors Irán Ramos-Prieto, Ulises Ruíz, Israel Julián-Macías, Francisco Soto-Eguibar, David Sánchez-de-la-Llave, Héctor M. Moya-Cessa

Atomic Physics · Cross-listed from hep-ph

Searching for ultralight bosons with Josephson junction interferometry

Djuna Croon and Tanmay Kumar Poddar

Ultralight bosons sourced by macroscopic objects can generate long-range spin-independent and spin-dependent potentials that are accessible to precision interferometry. Such potentials induce phase shifts in Josephson junctions, detectable through precision current measurements. We propose three experimental scenarios to probe photophilic scalar interactions, Lorentz-violating scalar-mediated interactions, and axion-mediated monopole-dipole interactions, depending on the nature (unpolarized or polarized) of the source. The proposed setups provide sensitivities to novel mixed couplings that are largely unconstrained by existing bounds and enables the exploration of new forces at centimeter to micrometer length scales.
Read the full abstract

Fluid Dynamics

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics

Ashwin Suriyanarayanan, Dibyajyoti Chakraborty and Romit Maulik

The differentiable physics paradigm may be leveraged as an a-posteriori approach for discovering turbulence closure models by embedding a neural network parameterization directly inside the solver and optimizing it given potentially sparse target data. This addresses a key limitation of a-priori learning where direct numerical simulation (DNS) data is used to approximate the subgrid stress with the assumption of a low-pass filter. Closures trained in this a-priori manner frequently lead to unstable deployments due to the mismatch between the assumed filter and the effect of numerical discretizations and coarse-graining. In comparison, while typically stable during deployment, a-posteriori learning incurs high computational costs due to the need to backpropagate through a large eddy simulation (LES) solver. Furthermore, a-posteriori methods are challenging to apply broadly since they require significant modification of existing solvers. Finally, both approaches are limited when generalization is desired across different numerical schemes with their implicit filtering characteristics. In this work, we present a deep-learning approach for turbulence closure modeling built on the continuous data assimilation framework. Our approach enables the a-priori training of closures using sparsely observed DNS data without modifying or differentiating through the LES solver, while preserving stability during deployment for the recovery of invariant statistics. We focus on the model's ability to adapt to different discretizations by explicitly conditioning it on the numerical scheme. We use two- and three-dimensional canonical cases to test our framework and show that the learned correction systematically tracks the discretization error of the coarse solver.
Read the full abstract

Plasma Physics · Cross-listed from astro-ph.HE

Alfven-winged pulsar

Maxim Lyutikov

Detecting possible electromagnetic precursors to the gravitational signal from merging compact objects is challenging, but it can reveal intricate physical properties of the merging stars through their gravitational and electromagnetic interactions. We demonstrate, using 3D Particle-In-Cell simulations, that a neutron star moving through the magnetosphere of a merging companion generates a complicated system of dissipative currents, a relativistic analogue of planetary Alfven wings. Generated electric currents carry a large fraction of the electromagnetic power intersected by the neutron star. These currents may lead to the generation of beamed, pulsar-like coherent radio and high-energy emission. Orbital modulation will produce a nearly periodic signal, an Alfven-winged pulsar.
Read the full abstract