arXiv subjects

Konstantinos Georgopoulos

Publications and source records attributed to Konstantinos Georgopoulos.

8 recordsLinked to original sources

arXiv2026

Spectral Gap Informed Ramp QAOA

A challenge with the Quantum Approximate Optimisation Algorithm (QAOA), and variational algorithms in general, is finding good variational parameters, a task which in itself can be NP-hard. Recent work has sought to de-variationalise QAOA by picking well-informed guesses for the variational parameters. The Linear Ramp QAOA (LR-QAOA) achieves this by using parameter schedules inspired by the quantum adiabatic algorithm. In this work, we propose Spectral Gap Informed Ramp QAOA (SGIR-QAOA), a new QAOA variant that incorporates spectral gap information from an adiabatic Hamiltonian, with the QAOA mixer Hamiltonian as the initial Hamiltonian, to construct smooth parameter schedules. SGIR-QAOA performs slow evolution where the spectral gap of the adiabatic Hamiltonian is small. We show that SGIR-QAOA has performance improvements over the LR-QAOA on Grover's problem at constant depth and that SGIR-QAOA requires shorter depths to achieve the same optimal solution probability. We then show that these performance benefits extend to a problem with potential practical applications - the Maximum Independent Set (MIS) problem. Finally, we demonstrate the scalability of the SGIR-QAOA method using extrapolated spectral gap information for scales that the spectral gap cannot be exactly evaluated, and show that the advantage appears to persist under mild depolarising noise.

quant-ph↗

arXiv2026

Cross-Platform Benchmarking of Near-Term Quantum Optimisation Algorithms

Quantum computers show potential for achieving computational advantage over classical computers, with many candidate applications in combinatorial optimisation. We present an application level benchmarking framework for near-term quantum optimisation algorithms using a dense Quadratic Unconstrained Binary Optimisation (QUBO) materials science problem as a representative test-case. To solve this problem, we implement two methods, the Variational Quantum Eigensolver (VQE) and Quantum Annealing (QA), on commercially-available gate-based and quantum annealing devices that are accessible via Quantum-Computing-as-a-Service (QCaaS) models. To analyse the performance of these algorithms, we use a toolbox of relevant metrics and compare performance against three classical algorithms. We employ quantum methods to solve fully-connected QUBOs of up to $72$ variables, and find that algorithm performance beyond this is restricted by device connectivity, noise and classical computation time overheads. The applicability of our approach goes beyond the selected configurational analysis test-case, and we anticipate that our approach will be of use for optimisation problems in general.

quant-ph↗

arXiv2026

Resource-efficient Quantum Algorithms for Selected Hamiltonian Subspace Diagonalization

Quantum algorithms for selecting a subspace of Hamiltonians to diagonalize have emerged as a promising alternative to variational algorithms in the NISQ era. So far, such algorithms, which include the quantum selected configuration interaction (QSCI) and sample-based quantum diagonalization (SQD), have been formulated within second-quantization in Fock space, which leads to inefficient usage of qubit resources. We introduce the first QSCI algorithm developed in the CI-matrix (CIM) framework, which is known to have optimal qubit scaling of exactly $\lceil \log_2 (N) \rceil$ where $N$ is the size of the CIM. In addition, we introduce a novel single-bit flip error mitigation which comes at the overhead of a single qubit and we combine this with a stochastic approximate Trotterization evolution adapted from qDRIFT. Simulating benchmark N$_2$ and naphthalene molecules on quantum hardware, our results achieved similar accuracy as SQD methods but with significantly less quantum resources. However, our CIM-QSCI algorithm and SQD methods could not match the performance of classical heat-bath CI (HCI) for the same task. Hence, we introduce an augmented version of QSCI called quantum selected heat-bath CI (QSHCI). This variant replaces classical heat-bath sampling with quantum sampling from QSCI to achieve performance comparable to HCI. We note that a current drawback of our approach is the preprocessing cost of $\mathcal{O}(N^2\log N)$ for constructing the CIM and performing the Pauli decomposition. This can be further improved by considering efficient CIM access models for the stochastic Trotter evolution.

quant-ph↗

arXiv2025

A Review and Collection of Metrics and Benchmarks for Quantum Computers: definitions, methodologies and software

Quantum computers have the potential to provide an advantage over classical computers in a number of areas. Numerous metrics to benchmark the performance of quantum computers, ranging from their individual hardware components to entire applications, have been proposed over the years. Navigating the resulting extensive literature can be overwhelming. Objective comparisons are further hampered in practice as different variations of the same metric are used, and the data disclosed together with a reported metric value is often not sufficient to reproduce the measurements. This article addresses these challenges by providing a review of metrics and benchmarks for quantum computers and 1) a comprehensive collection of benchmarks allowing holistic comparisons of quantum computers, 2) a consistent format of the definitions across all metrics including a transparent description of the methodology and of the main assumptions and limitations, and 3) a reproducible approach by linking the metrics to open-source software used to evaluate them. We identify five areas where international standardization working groups could be established, namely: i) the identification and agreement on the categories of metrics that comprehensively benchmark device performance; ii) the identification and agreement on a set of well-established metrics that together comprehensively benchmark performance; iii) the identification of metrics specific to hardware platforms, including non-gate-based quantum computers; iv) inter-laboratory comparison studies to develop best practice guides for measurement methodology; and v) agreement on what data and software should be reported together with a metric value to ensure trust, transparency and reproducibility. We provide potential routes to advancing these areas. We expect this compendium to accelerate the progress of quantum computing hardware towards quantum advantage.

quant-ph↗

arXiv2024

LightningNet: Distributed Graph-based Cellular Network Performance Forecasting for the Edge

The cellular network plays a pivotal role in providing Internet access, since it is the only global-scale infrastructure with ubiquitous mobility support. To manage and maintain large-scale networks, mobile network operators require timely information, or even accurate performance forecasts. In this paper, we propose LightningNet, a lightweight and distributed graph-based framework for forecasting cellular network performance, which can capture spatio-temporal dependencies that arise in the network traffic. LightningNet achieves a steady performance increase over state-of-the-art forecasting techniques, while maintaining a similar resource usage profile. Our architecture ideology also excels in the respect that it is specifically designed to support IoT and edge devices, giving us an even greater step ahead of the current state-of-the-art, as indicated by our performance experiments with NVIDIA Jetson.

cs.NI↗

arXiv2021

Quantum Computer Benchmarking via Quantum Algorithms

We present a framework that utilizes quantum algorithms, an architecture aware quantum noise model and an ideal simulator to benchmark quantum computers. The benchmark metrics highlight the difference between the quantum computer evolution and the simulated noisy and ideal quantum evolutions. We utilize our framework for benchmarking three IBMQ systems. The use of multiple algorithms, including continuous-time ones, as benchmarks stresses the computers in different ways highlighting their behaviour for a diverse set of circuits. The complexity of each quantum circuit affects the efficiency of each quantum computer, with increasing circuit size resulting in more noisy behaviour. Furthermore, the use of both a continuous-time quantum algorithm and the decomposition of its Hamiltonian also allows extracting valuable comparisons regarding the efficiency of the two methods on quantum systems. The results show that our benchmarks provide sufficient and well-rounded information regarding the performance of each quantum computer.

quant-ph↗

arXiv2021

Modelling and Simulating the Noisy Behaviour of Near-term Quantum Computers

Noise dominates every aspect of near-term quantum computers, rendering it exceedingly difficult to carry out even small computations. In this paper we are concerned with the modelling of noise in Noisy Intermediate-Scale Quantum (NISQ) computers. We focus on three error groups that represent the main sources of noise during a computation and present quantum channels that model each source. We engineer a noise model that combines all three noise channels and simulates the evolution of the quantum computer using its calibrated error rates. We run various experiments of our model, showcasing its behaviour compared to other noise models and an IBM quantum computer. We find that our model provides a better approximation of the quantum computer's behaviour than the other models. Following this, we use a genetic algorithm to optimize the parameters used by our noise model, bringing the behaviour of the model even closer to the quantum computer. Finally, a comparison between the pre and postoptimization parameters reveals that, according to our model, certain operations can be more or less erroneous than the hardware-calibrated parameters show.

quant-ph↗

arXiv2021

A Comparison of Quantum Walk Implementations on NISQ Computers

This paper explores two circuit approaches for quantum walks: the first consists of generalised controlled inversions, whereas the second one effectively replaces them with rotation operations around the basis states. We show the theoretical foundation of the rotational implementation. The rotational approach nullifies the large amount of ancilla qubits required to carry out the computation when using the inverter implementation. Our results concentrate around the comparison of the two architectures in terms of structure, benefits and detriments, as well as the computational resources needed for each approach. We show that the inverters approach requires exponentially fewer gates than the rotations but almost half the number of qubits in the system. Finally, we execute a number of experiments using an IBM quantum computer. The experiments show the effects of noise in our circuits. Small two-qubit quantum walks evolve closer to our expectations, whereas for a larger number of steps or state space the evolution is severely affected by noise.

quant-ph↗