arXiv subjects

Giuseppe Bisicchia

Publications and source records attributed to Giuseppe Bisicchia.

10 recordsLinked to original sources

arXiv2026

StableShots: Online Shot Stopping for Quantum Circuit Execution

Quantum circuit execution estimates output distributions by repeated measurements, yet developers commonly choose a fixed shot budget before execution. This static choice is brittle: low budgets can under-sample the distribution, while high budgets waste measurements. In this paper, we present StableShots, a black-box online stopping rule for static quantum circuits. The method executes a fixed circuit in small batches, monitors the total-variation distance between cumulative empirical distributions, and stops after repeated evidence of local stability. We evaluate StableShots on 180 QSimBench traces spanning six circuit families, six sizes from 4 to 14 qubits, and five noisy IBM simulated backends. With validation-only calibration and 100 repeated backend-holdout splits, the selected configuration reaches TVD <= 0.05 on all held-out test evaluations with median 7,650 shots, whereas fixed-shot baselines either fail more often or spend substantially more shots.

quant-ph↗

arXiv2026

How Many Shots Are Enough for a Quantum Circuit?

Quantum algorithms require repeated circuit executions, known as shots, to estimate output distributions accurately. Determining the minimal number of shots needed to meet a target accuracy is crucial to reduce costs and resource usage, especially on today's noisy and expensive quantum hardware. In this paper, we address the shot optimisation problem in a black-box setting, where no assumptions are made about the structure of the quantum circuit or the noise model of the backend. We introduce IncrementalExecution, a novel online framework that dynamically determines when to stop executing shots based on the principle of point of diminishing returns: the point at which additional shots no longer significantly alter the empirical distribution of a fixed circuit. The framework supports customisable policies for shot management, enabling flexible trade-offs between execution cost and result fidelity within static execution scenarios. We assess our proposal through an extensive experimental evaluation spanning 33,750 framework configurations across 180 unique static quantum circuit-backend combinations, for a total of 7.3M independent experiments. Unlike prior work that relies on problem-specific knowledge or algorithm-dependent assumptions (e.g., variational or adaptive workflows), our approach is applicable to a large set of static circuits and immediately deployable on current quantum cloud platforms.

quant-ph↗

arXiv2026

A Neurosymbolic Prolog Skill for LLM-Driven Service Placement

Service placement in the cloud-edge continuum requires assigning application components to heterogeneous resources under multiple constraints, including latency, locality, and policy requirements. Existing approaches rely on optimisation models or heuristics that require explicit modelling, while neural methods lack transparency and formal guarantees. This work proposes a neuro-symbolic alternative based on a Prolog skill, a reusable interface for schema-constrained fact generation and querying, for constraint-aware placement. The skill enables a language model to structure placement intent into symbolic facts, rules, and queries, while delegating validation and reasoning to Prolog. This design bridges high-level intent and formal constraint evaluation, enabling inspectable and policy-aware placement decisions in cloud-edge environments.

cs.DC↗

arXiv2026

Evaluating Security Properties in the Execution of Quantum Circuits

Quantum computing is a disruptive technology that is expected to offer significant advantages in many critical fields (e.g. drug discovery and cryptography). The security of information processed by such machines is therefore paramount. Currently, modest Noisy Intermediate-Scale Quantum (NISQ) devices are available. The goal of this work is to identify a practical, heuristic methodology to evaluate security properties, such as secrecy and integrity, while using quantum processors owned by potentially untrustworthy providers.

quant-ph↗

arXiv2025

Rethinking Services in the Quantum Age: The SOQ Paradigm

Quantum computing is rapidly progressing from theoretical promise to practical implementation, offering significant computational advantages for tasks in optimization, simulation, cryptography, and machine learning. However, its integration into real-world software systems remains constrained by hardware fragility, platform heterogeneity, and the absence of robust software engineering practices. This paper introduces Service-Oriented Quantum (SOQ), a novel paradigm that reimagines quantum software systems through the lens of classical service-oriented computing. Unlike prior approaches such as Quantum Service-Oriented Computing (QSOC), which treat quantum capabilities as auxiliary components within classical systems, SOQ positions quantum services as autonomous, composable, and interoperable entities. We define the foundational principles of SOQ, propose a layered technology stack to support its realization, and identify the key research and engineering challenges that must be addressed, including interoperability, hybridity, pricing models, service abstractions, and workforce development. This approach is of vital importance for the advancement of quantum technology because it enables the scalable, modular, and interoperable integration of quantum computing into real-world software systems independently and without relying on a dedicated classical environment to manage quantum processing.

cs.SE↗

arXiv2025

Quantum Executor: A Unified Interface for Quantum Computing

As quantum computing evolves from theoretical promise to practical deployment, the demand for robust, portable, and scalable tools for quantum software experimentation is growing. This paper introduces Quantum Executor, a backend-agnostic execution engine designed to orchestrate quantum experiments across heterogeneous platforms. Quantum Executor provides a declarative and modular interface that decouples experiment design from backend execution, enabling seamless interoperability and code reuse across diverse quantum and classical resources. Key features include support for asynchronous and distributed execution, customizable execution strategies and a unified API for managing quantum experiments. We illustrate its applicability through two life-like usage scenarios such as automated benchmarking and hybrid validation, discussing its capacity to streamline quantum development. We conclude by discussing current limitations and outlining a roadmap for future enhancements.

quant-ph↗

arXiv2024

Distributing Quantum Computations, Shot-wise

NISQ (Noisy Intermediate-Scale Quantum) era constraints, high sensitivity to noise and limited qubit count, impose significant barriers on the usability of QPUs (Quantum Process Units) capabilities. To overcome these challenges, researchers are exploring methods to maximize the utility of existing QPUs despite their limitations. Building upon the idea that the execution of a quantum circuit's shots needs not to be treated as a singular monolithic unit, we propose a methodological framework, termed shot-wise, which enables the distribution of shots for a single circuit across multiple QPUs. Our framework features customizable policies to adapt to various scenarios. Additionally, it introduces a calibration method to pre-evaluate the accuracy and reliability of each QPU's output before the actual distribution process and an incremental execution mechanism for dynamically managing the shot allocation and policy updates. Such an approach enables flexible and fine-grained management of the distribution process, taking into account various user-defined constraints and (contrasting) objectives. Experimental findings show that while these strategies generally do not exceed the best individual QPU results, they maintain robustness and align closely with average outcomes. Overall, the shot-wise methodology improves result stability and often outperforms single QPU runs, offering a flexible approach to managing variability in quantum computing.

quant-ph↗

arXiv2024

From Quantum Mechanics to Quantum Software Engineering: A Historical Review

Victor Hugo's timeless observation, "Nothing is more powerful than an idea whose time has come", resonates today as Quantum Computing, once only a dream of a physicist, stands at the threshold of reality with the potential to revolutionise the world. To comprehend the surge of attention it commands today, one must delve into the motivations that birthed and nurtured Quantum Computing. While the past of Quantum Computing provides insights into the present, the future could unfold through the lens of Quantum Software Engineering. Quantum Software Engineering, guided by its principles and methodologies investigates the most effective ways to interact with Quantum Computers to unlock their true potential and usher in a new era of possibilities. To gain insight into the present landscape and anticipate the trajectory of Quantum Computing and Quantum Software Engineering, this paper embarks on a journey through their evolution and outlines potential directions for future research. By doing so, we aim to equip readers (ideally software engineers and computer scientists not necessarily with quantum expertise) with the insights necessary to navigate the ever-evolving landscape of Quantum Computing and anticipate the trajectories that lie ahead.

quant-ph↗

arXiv2023

Continuous QoS-compliant Orchestration in the Cloud-Edge Continuum

The problem of managing multi-service applications on top of Cloud-Edge networks in a QoS-aware manner has been thoroughly studied in recent years from a decision-making perspective. However, only a few studies addressed the problem of actively enforcing such decisions while orchestrating multi-service applications and considering infrastructure and application variations. In this article, we propose a next-gen orchestrator prototype based on Docker to achieve the continuous and QoS-compliant management of multiservice applications on top of geographically distributed Cloud-Edge resources, in continuity with CI/CD pipelines and infrastructure monitoring tools. Finally, we assess our proposal over a geographically distributed testbed across Italy.

cs.SE↗

arXiv2021

A Declarative Goal-oriented Framework for Smart Environments with LPaaS

Smart environments powered by the Internet of Things aim at improving our daily lives by automatically tuning ambient parameters (e.g. temperature, interior light) and by achieving energy savings through self-managing cyber-physical systems. Commercial solutions, however, only permit setting simple target goals on those parameters and do not consider mediating conflicting goals among different users and/or system administrators, and feature limited compatibility across different IoT verticals. In this article, we propose a declarative framework to represent smart environments, user-set goals and customisable mediation policies to reconcile contrasting goals encompassing multiple IoT systems. An open-source Prolog prototype of the framework is showcased over two lifelike motivating examples.

eess.SP↗