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At least 595 records · Page 33

Out-of-time ordered correlation functions for the localized 𝑓 electrons in the Falicov-Kimball model

We provide an exact evaluation of the out-of-time correlation (OTOC) functions for the localized 𝑓-particle states in the Falicov-Kimball model within dynamical mean-field theory. Different regimes of quantum chaos and quantum scrambling are distinguished by the winding numbers of the block Toeplitz matrices used in the calculation. The similarities of these fermionic OTOCs and their logarithmic derivatives for time evolution with the OTOCs for quantum spin models with disorder are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The development and applications of multidimensional biomolecular spectroscopy illustrated by photosynthetic light harvesting

The parallel and synergistic developments of atomic resolution structural information, new spectroscopic methods, their underpinning formalism, and the application of sophisticated theoretical methods have led to a step function change in our understanding of photosynthetic light harvesting, the process by which photosynthetic organisms collect solar energy and supply it to their reaction centers to initiate the chemistry of photosynthesis. The new spectroscopic methods, in particular multidimensional spectroscopies, have enabled a transition from recording rates of processes to focusing on mechanism. We discuss two ultrafast spectroscopies – two-dimensional electronic spectroscopy and two-dimensional electronic-vibrational spectroscopy – and illustrate their development through the lens of photosynthetic light harvesting. Both spectroscopies provide enhanced spectral resolution and, in different ways, reveal pathways of energy flow and coherent oscillations which relate to the quantum mechanical mixing of, for example, electronic excitations (excitons) and nuclear motions. The new types of information present in these spectra provoked the application of sophisticated quantum dynamical theories to describe the temporal evolution of the spectra and provide new questions for experimental investigation. While multidimensional spectroscopies have applications in many other areas of science, we feel that the investigation of photosynthetic light harvesting has had the largest influence on the development of spectroscopic and theoretical methods for the study of quantum dynamics in biology, hence the focus of this review. We conclude with key questions for the next decade of this review.

59 BASIC BIOLOGICAL SCIENCES↗

Optical versus radiographic imaging and tomography: introduction to the ROADS feature issue

Optical imaging is an ancient branch of imaging dating back to thousands of years. Radiographic imaging and tomography (RadIT), including the first use of X-rays by Wilhelm Röntgen, and then, $γ$ -rays, energetic charged particles, neutrons, etc. are about 130 years young. The synergies between optical and radiographic imaging can be cast in the framework of these building blocks: Physics, Sources, Detectors, Methods, and Data Science, as described in Appl. Opt. 61, RDS1 (2022). Optical imaging has expanded to include three-dimensional (3D) tomography (including holography), due in to part the invention of optical (including infrared) lasers. RadIT are intrinsically 3D because of the penetrating power of ionizing radiation. Both optical imaging and tomography (OIT) and RadIT are evolving into even higher dimensional regimes, such as time-resolved tomography (4D) and temporarily and spectroscopically resolved tomography (4D + ). Further advances in OIT and RadIT will continue to be driven by desires for higher information yield, higher resolutions, and higher probability models with reduced uncertainties. Synergies in quantum physics, laser-driven sources, low-cost detectors, data-driven methods, automated processing of data, and artificially intelligent data acquisition protocols will be beneficial to both branches of imaging in many applications. These topics, along with an overview of the Radiography, Applied Optics, and Data Science virtual feature issue, are discussed here.

47 OTHER INSTRUMENTATION↗

Sub-1 Volt and high-bandwidth visible to near-infrared electro-optic modulators

Abstract Integrated electro-optic (EO) modulators are fundamental photonics components with utility in domains ranging from digital communications to quantum information processing. At telecommunication wavelengths, thin-film lithium niobate modulators exhibit state-of-the-art performance in voltage-length product ( V π L ), optical loss, and EO bandwidth. However, applications in optical imaging, optogenetics, and quantum science generally require devices operating in the visible-to-near-infrared (VNIR) wavelength range. Here, we realize VNIR amplitude and phase modulators featuring V π L ’s of sub-1 V ⋅ cm, low optical loss, and high bandwidth EO response. Our Mach-Zehnder modulators exhibit a V π L as low as 0.55 V ⋅ cm at 738 nm, on-chip optical loss of ~0.7 dB/cm, and EO bandwidths in excess of 35 GHz. Furthermore, we highlight the opportunities these high-performance modulators offer by demonstrating integrated EO frequency combs operating at VNIR wavelengths, with over 50 lines and tunable spacing, and frequency shifting of pulsed light beyond its intrinsic bandwidth (up to 7x Fourier limit) by an EO shearing method.

42 ENGINEERING↗

Disordered topological graphs enhancing nonlinear phenomena

Complex networks play a fundamental role in understanding phenomena from the collective behavior of spins, neural networks, and power grids to the spread of diseases. Topological phenomena in such networks have recently been exploited to preserve the response of systems in the presence of disorder. We propose and demonstrate topological structurally disordered systems with a modal structure that enhances nonlinear phenomena in the topological channels by inhibiting the ultrafast leakage of energy from edge modes to bulk modes. We present the construction of the graph and show that its dynamics enhances the topologically protected photon pair generation rate by an order of magnitude. Disordered nonlinear topological graphs will enable advanced quantum interconnects, efficient nonlinear sources, and light-based information processing for artificial intelligence.

42 ENGINEERING↗

Control of chiral orbital currents in a colossal magnetoresistance material

Colossal magnetoresistance (CMR) is an extraordinary enhancement of the electrical conductivity in the presence of a magnetic field. It is conventionally associated with a field-induced spin polarization that drastically reduces spin scattering and electric resistance. Ferrimagnetic Mn 3 Si 2 Te 6 is an intriguing exception to this rule: it exhibits a seven-order-of-magnitude reduction in ab plane resistivity that occurs only when a magnetic polarization is avoided 1,2 . Here, we report an exotic quantum state that is driven by ab plane chiral orbital currents (COC) flowing along edges of MnTe 6 octahedra. The c axis orbital moments of ab plane COC couple to the ferrimagnetic Mn spins to drastically increase the ab plane conductivity (CMR) when an external magnetic field is aligned along the magnetic hard c axis. Consequently, COC-driven CMR is highly susceptible to small direct currents exceeding a critical threshold, and can induce a time-dependent, bistable switching that mimics a first-order ‘melting transition’ that is a hallmark of the COC state. Further, the demonstrated current-control of COC-enabled CMR offers a new paradigm for quantum technologies.

36 MATERIALS SCIENCE↗

Broadband Nonreciprocity Enabled by Strong Coupling of Magnons and Microwave Photons

Nonreciprocity of signal transmission enhances the capacity of communication channels and protects the transmission quality against possible signal instabilities, thus becoming an important component for ensuring coherent information processing. However, nonreciprocal transmission requires breaking time-reversal symmetry (TRS), which poses challenges of both practical and fundamental character that hinder progress. Here we report an alternative scheme for achieving broadband nonreciprocity using a specially engineered hybrid microwave cavity. The TRS breaking is realized via strong coherent coupling between a selected chiral mode in the microwave cavity and a single collective spin excitation (magnon) in a ferromagnetic yttrium iron garnet sphere. The nonreciprocity in transmission is observed to span nearly a 0.5-GHz frequency band, which outperforms by two orders of magnitude the previously achieved bandwidths. Our findings suggest a promising direction for robust coherent information processing in a broad range of systems in both the classical and the quantum regime.

36 MATERIALS SCIENCE↗

CMOS-Compatible Ultrathin Superconducting NbN Thin Films Deposited by Reactive Ion Sputtering on 300 mm Si Wafer

We report a milestone in achieving large-scale, ultrathin (~5 nm) superconducting NbN thin films on 300 mm Si wafers using a high-volume manufacturing (HVM) industrial physical vapor deposition (PVD) system. The NbN thin films possess remarkable structural uniformity and consistently high superconducting quality across the entire 300 mm Si wafer, by incorporating an AlN buffer layer. High-resolution X-ray diffraction and transmission electron microscopy analyses unveiled enhanced crystallinity of (111)-oriented δ-phase NbN with the AlN buffer layer. Notably, NbN films deposited on AlN-buffered Si substrates exhibited a significantly elevated superconducting critical temperature (~2 K higher for the 10 nm NbN) and a higher upper critical magnetic field or H c2 (34.06 T boost in H c2 for the 50 nm NbN) in comparison with those without AlN. These findings present a promising pathway for the integration of quantum-grade superconducting NbN films with the existing 300 mm CMOS Si platform for quantum information applications.

36 MATERIALS SCIENCE↗

QUCODE: End-to-End Qubit Co-Design

The design of a quantum computer can be broken down into different steps, e.g., the material science aspect of designing qubits and devices, considerations of controlling the state of the qubits and their environment, the computer science aspects of mapping algorithms to the available primitives of the quantum computer, and the programming of an application in terms of the available algorithms. Research in these areas is currently fairly isolated, and there is framework for an end-to-end design approach where a desired application informs the choice of materials for the qubits and their environment, and vice versa.We identify knowledge gaps and opportunities for research that builds on existing PNNL capabilities.

36 MATERIALS SCIENCE↗

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗

2024 roadmap on magnetic microscopy techniques and their applications in materials science

Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition to structural and integral magnetic characterisations, imaging of magnetisation patterns, current distributions and magnetic fields at nano- and microscale is of major importance to understand the material responses and qualify them for specific applications. In this roadmap, we aim to cover a broad portfolio of techniques to perform nano- and microscale magnetic imaging using superconducting quantum interference devices, spin centre and Hall effect magnetometries, scanning probe microscopies, x-ray- and electron-based methods as well as magnetooptics and nanoscale magnetic resonance imaging. The roadmap is aimed as a single access point of information for experts in the field as well as the young generation of students outlining prospects of the development of magnetic imaging technologies for the upcoming decade with a focus on physics, materials science, and chemistry of planar, three-dimensional and geometrically curved objects of different material classes including two-dimensional materials, complex oxides, semi-metals, multiferroics, skyrmions, antiferromagnets, frustrated magnets, magnetic molecules/nanoparticles, ionic conductors, superconductors, spintronic and spinorbitronic materials.

2D materials↗

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms

The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One of the primary limitations of QAOA is the task of finding a set of good parameters, which is usually done using a variational optimization loop. Parameter transfer, or parameter concentration, is a phenomenon where QAOA angles trained on problem instances that are self-similar tend to perform well for other problem instances from that similar class. This suggests a potentially highly efficient and scalable non-variational learning method for QAOA angle finding. In this work, we systematically study QAOA parameter transferability from small problem sizes (16 and 27 decision variables) onto large problem instances (up to 156 qubits) for heavy-hex graph Ising models with geometrically local higher order terms using the Julia based QAOA simulation tool \texttt{JuliQAOA} to perform classical angle finding for up to $49$ QAOA layers ($p$). Parameter transfer of the fixed angles is validated using a combination of full statevector, Projected Entangled Pair States (PEPS), Matrix Product State (MPS), and LOWESA numerical simulations. We find that the QAOA parameter transfer from single instances applied to other (unseen) problem instances does not in general provide monotonically improving performance as a function of $p$ - there are many cases where the performance temporarily decreases as a function of $p$ - but despite this the transferred angles have a general trend of improved expectation value as the QAOA depth increases, in many cases converging close to the true ground-state energy of the $100+$ qubit instances. We also sample the hardware-compatible Ising models using the ensemble of transfer-learned QAOA parameters on several superconducting qubit IBM Quantum processors with 127, 133, and 156 qubits. We find continuous solution quality improvement of the hardware-compatible QAOA circuits run on the IBM NISQ processors up to $p=5$ on \texttt{ibm\_fez}, up to $p=9$ on \texttt{ibm\_torino}, and up to $p=10$ on \texttt{ibm\_pittsburgh}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

First-principles calculations of defects and electron–phonon interactions: Seminal contributions of Audrius Alkauskas to the understanding of recombination processes

First-principles calculations of defects and electron–phonon interactions play a critical role in the design and optimization of materials for electronic and optoelectronic devices. The late Audrius Alkauskas made seminal contributions to developing rigorous first-principles methodologies for the computation of defects and electron–phonon interactions, especially in the context of understanding the fundamental mechanisms of carrier recombination in semiconductors. Alkauskas was also a pioneer in the field of quantum defects, helping to build a first-principles understanding of the prototype nitrogen-vacancy center in diamond, as well as identifying novel defects. Here, we describe the important contributions made by Alkauskas and his collaborators and outline fruitful research directions that Alkauskas would have been keen to pursue. Audrius Alkauskas’ scientific achievements and insights highlighted in this article will inspire and guide future developments and advances in the field.

36 MATERIALS SCIENCE↗

First-principles calculation of Hubbard U for Terbium metal under high pressure

Abstract Using density functional theory (DFT) and linear response approaches, we compute the on-site Hubbard interaction U of elemental Terbium (Tb) metal in the pressure range ∼ 0–65 GPa. The resulting first-principles U values with experimental crystal structures enable us to examine the magnetic properties of Tb using a DFT+U method. The lowest-energy magnetic states in our calculations for different high-pressure Tb phases—including hcp, α -Sm, and dhcp—are found to be compatible with the corresponding magnetic ordering vectors reported in experiments. The result shows that the inclusion of Hubbard U substantially improves the accuracy and efficiency in modeling correlated rare-earth materials. Our study also provides the necessary U information for other quantum many-body techniques to study Tb under extreme pressure conditions.

36 MATERIALS SCIENCE↗

Adiabatic approximation and Aharonov-Casher bands in twisted homobilayer transition metal dichalcogenides

Topological flat moiré bands with nearly ideal quantum geometry have been identified in homobilayer transition metal dichalcogenide moiré superlattices, and are thought to be crucial for understanding the fractional Chern insulating states recently observed therein. Previous study proposed viewing the system using an adiabatic approximation that replaces the position dependence of the layer spinor with a nonuniform periodic effective magnetic field. When the local zero-point kinetic energy of this magnetic field cancels identically against that of an effective Zeeman energy, a Bloch-band version of Aharonov-Casher zero-energy modes, which we refer to as Aharonov-Casher band, emerges leading to ideal quantum geometry. Here, we critically examine the validity of the adiabatic approximation and identify the parameter regimes under which Aharonov-Casher bands emerge. We show that the adiabatic approximation is accurate for a wide range of parameters including those realized in experiments. Furthermore, we show that while the cancellation leading to the emergence of Aharonov-Casher bands is generally not possible beyond the leading Fourier harmonic, the leading harmonic is the dominant term in the Fourier expansions of the zero-point kinetic energy and Zeeman energy. Finally, the leading harmonic expansion accurately captures the trend of the bandwidth and quantum geometry, although it may fail to quantitatively reproduce more detailed information about the bands such as the Berry curvature distribution.

36 MATERIALS SCIENCE↗

Logic operations with active topological defects

Logic operations performed by semiconductor-based transistors are the basis of modern computing. There is considerable interest in creating autonomous materials systems endowed with the capability to make decisions. In this work, we introduce the concept of using topological defects in active matter to perform logic operations. When an extensile active stress in a nematic liquid crystal is turned on, +1/2 defects can self-propel, in analogy to electron transport under a voltage gradient. By relying on hydrodynamic simulations of active nematics, we demonstrate that patterns of activity, when combined with surfaces imparting certain orientations, can be used to control the formation and transport of +1/2 defects. We further show that asymmetric high- and low-activity patterns can be used to create effective defect gates, tunnels, and amplifiers. The proposed active systems offer the potential to perform computations and transmit information in active soft materials, including actin-, tubulin-, and cell-based systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Direct observation of chirality-induced spin selectivity in electron donor–acceptor molecules

The role of chirality in determining the spin dynamics of photoinduced electron transfer in donor-acceptor molecules remains an open question. Although chirality-induced spin selectivity (CISS) has been demonstrated in molecules bound to substrates, experimental information about whether this process influences spin dynamics in the molecules themselves is lacking. Here we used time-resolved electron paramagnetic resonance spectroscopy to show that CISS strongly influences the spin dynamics of isolated covalent donor–chiral bridge–acceptor (D-Bχ-A) molecules in which selective photoexcitation of D is followed by two rapid, sequential electron-transfer events to yield D •+ -Bχ-A •– . Exploiting this phenomenon affords the possibility of using chiral molecular building blocks to control electron spin states in quantum information applications.

Science & Technology - Other Topics↗