arXiv subjects

Kecheng Liu

Publications and source records attributed to Kecheng Liu.

18 recordsLinked to original sources

arXiv2025

Dynamics Simulation of Arbitrary Non-Hermitian Systems Based on Quantum Monte Carlo

Non-Hermitian quantum systems exhibit unique properties and hold significant promise for diverse applications, yet their dynamical simulation poses a particular challenge due to intrinsic openness and non-unitary evolution. Here, we introduce a hybrid classical-quantum algorithm based on Quantum Monte Carlo (QMC) for simulating the dynamics of arbitrary time-dependent non-Hermitian systems. Notably, this approach constitutes a natural extension of the quantum imaginary-time evolution (QITE) algorithm. This algorithm combines the advantages of both classical and quantum computation and exhibits good applicability and adaptability, making it promising for simulating arbitrary non-Hermitian systems such as PT-symmetric systems, non-physical processes, and open quantum systems. To validate the algorithm, we applied it to the dynamic simulation of open quantum systems and achieved the desired results.

quant-ph↗

arXiv2025

Distinct amplitude mode dynamics upon resonant and off-resonant excitation across the charge density wave energy gap in LaTe3 investigated by time- and angle-resolved photoemission spectroscopy

Non-equilibrium states generated by ultrafast laser pulses are characterized by specific phenomena that are not accessible in static measurements. Previous time- and angle-resolved photoemission spectroscopy (TARPES) studies on rare-earth tritelluride materials have revealed the laser-driven melting of the charge density wave order as well as its collective amplitude mode excitation. Variation of the excess energy deposited by optical pumping in the material promises pathways to control the dynamic material response. To this end, we use an optical parametric amplifier to generate a tunable pump photon energy. Studying LaTe3 we compare the dynamics driven by pumping resonantly across the charge density wave energy gap with the effect of pumping at a twice higher photon energy in a TARPES pump-probe experiment. We clearly identify a pump photon energy dependent behavior. At the larger pump photon energy, the excess electronic energy generates lattice heating mediated by e-ph coupling and softening of the amplitude mode frequency from 3 to 2 THz. Remarkably, the resonant pumping across the CDW gap results in a time-independent amplitude mode frequency. We conclude that the resonant excitation across the energy gap excites the amplitude mode selectively while additional electronic excess energy deposited at higher pump photon energy modifies the crystal properties transiently by incoherent dissipative processes.

cond-mat.str-el↗

arXiv2025

Quantum Error Mitigation for Sampling Algorithms

Recent experimental breakthroughs have signalled the imminent arrival of the early fault-tolerant era. However, for a considerable period in the foreseeable future, relying solely on quantum error correction for full error suppression will remain extremely challenging due to its substantial hardware overhead. Additional help from quantum error mitigation (QEM) is essential for bridging this gap towards achieving quantum advantage. The application of QEM has so far been restricted to expectation value estimation, leaving its extension to sampling-based algorithms -- which is expected to play a pivotal role in the early fault-tolerant era -- an unresolved challenge. In this work, we present a framework for applying any QEM techniques to obtain the error-mitigated output distribution, showing that this incurs no greater cost than estimating a single observable. We also devised a way to sample from this distribution and constructed an explicit scheme for applying any QEM methods to quantum phase estimation, which can be generalised to other sampling algorithms. Numerical experiments were conducted to validate the efficacy of these methods. We believe our methods significantly broaden the scope of QEM, extending its applicability to most algorithms of practical interest and forming a crucial step towards realising quantum advantage.

quant-ph↗

arXiv2025

Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction

Referring Remote Sensing Image Segmentation (RRSIS) is critical for ecological monitoring, urban planning, and disaster management, requiring precise segmentation of objects in remote sensing imagery guided by textual descriptions. This task is uniquely challenging due to the considerable vision-language gap, the high spatial resolution and broad coverage of remote sensing imagery with diverse categories and small targets, and the presence of clustered, unclear targets with blurred edges. To tackle these issues, we propose \ours, a novel framework designed to bridge the vision-language gap, enhance multi-scale feature interaction, and improve fine-grained object differentiation. Specifically, \ours introduces: (1) the Bidirectional Spatial Correlation (BSC) for improved vision-language feature alignment, (2) the Target-Background TwinStream Decoder (T-BTD) for precise distinction between targets and non-targets, and (3) the Dual-Modal Object Learning Strategy (D-MOLS) for robust multimodal feature reconstruction. Extensive experiments on the benchmark datasets RefSegRS and RRSIS-D demonstrate that \ours achieves state-of-the-art performance. Specifically, \ours improves the overall IoU (oIoU) by 3.76 percentage points (80.57) and 1.44 percentage points (79.23) on the two datasets, respectively. Additionally, it outperforms previous methods in the mean IoU (mIoU) by 5.37 percentage points (67.95) and 1.84 percentage points (66.04), effectively addressing the core challenges of RRSIS with enhanced precision and robustness.

cs.CV↗

arXiv2025

Robust Mølmer-Sørensen Gate Against Symmetric and Asymmetric Errors

To achieve the entangling gate fidelity above the quantum error correction threshold, it is critical to suppress errors due to experimental imperfection. We consider the Mølmer-Sørensen gates in trapped-ion systems, and develop a general approach to suppress a family of noise sources that appeared as either symmetric or asymmetric errors. Using the time-average displacement minimization technique, both symmetric error and displacement-dependent part of the asymmetric errors are eliminated. Then, by analyzing the tangent space of displacement-independent errors, we obtain the analytic form of the generators of the correction operator to the remaining error terms. We then develop a compensation pulse to fully suppress the remaining displacement-independent errors. The effectiveness of our scheme is further verified by numerical analysis, through which we observe a significant reduction of entangling gate infidelity. Our findings enhance gate fidelity and robustness to noise for ion trap quantum computing.

quant-ph↗

arXiv2024

ECDQC: Efficient Compilation for Distributed Quantum Computing with Linear Layout

In this paper, we propose an efficient compilation method for distributed quantum computing (DQC) using the Linear Nearest Neighbor (LNN) architecture. By exploiting the LNN topology's symmetry, we optimize quantum circuit compilation for High Local Connectivity, Sparse Full Connectivity (HLC-SFC) algorithms like Quantum Approximate Optimization Algorithm (QAOA) and Quantum Fourier Transform (QFT). We also utilize dangling qubits to minimize non-local interactions and reduce SWAP gates. Our approach significantly decreases compilation time, gate count, and circuit depth, improving scalability and robustness for large-scale quantum computations.

quant-ph↗

arXiv2024

Unveiling van Hove singularity modulation and fluctuated charge order in kagome superconductor $\rm{CsV_3Sb_5}$ via time-resolved ARPES

Kagome superconductor CsV3Sb5, which exhibits intertwined unconventional charge density wave (CDW) and superconductivity, has garnered significant attention recently. Despite extensive static studies, the nature of these exotic electronic orders remains elusive. In this study, we investigate the non-equilibrium electronic structure of CsV3Sb5 via time- and angle-resolved photoemission spectroscopy. Our results reveal that upon laser excitation, the van Hove singularities immediately shift towards the Fermi level and subsequently oscillate in sync with a 1.3 THz coherent phonon mode. By analyzing the coherent intensity oscillations in the energy-momentum (E-k) map, we find that this coherent phonon is strongly coupled with electronic bands from both Sb and V orbitals. While typically observable only in the CDW state, remarkably, we find that the 1.3-THz coherent phonon mode can be persistently excited at temperatures above T_CDW, suggesting the potential existence of fluctuated CDW in CsV3Sb5. These findings enhance our understanding of the unconventional CDW control of kagome superconductivity.

cond-mat.mtrl-sci↗

arXiv2024

Separable Power of Classical and Quantum Learning Protocols Through the Lens of No-Free-Lunch Theorem

The No-Free-Lunch (NFL) theorem, which quantifies problem- and data-independent generalization errors regardless of the optimization process, provides a foundational framework for comprehending diverse learning protocols' potential. Despite its significance, the establishment of the NFL theorem for quantum machine learning models remains largely unexplored, thereby overlooking broader insights into the fundamental relationship between quantum and classical learning protocols. To address this gap, we categorize a diverse array of quantum learning algorithms into three learning protocols designed for learning quantum dynamics under a specified observable and establish their NFL theorem. The exploited protocols, namely Classical Learning Protocols (CLC-LPs), Restricted Quantum Learning Protocols (ReQu-LPs), and Quantum Learning Protocols (Qu-LPs), offer varying levels of access to quantum resources. Our derived NFL theorems demonstrate quadratic reductions in sample complexity across CLC-LPs, ReQu-LPs, and Qu-LPs, contingent upon the orthogonality of quantum states and the diagonality of observables. We attribute this performance discrepancy to the unique capacity of quantum-related learning protocols to indirectly utilize information concerning the global phases of non-orthogonal quantum states, a distinctive physical feature inherent in quantum mechanics. Our findings not only deepen our understanding of quantum learning protocols' capabilities but also provide practical insights for the development of advanced quantum learning algorithms.

quant-ph↗

arXiv2024

Towards Advantages of Parameterized Quantum Pulses

The advantages of quantum pulses over quantum gates have attracted increasing attention from researchers. Quantum pulses offer benefits such as flexibility, high fidelity, scalability, and real-time tuning. However, while there are established workflows and processes to evaluate the performance of quantum gates, there has been limited research on profiling parameterized pulses and providing guidance for pulse circuit design. To address this gap, our study proposes a set of design spaces for parameterized pulses, evaluating these pulses based on metrics such as expressivity, entanglement capability, and effective parameter dimension. Using these design spaces, we demonstrate the advantages of parameterized pulses over gate circuits in the aspect of duration and performance at the same time thus enabling high-performance quantum computing. Our proposed design space for parameterized pulse circuits has shown promising results in quantum chemistry benchmarks.

quant-ph↗

arXiv2024

Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm

In recent years, quantum computing has emerged as a transformative force in the field of combinatorial optimization, offering novel approaches to tackling complex problems that have long challenged classical computational methods. Among these, the Quantum Approximate Optimization Algorithm (QAOA) stands out for its potential to efficiently solve the Max-Cut problem, a quintessential example of combinatorial optimization. However, practical application faces challenges due to current limitations on quantum computational resource. Our work optimizes QAOA initialization, using Graph Neural Networks (GNN) as a warm-start technique. This sacrifices affordable computational resource on classical computer to reduce quantum computational resource overhead, enhancing QAOA's effectiveness. Experiments with various GNN architectures demonstrate the adaptability and stability of our framework, highlighting the synergy between quantum algorithms and machine learning. Our findings show GNN's potential in improving QAOA performance, opening new avenues for hybrid quantum-classical approaches in quantum computing and contributing to practical applications.

quant-ph↗

arXiv2024

Time- and angle-resolved photoemission spectroscopy with wavelength-tunable pump and extreme ultraviolet probe enabled by twin synchronized amplifiers

We describe a setup for time- and angle-resolved photoemission spectroscopy with wavelength-tunable excitation and extreme ultraviolet probe. It is enabled by using the 10 kHz twin Ti:sapphire amplifiers seeded by the common Ti:sapphire oscillator. The typical probe energy is 21.7 eV, and the wavelength of the pump excitation is tuned between 2400 and 1200 nm by using the optical parametric amplifier. The total energy resolution of 133 meV is achieved, and the time resolution is dependent on the wavelength for the pump, typically better than 100 fs. This system enables the pump energy to be matched with a specific interband transition and to probe a wider energy-momentum space. We present the results for the prototypical materials of highly oriented pyrolytic graphite and Bi2Se3 to show the performance of our system.

cond-mat.mtrl-sci↗

arXiv2023

Nodeless electron pairing in CsV$_3$Sb$_5$-derived kagome superconductors

The newly discovered kagome superconductors represent a promising platform for investigating the interplay between band topology, electronic order, and lattice geometry. Despite extensive research efforts on this system, the nature of the superconducting ground state remains elusive. In particular, consensus on the electron pairing symmetry has not been achieved so far, in part owing to the lack of a momentum-resolved measurement of the superconducting gap structure. Here we report the direct observation of a nodeless, nearly isotropic, and orbital-independent superconducting gap in the momentum space of two exemplary CsV$_3$Sb$_5$-derived kagome superconductors -- Cs(V$_{0.93}$Nb$_{0.07}$)$_3$Sb$_5$ and Cs(V$_{0.86}$Ta$_{0.14}$)$_3$Sb$_5$, using ultrahigh resolution and low-temperature angle-resolved photoemission spectroscopy (ARPES). Remarkably, such a gap structure is robust to the appearance or absence of charge order in the normal state, tuned by isovalent Nb/Ta substitutions of V. Moreover, we observe a signature of the time-reversal symmetry (TRS) breaking inside the superconducting state, which extends the previous observation of TRS-breaking CDW in the kagome lattice. Our comprehensive characterizations of the superconducting state provide indispensable information on the electron pairing of kagome superconductors, and advance our understanding of unconventional superconductivity and intertwined electronic orders.

cond-mat.supr-con↗

arXiv2022

Unbiased random circuit compiler for time-dependent Hamiltonian simulation

Time-dependent Hamiltonian simulation (TDHS) is a critical task in quantum computing. Existing algorithms are generally biased with a small algorithmic error $\varepsilon$, and the gate complexity scales as $O(\text{poly}(1/\varepsilon))$ for product formula-based methods and could be improved to be polylogarithmic with complicated circuit constructions. Here, we develop an unbiased random compiler for TDHS by combining Dyson expansion, an unbiased continuous sampling method for quantum evolution, and leading order rotations, and it is free from algorithmic errors. Our method has the single- and two-qubit gate complexity $O(Λ^2)$ with a constant sampling overhead, where $Λ$ is the time integration of the Hamiltonian strength. We perform numerical simulations for a spin model under the interaction picture and the adiabatic ground state preparation for molecular systems. In both examples, we observe notable improvements of our method over existing ones. Our work paves the way to efficient realizations of TDHS.

quant-ph↗

arXiv2022

Photo-induced nonlinear band shift and valence transition in SmS

The photo-induced band structure variation of a rare-earth-based semiconductor, samarium monosulfide (SmS), was investigated using high-harmonic-generation laser-based time-resolved photoelectron spectroscopy. A nonlinear photo-induced band shift of the Sm 4f multiplets was observed. The first one is a shift to the high-binding-energy side due to a large surface photovoltage (SPV) effect of approximately 93 meV, comparable to the size of the bulk band gap, with a much longer relaxation time than 0.1 ms. The second one is an ultrafast band shift to the low binding energy side, which is in the opposite direction to the SPV shift, suggesting an ultrafast valence transition from divalent to trivalent Sm ions due to photo-excitation. The latter energy shift was approximately 58 meV, which is consistent with the energy gap shift from ambient pressure to the boundary between the black insulator and golden metallic phase with the application of pressure. This suggests that the photo-induced valence transition can reach the phase boundary, but other effects are necessary to realize the golden metallic phase.

cond-mat.mtrl-sci↗

arXiv2021

Information Cocoons in Online Navigation

Social media and online navigation bring us enjoyable experience in accessing information, and simultaneously create information cocoons (ICs) in which we are unconsciously trapped with limited and biased information. We provide a formal definition of IC in the scenario of online navigation. Subsequently, by analyzing real recommendation networks extracted from Science, PNAS and Amazon websites, and testing mainstream algorithms in disparate recommender systems, we demonstrate that similarity-based recommendation techniques result in ICs, which suppress the system navigability by hundreds of times. We further propose a flexible recommendation strategy that solves the IC-induced problem and improves retrieval accuracy in navigation, demonstrated by simulations on real data and online experiments on the largest video website in China.

physics.soc-ph↗

arXiv2021

Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack

To explore the robustness of recommender systems, researchers have proposed various shilling attack models and analyzed their adverse effects. Primitive attacks are highly feasible but less effective due to simplistic handcrafted rules, while upgraded attacks are more powerful but costly and difficult to deploy because they require more knowledge from recommendations. In this paper, we explore a novel shilling attack called Graph cOnvolution-based generative shilling ATtack (GOAT) to balance the attacks' feasibility and effectiveness. GOAT adopts the primitive attacks' paradigm that assigns items for fake users by sampling and the upgraded attacks' paradigm that generates fake ratings by a deep learning-based model. It deploys a generative adversarial network (GAN) that learns the real rating distribution to generate fake ratings. Additionally, the generator combines a tailored graph convolution structure that leverages the correlations between co-rated items to smoothen the fake ratings and enhance their authenticity. The extensive experiments on two public datasets evaluate GOAT's performance from multiple perspectives. Our study of the GOAT demonstrates technical feasibility for building a more powerful and intelligent attack model with a much-reduced cost, enables analysis the threat of such an attack and guides for investigating necessary prevention measures.

cs.LG↗

arXiv2019

Diffie-Hellman in the Air: A Link Layer Approach for In-Band Wireless Pairing

Key establishment is one fundamental issue in wireless security. The widely used Diffie-Hellman key exchange is vulnerable to the man-in-the-middle attack. This paper presents a novel in-band solution for defending the man-in-the-middle attack during the key establishment process for wireless devices. Our solution is based on the insight that an attacker inevitably affects the link layer behavior of the wireless channel, and this behavior change introduced by the attacker can be detected by the legitimate users. Specifically, we propose a key exchange protocol and its corresponding channel access mechanism for the protocol message transmission, in which the Diffie-Hellman parameter is transmitted multiple times in a row without being interrupted by other data transmission on the same wireless channel. The proposed key exchange protocol forces the MITM attacker to cause multiple packet collisions consecutively at the receiver side, which can then be monitored by the proposed detection algorithm. The performance of the proposed solution is validated through both theoretical analysis and simulation: the proposed solution is secure against the MITM attack and can achieve an arbitrarily low false positive ratio. This proposed link layer solution works completely in-band, and can be easily implemented on off-the-shelf wireless devices without the requirement of any special hardware.

cs.CR↗

arXiv1996

Cofinalities of elementary substructures of structures on aleph_omega

Let 0 n^*+1 be a function where X subseteq omega backslash (n^*+1) is infinite. Consider the following set S_f= {x subset aleph_omega : |x| <= aleph_{n^*} & (for all n in X)cf(x cap alpha_n)= aleph_{f(n)}}. The question, first posed by Baumgartner, is whether S_f is stationary in [alpha_omega]^{< aleph_{n^*+1}}. By a standard result, the above question can also be rephrased as certain transfer property. Namely, S_f is stationary iff for any structure A=< aleph_omega, ... > there's a B prec A such that |B|= aleph_{n^*} and for all n in X we have cf(B cap aleph_n)= aleph_{f(n)}. In this paper, we are going to prove a few results concerning the above question.

math.LO↗