Quantum Physics (quant-ph)

Abstract: Superconducting qubits are one of the most advanced candidates to realize scalable and fault-tolerant quantum computing. Despite recent significant advancements in the qubit lifetimes, the origin of the loss mechanism for state-of-the-art qubits is still subject to investigation. Moreover, successful implementation of quantum error correction requires negligible correlated errors among qubits. Here, we realize ultra-coherent superconducting transmon qubits based on niobium capacitor electrodes, with lifetimes exceeding 0.4 ms. By employing a nearly quantum-limited readout chain based on a Josephson traveling wave parametric amplifier, we are able to simultaneously record bit-flip errors occurring in a multiple-qubit device, revealing that the bit-flip errors in two highly coherent qubits are strongly correlated. By introducing a novel time-resolved analysis synchronized with the operation of the pulse tube cooler in a dilution refrigerator, we find that a pulse tube mechanical shock causes nonequilibrium dynamics of the qubits, leading to correlated bit-flip errors as well as transitions outside of the computational state space. Our observations confirm that coherence improvements are still attainable in transmon qubits based on the superconducting material that has been commonly used in the field. In addition, our findings are consistent with qubit dynamics induced by two-level systems and quasiparticles, deepening our understanding of the qubit error mechanisms. Finally, these results inform possible new error-mitigation strategies by decoupling superconducting qubits from their mechanical environments.

Abstract: It has been known that the fundamental Lifshitz theory, which is based on first principles of thermal quantum field theory, experiences difficulties when compared with precise measurements of the Casimir force. We analyze the nonconventional fit of response functions of many materials along the imaginary frequency axis to the empirical model of "modified" oscillators which was recently proposed in the literature. According to our results, this model is unacceptable because at high frequencies it leads to the asymptotic behavior of response functions which is in contradiction with that following from the fundamental physical principles. We calculate the Casimir interaction in the configurations of several precise experiments using the Lifshitz theory and the response functions to quantized electromagnetic field expressed in terms of modified oscillators and demonstrate that the obtained results are excluded by the measurement data. This invalidates a claim made in the literature that the Casimir-van der Waals forces calculated using these response functions are in remarkable agreement with the experimental values. Possible reasons for a disagreement between experiment and theory are discussed, and the way to improve the situation is directed.

Abstract: Quantum networks constitute a major part of quantum technologies. They will boost distributed quantum computing drastically by providing a scalable modular architecture of quantum chips, or by establishing an infrastructure for measurement based quantum computing. Moreover, they will provide the backbone of the future quantum internet, allowing for high margins of security. Interestingly, the advantages that the quantum networks would provide for communications, rely on entanglement distribution, which suffers from high latency in protocols based on Bell pair distribution and bipartite entanglement swapping. Moreover, the designed algorithms for multipartite entanglement routing suffer from intractability issues making them unsolvable exactly in polynomial time. In this paper, we investigate a new approach for graph states distribution in quantum networks relying inherently on local quantum coding -- LQC -- isometries and on multipartite states transfer. Additionally, single-shot bounds for stabilizer states distribution are provided. Analogously to network coding, these bounds are shown to be achievable if appropriate isometries/stabilizer codes in relay nodes are chosen, which induces a lower latency entanglement distribution. As a matter of fact, the advantages of the protocol for different figures of merit of the network are provided.

Abstract: 3SAT instances need to be transformed into instances of Quadratic Unconstrained Binary Optimization (QUBO) to be solved on a quantum annealer. Although it has been shown that the choice of the 3SAT-to-QUBO transformation can impact the solution quality of quantum annealing significantly, currently only a few 3SAT-to-QUBO transformations are known. Additionally, all of the known 3SAT-to-QUBO transformations were created manually (and not procedurally) by an expert using reasoning, which is a rather slow and limiting process. In this paper, we will introduce the name Pattern QUBO for a concept that has been used implicitly in the construction of 3SAT-to-QUBO transformations before. We will provide an in-depth explanation for the idea behind Pattern QUBOs and show its importance by proposing an algorithmic method that uses Pattern QUBOs to create new 3SAT-to-QUBO transformations automatically. As an additional application of Pattern QUBOs and our proposed algorithmic method, we introduce approximate 3SAT-to-QUBO transformations. These transformations sacrifice optimality but use significantly fewer variables (and thus physical qubits on quantum hardware) than non-approximate 3SAT-to-QUBO transformations. We will show that approximate 3SAT-to-QUBO transformations can nevertheless be very effective in some cases.

Abstract: We present a simple and efficient way to reduce the contraction cost of a tensor network to simulate a quantum circuit. We start by interpreting the circuit as a ZX-diagram. We then use simplification and local complementation rules to sparsify it. We find that optimizing graph-like ZX-diagrams improves existing state of the art contraction cost by several order of magnitude. In particular, we demonstrate an average contraction cost 1180 times better for Sycamore circuits of depth 20, and up to 4200 times better at peak performance.

Abstract: We present extensive simulations of the recently reported quantum version of the well-known Hopfield Neural Network to explore its emergent behavior. The system is constituted of a network of $N$ qubits oscillating at a given $\Omega$ frequency and which are coupled via Lindblad jump operators that depend on local fields $h_i$ depending on some given stored patterns. In agreement with previous results, our simulations show pattern-antipattern oscillations of the overlaps with the stored patterns similar to those reported within a mean-field description of such a system, and which are due to metastability originated by the quantum effect driven by the $s_x^i$ qubit operators. In simulations, we observe that such oscillations are stochastic due to the inherent metastability of the pattern attractors induced by the quantum term and disappear in finite systems when one averages over many quantum trajectories. In addition, we report the system behavior when the number of stored patterns enlarges, for the minimum temperature we can reach in simulations (namely $T=0.005$). Our study reveals that the quantum term of the Hamiltonian has a negative effect on storage capacity, decreasing the overlap with the starting memory pattern for increased values of $\Omega$ and the number of stored patterns. However, although the initial pattern destabilizes due to quantum oscillations, other patterns can be retrieved and remain stable for a large number of stored patterns, implying a quantum-dependent nonlinear relationship between the recall process and the number of stored patterns.

Abstract: This paper explores the feasibility of quantum simulation for partial differential equations (PDEs) with physical boundary or interface conditions. Semi-discretisation of such problems does not necessarily yield Hamiltonian dynamics and even alters the Hamiltonian structure of the dynamics when boundary and interface conditions are included. This seemingly intractable issue can be resolved by using a recently introduced Schr\"odingerisation method (Jin et al. 2022) -- it converts any linear PDEs and ODEs with non-Hermitian dynamics to a system of Schr\"odinger equations, via the so-called warped phase transformation that maps the equation into one higher dimension. We implement this method for several typical problems, including the linear convection equation with inflow boundary conditions and the heat equation with Dirichlet and Neumann boundary conditions. For interface problems, we study the (parabolic) Stefan problem, linear convection, and linear Liouville equations with discontinuous and even measure-valued coefficients. We perform numerical experiments to demonstrate the validity of this approach, which helps to bridge the gap between available quantum algorithms and computational models for classical and quantum dynamics with boundary and interface conditions.

Abstract: We assess the cavity molecular dynamics method for the calculation of vibrational polariton spectra, using liquid water as a specific example. We begin by disputing a recent suggestion that nuclear quantum effects may lead to a broadening of polariton bands, finding instead that they merely result in anharmonic red shifts in the polariton frequencies. We go on to show that our simulated cavity spectra can be reproduced to graphical accuracy with a harmonic model that uses just the cavity-free spectrum and the geometry of the cavity as input. We end by showing that this harmonic model can be combined with the experimental cavity-free spectrum to give results in good agreement with optical cavity measurements. Since the input to our harmonic model is equivalent to the input to the transfer matrix method of applied optics, we conclude that cavity molecular dynamics cannot provide any more insight into the effect of vibrational strong coupling on the absorption spectrum than this transfer matrix method, which is already widely used by experimentalists to corroborate their cavity results.

Abstract: The recent physical realisation of quantum computers with dozens to hundreds of noisy qubits has given birth to an intense search for useful applications of their unique capabilities. One area that has received particular attention is quantum machine learning (QML), the study of machine learning algorithms running natively on quantum computers. Such algorithms have begun to be applied to data intensive problems in particle physics, driven by the expected increased capacity for pattern recognition of quantum computers. In this work we develop and apply QML methods to B meson flavour tagging, an important component of experiments in particle physics which probe heavy quark mixing and CP violation in order to obtain a better understanding of the matter-antimatter asymmetry observed in the universe. We simulate boosted ensembles of quantum support vector machines (QSVMs) based on both conventional qubit-based and continuous variable architectures, attaining effective tagging efficiencies of 28.0% and 29.2% respectively, comparable with the leading published result of 30.0% using classical machine learning algorithms. The ensemble nature of our classifier is of particular importance, doubling the effective tagging efficiency of a single QSVM, which we find to be highly prone to overfitting. These results are obtained despite the strong constraint of working with QSVM architectures that are classically simulable, and we find evidence that continuous variable QSVMs beyond the classically simulable regime may be able to realise even higher performance, surpassing the reported classical results, when sufficiently powerful quantum hardware is developed to execute them.

Abstract: An effective time-dependent Hamiltonian can be implemented by making a quantum system fly through an inhomogeneous potential, realizing, for example, a quantum gate on its internal degrees of freedom. However, flying systems have a spatial spread that will generically entangle the internal and spatial degrees of freedom, leading to decoherence in the internal state dynamics, even in the absence of any external reservoir. We provide formulas valid at all times for the dynamics, fidelity, and change of entropy for small spatial spreads, quantified by $\Delta x$. This decoherence is non-Markovian and its effect can be significant for ballistic qubits (scaling as $\Delta x^2$) but not for qubits carried by a moving potential well (scaling as $\Delta x^6$). We also discuss a method to completely counteract this decoherence for a ballistic qubit later measured.

Abstract: We introduce a variational hybrid classical-quantum algorithm to simulate the Lindblad master equation and its adjoint for time-evolving Markovian open quantum systems and quantum observables. Our method is based on a direct representation of density matrices and quantum observables as quantum superstates. We design and optimize low-depth variational quantum circuits that efficiently capture the unitary and non-unitary dynamics of the solutions. We benchmark and test the algorithm on different system sizes, showing its potential for utility with near-future hardware.

Abstract: We present an optomechanical model to show that entanglement can be a sufficient condition for quantum synchronization of two mechanical oscillators. As both these entities can be characterized in terms of variances of a set of EPR-like conjugate quadratures, we investigate whether this leads to a specific condition for simultaneous existence of the both. In our model, one of the oscillators makes the cavity, while the other is kept suspended inside the cavity, and the always-on coupling between the two is mediated via the same cavity mode. We show that in presence of amplitude modulation with the same frequency as that of the oscillators, these oscillators get nearly complete quantum synchronized and entangled simultaneously in the steady state. We also show that entanglement always becomes accompanied by quantum synchronization, though the reverse is not necessarily true. Thus, entanglement becomes a sufficient condition for the quantum synchronization. This behaviour can be observed for a large range of system parameters.

Abstract: Quantum generative models, in providing inherently efficient sampling strategies, show promise for achieving a near-term advantage on quantum hardware. Nonetheless, important questions remain regarding their scalability. In this work, we investigate the barriers to the trainability of quantum generative models posed by barren plateaus and exponential loss concentration. We explore the interplay between explicit and implicit models and losses, and show that using implicit generative models (such as quantum circuit-based models) with explicit losses (such as the KL divergence) leads to a new flavour of barren plateau. In contrast, the Maximum Mean Discrepancy (MMD), which is a popular example of an implicit loss, can be viewed as the expectation value of an observable that is either low-bodied and trainable, or global and untrainable depending on the choice of kernel. However, in parallel, we highlight that the low-bodied losses required for trainability cannot in general distinguish high-order correlations, leading to a fundamental tension between exponential concentration and the emergence of spurious minima. We further propose a new local quantum fidelity-type loss which, by leveraging quantum circuits to estimate the quality of the encoded distribution, is both faithful and enjoys trainability guarantees. Finally, we compare the performance of different loss functions for modelling real-world data from the High-Energy-Physics domain and confirm the trends predicted by our theoretical results.

Abstract: It has recently been proposed classical analogs of the purity, linear quantum entropy, and von Neumann entropy for classical integrable systems, when the corresponding quantum system is in a Gaussian state. We generalized these results by providing classical analogs of the generalized purities, Bastiaans-Tsallis entropies, R\'enyi entropies, and logarithmic negativity for classical integrable systems. These classical analogs are entirely characterized by the classical covariance matrix. We compute these classical analogs exactly in the cases of linearly coupled harmonic oscillators, a generalized harmonic oscillator chain, and a one-dimensional circular lattice of oscillators. In all of these systems, the classical analogs reproduce the results of their quantum counterparts whenever the system is in a Gaussian state. In this context, our results show that quantum information of Gaussian states can be reproduced by classical information.

Abstract: Magneto-optical microscopies, including optical measurements of magnetic circular dichroism, are increasingly ubiquitous tools for probing spin-orbit coupling, charge-carrier g-factors, and chiral excitations in matter, but the minimum detectable signal in classical magnetic circular dichroism measurements is fundamentally limited by the shot-noise limit of the optical readout field. Here, we use a two-mode squeezed light source to improve the minimum detectable signal in magnetic circular dichroism measurements by 3 dB compared with state-of-the-art classical measurements, even with relatively lossy samples like terbium gallium garnet. We also identify additional opportunities for improvement in quantum-enhanced magneto-optical microscopies, and we demonstrate the importance of these approaches for environmentally sensitive materials and for low temperature measurements where increased optical power can introduce unacceptable thermal perturbations.

Abstract: Parametric coupling is a powerful technique for generating tunable interactions between superconducting circuits using only microwave tones. Here, we present a highly flexible parametric coupling scheme demonstrated with two transmon qubits, which can be employed for multiple purposes, including the removal of residual $ZZ$ coupling and the implementation of driven swap or swap-free controlled-$Z$ (c$Z$) gates. Our fully integrated coupler design is only weakly flux tunable, cancels static linear coupling between the qubits, avoids internal coupler dynamics or excitations, and operates with rf-pulses. We show that residual $ZZ$ coupling can be reduced with a parametric dispersive tone down to an experimental uncertainty of 5.5 kHz. Additionally, randomized benchmarking reveals that the parametric swap c$Z$ gate achieves a fidelity of 99.4% in a gate duration of 60 ns, while the dispersive parametric swap-free c$Z$ gate attains a fidelity of 99.5% in only 30 ns. We believe this is the fastest and highest fidelity gate achieved with on-chip parametric coupling to date. We further explore the dependence of gate fidelity on gate duration for both p-swap and p-swap-free c$Z$ gates, providing insights into the possible error sources for these gates. Overall, our findings demonstrate a versatility, precision, speed, and high performance not seen in previous parametric approaches. Finally, our design opens up new possibilities for creating larger, modular systems of superconducting qubits.

Abstract: We demonstrate high fidelity repetitive projective measurements of nuclear spin qubits in an array of neutral ytterbium-171 ($^{171}$Yb) atoms. We show that the qubit state can be measured with a fidelity of 0.995(4) under a condition that leaves it in the state corresponding to the measurement outcome with a probability of 0.993(6) for a single tweezer and 0.981(4) averaged over the array. This is accomplished by near-perfect cyclicity of one of the nuclear spin qubit states with an optically excited state under a magnetic field of $B=58$ G, resulting in a bright/dark contrast of $\approx10^5$ during fluorescence readout. The performance improves further as $\sim1/B^2$. The state-averaged readout survival of 0.98(1) is limited by off-resonant scattering to dark states and can be addressed via post-selection by measuring the atom number at the end of the circuit, or during the circuit by performing a measurement of both qubit states. We combine projective measurements with high-fidelity rotations of the nuclear spin qubit via an AC magnetic field to explore several paradigmatic scenarios, including the non-commutivity of measurements in orthogonal bases, and the quantum Zeno mechanism in which measurements "freeze" coherent evolution. Finally, we employ real-time feedforward to repetitively deterministically prepare the qubit in the $+z$ or $-z$ direction after initializing it in an orthogonal basis and performing a projective measurement in the $z$-basis. These capabilities constitute an important step towards adaptive quantum circuits with atom arrays, such as in measurement-based quantum computation, fast many-body state preparation, holographic dynamics simulations, and quantum error correction.

Abstract: We present the first hybrid matter-photon implementation of verifiable blind quantum computing. We use a trapped-ion quantum server and a client-side photonic detection system connected by a fibre-optic quantum network link. The availability of memory qubits and deterministic quantum logic enables interactive protocols without post-selection - a requirement for any scalable blind quantum cloud server which previous realisations could not provide. Our apparatus supports guaranteed privacy with <0.001 leaked bits per qubit and shows a clear path to fully verified quantum computing in the cloud.

Abstract: We propose a novel hierarchical qubit mapping and routing algorithm. First, a circuit is decomposed into blocks that span an identical number of qubits. In the second stage permutation-aware synthesis (PAS), each block is optimized and synthesized in isolation. In the third stage a permutation-aware mapping (PAM) algorithm maps the blocks to the target device based on the information from the second stage. Our approach is based on the following insights: (1) partitioning the circuit into blocks is beneficial for qubit mapping and routing; (2) with PAS, any block can implement an arbitrary input-output qubit mapping that reduces the gate count; and (3) with PAM, for two adjacent blocks we can select input-output permutations that optimize each block together with the amount of communication required at the block boundary. Whereas existing mapping algorithms preserve the original circuit structure and only introduce "minimal" communication via inserting SWAP or bridge gates, the PAS+PAM approach can additionally change the circuit structure and take full advantage of hardware-connectivity. Our experiments show that we can produce better-quality circuits than existing mapping algorithms or commercial compilers (Qiskit, TKET, BQSKit) with maximum optimization settings. For a combination of benchmarks we produce circuits shorter by up to 68% (18% on average) fewer gates than Qiskit, up to 36% (9% on average) fewer gates than TKET, and up to 67% (21% on average) fewer gates than BQSKit. Furthermore, the approach scales, and it can be seamlessly integrated into any quantum circuit compiler or optimization infrastructure.

Abstract: A quantum many-body system undergoes phase transitions of distinct species with variations of local and global parameters. We propose a framework in which a dynamical quantity can change its behavior with the quenching of either global (coarse-grained criteria) or local system parameters (fine-grained criteria), revealing the transition points present in global ones. We illustrate our technique by employing a long-range extended Ising model in the presence of a transverse magnetic field which can be mapped to spinless fermions and hence can be investigated for large system size. We report that the scaling law followed by the total correlation, the composition of both quantum and classical correlations in the steady state, can identify the transition points at which the known indicators like rate function or entanglement length fail. Specifically, in a fine-grained scenario, total correlation either follows the same scaling law with the quenching at and across the critical points along the transverse magnetic field, or obeys the different laws, thereby establishing a transition in the range of interactions.

Abstract: Supervised quantum learning is an emergent multidisciplinary domain bridging between variational quantum algorithms and classical machine learning. Here, we study experimentally a hybrid classifier model accelerated by a quantum simulator - a linear array of four superconducting transmon artificial atoms - trained to solve multilabel classification and image recognition problems. We train a quantum circuit on simple binary and multi-label tasks, achieving classification accuracy around 95%, and a hybrid model with data re-uploading with accuracy around 90% when recognizing handwritten decimal digits. Finally, we analyze the inference time in experimental conditions and compare the performance of the studied quantum model with known classical solutions.

Abstract: We report the first coexistence experiment of 1550 nm single-mode squeezed states of light with a 1310 nm classical telecom channel over a 10 km fiber channel while measuring squeezing using a locally generated local oscillator. This is achieved using real-time optical heterodyne phase locking, allowing us to measure up to 0.5 dB of squeezing with a phase noise of 2.2 degrees.

Abstract: For most practical applications, quantum algorithms require large resources in terms of qubit number, much larger than those available with current NISQ processors. With the network and communication functionalities provided by the Quantum Internet, Distributed Quantum Computing (DQC) is considered as a scalable approach for increasing the number of available qubits for computational tasks. For DQC to be effective and efficient, a quantum compiler must find the best partitioning for the quantum algorithm and then perform smart remote operation scheduling to optimize EPR pair consumption. At the same time, the quantum compiler should also find the best local transformation for each partition. In this paper we present a modular quantum compilation framework for DQC that takes into account both network and device constraints and characteristics. We implemented and tested a quantum compiler based on the proposed framework with some circuits of interest, such as the VQE and QFT ones, considering different network topologies, with quantum processors characterized by heavy hexagon coupling maps. We also devised a strategy for remote scheduling that can exploit both TeleGate and TeleData operations and tested the impact of using either only TeleGates or both. The evaluation results show that TeleData operations may have a positive impact on the number of consumed EPR pairs, while choosing a more connected network topology helps reduce the number of layers dedicated to remote operations.

Abstract: We question the role of entanglement in masking quantum information contained in a set of mixed quantum states. We first show that a masker that can mask any two single-qubit pure states, can mask the entire set of mixed states comprising of the classical mixtures of those two pure qubit states as well. We then try to find the part played by entanglement in masking two different sets: One, a set of mixed states formed by the classical mixtures of two single-qubit pure commuting states, and another, a set of mixed states obtained by mixing two single-qubit pure non-commuting states. For both cases, we show that the masked states remain entangled unless the input state is an equal mixture of the two pure states. This in turn reveals that entanglement is necessary as well as sufficient for masking an arbitrary set of two single qubit states, regardless of their mixednesses and mutual commutativity.

Abstract: Methods of quantum error correction are starting to be beneficial on current quantum computing hardware. Typically this requires to perform measurements which yield information about the occurred errors on the system. However, these syndrome measurements themselves introduce noise to the system. A full characterization of the measurements is very costly. Here we present a calibration method which allows to take the additional noise into account. Under reasonable assumptions we require only a single additional experiment. We give examples of how to apply this method to noise estimation and error correction. Finally we discuss the results of experiments carried out on an IBM quantum computer.

Abstract: Kupczynski (2023) claims that Gill and Lambare (2022a, 2022b) misrepresent several of his published papers. This paper shows that the latest version of his "contextuality by default" model of a Bell experiment places no constraints whatsoever on the statistics of observed results in Bell type experiments. It thereby effectively allows arbitrary non-locality, ie direct causal effects of local measurement settings on distant measurement outcomes.

Abstract: Electronic excited states of molecules are central to many physical and chemical processes, and yet they are typically more difficult to compute than ground states. In this paper we leverage the advantages of quantum computers to develop an algorithm for the highly accurate calculation of excited states. We solve a contracted Schr\"odinger equation (CSE) -- a contraction (projection) of the Schr\"odinger equation onto the space of two electrons -- whose solutions correspond identically to the ground and excited states of the Schr\"odinger equation. While recent quantum algorithms for solving the CSE, known as contracted quantum eigensolvers (CQE), have focused on ground states, we develop a CQE based on the variance that is designed to optimize rapidly to a ground or excited state. We apply the algorithm in a classical simulation without noise to computing the ground and excited states of H$_{4}$ and BH.