John J. Rehr, Fernando D. Vila, Joshua J. Kas, Nitzan Y. Hirshberg, Karol Kowalski, Bo Peng
We present an equation of motion coupled cluster approach for calculating and understanding intrinsic inelastic losses in core level x-ray absorption spectra (XAS). The method is based on a factorization of the transition amplitude in the time-domain, which leads to a convolution of an effective one-body spectrum and the core-hole spectral function. The spectral function characterizes these losses in terms of shake-up excitations and satellites, and is calculated using a cumulant representation of the core-hole Green's function that includes non-linear corrections. The one-body spectrum also includes orthogonality corrections that enhance the XAS at the edge.
Nicholas P Bauman, Bo Peng, Karol Kowalski
We demonstrate that the effective Hamiltonians obtained with the downfolding procedure based on double unitary coupled cluster (DUCC) ansatz can be used in the context of Greens function coupled cluster (GFCC) formalism to calculate spectral functions of molecular systems. This combined approach (DUCC-GFCC) provides a significant reduction of numerical effort and good agreement with the corresponding all-orbital GFCC methods in energy windows that are consistent with the choice of active space. These features are demonstrated on the example of two benchmark systems: H2O and N2, where DUCC-GFCC calculations were performed for active spaces of various sizes.
Guang Hua Duan, Chengcheng Han, Bo Peng, Lei Wu, Jin Min Yang
The stau-neutralino coannihilation provides a feasible way to accommodate the observed cosmological dark matter (DM) relic density in the minimal supersymmetric standard model (MSSM). In such a coannihilation mechanism the stau mass usually has an upper bound since its annihilation rate becomes small with the increase of DM mass. Inspired by this observation, we examine the upper limit of stau mass in the parameter space with a large mixing of staus. We find that the stau pair may dominantly annihilate into dibosons and hence the upper bound on the stau mass ($\sim400$ GeV) obtained from the $f\bar{f}$ final states can be relaxed. Imposing the DM relic density constraint and requiring a long lifetime of the present vacuum, we find that the lighter stau mass can be as heavy as about 1.4 TeV for the stau maximum mixing. However, if requiring the present vacuum to survive during the thermal history of the universe, this mass limit will reduce to about 0.9 TeV. We also discuss the complementarity of vacuum stability and direct detections in probing this stau coannihilation scenario.
Samuel Stein, Yufei Ding, Nathan Wiebe, Bo Peng, Karol Kowalski, Nathan Baker, James Ang, Ang Li
Nov 29, 2021·quant-ph·PDF Variational quantum algorithm (VQA), which is comprised of a classical optimizer and a parameterized quantum circuit, emerges as one of the most promising approaches for harvesting the power of quantum computers in the noisy intermediate scale quantum (NISQ) era. However, the deployment of VQAs on contemporary NISQ devices often faces considerable system and time-dependant noise and prohibitively slow training speeds. On the other hand, the expensive supporting resources and infrastructure make quantum computers extremely keen on high utilization. In this paper, we propose a virtualized way of building up a quantum backend for variational quantum algorithms: rather than relying on a single physical device which tends to introduce temporal-dependant device-specific noise with worsening performance as time-since-calibration grows, we propose to constitute a quantum ensemble, which dynamically distributes quantum tasks asynchronously across a set of physical devices, and adjusting the ensemble configuration with respect to machine status. In addition to reduced machine-dependant noise, the ensemble can provide significant speedups for VQA training. With this idea, we build a novel VQA training framework called EQC that comprises: (i) a system architecture for asynchronous parallel VQA cooperative training; (ii) an analytic model for assessing the quality of the returned VQA gradient over a particular device concerning its architecture, transpilation, and runtime conditions; (iii) a weighting mechanism to adjust the quantum ensemble's computational contribution according to the systems' current performance. Evaluations comprising 500K circuit evaluations across 10 IBMQ devices using a VQE and a QAOA applications demonstrate that EQC can attain error rates close to the most performant device of the ensemble, while boosting the training speed by 10.5x on average (up to 86x and at least 5.2x).
Bo Peng, Hongxing Fan, Wei Wang, Jing Dong, Yuezun Li, Siwei Lyu, Qi Li, Zhenan Sun, Han Chen, Baoying Chen, Yanjie Hu, Shenghai Luo, Junrui Huang, Yutong Yao, Boyuan Liu, Hefei Ling, Guosheng Zhang, Zhiliang Xu, Changtao Miao, Changlei Lu, Shan He, Xiaoyan Wu, Wanyi Zhuang
This paper presents a summary of the DFGC 2021 competition. DeepFake technology is developing fast, and realistic face-swaps are increasingly deceiving and hard to detect. At the same time, DeepFake detection methods are also improving. There is a two-party game between DeepFake creators and detectors. This competition provides a common platform for benchmarking the adversarial game between current state-of-the-art DeepFake creation and detection methods. In this paper, we present the organization, results and top solutions of this competition and also share our insights obtained during this event. We also release the DFGC-21 testing dataset collected from our participants to further benefit the research community.
Bo Peng, Nicholas P. Bauman, Sahil Gulania, Karol Kowalski
Coupled cluster Green's function (CCGF) approach has drawn much attention in recent years for targeting the molecular and material electronic structure problems from a many-body perspective in a systematically improvable way. Here, we will present a brief review of the history of how the Green's function method evolved with the wavefunction, early and recent development of CCGF theory, and more recently scalable CCGF software development. We will highlight some of the recent applications of CCGF approach and propose some potential applications that would emerge in the near future.
Joseph C. Aulicino, Trevor Keen, Bo Peng
Sep 27, 2021·quant-ph·PDF Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quantum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ devices impedes the conventional quantum algorithms to be implemented. Practical strategies usually exploit hybrid quantum classical algorithms to demonstrate potentially useful applications of quantum computing in the NISQ era. Among the numerous hybrid algorithms, recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments, $\langle φ| \hat{\mathcal{H}}^n | φ\rangle$ ($n=1,2,\cdots$), with respect to quantum state $|φ\rangle$. In this tutorial, we will give a brief review of these quantum algorithms with focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies based on the quantum computed moments. Furthermore, we will present a tutorial to show how we can measure and compute the Hamiltonian moments of a four-site Heisenberg model, and compute the energy and magnetization of the model utilizing the imaginary time evolution in the real IBM-Q NISQ hardware environment. Along this line, we will further discuss some practical issues associated with these algorithms. We will conclude this tutorial review by overviewing some possible developments and applications in this direction in the near future.
Bo Peng, Wei Wang, Jing Dong, Tieniu Tan
Learning to reconstruct 3D shapes using 2D images is an active research topic, with benefits of not requiring expensive 3D data. However, most work in this direction requires multi-view images for each object instance as training supervision, which oftentimes does not apply in practice. In this paper, we relax the common multi-view assumption and explore a more challenging yet more realistic setup of learning 3D shape from only single-view images. The major difficulty lies in insufficient constraints that can be provided by single view images, which leads to the problem of pose entanglement in learned shape space. As a result, reconstructed shapes vary along input pose and have poor accuracy. We address this problem by taking a novel domain adaptation perspective, and propose an effective adversarial domain confusion method to learn pose-disentangled compact shape space. Experiments on single-view reconstruction show effectiveness in solving pose entanglement, and the proposed method achieves on-par reconstruction accuracy with state-of-the-art with higher efficiency.
Bo Peng, Cody Lamarche, Gordon Stacey, Thomas Nikola, Amit Vishwas, Carl Ferkinhoff, Christopher Rooney, Catherine Ball, Drew Brisbin, James Higdon, Sarah Higdon
Dec 18, 2020·astro-ph.GA·PDF The Nitrogen-to-Oxygen (N/O) abundance ratio is an important diagnostic of galaxy evolution since the ratio is closely tied to the growth of metallicity and the star formation history in galaxies. Estimates for the N/O ratio are traditionally accomplished with optical lines that could suffer from extinction and excitation effects, so the N/O ratio is arguably measured better through far-infrared (far-IR) fine-structure lines. Here we show that the [N III]57$μ$m/[O III]52$μ$m line ratio, denoted $N3O3$, is a physically robust probe of N/O. This parameter is insensitive to gas temperature and only weakly dependent on electron density. Though it has a dependence on the hardness of the ionizing radiation field, we show that it is well corrected by including the [Ne III]15.5$μ$m/[Ne II]12.8$μ$m line ratio. We verify the method, and characterize its intrinsic uncertainties by comparing the results to photoionization models. We then apply our method to a sample of nearby galaxies using new observations obtained with SOFIA/FIFI-LS in combination with available Herschel/PACS data, and the results are compared with optical N/O estimates. We find evidence for a systematic offset between the far-IR and optically derived N/O ratio. We argue this is likely due to that our far-IR method is biased towards younger and denser H II regions, while the optical methods are biased towards older H II regions as well as diffuse ionized gas. This work provides a local template for studies of ISM abundance in the early Universe.
Bo Peng, Karol Kowalski
Jun 17, 2022·quant-ph·PDF Non-unitary theories are commonly seen in the classical simulations of quantum systems. Among these theories, the method of moments of coupled-cluster equations (MMCCs) and the ensuing classes of the renormalized coupled-cluster (CC) approaches have evolved into one of the most accurate approaches to describe correlation effects in various quantum systems. The MMCC formalism provides an effective way for correcting energies of approximate CC formulations (parent theories) using moments, or CC equations, that are not used to determine approximate cluster amplitudes. In this paper, we propose a quantum algorithm for computing MMCC ground-state energies that provide two main advantages over classical computing or other quantum algorithms: (i) the possibility of forming superpositions of CC moments of arbitrary ranks in the entire Hilbert space and using an arbitrary form of the parent cluster operator for MMCC expansion; and (ii) significant reduction in the number of measurements in quantum simulation through a compact unitary representation for a generally non-unitary operator. We illustrate the robustness of our approach over a broad class of test cases, including ~40 molecular systems with varying basis sets encoded using 4~40 qubits, and exhibit the detailed MMCC analysis for the 8-qubit half-filled, four-site, single impurity Anderson model and 12-qubit hydrogen fluoride molecular system from the corresponding noise-free and noisy MMCC quantum computations. We also outline the extension of MMCC formalism to the case of unitary CC wave function ansatz.
Guang Hua Duan, Xiang Fan, Ken-ichi Hikasa, Bo Peng, Jin Min Yang
In the minimal supersymmetric model, the coannihilation of the lighter stop $\tilde{t}_1$ and bino-like dark matter $χ$ provides a feasible way to accommodate the correct dark matter relic abundance. In this scenario, due to the compressed masses, $\tilde{t}_1$ merely appears as missing energy at the LHC and thus the pair production of $\tilde{t}_1$ can only be probed by requiring an associated energetic jet. Meanwhile, since $\tilde{t}_2$ and $\tilde{b}_1$ are correlated in mass and mixing with $\tilde{t}_1$, the production of $\tilde{t}_2\tilde{t}_2^*$ or $\tilde{b}_1\tilde{b}_1^*$, each of which dominantly decays into $\tilde{t}_1$ plus $Z$, $h$ or $W$ boson, may serve as a complementary probe. We examine all these processes at the HL-LHC and find that the $2σ$ sensitivity to $χ$ mass can be as large as about 570 GeV, 600 GeV and 1.1 TeV from the production process of $\tilde{t}_1\tilde{t}_1^*+{\rm jet}$, $\tilde{t}_2\tilde{t}_2^*$ and $\tilde{b}_1\tilde{b}_1^*$, respectively.
Muqing Zheng, Bo Peng, Nathan Wiebe, Ang Li, Xiu Yang, Karol Kowalski
Dec 19, 2022·quant-ph·PDF This paper discusses quantum algorithms for the generator coordinate method (GCM) that can be used to benchmark molecular systems. The GCM formalism defined by exponential operators with exponents defined through generators of the Fermionic U(N) Lie algebra (Thouless theorem) offers a possibility of probing large sub-spaces using low-depth quantum circuits. In the present studies, we illustrate the performance of the quantum algorithm for constructing a discretized form of the Hill-Wheeler equation for ground and excited state energies. We also generalize the standard GCM formulation to multi-product extension that when collective paths are properly probed, can systematically introduce higher rank effects and provide elementary mechanisms for symmetry purification when generator states break the spatial or spin symmetries. The GCM quantum algorithms also can be viewed as an alternative to existing variational quantum eigensolvers, where multi-step classical optimization algorithms are replaced by a single-step procedure for solving the Hill-Wheeler eigenvalue problem.
Bo Peng, Hao Zhang, Hezhu Shao, Yuanfeng Xu, Xiangchao Zhang, Heyuan Zhu
The intrinsic lattice thermal conductivity of MoS$_2$ is an important aspect in the design of MoS$_2$-based nanoelectronic devices. We investigate the lattice dynamics properties of MoS$_2$ by first principles calculations. The intrinsic thermal conductivity of single-layer MoS$_2$ is calculated using the Boltzmann transport equation for phonons. The obtained thermal conductivity agrees well with the measurements. The contributions of acoustic and optical phonons to the lattice thermal conductivity are evaluated. The size dependence of thermal conductivity is investigated as well.
Zichang He, Bo Peng, Yuri Alexeev, Zheng Zhang
Aug 28, 2023·quant-ph·PDF Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is that quantum noise is highly unstable and thus it is likely to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step towards improving the reliability of VQAs influenced by shifted noise from the parameter optimization perspective.
Bo Peng, Xinyuan Chen, Yaohui Wang, Chaochao Lu, Yu Qiao
Recent works have successfully extended large-scale text-to-image models to the video domain, producing promising results but at a high computational cost and requiring a large amount of video data. In this work, we introduce ConditionVideo, a training-free approach to text-to-video generation based on the provided condition, video, and input text, by leveraging the power of off-the-shelf text-to-image generation methods (e.g., Stable Diffusion). ConditionVideo generates realistic dynamic videos from random noise or given scene videos. Our method explicitly disentangles the motion representation into condition-guided and scenery motion components. To this end, the ConditionVideo model is designed with a UNet branch and a control branch. To improve temporal coherence, we introduce sparse bi-directional spatial-temporal attention (sBiST-Attn). The 3D control network extends the conventional 2D controlnet model, aiming to strengthen conditional generation accuracy by additionally leveraging the bi-directional frames in the temporal domain. Our method exhibits superior performance in terms of frame consistency, clip score, and conditional accuracy, outperforming other compared methods.
Bo Peng, Jun Hu, Jingtao Zhou, Xuan Gao, Juyong Zhang
Recently, many works have been proposed to utilize the neural radiance field for novel view synthesis of human performers. However, most of these methods require hours of training, making them difficult for practical use. To address this challenging problem, we propose IntrinsicNGP, which can train from scratch and achieve high-fidelity results in few minutes with videos of a human performer. To achieve this target, we introduce a continuous and optimizable intrinsic coordinate rather than the original explicit Euclidean coordinate in the hash encoding module of instant-NGP. With this novel intrinsic coordinate, IntrinsicNGP can aggregate inter-frame information for dynamic objects with the help of proxy geometry shapes. Moreover, the results trained with the given rough geometry shapes can be further refined with an optimizable offset field based on the intrinsic coordinate.Extensive experimental results on several datasets demonstrate the effectiveness and efficiency of IntrinsicNGP. We also illustrate our approach's ability to edit the shape of reconstructed subjects.
Sahil Gulania, Zichang He, Bo Peng, Niranjan Govind, Yuri Alexeev
Dec 13, 2022·quant-ph·PDF QuYBE is an open-source algebraic compiler for the compression of quantum circuits. It has been applied for the efficient simulation of the Heisenberg Hamiltonian on quantum computers. Currently, it can simulate the time dynamics of one-dimensional chains. It includes modules to generate the quantum circuits for the above as well as produce the compressed circuits, which are independent of the time step. It utilizes the Yang-Baxter equation (YBE) to perform the compression. QuYBE enables users to seamlessly design, execute, and analyze the time dynamics of the Heisenberg Hamiltonian on quantum computers. QuYBE is the first step toward making the YBE technique available to a broader community of scientists from multiple domains. The QuYBE compiler is available at https://github.com/ZichangHe/QuYBE
Bo Peng, Gunnar F. Lange, Daniel Bennett, Kang Wang, Robert-Jan Slager, Bartomeu Monserrat
Ultrathin bismuth exhibits rich physics including strong spin-orbit coupling, ferroelectricity, nontrivial topology, and light-induced structural dynamics. We use \textit{ab initio} calculations to show that light can induce structural transitions to four transient phases in bismuth monolayers. These light-induced phases exhibit nontrivial topological character, which we illustrate using the recently introduced concept of spin bands and spin-resolved Wilson loops. Specifically, we find that the topology changes via the closing of the electron and spin band gaps during photo-induced structural phase transitions, leading to distinct edge states. Our study provides strategies to tailor electronic and spin topology via ultrafast control of photo-excited carriers and associated structural dynamics.
Yuanfeng Xu, Bo Peng, Hao Zhang, Hezhu Shao, Rongjun Zhang, Hongliang Lu, David Wei Zhang, Heyuan Zhu
Recently a stable monolayer of antimony in buckled honeycomb structure called antimonene was successfully grown on 3D topological insulator Bi$_2$Te$_3$ and Sb$_2$Te$_3$, which displays semiconducting properties. By first principle calculations, we systematically investigate the phononic, electronic and optical properties of $α-$ and $β-$ allotropes of monolayer arsenene/antimonene. We investigate the dynamical stabilities of these four materials by considering the phonon dispersions. The obtained electronic structures reveal the direct band gap of monolayer $α-$As/Sb and indirect band gap of $β-$As/Sb. Significant absorption is observed in $α-$Sb, which can be used as a broad saturable absorber.
Muqing Zheng, Bo Peng, Ang Li, Xiu Yang, Karol Kowalski
Dec 12, 2023·quant-ph·PDF Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.