QUROPE Quantum Information Processing and Communication in Europe

Lines of exceptional points are robust in the 3-dimensional non-Hermitian parameter space without requiring any symmetry. However, when more elaborate exceptional structures are considered, the role of symmetry becomes critical. One such case is the exceptional chain (EC), which is formed by the intersection or osculation of multiple exceptional lines (ELs). In this study, we investigate a non-Hermitian classical mechanical system and reveal that a symmetry intrinsic to second-order dynamical equations, in combination with the source-free principle of ELs, guarantees the emergence of ECs. This symmetry can be understood as a non-Hermitian generalized latent symmetry, which is absent in prevailing formalisms rooted in first-order Schr\"odinger-like equations and has largely been overlooked so far. We experimentally confirm and characterize the ECs using an active mechanical oscillator system. Moreover, by measuring eigenvalue braiding around the ELs meeting at a chain point, we demonstrate the source-free principle of directed ELs that underlies the mechanism for EC formation. Our work not only enriches the diversity of non-Hermitian degeneracies, but also highlights the new potential for non-Hermitian physics in second-order dynamical systems.

Geometric phase is a concept of central importance in virtually every branch of physics. In this paper, we show that the evolution time of a cyclically evolving quantum system is restricted by the system's energy resources and the geometric phase acquired by the state. Specifically, we derive and examine three tight lower bounds on the time required to generate any prescribed Aharonov-Anandan geometric phase. The derivations are based on recent results on the geometric character of the Mandelstam-Tamm and Margolus-Levitin quantum speed limits.

K\'arolyh\'azy's original proposal, suggesting that space-time fluctuations could be a source of decoherence in space, faced a significant challenge due to an unexpectedly high emission of radiation (13 orders of magnitude more than what was observed in the latest experiment). To address this issue, we reevaluated K\'arolyh\'azy's assumption that the stochastic metric fluctuation must adhere to a wave equation. By considering more general correlation functions of space-time fluctuations, we resolve the problem and consequently revive the aforementioned proposal.

In this paper, we investigate the interference engineering of the open quantum system, where the environment is made indefinite either through the use of an interferometer or the introduction of auxiliary qubits. The environments are modeled by fully connected qubit baths with exact analytical dynamics. As the system passes through the interferometer or is controlled by auxiliary qubits, it is propagated along different paths or their superpositions, leading to distinct interactions with the environment in each path. This results in the superposition of the environments, which can be detected through specific measurements that retain certain coherent information about the paths. Our results demonstrate that the indefiniteness of the environment can significantly enhance the quantum correlations. However, only the statistical mixture of the influences from the environments preserves provided that the path coherence is destructed. We also examine the serviceability of the indefiniteness as a resource for teleportation and quantum parameter estimation. Additionally, we discuss how to quantify the indefiniteness and the ways in which it affects the system's dynamics from the perspective of wave-particle-entanglement-ignorance complementarity. Overall, our study highlights the potential benefits of an indefinite environment in quantum information processing and sheds light on the fundamental principles underlying its effects.

Arguments by Sorkin arXiv:gr-qc/9302018 and Borsten, Jubb, and Kells arXiv:1912.06141 establish that a natural extension of quantum measurement theory from non-relativistic quantum mechanics to relativistic quantum theory leads to the unacceptable consequence that expectation values in one region depend on which unitary operation is performed in a spacelike separated region. Sorkin labels such scenarios "impossible measurements". We explicitly present these arguments as a no-go result with the logical form of a reductio argument and investigate the consequences for measurement in quantum field theory (QFT). Sorkin-type impossible measurement scenarios clearly illustrate the moral that Microcausality is not by itself sufficient to rule out superluminal signalling in relativistic quantum theories that use L\"uders' rule. We review three different approaches to formulating an account of measurement for QFT and analyze their responses to the "impossible measurements" problem. Two of the approaches are: a measurement theory based on detector models proposed in Polo-G\'omez, Garay, and Mart\'in-Mart\'Inez arXiv:2108.02793 and a measurement framework for algebraic QFT proposed in Fewster and Verch arXiv:1810.06512. Of particular interest for foundations of QFT is that they share common features that may hold general morals about how to represent measurement in QFT. These morals are about the role that dynamics plays in eliminating "impossible measurements", the abandonment of the operational interpretation of local algebras as representing possible operations carried out in a region, and the interpretation of state update rules. Finally, we examine the form that the "impossible measurements" problem takes in histories-based approaches and we discuss the remaining challenges.

This paper presents a quantum efficiency measurement setup based on a 2D motorized stage, a wide spectrum xenon lamp, a beam splitter system, and two calibrated photo-diodes for measuring the quantum efficiency (QE) of photomultiplier tubes (1 to 10 inches). We will demonstrate the effectiveness of technical refinements on the measurements procedures over some existing setups already shown in literature. The large area covered by the 2D stages permit to study the quantum efficiency of PMTs with diameter up to ten inches. The results obtained will show the high precision and accuracy in characterizing the quantum efficiency versus wavelength over the range of 250 nm to 1100 nm and along the photo-catode surface. The setup monitors the light intensity synchronously with the output current yield from photosensors under test. This ensures the accuracy and repeatability of the measurements. The motorized stage allows precise positioning of the light source with respect to the active area. The emission spectrum of the xenon lamp provides a broad range of illumination in terms of dynamics and wavelength span.

Multipartite quantum correlation (MQC) not only explains many novel microscopic and macroscopic quantum phenomena, but also holds promise for specific quantum technologies with superiorities. MQCs descriptions and measures have been an open topic, due to their rich and complex organization and structure. Here reconsidering MQC descriptions and their practical applications in some quantum technologies, we propose a novel description called multipartite two-partite QC, which provides an intuitive and clear physical picture. Specifically, we present three types of measures: one class based on minimal entropy-like difference of local measurement fore-and-aft multipartite two-partite density matrix such as multipartite two-partite quantum discord (QD), another class based on minimal trace-like geometric distance such as multipartite two-partite Hilbert-Schmidt Distance (HSD), and a third class based on decoherence such as multipartite two-partite Local Measurement-Induced Minimal Decoherence (LMIMD) and Local Eigen-Measurement-Induced Decoherence (LEMID). Their computations required for these measures are relatively easy. All of the advantages make them promising candidates for specific potential applications in various quantum technologies. Finally, we employ these three types of measures to explore the organization and structure of some typical genuine MQCs, and analyze their relative characteristics based on their physical implications and mathematical structures.

As a hybrid of artificial intelligence and quantum computing, quantum neural networks (QNNs) have gained significant attention as a promising application on near-term, noisy intermediate-scale quantum (NISQ) devices. Conventional QNNs are described by parametrized quantum circuits, which perform unitary operations and measurements on quantum states. In this work, we propose a novel approach to enhance the expressivity of QNNs by incorporating randomness into quantum circuits. Specifically, we introduce a random layer, which contains single-qubit gates sampled from an trainable ensemble pooling. The prediction of QNN is then represented by an ensemble average over a classical function of measurement outcomes. We prove that our approach can accurately approximate arbitrary target operators using Uhlmann's theorem for majorization, which enables observable learning. Our proposal is demonstrated with extensive numerical experiments, including observable learning, R\'enyi entropy measurement, and image recognition. We find the expressivity of QNNs is enhanced by introducing randomness for multiple learning tasks, which could have broad application in quantum machine learning.

Continuous-variable quantum key distribution (CV-QKD) using a true local (located at the receiver) oscillator (LO) has been proposed to remove any possibility of side-channel attacks associated with transmission of the LO as well as reduce the cross-pulse contamination. Here we report an implementation of true LO CV-QKD using "off-the-shelf" components and conduct QKD experiments using the fiber optical network at Oak Ridge National Laboratory. A phase reference and quantum signal are time multiplexed and then wavelength division multiplexed with the classical communications which "coexist" with each other on a single optical network fiber. This is the first demonstration of CV-QKD with a receiver-based true LO over a deployed fiber network, a crucial step for its application in real-world situations.

We use a tensor network renormalization group method to study random $S=2$ antiferromagnetic Heisenberg chains with alternating bond strength distributions. In the absence of randomness, bond alternation induces two quantum critical points between the $S=2$ Haldane phase, a partially dimerized phase and a fully dimerized phase, depending on the strength of dimerization. These three phases, called ($\sigma$,$4-\sigma$)=(2,2), (3,1) and (4,0) phases, are valence-bond solid (VBS) states characterized by $\sigma$ valence bonds forming across even links and $4-\sigma$ valence bonds on odd links. Here we study the effects of bond randomness on the ground states of the dimerized spin chain, calculating disorder-averaged twist order parameters and spin correlations. We classify the types of random VBS phases depending on the strength of bond randomness $R$ and dimerization $D$ using the twist order parameter, which has a negative/positive sign for a VBS phase with odd/even $\sigma$. Our results demonstrate the existence of a multicritical point in the intermediate disorder regime with finite dimerization, where (2,2), (3,1) and (4,0) phases meet. This multicritical point is at the junction of three phase boundaries in the $R$-$D$ plane: the (2,2)-(3,1) and (3,1)-(4,0) boundaries that extend to zero randomness, and the (2,2)-(4,0) phase boundary that connects another multicritical point in the undimerized limit. The undimerized multicritical point separates a gapless Haldane phase and an infinite-randomness critical line with the diverging dynamic critical exponent in the large $R$ limit at $D=0$. Furthermore, we identify the (3,1)-(4,0) phase boundary as an infinite-randomness critical line even at small $R$, and find the signature of infinite randomness at the (2,2)-(3,1) phase boundary only in the vicinity of the multicritical point.

Investigating the behavior of noninteracting fermions subjected to local dephasing, we reveal that quasi-particle dephasing can induce superdiffusive transport. This superdiffusion arises from nodal points within the momentum distribution of local dephasing quasi-particles, leading to asymptotic long-lived modes. By studying the dynamics of the Wigner function, we rigorously elucidate how the dynamics of these enduring modes give rise to L\'evy walk processes, a renowned mechanism underlying superdiffusion phenomena. Our research demonstrates the controllability of dynamical scaling exponents by selecting quasi-particles and extends its applicability to higher dimensions, underlining the pervasive nature of superdiffusion in dephasing models.

Quantum computers are expected to contribute more efficient and accurate ways of modeling economic processes. Quantum hardware is currently available at a relatively small scale, but effective algorithms are limited by the number of logic gates that can be used, before noise from gate inaccuracies tends to dominate results. Some theoretical algorithms that have been proposed and studied for years do not perform well yet on quantum hardware in practice. This encourages the development of suitable alternative algorithms that play similar roles in limited contexts.

This paper implements this strategy in the case of quantum counting, which is used as a component for keeping track of position in a quantum walk, which is used as a model for simulating asset prices over time. We introduce quantum approximate counting circuits that use far fewer 2-qubit entangling gates than traditional quantum counting that relies on binary positional encoding. The robustness of these circuits to noise is demonstrated.

We compare the results to price change distributions from stock indices, and compare the behavior of quantum circuits with and without mid-measurement to trends in the housing market. The housing data shows that low liquidity brings price volatility, as expected with the quantum models.

Quantum waveform estimation, in which quantum sensors sample entire time series, promises to revolutionize the sensing of weak and stochastic signals, such as the biomagnetic impulses emitted by firing neurons. For long duration signals with rapid transients, regular quantum sampling becomes prohibitively resource intensive as it demands many measurements with distinct control and readout. In this Manuscript, we demonstrate how careful choice of quantum measurements, along with the modern mathematics of compressive sensing, achieves quantum waveform estimation of sparse signals in a number of measurements far below the Nyquist requirement. We sense synthesized neural-like magnetic signals with radiofrequency-dressed ultracold atoms, retrieving successful waveform estimates with as few measurements as compressive theoretical bounds guarantee.

The nonstabilizerness, or magic, is an essential quantum resource to perform universal quantum computation. Robustness of magic (RoM) in particular characterizes the degree of usefulness of a given quantum state for non-Clifford operation. While the mathematical formalism of RoM can be given in a concise manner, it is extremely challenging to determine the RoM in practice, since it involves superexponentially many pure stabilizer states. In this work, we present efficient novel algorithms to compute the RoM. The crucial technique is a subroutine that achieves the remarkable features in calculation of overlaps between pure stabilizer states: (i) the time complexity per each stabilizer is reduced exponentially, (ii) the space complexity is reduced superexponentially. Based on this subroutine, we present algorithms to compute the RoM for arbitrary states up to $n=7$ qubits on a laptop, while brute-force methods require a memory size of 86 TiB. As a byproduct, the proposed subroutine allows us to simulate the stabilizer fidelity up to $n=8$ qubits, for which naive methods require memory size of 86 PiB so that any state-of-the-art classical computer cannot execute the computation. We further propose novel algorithms that utilize the preknowledge on the structure of target quantum state such as the permutation symmetry of disentanglement, and numerically demonstrate our state-of-the-art results for copies of magic states and partially disentangled quantum states. The series of algorithms constitute a comprehensive ``handbook'' to scale up the computation of the RoM, and we envision that the proposed technique applies to the computation of other quantum resource measures as well.

The Quantum Approximate Optimization Algorithm (QAOA) exhibits significant potential for tackling combinatorial optimization problems. Despite its promise for near-term quantum devices, a major challenge in applying QAOA lies in the optimization cost associated with parameter setting. Existing methods for parameter setting generally incur at least a superlinear optimization cost. In this study, we propose a novel adiabatic-passage-based parameter setting method that remarkably reduces the optimization cost, specifically when applied to the 3-SAT problem, to a sublinear level concerning the depth p of QAOA. Beginning with an analysis of the random model of 3-SAT problem, this method applies a problem-dependent preprocessing on the problem Hamiltonian, effectively segregating the magnitude of parameters from the scale of the problem. Consequently, a problem-independent initialization is achieved without incurring any optimization cost. Furthermore, the parameter space is adjusted based on the continuity of the optimal adiabatic passage, resulting in a reduction in the disparity of parameters between adjacent layers of QAOA. By leveraging this continuity, the cost to find quasi-optimal parameters is significantly reduced to a sublinear level.

With the emergence of quantum computing, a growing number of quantum devices is accessible via cloud offerings. However, due to the rapid development of the field, these quantum-specific service offerings vary significantly in capabilities and requirements they impose on software developers. This is particularly challenging for practitioners from outside the quantum computing domain who are interested in using these offerings as parts of their applications. In this paper, we compare several devices based on different hardware technologies and provided through different offerings, by conducting the same experiment on each of them. By documenting the lessons learned from our experiments, we aim to simplify the usage of quantum-specific offerings and illustrate the differences between predominant quantum hardware technologies.

The Large Hadron Collider's high luminosity era presents major computational challenges in the analysis of collision events. Large amounts of Monte Carlo (MC) simulation will be required to constrain the statistical uncertainties of the simulated datasets below these of the experimental data. Modelling of high-energy particles propagating through the calorimeter section of the detector is the most computationally intensive MC simulation task. We introduce a technique combining recent advancements in generative models and quantum annealing for fast and efficient simulation of high-energy particle-calorimeter interactions.

In this paper, we present a Python-based solution designed to simulate a one-dimensional quantum system that incorporates multiple Dirac delta potentials. The primary aim of this research is to investigate the scattering phenomenon within such a system. By developing this program, we can generate wave functions throughout the system and compute transmission and reflection coefficients analytically and numerically for an infinite range of combinations involving potential strengths, distances, and the number of Dirac delta potentials. Furthermore, by modifying the code, we investigate transmission resonances, which yields the energy eigenvalues for particles undergoing perfect transmission through the quantum system. Subsequently, our research can be extended by considering impurities in the system. Finally, we attain the general analytical solution for transmission and reflection probabilities applicable to any number of potentials, and we possess the capability to generate variation plots that effectively explore the behavior of the system under scattering.

The rapid growth in size of quantum devices demands efficient ways to control them, which is challenging for systems with thousands of qubits or more. Here, we present a simple yet powerful solution: robust, site-dependent control of an arbitrary number of qubits in parallel with only minimal local tunability of the driving field. Inspired by recent experimental advances, we consider access to only one of three constrained local control capabilities: local control of either the phase or amplitude of the beam at each qubit, or individual Z rotations. In each case, we devise parallelizable composite pulse sequences to realize arbitrary single-qubit unitaries robust against quasistatic amplitude and frequency fluctuations. Numerical demonstration shows that our approach outperforms existing sequences such as BB1 and CORPSE in almost all regimes considered, achieving average fidelity $>0.999$ under a decoherence rate $\sim 10^{-5}$, even with a few percent amplitude and frequency error. Our results indicate that even for very large qubit ensembles, accurate, individual manipulation can be achieved despite substantial control inhomogeneity.

Gaussian Boson Sampling is a promising method for experimental demonstrations of quantum advantage because it is easier to implement than other comparable schemes. While most of the properties of Gaussian Boson Sampling are understood to the same degree as for these other schemes, we understand relatively little about the statistical properties of its output distribution. The most relevant statistical property, from the perspective of demonstrating quantum advantage, is the anticoncentration of the output distribution as measured by its second moment. The degree of anticoncentration features in arguments for the complexity-theoretic hardness of Gaussian Boson Sampling, and it is also important to know when using cross-entropy benchmarking to verify experimental performance. In this work, we develop a graph-theoretic framework for analyzing the moments of the Gaussian Boson Sampling distribution. Using this framework, we show that Gaussian Boson Sampling undergoes a transition in anticoncentration as a function of the number of modes that are initially squeezed compared to the number of photons measured at the end of the circuit. When the number of initially squeezed modes scales sufficiently slowly with the number of photons, there is a lack of anticoncentration. However, if the number of initially squeezed modes scales quickly enough, the output probabilities anticoncentrate weakly.