QUROPE Quantum Information Processing and Communication in Europe

In the framework of the hybrid quantum-classical variational cluster approach (VCA) to strongly correlated fermion systems one of the goals of a quantum subroutine is to find single-particle correlation functions of lattice fermions in polynomial time. Previous works suggested to use variants of the Hadamard test for this purpose. However, it requires an implementation of controlled unitaries specifying the full dynamics of the simulated model. In this work, we propose a new quantum algorithm, which uses an analog of the Kubo formula within linear response theory adapted to a quantum circuit simulating the Hubbard model. It allows to access the Green's function of a cluster directly and thereby circumvents the usage of the Hadamard test. We find a drastic reduction in gate count of two-qubits gates and limitations on hardware design as compared to previous approaches.

Quantum kernel methods are a promising method in quantum machine learning thanks to the guarantees connected to them. Their accessibility for analytic considerations also opens up the possibility of prescreening datasets based on their potential for a quantum advantage. To do so, earlier works developed the geometric difference, which can be understood as a closeness measure between two kernel-based machine learning approaches, most importantly between a quantum kernel and classical kernel. This metric links the quantum and classical model complexities. Therefore, it raises the question of whether the geometric difference, based on its relation to model complexity, can be a useful tool in evaluations other than for the potential for quantum advantage. In this work, we investigate the effects of hyperparameter choice on the model performance and the generalization gap between classical and quantum kernels. The importance of hyperparameter optimization is well known also for classical machine learning. Especially for the quantum Hamiltonian evolution feature map, the scaling of the input data has been shown to be crucial. However, there are additional parameters left to be optimized, like the best number of qubits to trace out before computing a projected quantum kernel. We investigate the influence of these hyperparameters and compare the classically reliable method of cross validation with the method of choosing based on the geometric difference. Based on the thorough investigation of the hyperparameters across 11 datasets we identified commodities that can be exploited when examining a new dataset. In addition, our findings contribute to better understanding of the applicability of the geometric difference.

The interest in the Werner-Holevo channel has been mainly due to its abstract mathematical properties. We show that in three dimensions and with a slight modification, this channel can be realized as rotation of qutrit states in random directions by random angles. Therefore and in view of the potential use of qutrits in quantum processing tasks and their realization in many different platforms, the modifed Werner-Holevo channel can be used as a very simple and realistic noise model, in the same way that the depolarizing channel is for qubits. We will make a detailed study of this channel and derive its various properties. In particular we will use the recently proposed flag extension and other techniques to derive analytical expressions and bounds for different capacities of this channel. The role of symmetry is revealed in these derivations.

We show how to capture both the non-unitary Page curve and replica wormhole-like contributions that restore unitarity in a toy quantum system with random dynamics. The motivation is to find the simplest dynamical model that captures this aspect of gravitational physics. In our model, we evolve with an ensemble of Hamiltonians with GUE statistics within microcanonical windows. The entropy of the averaged state gives the non-unitary curve, the averaged entropy gives the unitary curve, and the difference comes from matrix index contractions in the Haar averaging that connect the density matrices in a replica wormhole-like manner.

Quantum programs are notoriously difficult to code and verify due to unintuitive quantum knowledge associated with quantum programming. Automated tools relieving the tedium and errors associated with low-level quantum details would hence be highly desirable. In this paper, we initiate the study of program synthesis for quantum unitary programs that recursively define a family of unitary circuits for different input sizes, which are widely used in existing quantum programming languages. Specifically, we present QSynth, the first quantum program synthesis framework, including a new inductive quantum programming language, its specification, a sound logic for reasoning, and an encoding of the reasoning procedure into SMT instances. By leveraging existing SMT solvers, QSynth successfully synthesizes ten quantum unitary programs including quantum adder circuits, quantum eigenvalue inversion circuits and Quantum Fourier Transformation, which can be readily transpiled to executable programs on major quantum platforms, e.g., Q#, IBM Qiskit, and AWS Braket.

The identification, description, and classification of topological features is an engine of discovery and innovation in several fields of physics. This research encompasses a broad variety of systems, from the integer and fractional Chern insulators in condensed matter, to protected states in complex photonic lattices in optics, and the structure of the QCD vacuum. Here, we introduce another playground for topology: the dissipative dynamics of the Sachdev-Ye-Kitaev (SYK) model, $N$ fermions in zero dimensions with strong $q$-body interactions coupled to a Markovian bath. For $q = 4, 8, \ldots$ and certain choices of $N$ and bath details, involving pseudo-Hermiticity, we find a rectangular block representation of the vectorized Liouvillian that is directly related to the existence of an anomalous trace of the unitary operator implementing fermionic exchange. As a consequence of this rectangularization, the Liouvillian has purely real modes for any coupling to the bath. Some of them are demonstrated to be topological by an explicit calculation of the spectral flow, leading to a symmetry-dependent topological index $\nu$. Topological properties have universal features: they are robust to changes in the Liouvillian provided that the symmetries are respected and they are also observed if the SYK model is replaced by a quantum chaotic dephasing spin chain in the same symmetry class. Moreover, the topological symmetry class can be robustly characterized by the level statistics of the corresponding random matrix ensemble. In the limit of weak coupling to the bath, topological modes govern the approach to equilibrium, which may enable a direct path for experimental confirmation of topology in dissipative many-body quantum chaotic systems.

Row-column multiplexing has proven to be an effective strategy in scaling single-photon detector arrays to kilopixel and megapixel spatial resolutions. However, with this readout mechanism, multiphoton coincidences on the array cannot be easily resolved due to ambiguities concerning their spatial locations of incidence. In this work, we propose a method to resolve up to 4-photon coincidences in single-photon detector arrays with row-column readouts. By utilizing unambiguous single-photon measurements to estimate probabilities of detection at each pixel, we redistribute the ambiguous multiphoton counts among candidate pixel locations such that the peak signal-to-noise-ratio of the reconstruction is increased between 3 and 4 dB compared to conventional methods at optimal operating conditions. We also show that our method allows the operation of these arrays at higher incident photon fluxes as compared to previous methods. The application of this technique to imaging natural scenes is demonstrated using Monte Carlo experiments.