Search

The continued miniaturization of semiconductor devices, represented by Moore's law, has reached the atomic scale limit, requiring nanoscale quantum mechanical effects to be included in device simulations without empirical parameters. For this purpose, a method that combines density functional theory (DFT) and non-equilibrium Green's function (NEGF) theory has been established as the standard approach for atomic-scale device simulations. However, the DFT-NEGF scheme has several inherent weaknesses due to the underlying Landauer or grand canonical viewpoint. To overcome these challenges, over the years, we have developed an alternative approach, the multi-space constrained-search DFT (MS-DFT) formalism. The central starting point of this development is the replacement of the Landauer picture by the multi-space excitation viewpoint or the mapping of the quantum transport process to the energy- and position-space electron excitation within a (micro)canonical ensemble device model. This change in the viewpoint leads to several fundamental advantages of MS-DFT over its DFT-NEGF counterparts, such as the variational determination of non-equilibrium total energy, the explicit extraction of quasi-Fermi level distributions, and the possibility of faithfully modeling finite 2D electrodes. In this article, we highlight the key features and applications of the MS-DFT formalism.

In light of recent experimental data indicating a substantial thermal Hall effect in square lattice antiferromagnetic Mott insulators, we investigate whether a simple Mott insulator can sustain a finite thermal Hall effect. We verify that the answer is "no" if one performs calculations within a spin-only low-energy effective spin model with non-interacting magnons. However, by performing determinant quantum Monte Carlo simulations, we show the single-band $t$-$t'$-$U$ Hubbard model coupled to an orbital magnetic field does support a finite thermal Hall effect when $t' \neq 0$ and $B \neq 0$ in the Mott insulating phase. We argue that the (carrier agnostic) necessary conditions for observing a finite thermal Hall effect are time-reversal and particle-hole symmetry breaking. By considering magnon-magnon scattering using a semi-classical Boltzmann analysis, we illustrate a physical mechanism by which finite transverse thermal conductivity may arise, consistent with our symmetry argument and numerical results. Our results contradict the conventional wisdom that square and triangular lattices with SU(2) symmetry do not support a finite thermal Hall effect and call for a critical re-examination of thermal Hall effect data in insulating magnets, as the magnon contribution should not be excluded a priori., Comment: 6+23 pages, 3+11 figures

Quantum entanglement serves as a foundational resource for various quantum technologies. In optical systems, entanglement distribution rely on the indistinguishability and spatial overlap of photons. Heralded schemes play a crucial role in ensuring the reliability of entanglement generation by detecting ancillary photons to signal the creation of desired entangled states. However, photon losses in quantum channels remain a significant challenge, limiting the distance and capacity of entanglement distributions. This study suggests three heralded schemes that distribute multipartite Greenberger-Horne-Zeilinger (GHZ) states via lossy quantum channels. These schemes utilize different photon sources (Bell states or single-photons) and channel structures (centralized or decentralized heralding detectors). By comparing success probabilities and heralding efficiency, we find that each scheme has its own advantage according to the number of parties and the channel distance and the security requirement. This analysis provides insights into designing resilient heralded circuits for quantum information processing over lossy channels., Comment: 15 pages, 7 figures. Comments are welcom

Quantum dynamics compilation is an important task for improving quantum simulation efficiency: It aims to synthesize multi-qubit target dynamics into a circuit consisting of as few elementary gates as possible. Compared to deterministic methods such as Trotterization, variational quantum compilation (VQC) methods employ variational optimization to reduce gate costs while maintaining high accuracy. In this work, we explore the potential of a VQC scheme by making use of out-of-distribution generalization results in quantum machine learning (QML): By learning the action of a given many-body dynamics on a small data set of product states, we can obtain a unitary circuit that generalizes to highly entangled states such as the Haar random states. The efficiency in training allows us to use tensor network methods to compress such time-evolved product states by exploiting their low entanglement features. Our approach exceeds state-of-the-art compilation results in both system size and accuracy in one dimension ($1$D). For the first time, we extend VQC to systems on two-dimensional (2D) strips with a quasi-1D treatment, demonstrating a significant resource advantage over standard Trotterization methods, highlighting the method's promise for advancing quantum simulation tasks on near-term quantum processors.

Entangled photon sources are essential for quantum information applications, including quantum computation, quantum communication, and quantum metrology. Periodically poled (PP) crystals are commonly used to generate bright photon sources through quasi-phase matching. However, fabricating uniform micron-scale periodic structures poses significant technical difficulties, typically limiting the crystal thickness to less than a millimeter. Here, we adopt non-critical phase matching to produce a robust and bright polarization-entangled photon source based on a Sagnac interferometer. This method is tolerant of variations in pump incidence angles and temperature, and theoretically offers about a 2.5-fold brightness enhancement compared to quasi-phase matching. Additionally, the absence of periodic poling allows for a larger crystal cross-section. Using a bulk KTP crystal without a PP structure, we experimentally produce the four Bell states with a brightness of 25.1 kHz/mW, achieving purity, concurrence, and fidelity values close to 0.99. We believe our scheme will serve as a key building block for scalable and practical photonic quantum information applications., Comment: 7 pages, 5 figures, 2 tables, and supplementary note

Quantum machine learning is emerging as a promising application of quantum computing due to its distinct way of encoding and processing data. It is believed that large-scale quantum machine learning demonstrates substantial advantages over classical counterparts, but a reliable scale-up is hindered by the fragile nature of quantum systems. Here we present an experimentally accessible distributed quantum machine learning scheme that integrates quantum processor units via classical communication. As a demonstration, we perform data classification tasks on 8-dimensional synthetic datasets by emulating two 4-qubit processors and employing quantum convolutional neural networks. Our results indicate that incorporating classical communication notably improves classification accuracy compared to schemes without communication. Furthermore, at the tested circuit depths, we observe that the accuracy with classical communication is no less than that achieved with quantum communication. Our work provides a practical path to demonstrating large-scale quantum machine learning on intermediate-scale quantum processors by leveraging classical communication that can be implemented through currently available mid-circuit measurements., Comment: 9 pages, 6 figures

Accurate patient selection is critical in radiotherapy (RT) to prevent ineffective treatments. Traditional survival prediction models, relying on structured data, often lack precision. This study explores the potential of large language models (LLMs) to structure unstructured electronic health record (EHR) data, thereby improving survival prediction accuracy through comprehensive clinical information integration. Data from 34,276 patients treated with RT at Yonsei Cancer Center between 2013 and 2023 were analyzed, encompassing both structured and unstructured data. An open-source LLM was used to structure the unstructured EHR data via single-shot learning, with its performance compared against a domain-specific medical LLM and a smaller variant. Survival prediction models were developed using statistical, machine learning, and deep learning approaches, incorporating both structured and LLM-structured data. Clinical experts evaluated the accuracy of the LLM-structured data. The open-source LLM achieved 87.5% accuracy in structuring unstructured EHR data without additional training, significantly outperforming the domain-specific medical LLM, which reached only 35.8% accuracy. Larger LLMs were more effective, particularly in extracting clinically relevant features like general condition and disease extent, which closely correlated with patient survival. Incorporating LLM-structured clinical features into survival prediction models significantly improved accuracy, with the C-index of deep learning models increasing from 0.737 to 0.820. These models also became more interpretable by emphasizing clinically significant factors. This study shows that general-domain LLMs, even without specific medical training, can effectively structure large-scale unstructured EHR data, substantially enhancing the accuracy and interpretability of clinical predictive models., Comment: 23 pages, 2 tables, 4 figures

We propose a fault-tolerant quantum computation scheme in a measurement-based manner with finite-sized entangled resource states and encoded fusion scheme with linear optics. The encoded-fusion is an entangled measurement devised to enhance the fusion success probability in the presence of losses and errors based on a quantum error-correcting code. We apply an encoded-fusion scheme, which can be performed with linear optics and active feedforwards to implement the generalized Shor code, to construct a fault-tolerant network configuration in a three-dimensional Raussendorf-Harrington-Goyal lattice based on the surface code. Numerical simulations show that our scheme allows us to achieve up to 10 times higher loss thresholds than nonencoded fusion approaches with limited numbers of photons used in fusion. Our scheme paves an efficient route toward fault-tolerant quantum computing with finite-sized entangled resource states and linear optics., Comment: 14 pages including 5 Appendices, 14 figures

Dipolar-octupolar (DO) pyrochlore systems Ce$_2$(Zr,Sn,Hf)$_2$O$_7$ have garnered much attention as recent investigations suggest that they may stabilize a novel quantum spin ice (QSI), a quantum spin liquid (QSL) with an emergent $U(1)$ gauge field. In particular, the experimentally estimated microscopic exchange parameters place Ce$_2$Zr$_2$O$_7$ in the $\pi$-flux QSI regime, and recent neutron scattering experiments have corroborated some key theoretical predictions. On the other hand, to make a definitive conclusion, more multifaceted experimental signatures are desirable. In this regard, recent neutron scattering investigation of the magnetic field dependence of the spin correlations in Ce$_2$Zr$_2$O$_7$ may provide valuable information. However, there have not been any comprehensive theoretical studies for comparison. In this work, we provide such information using gauge mean-field theory (GMFT), allowing for theoretical investigation beyond the perturbative regime. In particular, we construct the phase diagrams for the [110], [111], and [001] field directions. Furthermore, we demonstrate the distinctive evolution of the equal-time and dynamical spin structure factors as a function of the magnetic field for each field direction. These predictions will help future experiments confirm the true nature of the DO-QSI., Comment: 14+11 pages, 11+7 figures

Quantum computers have long been anticipated to excel in simulating quantum many-body physics. While most previous work has focused on Hermitian physics, we demonstrate the power of variational quantum circuits for resource-efficient simulations of dynamical and equilibrium physics in non-Hermitian systems, revealing new phenomena beyond standard Hermitian quantum machines. Using a variational quantum compilation scheme for fermionic systems, we reduce gate count, save qubits, and eliminate the need for postselection, a major challenge in simulating non-Hermitian dynamics via standard Trotterization. Experimentally, we observed a supersonic mode in the connected density-density correlation function on an $ n = 18 $ fermionic chain after a non-Hermitian, locally interacting quench, which would otherwise be forbidden by the Lieb-Robinson bound in a Hermitian system. Additionally, we investigate sequential quantum circuits generated by tensor networks for ground state preparation, here defined as the eigenstate with the lowest real part eigenvalue, using a variance minimization scheme. Through a trapped-ion implementation on the Quantinuum H1 quantum processor, we accurately capture correlation functions and energies across an exceptional point on a dissipative spin chain up to length $ n = 20 $ using only 3 qubits. Motivated by these advancements, we provide an analytical example demonstrating that simulating single-qubit non-Hermitian dynamics for $\Theta(\log(n))$ time from certain initial states is exponentially hard on a quantum computer, offering insights into the opportunities and limitations of using quantum computation for simulating non-Hermitian physics.

High-dimensional multipartite entanglement plays a crucial role in quantum information science. However, existing schemes for generating such entanglement become increasingly complex and costly as the dimension of quantum units increases. In this work, we overcome the limitation by proposing a significantly enhanced linear optical heralded scheme that generates the $d$-level $N$-partite GHZ state with single-photon sources and their linear operations. Our scheme requires $dN$ photons to generate the target state with substantially improved success probability from previous schemes. It employs linear optical logic gates compatible with any qudit encoding system and can generate generalized GHZ states with installments of beamsplitters. With efficient generations of high-dimensional resource states, our work opens avenues for further exploration in high-dimensional quantum information processing., Comment: 11 pages, comments welcome

Diffusion models have demonstrated great potential in generating high-quality content for images, natural language, protein domains, etc. However, how to perform user-preferred targeted generation via diffusion models with only black-box target scores of users remains challenging. To address this issue, we first formulate the fine-tuning of the targeted reserve-time stochastic differential equation (SDE) associated with a pre-trained diffusion model as a sequential black-box optimization problem. Furthermore, we propose a novel covariance-adaptive sequential optimization algorithm to optimize cumulative black-box scores under unknown transition dynamics. Theoretically, we prove a $O(\frac{d^2}{\sqrt{T}})$ convergence rate for cumulative convex functions without smooth and strongly convex assumptions. Empirically, experiments on both numerical test problems and target-guided 3D-molecule generation tasks show the superior performance of our method in achieving better target scores.

Recently, remote-controlled quantum information processing has been proposed for its applications in secure quantum processing protocols and distributed quantum networks. For remote-controlled quantum gates, the experimental realization of controlled unitary (CU) gates between any quantum gates is an essential task. Here, we propose and experimentally demonstrate a scheme for implementing CU gates between arbitrary pairs of unitary gates using the polarization and time-bin degrees of freedom of single-photons. Then, we experimentally implement remote-controlled single-qubit unitary gates by controlling either the state preparation or measurement of the control qubit with high process fidelities. We believe that the proposed remote-controlled quantum gate model can pave the way for secure and efficient quantum information processing., Comment: 7 pages, 4 figures

Entanglement shared between distant parties is a key resource in quantum networks. However, photon losses in quantum channels significantly reduce the success probability of entanglement sharing, which scales quadratically with the channel transmission. Quantum repeaters using entanglement swapping can mitigate this effect, but usually require high-performance photonic quantum memories to synchronize photonic qubits. In this work, we theoretically and experimentally investigate an entanglement swapping protocol using photon-number-encoded states that can effectively alleviate quantum channel losses without requiring photonic quantum memories. We demonstrate that the protocol exhibits a success probability scaling linearly with the channel transmission. Furthermore, we show that while unbalanced channel losses can degrade the shared entanglement, this effect can be compensated by optimally adjusting the initial entangled states. Our results highlight the potential of photon-number encoding for realizing robust entanglement distribution in lossy quantum networks., Comment: 7 pages, 6 figures, 39 references

Inelastic neutron scattering (INS) has traditionally been one of the primary methods for investigating quantum magnets, particularly in identifying a continuum of excitations as a hallmark of spin fractionalization in quantum spin liquids (QSLs). However, INS faces severe limitations due to its inability to distinguish between such QSL signatures and similar excitation continua arising from highly frustrated magnetic orders with large unit cells or classical spin liquids. In contrast, two-dimensional coherent spectroscopy (2DCS) has emerged as a powerful tool to probe nonlinear excitation dynamics, offering insights into the underlying mechanisms behind these broad spectral features. In this paper, we utilize classical molecular dynamics (MD) techniques to explore the 2DCS responses of frustrated magnets with dominant Kitaev interactions. Comparing the classical and quantum versions of the pure Kitaev model our results indicate both clear similarities, in the form of sharp line features, and clear distinctions, in the locations of these features and in selection rules. Moreover, in the extended $K\Gamma\Gamma'$ model, we show that the 2DCS response of the Kitaev spin liquid is completely distinct from that of large unit cell magnetic orders, despite both generating a broad continuum in INS. Additionally, we demonstrate the extreme sensitivity of classical 2DCS to thermal fluctuations and discuss the potential significance of quantum coherence in experimental settings. Overall, our work illustrates the potential of 2DCS in resolving the complex physics underlying ambiguous spin excitation continua, thereby enhancing our understanding of the dynamics in these frustrated systems., Comment: 10 pages, 5+1 figures

Variational quantum eigensolver (VQE), which combines quantum systems with classical computational power, has been arisen as a promising candidate for near-term quantum computing applications. However, the experimental resources such as the number of measurements to implement VQE rapidly increases as the Hamiltonian problem size grows. Applying entanglement measurements to reduce the number of measurement setups has been proposed to address this issue, however, entanglement measurements themselves can introduce additional resource demands. Here, we apply entanglement measurements to the photonic VQE utilizing polarization and path degrees of freedom of a single-photon. In our photonic VQE, entanglement measurements can be deterministically implemented using linear optics, so it takes full advantage of introducing entanglement measurements without additional experimental demands. Moreover, we show that such a setup can mitigate errors in measurement apparatus for a certain Hamiltonian., Comment: Comments are welcome

The weak Mott insulating regime of the triangular lattice Hubbard model exhibits a rich magnetic phase diagram as a result of the ring exchange interaction in the spin Hamiltonian. These phases include the Kalmeyer-Laughlin type chiral spin liquid (CSL) and a valence bond solid (VBS). A natural question arises regarding the robustness of these phases in the presence of a weak spin-orbit coupling (SOC). In this study, we derive the effective spin model for the spin-orbit coupled triangular lattice Hubbard model in the weak Mott insulting regime, including all SOC-mediated spin-bilinears and ring-exchange interactions. We then construct a simplified spin model keeping only the most relevant SOC-mediated spin interactions. Using infinite density matrix renormalization group (iDMRG) we show that the CSL and VBS phases of the triangular lattice Hubbard model can be stabilized in the presence of a weak SOC. The stabilization results from a compensation between the Dzyaloshinskii-Moriya interaction and a SOC-mediated ring exchange interaction. We also provide additional qualitative arguments to intuitively understand the compensation mechanism in the iDMRG quantum phase diagrams. This mechanism for stabilization can potentially be useful for the experimental realization of quantum spin liquids., Comment: 20 pages, 13 figures

We introduce StaccaToe, a human-scale, electric motor-powered single-leg robot designed to rival the agility of human locomotion through two distinctive attributes: an actuated toe and a co-actuation configuration inspired by the human leg. Leveraging the foundational design of HyperLeg's lower leg mechanism, we develop a stand-alone robot by incorporating new link designs, custom-designed power electronics, and a refined control system. Unlike previous jumping robots that rely on either special mechanisms (e.g., springs and clutches) or hydraulic/pneumatic actuators, StaccaToe employs electric motors without energy storage mechanisms. This choice underscores our ultimate goal of developing a practical, high-performance humanoid robot capable of human-like, stable walking as well as explosive dynamic movements. In this paper, we aim to empirically evaluate the balance capability and the exertion of explosive ground reaction forces of our toe and co-actuation mechanisms. Throughout extensive hardware and controller development, StaccaToe showcases its control fidelity by demonstrating a balanced tip-toe stance and dynamic jump. This study is significant for three key reasons: 1) StaccaToe represents the first human-scale, electric motor-driven single-leg robot to execute dynamic maneuvers without relying on specialized mechanisms; 2) our research provides empirical evidence of the benefits of replicating critical human leg attributes in robotic design; and 3) we explain the design process for creating agile legged robots, the details that have been scantily covered in academic literature., Comment: Submitted to 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)

A quantum spin liquid (QSL) arises from a highly entangled superposition of many degenerate classical ground states in a frustrated magnet, and is characterized by emergent gauge fields and deconfined fractionalized excitations (spinons). Because such a novel phase of matter is relevant to high-transition-temperature superconductivity and quantum computation, the microscopic understanding of QSL states is a long-sought goal in condensed matter physics. The 3D pyrochlore lattice of corner-sharing tetrahedra can host a QSL with U(1) gauge fields called quantum spin ice (QSI), which is a quantum (with effective $S=1/2$) analog of the classical (with large effective moment) spin ice. A key difference between QSI and classical spin ice is the predicted presence of the linearly dispersing collective excitations near zero energy, dubbed the "photons", arising from emergent quantum electrodynamics, in addition to the spinons at higher energies. Recently, 3D pyrochlore systems Ce2M2O7 (M = Sn, Zr, Hf) have been suggested as effective $S=1/2$ QSI candidates, but there has been no evidence of quasielastic magnetic scattering signals from photons, a key signature for a QSI. Here, we use polarized neutron scattering experiments on single crystals of Ce2Zr2O7 to conclusively demonstrate the presence of magnetic excitations near zero energy at 50 mK in addition to signatures of spinons at higher energies. By comparing the energy (E), wave vector (Q), and polarization dependence of the magnetic excitations with theoretical calculations, we conclude that Ce2Zr2O7 is the first example of a dipolar-octupolar $\pi$ flux QSI with dominant dipolar Ising interactions, therefore identifying a microscopic Hamiltonian responsible for a QSL.

The self-consistent field (SCF) generation of the three-dimensional (3D) electron density distribution ($\rho$) represents a fundamental aspect of density functional theory (DFT) and related first-principles calculations, and how one can shorten or bypass the SCF loop represents a critical question from both practical and fundamental standpoints. Herein, a machine learning strategy DeepSCF is presented in which the map between the SCF $\rho$ and the initial guess density ($\rho_0$) constructed by the summation of neutral atomic densities is learned using 3D convolutional neural networks (CNNs). High accuracy and transferability of DeepSCF are achieved by expanding the input features to include atomic fingerprints beyond $\rho_0$ and encoding them on a 3D grid. The prediction of the residual density ($\delta\rho$) rather than $\rho$ itself is targeted, and, since $\delta\rho$ corresponds to chemical bonding information, a dataset of small-sized organic molecules featuring diverse bonding characters is adopted. After enhancing the fidelity of the method by subjecting the atomic geometries in the dataset to random strains and rotations, the effectiveness of DeepSCF is finally demonstrated using a complex large carbon nanotube-based DNA sequencer model. This work evidences that the nearsightedness in electronic structures can be optimally represented via the local connectivity in CNNs., Comment: 9 pages, 6 figures

Early efforts to realize exotic quantum ground states in frustrated magnets focused on frustration arising from the lattice geometry alone. Attention has shifted to bond-dependent anisotropic interactions, as well as further-neighbor interactions, on non-geometrically-frustrated lattices due to their greater versatility. The honeycomb magnet BaCo$_2$(AsO$_4$)$_2$ recently emerged as a candidate host for both bond-dependent (e.g. Kitaev) and third-neighbor ($J_3$) interactions, and has become a model experimental system due to its relatively low levels of disorder. Understanding the relative importance of different exchange interactions holds the key to achieving novel ground states, such as quantum spin liquids. Here, we use the magnetotropic susceptibility to map out the intermediate and high-field phase diagram of BaCo$_2$(AsO$_4$)$_2$ as a function of the out-of-plane magnetic field direction at $T = 1.6$ K. We show that the experimental data are qualitatively consistent with classical Monte Carlo results of the XXZ-$J_1$-$J_3$ model with small Kitaev and off-diagonal exchange couplings included. However, the calculated critical fields are systematically larger than the experimental values. Infinite-DMRG computations on the quantum model reveal that quantum corrections from a nearby ferromagnetic state are likely responsible for the suppressed critical fields. Together, our experiment and theory analyses demonstrate that, while quantum fluctuations play an important role in determining the phase diagram, most of the physics of BaCo$_2$(AsO$_4$)$_2$ can be understood in terms of the classical dynamics of long-range ordered states, leaving little room for the possibility of a quantum spin liquid., Comment: 16 pages, 12 figures

In this paper, we study tidal forces in the Schwarzschild black hole whose metric includes explicitly a generalized uncertainty principle (GUP) effect. We also investigate interesting features of the geodesic equations and tidal effects dependent on the GUP parameter $\alpha$ related to a minimum length. Then, by solving geodesic deviation equations explicitly with appropriate boundary conditions, we show that $\alpha$ in the effective metric affects both the radial and angular components of the geodesic equation, particularly near the singularities., Comment: 13 pages, 9 figures, version to appear in Communications in Theoretical Physics

In this paper, we propose a radar odometry structure that directly utilizes radar velocity measurements for dead reckoning while maintaining its ability to update estimations within the Kalman filter framework. Specifically, we employ the Doppler velocity obtained by a 4D Frequency Modulated Continuous Wave (FMCW) radar in conjunction with gyroscope data to calculate poses. This approach helps mitigate high drift resulting from accelerometer biases and double integration. Instead, tilt angles measured by gravitational force are utilized alongside relative distance measurements from radar scan matching for the filter's measurement update. Additionally, to further enhance the system's accuracy, we estimate and compensate for the radar velocity scale factor. The performance of the proposed method is verified through five real-world open-source datasets. The results demonstrate that our approach reduces position error by 62% and rotation error by 66% on average compared to the state-of-the-art radar-inertial fusion method in terms of absolute trajectory error., Comment: 9 pages, 5 figures, 1 table, IROS 2024