QUROPE Quantum Information Processing and Communication in Europe

Quantum counting is a key quantum algorithm that aims to determine the number of marked elements in a database. This algorithm is based on the quantum phase estimation algorithm and uses the evolution operator of Grover's algorithm because its non-trivial eigenvalues are dependent on the number of marked elements. Since Grover's algorithm can be viewed as a quantum walk on a complete graph, a natural way to extend quantum counting is to use the evolution operator of quantum-walk-based search on non-complete graphs instead of Grover's operator. In this paper, we explore this extension by analyzing the coined quantum walk on the complete bipartite graph with an arbitrary number of marked vertices. We show that some eigenvalues of the evolution operator depend on the number of marked vertices and using this fact we show that the quantum phase estimation can be used to obtain the number of marked vertices. The time complexity for estimating the number of marked vertices in the bipartite graph with our algorithm aligns closely with that of the original quantum counting algorithm.

Quantum hardware suffers from high error rates and noise, which makes directly running applications on them ineffective. Quantum Error Correction (QEC) is a critical technique towards fault tolerance which encodes the quantum information distributively in multiple data qubits and uses syndrome qubits to check parity. Minimum-Weight-Perfect-Matching (MWPM) is a popular QEC decoder that takes the syndromes as input and finds the matchings between syndromes that infer the errors. However, there are two paramount challenges for MWPM decoders. First, as noise in real quantum systems can drift over time, there is a potential misalignment with the decoding graph's initial weights, leading to a severe performance degradation in the logical error rates. Second, while the MWPM decoder addresses independent errors, it falls short when encountering correlated errors typical on real hardware, such as those in the 2Q depolarizing channel.

We propose DGR, an efficient decoding graph edge re-weighting strategy with no quantum overhead. It leverages the insight that the statistics of matchings across decoding iterations offer rich information about errors on real quantum hardware. By counting the occurrences of edges and edge pairs in decoded matchings, we can statistically estimate the up-to-date probabilities of each edge and the correlations between them. The reweighting process includes two vital steps: alignment re-weighting and correlation re-weighting. The former updates the MWPM weights based on statistics to align with actual noise, and the latter adjusts the weight considering edge correlations.

Extensive evaluations on surface code and honeycomb code under various settings show that DGR reduces the logical error rate by 3.6x on average-case noise mismatch with exceeding 5000x improvement under worst-case mismatch.

The field of superconducting quantum computing, based on Josephson junctions, has recently seen remarkable strides in scaling the number of logical qubits. In particular, the fidelities of one- and two-qubit gates are close to the breakeven point with the novel error mitigation and correction methods. Parallel to these advances is the effort to expand the Hilbert space within a single device by employing high-dimensional qubits, otherwise known as qudits. Research has demonstrated the possibility of driving higher-order transitions in a transmon or designing innovative multimode superconducting circuits, termed multimons. These advances can significantly expand the computational basis while simplifying the interconnects in a large-scale quantum processor. This thesis provides a detailed introduction to the superconducting qudit and demonstrates a comprehensive analysis of decoherence in an artificial atom with more than two levels using Lindblad master equations and stochastic master equations (SMEs). After extending the theory of the design, control, and readout of a conventional superconducting qubit to that of a qudit, the thesis focuses on modeling the dispersive measurement of a transmon qutrit in an open quantum system using quadrature detections. Under the Markov assumption, master equations with different levels of abstraction are proposed and solved; in addition, both the ensemble-averaged and the quantum-jump approach of decoherence analysis are presented and compared analytically and numerically. The thesis ends with a series of experimental results on a transmon-type qutrit, verifying the validity of the stochastic model.

Studies on Quantum Computing have been developed since the 1980s, motivating researches on quantum algorithms better than any classical algorithm possible. An example of such algorithms is Grover's algorithm, capable of finding $k$ (marked) elements in an unordered database with $N$ elements using $O(\sqrt{N/k})$ steps. Grover's algorithm can be interpreted as a quantum walk in a complete graph (with loops) containing $N$ vertices from which $k$ are marked. This interpretation motivated search algorithms in other graphs -- complete bipartite graph, grid, and hypercube. Using Grover's algorithm's linear operator, the quantum counting algorithm estimates the value of $k$ with an error of $O(\sqrt{k})$ using $O(\sqrt{N})$ steps. This work tackles the problem of using the quantum counting algorithm for estimating the value $k$ of marked elements in other graphs; more specifically, the complete bipartite graph. It is concluded that for a particular case, running the proposed algorithm at most $t$ times wields an estimation of $k$ with an error of $O(\sqrt{k})$ using $O(t\sqrt{N})$ steps and success probability of at least $(1 - 2^{-t})8/\pi^2$.

A variational expression of the reduced relative entropy is given. A reduced Tsallis relative entropy is defined and some results are given. In particular, the convexity of the reduced Tsallis relative entropy is given. An interpolational inequality between Golden--Thompson and Jensen's trace inequalitie is given for one--parameter extended exponential function and positive definite matrices. In addition, a lower bound of the reduced Tsallis relative entropy is given under a certain assumption, by showing a variational expression of the reduced Tsallis relative entropy. Finally, an upper bound of the reduced Tsallis relative entropy is given.

The topic of quantum reference frames (QRFs) has attracted a great deal of attention in the recent literature. Potentially, the correct description of such frames is important for both the technological applications of quantum mechanics and for its foundations, including the search for a future theory of quantum gravity. In this letter, we point out potential inconsistencies in the mainstream approach to this subject and propose an alternative definition that avoids these problems. Crucially, we reject the notion that transformations between QRFs can be represented by unitary operators and explain the clear physical reasons for this. An experimental protocol, capable of empirically distinguishing between competing definitions of the term, is also proposed. The implications of the new model, for uncertainty relations, spacetime symmetries, gauge symmetries, the quantisation of gravity, and other foundational issues are discussed, and possible directions for future work in this field are considered.

Exploring operational regimes of many-body cavity QED with multi-level atoms remains an exciting research frontier for their enhanced storage capabilities of intra-level quantum correlations. In this work, we propose an extension of a prototypical many-body cavity QED experiment from a two to a four-level description by optically addressing a combination of momentum and spin states of the ultracold atoms in the cavity. The resulting model comprises a pair of Dicke Hamiltonians constructed from pseudo-spin operators, effectively capturing two intertwined superradiant phase transitions. The phase diagram reveals regions featuring weak and strong entangled states of spin and momentum atomic degrees of freedom. These states exhibit different dynamical responses, ranging from slow to fast relaxation, with the added option of persistent entanglement temporal oscillations. We discuss the role of cavity losses in steering the system dynamics into such entangled states and propose a readout scheme that leverages different light polarizations within the cavity. Our work paves the way to connect the rich variety of non-equilibrium phase transitions that occur in many-body cavity QED to the buildup of quantum correlations in systems with multi-level atom descriptions.

Solving optimization problems is a key task for which quantum computers could possibly provide a speedup over the best known classical algorithms. Particular classes of optimization problems including semi-definite programming (SDP) and linear programming (LP) have wide applicability in many domains of computer science, engineering, mathematics, and physics. Here we focus on semi-definite and linear programs for which the dimensions of the variables involved are exponentially large, so that standard classical SDP and LP solvers are not helpful for such large-scale problems. We propose the QSlack and CSlack methods for estimating their optimal values, respectively, which work by 1) introducing slack variables to transform inequality constraints to equality constraints, 2) transforming a constrained optimization to an unconstrained one via the penalty method, and 3) replacing the optimizations over all possible non-negative variables by optimizations over parameterized quantum states and parameterized probability distributions. Under the assumption that the SDP and LP inputs are efficiently measurable observables, it follows that all terms in the resulting objective functions are efficiently estimable by either a quantum computer in the SDP case or a quantum or probabilistic computer in the LP case. Furthermore, by making use of SDP and LP duality theory, we prove that these methods provide a theoretical guarantee that, if one could find global optima of the objective functions, then the resulting values sandwich the true optimal values from both above and below. Finally, we showcase the QSlack and CSlack methods on a variety of example optimization problems and discuss details of our implementation, as well as the resulting performance. We find that our implementations of both the primal and dual for these problems approach the ground truth, typically achieving errors of order $10^{-2}$.

The Tavis-Cummings model is a paradigmatic central-mode model where a set of two-level quantum emitters (spins) are coupled to a collective cavity mode. Here we study the eigenstate spectrum, its localization properties and the effect on dynamics, focusing on the two-excitation sector relevant for nonlinear photonics. These models admit two sources of disorder: in the coupling between the spins and the cavity and in the energy shifts of the individual spins. While this model was known to be exactly solvable in the limit of a homogeneous coupling and inhomogeneous energy shifts, we here establish the solvability in the opposite limit of a homogeneous energy shift and inhomogeneous coupling, presenting the exact solution and corresponding conserved quantities. We identify three different classes of eigenstates, exhibiting different degrees of multifractality and semilocalization closely tied to the integrable points, and study their stability to perturbations away from these solvable points. The dynamics of the cavity occupation number away from equilibrium, exhibiting boson bunching and a two-photon blockade, is explicitly related to the localization properties of the eigenstates and illustrates how these models support a collective spin description despite the presence of disorder.

Quantum chaotic systems are conjectured to display a spectrum whose fine-grained features (gaps and correlations) are well described by Random Matrix Theory (RMT). We propose and develop a complementary version of this conjecture: quantum chaotic systems display a Lanczos spectrum whose local means and covariances are well described by RMT. To support this proposal, we first demonstrate its validity in examples of chaotic and integrable systems. We then show that for Haar-random initial states in RMTs the mean and covariance of the Lanczos spectrum suffices to produce the full long time behavior of general survival probabilities including the spectral form factor, as well as the spread complexity. In addition, for initial states with continuous overlap with energy eigenstates, we analytically find the long time averages of the probabilities of Krylov basis elements in terms of the mean Lanczos spectrum. This analysis suggests a notion of eigenstate complexity, the statistics of which differentiate integrable systems and classes of quantum chaos. Finally, we clarify the relation between spread complexity and the universality classes of RMT by exploring various values of the Dyson index and Poisson distributed spectra.

There are two major approaches to building good machine learning algorithms: feeding lots of data into large models, or picking a model class with an ''inductive bias'' that suits the structure of the data. When taking the second approach as a starting point to design quantum algorithms for machine learning, it is important to understand how mathematical structures in quantum mechanics can lead to useful inductive biases in quantum models. In this work, we bring a collection of theoretical evidence from the Quantum Cognition literature to the field of Quantum Machine Learning to investigate how non-commutativity of quantum observables can help to learn data with ''order effects'', such as the changes in human answering patterns when swapping the order of questions in a survey. We design a multi-task learning setting in which a generative quantum model consisting of sequential learnable measurements can be adapted to a given task -- or question order -- by changing the order of observables, and we provide artificial datasets inspired by human psychology to carry out our investigation. Our first experimental simulations show that in some cases the quantum model learns more non-commutativity as the amount of order effect present in the data is increased, and that the quantum model can learn to generate better samples for unseen question orders when trained on others - both signs that the model architecture suits the task.

The emission linewidth in active medium emerges due to homogeneous and inhomogeneous broadening. We demonstrate that in lasers with inhomogeneous broadening there is a critical pump rate, above which the special mode forms. This mode consists of locked-in oscillations of cavity mode and of the active particles with different transition frequencies. Below the critical value of the pump rate, the radiation spectrum of the laser has a Gaussian profile, provided that inhomogeneous broadening is dominant. Above the critical value of pump rate, the special mode mostly determines the laser radiation spectrum. As the result, the spectrum attains Lorentz shape characteristic for homogeneous broadening. We demonstrate that the formation of the special mode precedes lasing and that the critical pump rate plays the role of lasing prethreshold. We obtain expressions for the threshold and generation frequency of single-mode laser where both homogeneous and inhomogeneous broadening are present.

We introduce a family of identities that express general linear non-unitary evolution operators as a linear combination of unitary evolution operators, each solving a Hamiltonian simulation problem. This formulation can exponentially enhance the accuracy of the recently introduced linear combination of Hamiltonian simulation (LCHS) method [An, Liu, and Lin, Physical Review Letters, 2023]. For the first time, this approach enables quantum algorithms to solve linear differential equations with both optimal state preparation cost and near-optimal scaling in matrix queries on all parameters.

Measurement-based quantum computation relies on single qubit measurements of large multipartite entangled states, so-called lattice-graph or cluster states. Graph states are also an important resource for quantum communication, where tree cluster states are a key resource for one-way quantum repeaters. A photonic realization of this kind of state would inherit many of the benefits of photonic platforms, such as very little dephasing due to weak environmental interactions and the well-developed infrastructure to route and measure photonic qubits. In this work, a linear cluster state and GHZ state generation scheme is developed for group-IV color centers. In particular, this article focuses on an in-depth investigation of the required control operations, including the coherent spin and excitation gates. We choose an off-resonant Raman scheme for the spin gates, which can be much faster than microwave control. We do not rely on a reduced level scheme and use efficient approximations to design high-fidelity Raman gates. We benchmark the spin-control and excitation scheme using the tin vacancy color center coupled to a cavity, assuming a realistic experimental setting. Additionally, the article investigates the fidelities of the Raman and excitation gates in the presence of radiative and non-radiative decay mechanisms. Finally, a quality measure is devised, which emphasizes the importance of fast and high-fidelity spin gates in the creation of large entangled photonic states.

Suppressing errors is the central challenge for useful quantum computing, requiring quantum error correction for large-scale processing. However, the overhead in the realization of error-corrected ``logical'' qubits, where information is encoded across many physical qubits for redundancy, poses significant challenges to large-scale logical quantum computing. Here we report the realization of a programmable quantum processor based on encoded logical qubits operating with up to 280 physical qubits. Utilizing logical-level control and a zoned architecture in reconfigurable neutral atom arrays, our system combines high two-qubit gate fidelities, arbitrary connectivity, as well as fully programmable single-qubit rotations and mid-circuit readout. Operating this logical processor with various types of encodings, we demonstrate improvement of a two-qubit logic gate by scaling surface code distance from d=3 to d=7, preparation of color code qubits with break-even fidelities, fault-tolerant creation of logical GHZ states and feedforward entanglement teleportation, as well as operation of 40 color code qubits. Finally, using three-dimensional [[8,3,2]] code blocks, we realize computationally complex sampling circuits with up to 48 logical qubits entangled with hypercube connectivity with 228 logical two-qubit gates and 48 logical CCZ gates. We find that this logical encoding substantially improves algorithmic performance with error detection, outperforming physical qubit fidelities at both cross-entropy benchmarking and quantum simulations of fast scrambling. These results herald the advent of early error-corrected quantum computation and chart a path toward large-scale logical processors.

Correlation between transmon and its composite Josephson junctions (JJ) plays an important role in designing new types of superconducting qubits based on quantum materials. It is desirable to have a type of device that not only allows exploration for use in quantum information processing but also probing intrinsic properties in the composite JJs. Here, we construct a flux-tunable 3D transmon-type superconducting quantum circuit made of graphene as a proof-of-concept prototype device. This 3D transmon-type device not only enables coupling to 3D cavities for microwave probes but also permits DC transport measurements on the same device, providing useful connections between transmon properties and critical currents associated with JJ's properties. We have demonstrated how flux-modulation in cavity frequency and DC critical current can be correlated under the influence of Fraunhofer pattern of JJs in an asymmetric SQUID. The correlation analysis was further extended to link the flux-modulated transmon properties, such as flux-tunability in qubit and cavity frequencies, with SQUID symmetry analysis based on DC measurements. Our study paves the way towards integrating novel materials for exploration of new types of quantum devices for future technology while probing underlying physics in the composite materials.

High-dimensional teleportation provides various benefits in quantum networks and repeaters, but all these advantages rely on the high-quality distribution of high-dimensional entanglement over a noisy channel. It is essential to consider correlation effects when two entangled qutrits travel consecutively through the same channel. In this paper, we present two strategies for enhancing qutrit teleportation in correlated amplitude damping (CAD) noise by weak measurement (WM) and environment-assisted measurement (EAM). The fidelity of both approaches has been dramatically improved due to the probabilistic nature of WM and EAM. We have observed that the correlation effects of CAD noise result in an increase in the probability of success. A comparison has demonstrated that the EAM scheme consistently outperforms the WM scheme in regard to fidelity. Our research expands the capabilities of WM and EAM as quantum techniques to combat CAD noise in qutrit teleportation, facilitating the development of advanced quantum technologies in high-dimensional systems.

We study the effect of PT-symmetric non-hermiticity on the transport of edge state probability density arising as a result of a quench. A hybrid system involving a PT-symmetric SSH region sandwiched between two plain SSH systems is designed to study the dynamics. Geometrical arguments and numerical calculations were made to ascertain the nature of edge states. We then compute the quench dynamics numerically and demonstrate that the post-quench probability density light cones exhibit contrasting shapes as a result of asymmetrical reflections from the non-Hermitian part of the system depending on the direction of propagation of the transporting wave and, hence, on the initial localization of the edge state.

Quantum state discrimination is a central task in many quantum computing settings where one wishes to identify what quantum state they are holding. We introduce a framework that generalizes many of its variants and present a hybrid quantum-classical algorithm based on semidefinite programming to calculate the maximum reward when the states are pure and have efficient circuits. To this end, we study the (not necessarily linearly independent) pure state case and reduce the standard SDP problem size from $2^n L$ to $N L$ where $n$ is the number of qubits, $N$ is the number of states, and $L$ is the number of possible guesses (typically $L = N$). As an application, we give now-possible algorithms for the quantum change point identification problem which asks, given a sequence of quantum states, determine the time steps when the quantum states changed. With our reductions, we are able to solve SDPs for problem sizes of up to $220$ qubits in about $8$ hours and we also give heuristics which speed up the computations.

We study the spectrum of the Dirac Hamiltonian in one space dimension for a single electron in the electrostatic potential of a point nucleus, in the Born-Oppenheimer approximation where the nucleus is assumed fixed at the origin. The potential is screened at large distances so that it goes to zero exponentially at spatial infinity. We show that the Hamiltonian is essentially self-adjoint, the essential spectrum has the usual gap $(-mc^2,mc^2)$ in it, and that there are only finitely many eigenvalues in that gap, corresponding to ground and excited states for the system. We find a one-to-one correspondence between the eigenfunctions of this Hamiltonian and the heteroclinic saddle-saddle connectors of a certain dynamical system on a finite cylinder. We use this correspondence to study how the number of bound states changes with the nuclear charge.