Quantum Physics (quant-ph)

Abstract: Quantum computation architecture based on $d$-level systems, or qudits, has attracted considerable attention recently due to their enlarged Hilbert space. Extensive theoretical and experimental studies have addressed aspects of algorithms and benchmarking techniques for qudit-based quantum computation and quantum information processing. Here, we report a physical realization of qudit with upto 4 embedded levels in a superconducting transmon, demonstrating high-fidelity initialization, manipulation, and simultaneous multi-level readout. In addition to constructing SU($d$) operations and benchmarking protocols for quantum state tomography, quantum process tomography, and randomized benchmarking etc, we experimentally carry out these operations for $d=3$ and $d=4$. Moreover, we perform prototypical quantum algorithms and observe outcomes consistent with expectations. Our work will hopefully stimulate further research interest in developing manipulation protocols and efficient applications for quantum processors with qudits.

Abstract: Graph states are versatile resources for various quantum information processing tasks, including measurement-based quantum computing and quantum repeaters. Although the type-II fusion gate enables all-optical generation of graph states by combining small graph states, its non-deterministic nature hinders the efficient generation of large graph states. In this work, we present a graph-theoretical strategy to effectively optimize fusion-based generation of any given graph state, along with a Python package OptGraphState. Our strategy comprises three stages: simplifying the target graph state, building a fusion network, and determining the order of fusions. Utilizing this proposed method, we evaluate the resource overheads of random graphs and various well-known graphs. We expect that our strategy and software will assist researchers in developing and assessing experimentally viable schemes that use photonic graph states.

Abstract: We present a single-photon-sensitive spectrometer, based on a linear array of 512 single-photon avalanche diodes, with 0.04 nm spectral and 40 ps temporal resolutions. We employ a fast data-driven operation that allows direct measurement of time and frequency for simultaneous single photons. Combining excellent temporal and spectral resolution, our result is only a factor of ten above the Heisenberg Uncertainty Principle limit of hbar/2 for energy and time, despite the simplicity of our experimental setup. This work opens numerous applications in quantum photonics, especially when both spectral and temporal properties of single photons are exploited.

Abstract: Schr\"odinger's equation serves as a fundamental component in characterizing quantum systems, wherein both quantum state tomography and Hamiltonian learning are instrumental in comprehending and interpreting quantum systems. While numerous techniques exist for carrying out state tomography and learning Hamiltonians individually, no method has been developed to combine these two aspects. In this study, we introduce a new approach that employs the attention mechanism in transformer models to effectively merge quantum state tomography and Hamiltonian learning. By carefully choosing and preparing the training data, our method integrates both tasks without altering the model's architecture, allowing the model to effectively learn the intricate relationships between quantum states and Hamiltonian. We also demonstrate the effectiveness of our approach across various quantum systems, ranging from simple 2-qubit cases to more involved 2D antiferromagnetic Heisenberg structures. The data collection process is streamlined, as it only necessitates a one-way generation process beginning with state tomography. Furthermore, the scalability and few-shot learning capabilities of our method could potentially minimize the resources required for characterizing and optimizing quantum systems. Our research provides valuable insights into the relationship between Hamiltonian structure and quantum system behavior, fostering opportunities for additional studies on quantum systems and the advancement of quantum computation and associated technologies.

Abstract: In Layout Synthesis, the logical qubits of a quantum circuit are mapped to the physical qubits of a given quantum hardware platform, taking into account the connectivity of physical qubits. This involves inserting SWAP gates before an operation is applied on distant qubits. Optimal Layout Synthesis is crucial for practical Quantum Computing on current error-prone hardware: Minimizing the number of SWAP gates directly mitigates the error rates when running quantum circuits. In recent years, several approaches have been proposed for minimizing the required SWAP insertions. The proposed exact approaches can only scale to a small number of qubits. Proving that a number of swap insertions is optimal is much harder than producing near optimal mappings. In this paper, we provide two encodings for Optimal Layout Synthesis as a classical planning problem. We use optimal classical planners to synthesize the optimal layout for a standard set of benchmarks. Our results show the scalability of our approach compared to previous leading approaches. We can optimally map circuits with 7 qubits onto a 16 qubit platform, which could not be handled before by exact methods.

Abstract: Convex splitting is a powerful technique in quantum information theory used in proving the achievability of numerous information-processing protocols such as quantum state redistribution and quantum network channel coding. In this work, we establish a one-shot error exponent and a one-shot strong converse for convex splitting with trace distance as an error criterion. Our results show that the derived error exponent (strong converse exponent) is positive if and only if the rate is in (outside) the achievable region. This leads to new one-shot exponent results in various tasks such as communication over quantum wiretap channels, secret key distillation, one-way quantum message compression, quantum measurement simulation, and quantum channel coding with side information at the transmitter. We also establish a near-optimal one-shot characterization of the sample complexity for convex splitting, which yields matched second-order asymptotics. This then leads to stronger one-shot analysis in many quantum information-theoretic tasks.

Abstract: We show that the communication cost of quantum broadcast channel simulation under free entanglement assistance between the sender and the receivers is asymptotically characterized by an efficiently computable single-letter formula in terms of the channel's multipartite mutual information. Our core contribution is a new one-shot achievability result for multipartite quantum state splitting via multipartite convex splitting. As part of this, we face a general instance of the quantum joint typicality problem with arbitrarily overlapping marginals. The crucial technical ingredient to sidestep this difficulty is a conceptually novel multipartite mean-zero decomposition lemma, together with employing recently introduced complex interpolation techniques for sandwiched R\'enyi divergences. Moreover, we establish an exponential convergence of the simulation error when the communication costs are within the interior of the capacity region. As the costs approach the boundary of the capacity region moderately quickly, we show that the error still vanishes asymptotically.

Abstract: We propose a fully-passive twin-field quantum key distribution (QKD) setup where basis choice, decoy-state preparation and encoding are all implemented entirely by post-processing without any active modulation. Our protocol can remove the potential side-channels from both source modulators and detectors, and additionally retain the high key rate advantage offered by twin-field QKD, thus offering great implementation security and good performance. Importantly, we also propose a post-processing strategy that uses mismatched phase slices and minimizes the effect of sifting. We show with numerical simulation that the new protocol can still beat the repeaterless bound and provide satisfactory key rate.

Abstract: Optically-active spin defects in hexagonal boron nitride (hBN) are promising quantum systems for the design of two-dimensional quantum sensing units offering optimal proximity to the sample being probed. In this work, we first demonstrate that the electron spin resonance frequencies of boron vacancy centres (V$_\text{B}^-$) can be detected optically in the limit of few-atomic-layer thick hBN flakes despite the nanoscale proximity of the crystal surface that often leads to a degradation of the stability of solid-state spin defects. We then analyze the variations of the electronic spin properties of V$_\text{B}^-$ centres with the hBN thickness with a focus on (i) the zero-field splitting parameters, (ii) the optically-induced spin polarization rate and (iii) the longitudinal spin relaxation time. This work provides important insights into the properties of V$_\text{B}^-$ centres embedded in ultrathin hBN flakes, which are valuable for future developments of foil-based quantum sensing technologies.

Abstract: Shor's algorithm, which was proposed by Peter Shor [Proceedings of the 35th Annual Symposium on Foundations of Computer Science, 1994, pp. 124--134], is considered as one of the most significant quantum algorithms. Shor's algorithm can factor large integers with a certain probability of success in polynomial time. However, Shor's algorithm requires an unbearable amount of qubits and circuit depth in the NISQ (Noisy Intermediate-scale Quantum) era. To reduce the resources required for Shor's algorithm, we propose a new distributed quantum-classical hybrid order-finding algorithm for Shor's algorithm. The traditional order-finding algorithm needs to obtain an estimation of some $\dfrac{s}{r}$, where $r$ is the ``order'' and $s\in\{0,1,\cdots,r-1\}$. In our distributed algorithm, we use $k$ computers to estimate partial bits of $\dfrac{s}{r}$ separately. In order to reduce the errors of measuring results of these computers, we use classical programs to correct the measuring results of each computer to a certain extent. Compared with the traditional Shor's algorithm, our algorithm reduces nearly $(1-\dfrac{1}{k})L-\log_2k$ qubits for each computer when factoring an $L$-bit integer. Also, our algorithm reduces gate complexity and circuit depth to some extent for each computer. The communication complexity of our algorithm is $O(kL)$.

Abstract: We show that a simple telescoping sum trick, together with the triangle inequality and a tensorisation property of expected-contractive coefficients of random channels, allow us to achieve general simultaneous decoupling for multiple users via local actions. Employing both old [Dupuis et al. Commun. Math. Phys. 328:251-284 (2014)] and new methods [Dupuis, arXiv:2105.05342], we obtain bounds on the expected deviation from ideal decoupling either in the one-shot setting in terms of smooth min-entropies, or the finite block length setting in terms of R\'enyi entropies. These bounds are essentially optimal without the need to address the simultaneous smoothing conjecture, which remains unresolved. This leads to one-shot, finite block length, and asymptotic achievability results for several tasks in quantum Shannon theory, including local randomness extraction of multiple parties, multi-party assisted entanglement concentration, multi-party quantum state merging, and quantum coding for the quantum multiple access channel. Because of the one-shot nature of our protocols, we obtain achievability results without the need for time-sharing, which at the same time leads to easy proofs of the asymptotic coding theorems. We show that our one-shot decoupling bounds furthermore yield achievable rates (so far only conjectured) for multi-user randomness extraction, multipartite state merging and quantum multiple access channel communication in compound settings, that is for only partially known i.i.d. source or channel.

Abstract: Model-based quantum optimal control promises to solve a wide range of critical quantum technology problems within a single, flexible framework. The catch is that highly-accurate models are needed if the optimized controls are to meet the exacting demands set by quantum engineers. A practical alternative is to directly calibrate control parameters by taking device data and tuning until success is achieved. In quantum computing, gate errors due to inaccurate models can be efficiently polished if the control is limited to a few (usually hand-designed) parameters; however, an alternative tool set is required to enable efficient calibration of the complicated waveforms potentially returned by optimal control. We propose an automated model-based framework for calibrating quantum optimal controls called Learning Iteratively for Feasible Tracking (LIFT). LIFT achieves high-fidelity controls despite parasitic model discrepancies by precisely tracking feasible trajectories of quantum observables. Feasible trajectories are set by combining black-box optimal control and the bilinear dynamic mode decomposition, a physics-informed regression framework for discovering effective Hamiltonian models directly from rollout data. Any remaining tracking errors are eliminated in a non-causal way by applying model-based, norm-optimal iterative learning control to subsequent rollout data. We use numerical experiments of qubit gate synthesis to demonstrate how LIFT enables calibration of high-fidelity optimal control waveforms in spite of model discrepancies.

Abstract: We propose free-electron Rabi oscillation by creating an isolated two-level system in a synthetic energy space induced by laser. The {\pi}/2-pulse and {\pi}-pulse in synthetic Rabi dynamics can function as 'beam splitters' and 'mirrors' for free-electron interferometry, allowing us to detect local electromagnetic fields and plasmonic excitations. When the coupling field is quantized, we can observe quantum and vacuum Rabi oscillations of the two-level electron, which can be used to investigate the quantum statistics of optical excitations and electron-photon entanglement. Recent advances in laser control of electron microscopes and spectroscopes makes the experimental detection of synthetic Rabi oscillations possible. However, observing the quantum Rabi oscillation of electrons remains challenging. Our work has the potential to advance various fundamentals and applications of resonant light-matter interactions between low-energy electrons and quatum light.

Abstract: Hyper-entanglement between two or more photonic degrees of freedom (DOF) can enhance and enable new quantum protocols by allowing each DOF to perform the task it is optimally suited for. Here we demonstrate the generation of photon pairs hyper-entangled between pulse modes and frequency bins. The pulse modes are generated via parametric downconversion in a domain-engineered crystal and subsequently entangled to two frequency bins via a spectral mapping technique. The resulting hyper-entangled state is characterized and verified via measurement of its joint spectral intensity and non-classical two-photon interference patterns from which we infer its spectral phase. The protocol combines the robustness to loss, intrinsic high dimensionality and compatibility with standard fiber-optic networks of the energy-time DOF with the ability of hyper-entanglement to increase the capacity and efficiency of the quantum channel, already exploited in recent experimental applications in both quantum information and quantum computation.

Abstract: Quantum systems loose their properties due to information leaking into environment. On the other hand, we perceive the outer world through the environment. We show here that there is a gap between what leaks into the environment and what can be extracted from it. We quantify this gap, using the prominent example of the Caldeira-Leggett model, by demonstrating that information extraction is limited by its own lengthscale, called distinguishability length, larger than the celebrated thermal de Broglie wavelength, governing the decoherence. We also introduce a new integral kernel, called Quantum Fisher Information kernel, complementing the well-known dissipation and noise kernels, and show a type of disturbance-information gain trade-off, similar to the famous fluctuation-dissipation relation. Our results show that the destruction of quantum coherences and indirect observations happen at two different scales with a "gray zone" in between. This puts intrinsic limitations on capabilities of indirect observations.

Abstract: We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ~ 600 years using exact methods, whereas our quantum computer, Jiuzhang 3.0, takes only 1.27 us to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier ~ 3.1*10^10 years.

Abstract: Electron transfer within and between molecules is crucial in chemistry, biochemistry, and energy science. This study describes a quantum simulation method that explores the influence of light polarization on the electron transfer between two molecules. By implementing precise and coherent control among the quantum states of trapped atomic ions, we can induce quantum dynamics that mimic the electron transfer dynamics in molecules. We use $3$-level systems (qutrits), rather than traditional two-level systems (qubits) to enhance the simulation efficiency and realize high-fidelity simulations of electron transfer dynamics. We treat the quantum interference between the electron coupling pathways from a donor with two degenerate excited states to an acceptor and analyze the transfer efficiency. We also examine the potential error sources that enter the quantum simulations. The trapped ion systems have favorable scalings with system size compared to those of classical computers, promising access to electron-transfer simulations of increasing richness.

Abstract: In lumped-element electrical circuit theory, the problem of solving Maxwell's equations in the presence of media is reduced to two sets of equations. Those addressing the local dynamics of a confined energy density, the constitutive equations, encapsulating local geometry and dynamics, and those that enforce the conservation of charge and energy in a larger scale that we express topologically, the Kirchhoff equations. Following a consistent geometrical description, we develop a new and systematic way to write the dynamics of general lumped-element electrical circuits as first order differential equations derivable from a Lagrangian and a Rayleigh dissipation function. Leveraging the Faddeev-Jackiw method, we identify and classify all singularities that arise in the search for Hamiltonian descriptions of general networks. Furthermore we provide systematics to solve those singularities, which is a key problem in the context of canonical quantization of superconducting circuits. The core of our solution relies on the correct identification of the reduced manifold in which the circuit state is expressible, e.g., a mix of flux and charge degrees of freedom, including the presence of compact ones. We apply the fully programmable method to obtain (canonically quantizable) Hamiltonian descriptions of nonlinear and nonreciprocal circuits which would be cumbersome/singular if pure node-flux or loop-charge variables are used as a starting configuration space. This work unifies diverse existent geometrical pictures of electrical network theory, and will prove useful, for instance, to automatize the computation of exact Hamiltonian descriptions of superconducting quantum chips.

Abstract: We present a technique for enhancing the estimation of quantum state properties by incorporating approximate prior knowledge about the quantum state of interest. This method involves performing randomized measurements on a quantum processor and comparing the results with those obtained from a classical computer that stores an approximation of the quantum state. We provide unbiased estimators for expectation values of multi-copy observables and present performance guarantees in terms of variance bounds which depend on the prior knowledge accuracy. We demonstrate the effectiveness of our approach through numerical experiments estimating polynomial approximations of the von Neumann entropy and quantum state fidelities.

Abstract: Chemical component design is a computationally challenging procedure that often entails iterative numerical modeling and authentic experimental testing. We demonstrate a novel optimization method, Tensor train Optimization (TetraOpt), for the shape optimization of components focusing on a Y-shaped mixer of fluids. Due to its high parallelization and more extensive global search, TetraOpt outperforms commonly used Bayesian optimization techniques in accuracy and runtime. Besides, our approach can be used to solve general physical design problems and has linear complexity in the number of optimized parameters, which is highly relevant for complex chemical components. Furthermore, we discuss the extension of this approach to quantum computing, which potentially yields a more efficient approach.