Quantum Physics (quant-ph)

Abstract: Quantum approximate optimization algorithm (QAOA) is a promising variational quantum algorithm for combinatorial optimization problems. However, the implementation of QAOA is limited due to the requirement that the problems be mapped to Ising Hamiltonians and the nonconvex optimization landscapes. Although the Ising Hamiltonians for many NP hard problems have been obtained, a general method to obtain the Ising Hamiltonians for constrained combinatorial optimization problems (CCOPs) has not yet been investigated. In this paper, a general method is introduced to obtain the Ising Hamiltonians for CCOPs and the Metropolis-Hastings warm-starting algorithm for QAOA is presented which can provably converge to the global optimal solutions. The effectiveness of this method is demonstrated by tackling the minimum weight vertex cover (MWVC) problem, the minimum vertex cover (MVC) problem, and the maximal independent set problem as examples. The Ising Hamiltonian for the MWVC problem is obtained first time by using this method. The advantages of the Metropolis-Hastings warm-starting algorithm presented here is numerically analyzed through solving 30 randomly generated MVC cases with 1-depth QAOA.

Abstract: We propose novel charging protocols for quantum batteries based on quantum superpositions of trajectories. Specifically, we consider that a qubit (the battery) interacts with multiple cavities or a single cavity at various positions, where the cavities act as chargers. Further, we introduce a quantum control prepared in a quantum superposition state, allowing the battery to be simultaneously charged by multiple cavities or a single cavity with different entry positions. To assess the battery's performance, we evaluate the maximum extractable work, referred to as ergotropy. Our main result is that the proposed protocols can utilize quantum interference effects to speed up the charging process. For the protocol involving multiple cavities, we observe a substantial increase in ergotropy as the number of superposed trajectories increases. In the case of the single-cavity protocol, we show that two superposed trajectories (entry positions) are sufficient to achieve the upper limit of the ergotropy throughout the entire charging process. Furthermore, we propose circuit models for these charging protocols and conduct proof-of-principle demonstrations on IBMQ and IonQ quantum processors. The results validate our theoretical predictions, demonstrating a clear enhancement in ergotropy.

Abstract: The promising performance increase offered by quantum computing has led to the idea of applying it to neural networks. Studies in this regard can be divided into two main categories: simulating quantum neural networks with the standard quantum circuit model, and implementing them based on hardware. However, the ability to capture the non-linear behavior in neural networks using a computation process that usually involves linear quantum mechanics principles remains a major challenge in both categories. In this study, a hardware-efficient quantum neural network operating as an open quantum system is proposed, which presents non-linear behaviour. The model's compatibility with learning processes is tested through the obtained analytical results. In other words, we show that this dissipative model based on repeated interactions, which allows for easy parametrization of input quantum information, exhibits differentiable, non-linear activation functions.

Abstract: We propose a general framework for decoding quantum error-correcting codes with generative modeling. The model utilizes autoregressive neural networks, specifically Transformers, to learn the joint probability of logical operators and syndromes. This training is in an unsupervised way, without the need for labeled training data, and is thus referred to as pre-training. After the pre-training, the model can efficiently compute the likelihood of logical operators for any given syndrome, using maximum likelihood decoding. It can directly generate the most-likely logical operators with computational complexity $\mathcal O(2k)$ in the number of logical qubits $k$, which is significantly better than the conventional maximum likelihood decoding algorithms that require $\mathcal O(4^k)$ computation. Based on the pre-trained model, we further propose refinement to achieve more accurately the likelihood of logical operators for a given syndrome by directly sampling the stabilizer operators. We perform numerical experiments on stabilizer codes with small code distances, using both depolarizing error models and error models with correlated noise. The results show that our approach provides significantly better decoding accuracy than the minimum weight perfect matching and belief-propagation-based algorithms. Our framework is general and can be applied to any error model and quantum codes with different topologies such as surface codes and quantum LDPC codes. Furthermore, it leverages the parallelization capabilities of GPUs, enabling simultaneous decoding of a large number of syndromes. Our approach sheds light on the efficient and accurate decoding of quantum error-correcting codes using generative artificial intelligence and modern computational power.

Abstract: Superlocality and superunsteerability provide operational characterization of quantum correlations in certain local and unsteerable states respectively. Such quantum correlated states have a nonzero quantum discord. Nonzero quantum discord in both the ways is necessary for quantum correlations pointed out by superlocality. On the other hand, in this work, we demonstrate that a nonzero quantum discord in both the ways is not necessary to demonstrate superunsteerability. To this end, we demonstrate superunsteerability for one-way quantum discordant states. This in turn implies the existence of one-way superunsteerability and also the presence of superunsteerability without superlocality. Superunsteerability for nonzero quantum discord states implies steerability in a one-sided semi-device-independent way. Just like one-way steerability occurs for certain Bell-local states in a one-sided device-independent way, our result shows that one-way steerability can also occur for certain nonsuperlocal states but in a one-sided semi-device-independent way.

Abstract: Quantum speed limits provide upper bounds on the rate with which a quantum system can move away from its initial state. Here, we provide a different kind of speed limit, describing the divergence of a perturbed open system from its unperturbed trajectory. In the case of weak coupling, we show that the divergence speed is bounded by the quantum Fisher information under a perturbing Hamiltonian, up to an error which can be estimated from system and bath timescales. We give two applications of our speed limit. Firstly, it enables experimental estimation of quantum Fisher information in the presence of decoherence that is not fully characterised. Secondly, it implies that large quantum work fluctuations are necessary for a thermal system to be driven quickly out of equilibrium under a quench.

Abstract: We theoretically analyse an autonomous clock comprising a nanoelectromechanical system, which undergoes self-oscillations driven by electron tunnelling. The periodic mechanical motion behaves as the clockwork, similar to the swinging of a pendulum, while induced oscillations in the electrical current can be used to read out the ticks. We simulate the dynamics of the system in the quasi-adiabatic limit of slow mechanical motion, allowing us to infer statistical properties of the clock's ticks from the current auto-correlation function. The distribution of individual ticks exhibits a tradeoff between accuracy, resolution, and dissipation, as expected from previous literature. Going beyond the distribution of individual ticks, we investigate how clock accuracy varies over different integration times by computing the Allan variance. We observe non-monotonic features in the Allan variance as a function of time and applied voltage, which can be explained by the presence of temporal correlations between ticks. These correlations are shown to yield a precision advantage for timekeeping over the timescales that the correlations persist. Our results illustrate the non-trivial features of the tick series produced by nanoscale clocks, and pave the way for experimental investigation of clock thermodynamics using nanoelectromechanical systems.

Abstract: Quantum optical sensors are ubiquitous in various fields of research, from biological or medical sensors to large-scale experiments searching for dark matter or gravitational waves. Gravitational-wave detectors have been very successful in implementing cavities and quantum squeezed light for enhancing sensitivity to signals from black hole or neutron star mergers. However, the sensitivity to weak forces is limited by available energy and optical decoherence in the system. Here, we derive the fundamental sensitivity limit of cavity and squeezed-light enhanced interferometers with optical loss.This limit is attained by the optimal use of an additional internal squeeze operation, which allows to mitigate readout loss. We demonstrate the application of internal squeezing to various scenarios and confirm that it indeed allows to reach the best sensitivity in cavity and squeezed-light enhanced linear force sensors. Our work establishes the groundwork for the future development of optimal sensors in real-world scenarios where, up until now, the application of squeezed light was curtailed by various sources of decoherence.

Abstract: We use a variational method for generating probability distributions, specifically, the Uniform, the Normal, the Binomial distribution, and the Poisson distribution. To do the same, we use many different architectures for the two, three and four-qubit cases using the Jensen-Shannon divergence as our objective function. We use gradient descent with momentum as our optimization scheme instead of conventionally used gradient descent. To calculate the gradient, we use the parameter shift rule, whose formulation we modify to take the probability values as outputs instead of the conventionally taken expectation values. We see that this method can approximate probability distributions, and there exists a specific architecture which outperforms other architectures, and this architecture depends on the number of qubits. The four, three and two-qubit cases consist of a parameterized layer followed by an entangling layer; a parameterized layer followed by an entangling layer, which is followed by a parameterized layer and only parameterized layers, respectively.

Abstract: Discrimination of entangled states is an important element of quantum enhanced metrology. This typically requires low-noise detection technology. Such a challenge can be circumvented by introducing nonlinear readout process. Traditionally, this is realized by reversing the very dynamics that generates the entangled state, which requires a full control over the system evolution. In this work, we present nonlinear readout of highly entangled states by employing reinforcement learning (RL) to manipulate the spin-mixing dynamics in a spin-1 atomic condensate. The RL found results in driving the system towards an unstable fixed point, whereby the (to be sensed) phase perturbation is amplified by the subsequent spin-mixing dynamics. Working with a condensate of 10900 {87}^Rb atoms, we achieve a metrological gain of 6.97 dB beyond the classical precision limit. Our work would open up new possibilities in unlocking the full potential of entanglement caused quantum enhancement in experiments.

Abstract: At the core of quantum photonic information processing and sensing, two major building pillarsare single-photon emitters and single-photon detectors. In this review, we systematically summarize the working theory, material platform, fabrication process, and game-changing applications enabled by state-of-the-art quantum dots in nanowire emitters and superconducting nanowire single-photon detectors. Such nanowire-based quantum hardware offers promising properties for modern quantum optics experiments.We highlight several burgeoning quantum photonics applications using nanowires and discuss development trends of integrated quantum photonics. Also, we propose quantum information processing and sensing experiments for the quantum optics community, and future interdisciplinary applications.

Abstract: We describe the Hong-Ou-Mandel interference of two identical particles evolving on a one-dimensional tight-binding lattice where a potential barrier plays the role of a beam splitter. Careful consideration of the symmetries underlying the two-particle interference effect allows us to reformulate the problem in terms of ordinary wave interference in a Michelson interferometer. This approach is easily generalized to the case where the particles interact, and we compare the resulting analytical predictions for the bunching probability to numerical simulations of the two-particle dynamics.

Abstract: We study the Hong-Ou-Mandel interference of two identical, composite particles, each formed of two bosonic or fermionic constituents, as they scatter against a potential barrier in a one-dimensional lattice. For tightly bound composites, we show that the combination of their constituents' mutual interactions and exchange symmetry gives rise to an effective nearest-neighbour interaction between composites, which induces a reduction of the interference contrast.

Abstract: Noise is a major hurdle in realizing quantum technologies as it affects quantum protocols like teleportation, dense coding. It is possible to use techniques like weak measurements to reduce the noise effect and protect quantum correlations. This work addresses the extent of applicability of weak measurements to enhance the efficiency of the quantum teleportation of a qubit through a noisy quantum channel, aiming towards universal quantum teleportation. Due to the effects of noise, the average fidelity of teleportation tends to vary; weak measurements can reduce these fidelity deviations to a value close to zero. We also study the effect of memory and its impact on fidelity and fidelity deviations in the proposed teleportation protocol. The memory effects, with the aid of weak measurement and its reversal, are shown to give better results for teleportation. The extent of applicability of the proposed protocol for protecting quantum correlations, under the influence of different noise channels, are studied in the present work.

Abstract: In this paper, we consider all possible variants of Choi matrices of linear maps, and show that they are determined by non-degenerate bilinear forms on the domain space. We will do this in the setting of finite dimensional vector spaces. In case of matrix algebras, we characterize all variants of Choi matrices which retain the usual correspondences between $k$-superpositivity and Schmidt number $\le k$ as well as $k$-positivity and $k$-block-positivity. We also compare de Pillis' definition [Pacific J. Math. 23 (1967), 129--137] and Choi's definition [Linear Alg. Appl. 10 (1975), 285--290], which arise from different bilinear forms.

Abstract: Imperfections from devices can result in the decay or even vanish of non-n-local correlations as the number of parties n increases in the polygon and linear quantum networks ([Phys. Rev. A 106, 042206 (2022)] and [Phys. Rev. A 107, 032404 (2023)]). Even so this phenomenon is also for the special kind of noises, including consistency noises of a sequence of devices, which means the sequence of devices have the same probability fails to detect. However, in the paper, we discover that star network quantum non-n-local correlations can resist better consistency noises than these in polygon and linear networks. We first calculate the noisy expected value o f star network non-n-locality and analyze the persistency conditions theoretically. When assume that congener devices have the consistency noise, the persistency number of sources n has been rid of such noises, and approximates to the infinity. Polygon and linear network non-n-local correlations can not meet the requirements. Furthermore, we explore the change pattern of the maximal number of sources nmax such that non-nmax-local correlation can be demonstrated in the star network under the influence of partially consistent noises, which is more general than consistent ones.

Abstract: The many-electron Schr\"odinger equation is solved straightforwardly with a Transformer-based neural-network architecture (QiankunNet), which requires no external training data and significantly improves the accuracy and efficiency of first-principles calculations compared to previous Fermionic ansatz. The intricate quantum correlations are effectively captured by incorporating the attention mechanism into our methodology. Additionally, the batched sampling strategy is used to significantly improve the sampling accuracy and efficiency. Furthermore, a pre-training stage which incorporates the truncated configuration interaction solution into the variational ansatz, ensuring high expressiveness and further improving computational efficiency. QiankunNet demonstrates the power of the Transformer-based language model in achieving unprecedented efficiency in quantum chemistry calculations, which opens new avenues to chemical discovery and has the potential to solve the large-scale Schr\"odinger equation with modest computational cost.

Abstract: We theoretically propose a scheme to generate distant bipartite entanglement between various subsystems in coupled magnomechanical systems where both the microwave cavities are coupled through single photon hopping parameter. Each cavity also contains a magnon mode and phonon mode and this gives five excitation modes in our model Hamiltonian which are cavity-1 photons, cavity-2 photons, magnon, and phonon modes in both YIG spheres. We found that significant bipartite entanglement exists between indirectly coupled subsystems in coupled microwave cavities for an appropriate set of parameters regime. Moreover, we also obtain suitable cavity and magnon detuning parameters for a significant distant bipartite entanglement in different bipartitions. In addition, it can be seen that a single photon hopping parameter significantly affects both the degree as well as the transfer of quantum entanglement between various bipartitions. Hence, our present study related to coupled microwave cavity magnomechanical configuration will open new perspectives in coherent control of various quantum correlations including quantum state transfer among macroscopic quantum systems

Abstract: Rydberg atom arrays are among the leading contenders for the demonstration of quantum speedups. Motivated by recent experiments with up to 289 qubits [Ebadi et al., Science 376, 1209 (2022)] we study the maximum independent set problem on unit-disk graphs with a broader range of classical solvers beyond the scope of the original paper. We carry out extensive numerical studies and assess problem hardness, using both exact and heuristic algorithms. We find that quasi-planar instances with Union-Jack-like connectivity can be solved to optimality for up to thousands of nodes within minutes, with both custom and generic commercial solvers on commodity hardware, without any instance-specific fine-tuning. We also perform a scaling analysis, showing that by relaxing the constraints on the classical simulated annealing algorithms considered in Ebadi et al., our implementation is competitive with the quantum algorithms. Conversely, instances with larger connectivity or less structure are shown to display a time-to-solution potentially orders of magnitudes larger. Based on these results we propose protocols to systematically tune problem hardness, motivating experiments with Rydberg atom arrays on instances orders of magnitude harder (for established classical solvers) than previously studied.

Abstract: According to the statistical distribution laws, all the elementary particles in the real 3+1-dimensional world must and only be chosen as either bosons or fermions, without exception and not both. Here, we experimentally verified that a quantized current-biased Josephson junction (CBJJ), as an artificial macroscopic "particle", can be served as either boson or fermion, depending on its biased dc-current. By using the high vacuum two-angle electron beam evaporations, we fabricated the CBJJ devices and calibrated their physical parameters by applying low-frequency signal drivings. The microwave transmission characteristics of the fabricated CBJJ devices are analyzed by using the input-output theory and measured at 50mK temperature environment under low power limit. The experimental results verify the theoretical predictions, i.e., when the bias current is significantly lower than the critical one of the junction, the device works in a well linear regime and thus works as a harmonic oscillator, i.e., a "boson"; while if the biased current is sufficiently large (especially approaches to its critical current), the device works manifestly in the nonlinear regime and thus can be served as a two-level artificial atom, i.e., a "fermion". Therefore, by adjusting the biased dc-current, the CBJJ device can be effectively switched from the boson-type macroscopic particle to the fermion-type one, and thus may open the new approach of the superconducting quantum device application.

Abstract: Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors. Despite the good performance of neural decoders, important practical requirements remain to be achieved, such as minimizing the decoding time to meet typical rates of syndrome generation in repeated error correction schemes, and ensuring the scalability of the decoding approach as the code distance increases. Designing a dedicated integrated circuit to perform the decoding task in co-integration with a quantum processor appears necessary to reach these decoding time and scalability requirements, as routing signals in and out of a cryogenic environment to be processed externally leads to unnecessary delays and an eventual wiring bottleneck. In this work, we report the design and performance analysis of a neural decoder inference accelerator based on an in-memory computing (IMC) architecture, where crossbar arrays of resistive memory devices are employed to both store the synaptic weights of the decoder neural network and perform analog matrix-vector multiplications during inference. In proof-of-concept numerical experiments supported by experimental measurements, we investigate the impact of TiO$_\textrm{x}$-based memristive devices' non-idealities on decoding accuracy. Hardware-aware training methods are developed to mitigate the loss in accuracy, allowing the memristive neural decoders to achieve a pseudo-threshold of $9.23\times 10^{-4}$ for the distance-three surface code, whereas the equivalent digital neural decoder achieves a pseudo-threshold of $1.01\times 10^{-3}$. This work provides a pathway to scalable, fast, and low-power cryogenic IMC hardware for integrated QEC.

Abstract: We derive an exact solution for the steady state of a setup where two $XX$-coupled $N$-qubit spin chains (with possibly non-uniform couplings) are subject to boundary Rabi drives, and common boundary loss generated by a waveguide (either bidirectional or unidirectional). For a wide range of parameters, this system has a pure entangled steady state, providing a means for stabilizing remote multi-qubit entanglement without the use of squeezed light. Our solution also provides insights into a single boundary-driven dissipative $XX$ spin chain that maps to an interacting fermionic model. The non-equilibrium steady state exhibits surprising correlation effects, including an emergent pairing of hole excitations that arises from dynamically constrained hopping. Our system could be implemented in a number of experimental platforms, including circuit QED.