We present benchmarking results for single-qubit gates implemented on a neutral atom quantum processor using Direct Randomized Benchmarking (DRB) and Gate Set Tomography (GST). The DRB protocol involves preparing stabilizer states, applying $m$ layers of native single-qubit gates, and measuring in the computational basis, providing an efficient error characterization under a stochastic Pauli noise model. GST enables the full, self-consistent reconstruction of quantum processes, including gates, input states, and measurements. Both protocols provide robust to state preparation and measurement (SPAM) errors estimations of gate performance, offering complementary perspectives on quantum gate fidelity. For single-qubit gates, DRB yields an average fidelity of $99.963 \pm 0.016\%$. The protocol was further applied to a 25-qubit array under global single-qubit control. GST results are consistent with those obtained via DRB. We also introduce a gauge optimization procedure for GST that brings the reconstructed gates, input states, and measurements into a canonical frame, enabling meaningful fidelity comparisons while preserving physical constraints. These constraints of the operators -- such as complete positivity and trace preservation -- are enforced by performing the optimization over the Stiefel manifold. The combined analysis supports the use of complementary benchmarking techniques for characterizing scalable quantum architectures.

We present an experimental platform for linear-optical quantum information processing. Our setup utilizes multiphoton generation using a high-quality single-photon source, which is demultiplexed across multiple spatial channels, a custom-designed, programmable, low-loss photonic chip, and paired with high-efficiency single-photon detectors. We demonstrate the platform's capability in producing heralded arbitrary two-qubit dual-rail encoded states, a crucial building block for large-scale photonic quantum computers. The programmable chip was fully characterized through a calibration process that allowed us to create a numerical model accounting for fabrication imperfections and measurement errors. As a result, using on-chip quantum state tomography (QST), we achieved high-fidelity quantum state preparation, with a fidelity of 98.5% specifically for the Bell state.

We adopt a method of the quantum gate teleportation for converting circuit-based quantum computation primitives into fusion networks. By using the presented scheme for the CNOT gate we construct translation of the circuit for the foliated surface code into a fault tolerant fusion network. Finally, we construct two new fusion based quantum computation models and study their fault tolerance properties.

We developed an algorithm that constructs a model of a reconfigurable optical interferometer, independent of specific architectural constraints. The programming of unitary transformations on the interferometer's optical modes relies on either an analytical method for deriving the unitary matrix from a set of phase shifts or an optimization routine when such decomposition is not available. Our algorithm employs a supervised learning approach, aligning the interferometer model with a training set derived from the device being studied. A straightforward optimization procedure leverages this trained model to determine the phase shifts of the interferometer with a specific architecture, obtaining the required unitary transformation. This approach enables the effective tuning of interferometers without requiring a precise analytical solution, paving the way for the exploration of new interferometric circuit architectures.

Bell state measurements (BSM) play a significant role in quantum information and quantum computing, in particular, in fusion-based quantum computing (FBQC). The FBQC model is a framework for universal quantum computing provided that we are able to perform entangling measurements, called fusions, on qubits within small entangled resource states. Here we analyse the usage of different linear-optical BSM circuits as fusions in the FBQC schemes and numerically evaluate hardware requirements for fault-tolerance in this framework. We examine and compare the performance of several BSM circuits with varying additional resources and estimate the requirements on losses for every component of the linear-optical realization of fusions under which errors in fusion networks caused by these losses can be corrected. Our results show that fault-tolerant quantum computing in the FBQC model is possible with currently achievable levels of optical losses in an integrated photonic implementation, provided that we can create and detect single photons of the resource states with a total marginal efficiency higher than 0.973.

Large-scale programmable photonic circuits are opening up new possibilities for information processing providing fast and energy-efficient means for matrix-vector multiplication. Here, we introduce a novel architecture of photonic circuits capable of implementing non-unitary transfer matrices, usually required by photonic neural networks, iterative equation solvers or quantum samplers. Our architecture exploits compact low-depth beam-splitter meshes rather than bulky fully connected mixing blocks used in previous designs, making it more compatible with planar integrated photonics technology. We have shown that photonic circuits designed with our architecture have lower depth than their standard counterparts and are extremely tolerant to hardware errors.

We present a comparative analysis of physical constraints limiting the quality of spin entanglement created using the Rydberg blockade technique in an ensemble of trapped neutral 87 Rb atoms. Based on the approach developed earlier in Phys. Rev. A 106 , 042410 ( 2022 ) PLRAAN 1050-2947 10.1103/PhysRevA.106.042410 , we consider the complete multilevel Zeeman structure of the interacting atoms and apply our simulations to two excitation geometries featured by different transition types, both feasible for experimental verification. We demonstrate that the blockade shift strongly depends not only on the interatomic separation but also on the angular position of the atom pair with respect to the quantization axis determined by polarization of the driving fields. As an example, we have estimated fidelity for a promising design of a CZ gate, recently proposed by Levine et al . [ Phys. Rev. Lett. 123 , 230501 ( 2019 ) PRLTAO 0031-9007 10.1103/PhysRevLett.123.230501 ] for various possible experimental geometries. Anisotropic effects in entangling gates considered here are important for the optimal choice of proper geometry for quantum computing in two- and three-dimensional arrays of atomic qubits and are of considerable interest for quantum simulators, especially those that are designed for anisotropic physical models.

We study quantum computing technology based on neutral rubidium atoms. Effect of Rydberg blockade is use in order to achieve entanglement of two qubits. Rydberg states are obtained by shining on the array of cold atoms with two lasers. Stability of the driving lasers and noise reduction are required for high fidelity of quantum gates. Theoretical analysis and experimental setup of PDH-locking scheme with additional filtering resonator will be presented.

The constantly increasing dimensionality of artificial quantum systems demands for highly efficient methods for their characterization and benchmarking. Conventional quantum tomography fails for larger systems due to the exponential growth of the required number of measurements. The conceptual solution for this dimensionality curse relies on a simple idea - a complete description of a quantum state is excessive and can be discarded in favor of experimentally accessible information about the system. The probably approximately correct (PAC) learning theory has been recently successfully applied to a problem of building accurate predictors for the measurement outcomes using a dataset which scales only linearly with the number of qubits. Here we present a constructive and numerically efficient protocol which learns a tensor network model of an unknown quantum system. We discuss the limitations and the scalability of the proposed method.

We introduce a programmable eight-port interferometer with the recently proposed error-tolerant architecture capable of performing a broad class of transformations. The interferometer has been fabricated with femtosecond laser writing, and it is the largest programmable interferometer of this kind to date. We have demonstrated its advantageous error tolerance by showing an operation in a broad wavelength range from 920 to 980 nm, which is particularly relevant for quantum photonics due to efficient photon sources existing in this wavelength range. Our work highlights the importance of developing novel architectures of programmable photonics for information processing.

This paper introduces a method for general N mode transformation of light using multilayer interferometers, reducing the number of phase-shifter layers from 2N+3 to N+2. We show numerically that simple constant-depth mixing layer exhibits error-tolerance. (c) 2024 The Author(s)

We report low-loss multiscan waveguides fabricated in fused silica using femtosecond-laser-writing technology. The multiscan principle allows the writing regime to be tailored to excel at key features of any integrated photonic platform: coupling losses and propagation losses. We optimized the writing parameters for different sizes of square-shaped waveguides and reached the mode overlap value with a standard single- mode optical fiber of above 98.8% and demonstrated very low coupling losses of 0.2 dB/facet on average. Propagation losses in the fabricated waveguides amounted to 0.07 dB/cm. We applied the developed recipe to the fabrication of a fiber-coupled 25-channel interferometer with total insertion losses below 1 dB. The findings of this work are of interest for broad range of applications and in particular for optical information processing and quantum photonics.

Parametrized quantum circuits are essential components of variational quantum algorithms. Until now, optical implementations of these circuits have relied solely on adjustable linear optical units. In this study, we demonstrate that using programmable nonlinearities, rather than linear optics, offers a more efficient method for constructing quantum optical circuits -- especially quantum neural networks. This approach significantly reduces the number of adjustable parameters needed to achieve high-fidelity operation. Specifically, we explored a quantum optical neural network (QONN) architecture composed of meshes of two-mode interferometers programmable by adjustable Kerr-like nonlinearities. We assessed the capabilities of our quantum optical neural network architecture and compared its performance to previously studied architectures that use multimode linear optics units. Additionally, we suggest future research directions for improving programmable quantum optical circuits.

We present an experimental implementation of a two-qubit photonic quantum processor fabricated using femtosecond laser writing technology. We employ femtosecond laser writing to create a low-loss reconfigurable photonic chip, implementing precise single-qubit and two-qubit operations. We present a careful characterization of the performance of single- and two-qubit gates. An exemplary application of estimating the ground state energy of an H2 molecule using the variational quantum eigensolver algorithm is demonstrated. Our results highlight the potential of the femtosecond laser writing technology to deliver high quality small-scale quantum photonic processors.

Analyzing the properties of complex quantum systems is crucial for further development of quantum devices, yet this task is typically challenging and demanding with respect to required amount of measurements. A special attention to this problem appears within the context of characterizing outcomes of noisy intermediate-scale quantum devices, which produce quantum states with specific properties so that it is expected to be hard to simulate such states using classical resources. In this work, we address the problem of characterization of a boson sampling device, which uses interference of input photons to produce samples of non-trivial probability distributions that at certain condition are hard to obtain classically. For realistic experimental conditions the problem is to probe multi-photon interference with a limited number of the measurement outcomes without collisions and repetitions. By constructing networks on the measurements outcomes, we demonstrate a possibility to discriminate between regimes of indistinguishable and distinguishable bosons by quantifying the structures of the corresponding networks. Based on this we propose a machine-learning-based protocol to benchmark a boson sampler with unknown scattering matrix. Notably, the protocol works in the most challenging regimes of having a very limited number of bitstrings without collisions and repetitions. As we expect, our framework can be directly applied for characterizing boson sampling devices that are currently available in experiments.

We present a heuristic mathematical model of the relation between the geometry of a photonic crystal waveguide and the Purcell-enhancement factor at a particular wavelength of interest. We use this model to propose approaches to the design of a photonic crystal waveguide maximizing the Purcell enhancement at a target wavelength. Numerical simulations indicate that the proposed model allows controlled variation of Purcell-factor peak width and height, which can be used to achieve increased robustness with regard to fabrication defects.

We report a design and implementation of a resource-efficient spatial demultiplexer which produces four indistinguishable photons with efficiency of 39.7% per channel. Our scheme is based on a free-space storage/delay line which accumulates four photons and releases them by a controlled polarization rotation using a single Pockels cell.

We investigate the efficiency of a loop scheme for the spatial demultiplexing of N successive photons using only one Pockels cell at the center of the loop scheme. The maximum operating frequency of the Pockels cell, due to technical limitations, is 13.5 MHz. We experimentally find the maximum achievable demultiplexing efficiency with a single Pockels cell using continuous-wave and pulsed lasers and analog fast photodetectors. The maximum efficiency achieved at the maximum switching frequency is 87%.

The characteristics of a single-photon emitter based on a semiconductor quantum dot, such as their indistinguishability and brightness, depend on the stability of the recombination channel, which can switch spontaneously between exciton and trion. We show that dominant recombination through neutral exciton states can be achieved by careful control of the doping profile near an epitaxial InAs/GaAs quantum dot placed in a columnar microcavity with distributed Bragg reflectors. The Hong-Ou-Mandel experiments carried out in the fabricated device demonstrate the degree of indistinguishability of 91% of successively emitted single photons within 242 ns at an efficiency of 10% inside a single-mode optical fiber. The achieved brightness made it possible to implement spatio-temporal demultiplexing of photons in six independent spatial modes with an in-fiber generation frequency of more than 0.1 Hz.

The implementation of a quantum logic gate in a system of cold atoms in optical microtraps is analyzed. The dynamics of two spin qubits is simulated, and a number of processes that limit the efficiency of entanglement based on the Rydberg blockade effect are considered. A geometry of two-photon excitation of Rydberg states of atoms is proposed that makes it possible to increase the robustness of the system to variations in a number of parameters and to reduce losses associated with the incoherent scattering of the driving field.