Floquet engineering, the control of quantum systems using periodic driving, is an old concept in condensed matter physics dating back to ideas such as the inverse Faraday effect. However, there is a renewed interest in this concept owing to ( a) the rapid developments in laser and ultrafast spectroscopy techniques, ( b) discovery and understanding of various “quantum materials” hosting interesting exotic quantum properties, and ( c) communication with different areas of physics such as artificial matter and nonequilibrium quantum statistical physics. Here, starting from a nontechnical introduction with emphasis on the Floquet picture and effective Hamiltonians, we review the recent applications of Floquet engineering in ultrafast, nonlinear phenomena in the solid state. In particular, Floquet topological states and their application to ultrafast spintronics and strongly correlated electron systems are overviewed.
The invention of the scanning tunneling microscope was a singularity event in the field of surface science and condensed matter physics. The ability to visualize individual atoms in an atomic structure was a huge step forward in experimental development, one for which the inventors were awarded the Nobel Prize in Physics in 1986. While a groundbreaking development, the Scanning Tunneling Microscope is conceptually simple device which exploits both quantum mechanics and conventional mechanics in its operation. This paper will explore the scanning tunneling microscope, with a brief review of the history behind the development, then move on to discuss the physics and the art behind the use of STM, important developments made since its discovery, and where this technology is available to UTK students in the greater Knoxville area.
IntroductionUpright radiotherapy has gained increasing attention in recent years due to its potential advantages, including lower room costs, improved patient comfort, and possible anatomical/physiological benefits. In this pre-clinical study, we assess the feasibility of implementing upright radiotherapy for breast cancer by evaluating beam access, inframammary skin fold size, field length, and set-up comfort across a range of upright positions.Materials and methodsTwenty-one healthy participants were enrolled in the study. Each participant was set-up on an upright patient positioning system (Eve from Leo Cancer Care Ltd) with three different arm positions (arms up, arms down, and arms behind). Setups were conducted both without a bra (topless) and with the Chabner XRT Bra for Radiotherapy, an indexable bra designed for immobilisation during treatment. Optical surface scans were acquired, and the external contour of the breast was used to approximate a clinical target volume. Beam access was evaluated in multiple regions of the breast while field size and the ISF were measured for the different positions. Participants rated their comfort using a survey. ArUco markers were employed to evaluate ease of setup by measuring the unaided reproducibility of each upright position.ResultsThe ISF was smallest in the arms-up position when participants wore the Chabner XRT Bra. Beam access for photon treatment planning was assessed for 15 participants. Arm position significantly affected photon beam angle flexibility; with arms down, participants had fewer available angles for beam angle entry. The Chabner XRT Bra consistently reduced the required field length across all positions. Participants could typically reposition themselves with sub-centimetre accuracy, without any assistance from the study team.ConclusionOverall, this study demonstrates the feasibility of delivering breast radiotherapy in the upright position for both photon and proton treatments. The arms-up position was preferable in terms of photon beam access. While photon beam access was limited for the arms down position, it remained achievable in the majority of cases. The use of the Chabner XRT Bra significantly reduced the size of the ISF, which may help lower skin toxicity, as well as the field length required for treatment, potentially decreasing unwanted lung dose.
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Abstract Matrix geometric means between two positive definite matrices can be defined from distinct perspectives—as solutions to certain nonlinear systems of equations, as points along geodesics in Riemannian geometry, and as solutions to certain optimisation problems. We devise quantum subroutines for the matrix geometric means, and construct solutions to the algebraic Riccati equation—an important class of nonlinear systems of equations appearing in machine learning, optimal control, estimation, and filtering. Using these subroutines, we present a new class of quantum learning algorithms, for both classical and quantum data, called quantum geometric mean metric learning, for weakly supervised learning and anomaly detection. The subroutines are also useful for estimating geometric Rényi relative entropies and the Uhlmann fidelity, in particular achieving optimal dependence on precision for the Uhlmann and Matsumoto fidelities. Finally, we provide a BQP-complete problem based on matrix geometric means that can be solved by our subroutines.
U. de Freitas Carneiro da Graça, G. Gil da Silveira, C. Jahnke
et al.
The Brazilian High-Energy Physics (HEP) community has expanded remarkably since its first involvement at CERN and Fermilab in the 1980s. Its recent organization under the Brazilian Network for High-Energy Physics (RENAFAE), since 2008, has further strengthened its scientific and technological goals, particularly in detector instrumentation, computing, and industry partnerships. In 2024, Brazil became an Associate Member State of CERN, opening new opportunities for deeper engagement in accelerator and detector R&D. This input to the 2026 update of the European Strategy for Particle Physics highlights Brazil's current participation in LHC experiments as well as ongoing developments in detector and accelerator technology, and details the community's view towards future colliders. The potential for expanded scientific and industrial collaborations between Brazil and CERN is also discussed.
Abstract Extreme winds associated with tropical cyclones (TCs) can cause significant loss of life and economic damage globally, highlighting the need for accurate, high‐resolution modeling and forecasting for wind. However, due to their coarse horizontal resolution, most global climate and weather models suffer from chronic underprediction of TC wind speeds, limiting their use for impact analysis and energy modeling. In this study, we introduce a cascading deep learning framework designed to downscale high‐resolution TC wind fields given low‐resolution data. Our approach maps 85 TC events from ERA5 data (0.25° resolution) to high‐resolution (0.05° resolution) observations at 6‐hr intervals. The initial component is a debiasing neural network designed to model accurate wind speed observations using ERA5 data. The second component employs a generative super‐resolution strategy based on a conditional denoising diffusion probabilistic model (DDPM) to enhance the spatial resolution and to produce ensemble estimates. The model is able to accurately model intensity and produce realistic radial profiles and fine‐scale spatial structures of wind fields, with a percentage mean bias of −3.74% compared to the high‐resolution observations. Our downscaling framework enables the prediction of high‐resolution wind fields using widely available low‐resolution and intensity wind data, allowing for the modeling of past events and the assessment of future TC risks.
Geophysics. Cosmic physics, Information technology
CO<sub>2</sub> is one of the primary greenhouse gases impacting global climate change, making it crucial to understand the spatiotemporal variations of CO<sub>2</sub>. Currently, commonly used satellites serve as the primary means of CO<sub>2</sub> observation, but they often suffer from striping issues and fail to achieve complete coverage. This paper proposes a method for constructing a comprehensive high-spatiotemporal-resolution XCO<sub>2</sub> dataset based on multiple auxiliary data sources and satellite observations, utilizing multiple simple deep neural network (DNN) models. Global validation results against ground-based TCCON data demonstrate the excellent accuracy of the constructed XCO<sub>2</sub> dataset (R is 0.94, RMSE is 0.98 ppm). Using this method, we analyze the spatiotemporal variations of CO<sub>2</sub> in China and its surroundings (region: 0°–60° N, 70°–140° E) from 2019 to 2020. The gapless and fine-scale CO<sub>2</sub> generation method enhances people’s understanding of CO<sub>2</sub> spatiotemporal variations, supporting carbon-related research.
Jinlong Liu, Shubhangi Gupta, Jonny Rutqvist
et al.
Abstract We conducted two‐dimensional numerical simulations to investigate the mechanisms underlying the strong spatiotemporal correlation observed between submarine landslides and gas hydrate dissociation due to glacial sea‐level drops. Our results suggest that potential plastic deformation or slip could occur at localized and small scales in the shallow‐water portion of the gas hydrate stability zone (GHSZ). This shallow‐water portion of the GHSZ typically lies within the area enclosed by three points: the BGHSZ–seafloor intersection, the seafloor at ∼600 m below sea level (mbsl), and the base of the GHSZ (BGHSZ) at ∼1,050 mbsl in low‐latitude regions. The deep BGHSZ (>1,050 mbsl) could not slip; therefore, the entire BGHSZ was not a complete slip surface. Glacial hydrate dissociation alone is unlikely to cause large‐scale submarine landslides. Observed deep‐water (much greater than 600 mbsl) turbidites containing geochemical evidence of glacial hydrate dissociation potentially formed from erosion or detachment in the GHSZ pinch‐out zone.
The article is devoted to electromagnetic phenomena in the atmosphere. The set of experimental data on the thunderstorm activity is analyzed. It helps to identify a possible physical mechanism of lightning flashes. This mechanism can involve the formation of metallic bonds in thunderclouds. The analysis of the problem is performed at a microphysical level within the framework of quantum mechanics. The mechanism of appearance of metallic conductivity includes the resonant tunneling of electrons along resonance-percolation trajectories. Such bonds allow the charges from the vast cloud charged subsystems concentrate quickly in lightning channel. The formation of metal bonds in the thunderstorm cloudiness is described as the second-order phase transition. A successive mechanism for the process of formation and development of the lightning channel is suggested. This mechanism is associated with the change in the orientation of crystals in growing electric field. Possible consequences of the quantum-mechanical mechanism under discussion are compared with the results of observations.
Abstract Using 51 models of the AMIP and historical experiments of CMIP6, we investigate the inter‐model diversity of atmospheric and coupled models in the strength of the Indian Summer Monsoon Rainfall (ISMR)–El Niño‐Southern Oscillation (ENSO) relationship. In atmospheric models, the Walker Circulation (WC) intensity associated with the western Pacific convective activity is most responsible for the inter‐model diversity. Models with strong WC have a strong ISMR–ENSO relationship via enhancing ENSO‐induced anomalies of the WC and monsoon circulation. The secondary source is the monsoon circulation differences associated with meridional rainfall contrast over the Indian monsoon region. In coupled models, the primary (secondary) source is the ENSO amplitude (WC intensity). In observation, the decadal variation of WC can also explain the changes in the ISMR–ENSO relationship. This study provides a basis for improving the model performance and advances our understanding of the observed ISMR–ENSO relationship changes.