arXiv subjects

Antonio Russo

Publications and source records attributed to Antonio Russo.

At least 19 recordsLinked to original sources

arXiv2026

Optimal Fusion Strategies for Quantum Computation

Logical fusions are important for a number of tasks in quantum information, such as quantum error correction and quantum repeaters. In the photonic setting one must contend with the fact that physical fusions are probabilistic (i.e.~the associated qubits are measured in product bases), which---depending on the failures and the associated bases---can lead to a failure on the logical level. The choice of failure basis of each qubit is known as a fusion strategy, and finding good fusion strategies is important for optimizing performance of fusion-based quantum computation. Here we provide a complete characterization when $k=1$ qubits are encoded, and in particular characterize those codes and fusion strategies such that all but one physical fusion can fail, i.e.~\emph{perfect fusion strategies}. In doing so, we recover previously known perfect fusion strategies, and find perfect fusion strategies for quantum parity-check codes, answering an open question. We furthermore show that perfect fusion strategies are generic: random $[[n, 1, d]]$ graph codes admit a perfect fusion strategy with probability exponentially close to $1$. Additionally we motivate the study of a new graph parameter, namely the maximum degree of a graph at a given vertex taken over all LC-equivalent graphs, by giving a new operationally meaningful interpretation of it.

quant-ph↗

arXiv2026

Bitcoin Smart Accounts: Trust-Minimized Native Bitcoin DeFi Infrastructure

Bitcoin's limited programmability and transaction throughput have historically prevented native Bitcoin from participating in decentralized finance (DeFi) applications. Existing solutions depend on honest-majority thresholds, or centralized custodial entities that introduce significant trust requirements. This paper introduces Bitcoin Smart Accounts (BSA), a novel protocol that enables native Bitcoin to access DeFi through trust-minimized infrastructure while maintaining self-custody of funds. BSA achieves this through a combination of emulated Bitcoin covenants using Partially Signed Bitcoin Transactions (PSBTs) and Taproot scripts, a Trusted Execution Environment (TEE)-based arbitration system, and destination chain smart contracts that enable DeFi platforms to accept self-custodial Bitcoin as collateral without necessitating protocol-level modifications. The setup leverages liquidity secured by the Lombard Security Consortium which provides a twofold advantage: for a DeFi protocol, liquidators rely on fungible assets with deep liquidity to quickly exit positions, while for a depositor, the general trust assumptions of honest majority (m-of-n) are reduced to existential honesty (1-of-k). We present the complete protocol design, including the Bitcoin architecture, the TEE-based arbitration mechanism, and the Smart Account Registry for protocol management. We provide a security analysis that demonstrates the correctness, safety, and availability properties under our trust model. Our design enables native Bitcoin to serve as collateral in lending markets and other DeFi protocols without requiring users to relinquish custody of funds.

cs.CR↗

arXiv2025

Observer-Based Sampled-Data Stabilisation of Switched Systems with Lipschitz Nonlinearities and Dwell-Time

We investigate the stabilisation of nominally linear-affine switched systems with uncertain Lipschitz nonlinearities under dwell-time constraints, using a sampled-data switching law based on a state observer. We design the switching law based on Lyapunov-Metzler inequalities, accounting for the sampled-data output measurements, and we derive time-dependent LMI conditions for global asymptotic stability (or, in the presence of switching affine terms, ultimate boundedness) of the resulting closed-loop system. We obtain an estimate of the average quadratic cost and a bound on its maximum deviation from the actual cost. Moreover, we discuss the feasibility of the derived LMIs. Specifically, we show how the observer gains can be incorporated into the matrix inequalities, provide equivalent reduced-order LMI conditions, and prove that the time dependence of the LMIs can be removed by discretising on a finite grid. Numerical examples, including practical applications to real-world engineering scenarios in power systems, illustrate our theoretical results and compare them with an existing approach for output-feedback stabilisation of switched systems, subject to sampled-data measurements

math.OC↗

arXiv2025

A job-based assessment of economic complexity: from hidden to revealed

Economic complexity measures aim to quantify the capability content or endowment of industries and territories; however, capabilities are not observable, and therefore cannot be directly used in the computations. We estimate such endowments by quantifying the quality and diversity of the skills in the occupations required in specific industries. We refer to this job-based assessment as the hidden complexity, in contrast with the usual revealed complexity, which is computed from economic outputs such as exports or production. We show that our job-based measure of complexity is positively associated to wage levels and labor productivity growth, whereas the classic revealed measure is not. Finally, we discuss the application of these methods at the territorial level, showing their connection with economic growth.

econ.GN↗

arXiv2025

Input-Power-to-State Stability of Time-Varying Systems

When the state of a system may remain bounded even if both the input amplitude and energy are unbounded, then the state bounds given by the standard input-to-state stability (ISS) and integral-ISS (iISS) properties may provide no useful information. This paper considers an ISS-related concept suitable in such a case: input-power-to-state stability (IPSS). Necessary and sufficient conditions for IPSS are developed for time-varying systems under very mild assumptions on the dynamics. More precisely, it is shown that (a) the existence of a dissipation-form ISS-Lyapunov function implies IPSS, but not necessarily that of an implication-form one, (b) iISS with exponential class-$\KL$ function implies IPSS, and (c) ISS and stronger assumptions on the dynamics imply the existence of a dissipation-form ISS-Lyapunov function and hence IPSS. The latter result is based on a converse Lyapunov theorem for time-varying systems whose dynamics (i.e. state derivative) is not necessarily continuous with respect to time.

eess.SY↗

arXiv2024

Stabilization of Switched Affine Systems With Dwell-Time Constraint

This paper addresses the problem of stabilization of switched affine systems under dwell-time constraint, giving guarantees on the bound of the quadratic cost associated with the proposed state switching control law. Specifically, two switching rules are presented relying on the solution of differential Lyapunov inequalities and Lyapunov-Metzler inequalities, from which the stability conditions are expressed. The first one allows to regulate the state of linear switched systems to zero, whereas the second one is designed for switched affine systems proving practical stability of the origin. In both cases, the determination of a guaranteed cost associated with each control strategy is shown. In the cases of linear and affine systems, the existence of the solution for the Lyapunov-Metzler condition is discussed and guidelines for the selection of a solution ensuring suitable performance of the system evolution are provided. The theoretical results are finally assessed by means of three examples.

eess.SY↗

arXiv2024

Dimensionality reduction techniques to support insider trading detection

Identification of market abuse is an extremely complicated activity that requires the analysis of large and complex datasets. We propose an unsupervised machine learning method for contextual anomaly detection, which allows to support market surveillance aimed at identifying potential insider trading activities. This method lies in the reconstruction-based paradigm and employs principal component analysis and autoencoders as dimensionality reduction techniques. The only input of this method is the trading position of each investor active on the asset for which we have a price sensitive event (PSE). After determining reconstruction errors related to the trading profiles, several conditions are imposed in order to identify investors whose behavior could be suspicious of insider trading related to the PSE. As a case study, we apply our method to investor resolved data of Italian stocks around takeover bids.

q-fin.ST↗

arXiv2023

Further characterizations of integral input-to-state stability for hybrid systems

In this work we present further characterizations of integral input-to-state stability (iISS) for hybrid systems. In particular, the equivalence between 0-input uniform global asymptotic stability (0-UGAS) plus uniform bounded energy bounded state (UBEBS) and iISS is examined. In order to show this equivalence, some necessary conditions for 0-UGAS and UBEBS are provided. In addition, a non-smooth Lyapunov characterization for hybrid systems is proposed and proven. With the help of the aforementioned equivalence, the combination of local iISS and practical iISS, which are defined in this work, is also shown to be equivalent to iISS under one condition on the local and practical quantifiers.

eess.SY↗

arXiv2023

Error mitigation, optimization, and extrapolation on a trapped ion testbed

Current noisy intermediate-scale quantum (NISQ) trapped-ion devices are subject to errors which can significantly impact the accuracy of calculations if left unchecked. A form of error mitigation called zero noise extrapolation (ZNE) can decrease an algorithm's sensitivity to these errors without increasing the number of required qubits. Here, we explore different methods for integrating this error mitigation technique into the Variational Quantum Eigensolver (VQE) algorithm for calculating the ground state of the HeH+ molecule at 0.8 Angstrom in the presence of realistic noise. Using the Quantum Scientific Computing Open User Testbed (QSCOUT) trapped-ion device, we test three methods of scaling noise for extrapolation: time-stretching the two-qubit gates, scaling the sideband amplitude parameter, and inserting two-qubit gate identity operations into the ansatz circuit. We find time-stretching and sideband amplitude scaling fail to scale the noise on our particular hardware in a way that can be directly extrapolated to zero noise. Scaling our noise with global gate identity insertions and extrapolating after variational optimization, we achieve an estimate of the ground state energy within -0.004 +- 0.04 Hartree; outside chemical accuracy, but greatly improved over our non-error-mitigated estimate with error 0.127 +- 0.008 Hartree. Our results show that the efficacy of this error mitigation technique depends on choosing the correct implementation for a given device architecture.

quant-ph↗

arXiv2023

JaqalPaw: A Guide to Defining Pulses and Waveforms for Jaqal

One of the many challenges of developing an open user testbed such as QSCOUT is providing an interface that maintains simplicity without compromising expressibility or control. This interface comprises two distinct elements: a quantum assembly language designed for specifying quantum circuits at the gate level, and a low-level counterpart used for describing gates in terms of waveforms that realize specific quantum operations. Jaqal, or "Just another quantum assembly language," is the language used in QSCOUT for gate-level descriptions of quantum circuits. JaqalPaw, or "Jaqal pulses and waveforms," is its pulse-level counterpart. This document concerns the latter, and presents a description of the tools needed for precisely defining the underlying waveforms associated with a gate primitive.

quant-ph↗

arXiv2023

Quantifying $T$-gate-count improvements for ground-state-energy estimation with near-optimal state preparation

We study the question of when investing additional quantum resources in preparing a ground state will improve the aggregate runtime associated with estimating its energy. We analyze Lin and Tong's near-optimal state preparation algorithm and show that it can reduce a proxy for the runtime, the $T$-gate count, of ground state energy estimation near quadratically. Resource estimates are provided that specify the conditions under which the added cost of state preparation is worthwhile.

quant-ph↗

arXiv2023

Improving Blockchain Scalability with the Setchain Data-type

Blockchain technologies are facing a scalability challenge, which must be overcome to guarantee a wider adoption of the technology. This scalability issue is due to the use of consensus algorithms to guarantee the total order of the chain of blocks and of the transactions within each block. However, total order is often not fully necessary, since important advanced applications of smart-contracts do not require a total order among all operations. A much higher scalability can potentially be achieved if a more relaxed order can be exploited. In this paper, we propose a novel distributed concurrent data type, called Setchain, which improves scalability significantly. A Setchain implements a grow-only set whose elements are not ordered, unlike conventional blockchain operations. When convenient, the Setchain allows forcing a synchronization barrier that assigns permanently an epoch number to a subset of the latest elements added, agreed by consensus. Therefore, two operations in the same epoch are not ordered, while two operations in different epochs are ordered by their respective epoch number. We present different Byzantine-tolerant implementations of Setchain, prove their correctness and report on an empirical evaluation of a prototype implementation. Our results show that Setchain is orders of magnitude faster than consensus-based ledgers, since it implements grow-only sets with epoch synchronization instead of total order. Since Setchain barriers can be synchronized with the underlying blockchain, Setchain objects can be used as a sidechain to implement many decentralized solutions with much faster operations than direct implementations on top of blockchains. Finally, we also present an algorithm that encompasses in a single process the combined behavior of Byzantine servers, which simplifies correctness proofs by encoding the general attacker in a concrete implementation.

cs.DC↗

arXiv2022

A machine learning approach to support decision in insider trading detection

Identifying market abuse activity from data on investors' trading activity is very challenging both for the data volume and for the low signal to noise ratio. Here we propose two complementary unsupervised machine learning methods to support market surveillance aimed at identifying potential insider trading activities. The first one uses clustering to identify, in the vicinity of a price sensitive event such as a takeover bid, discontinuities in the trading activity of an investor with respect to his/her own past trading history and on the present trading activity of his/her peers. The second unsupervised approach aims at identifying (small) groups of investors that act coherently around price sensitive events, pointing to potential insider rings, i.e. a group of synchronised traders displaying strong directional trading in rewarding position in a period before the price sensitive event. As a case study, we apply our methods to investor resolved data of Italian stocks around takeover bids.

q-fin.ST↗

arXiv2022

Machine learning memory kernels as closure for non-Markovian stochastic processes

Finding the dynamical law of observable quantities lies at the core of physics. Within the particular field of statistical mechanics, the generalized Langevin equation (GLE) comprises a general model for the evolution of observables covering a great deal of physical systems with many degrees of freedom and an inherently stochastic nature. Although formally exact, the GLE brings its own great challenges. It depends on the complete history of the observables under scrutiny, as well as the microscopic degrees of freedom, all of which are often inaccessible. We show that these drawbacks can be overcome by adopting elements of machine learning from empirical data, in particular coupling a multilayer perceptron (MLP) with the formal structure of the GLE and calibrating the MLP with the data. This yields a powerful computational tool capable of describing noisy complex systems beyond the realms of statistical mechanics. It is exemplified with a number of representative examples from different fields: from a single colloidal particle and particle chains in a thermal bath to climatology and finance, showing in all cases excellent agreement with the actual observable dynamics. The new framework offers an alternative perspective for the study of non-equilibrium processes opening also a new route for stochastic modelling.

cond-mat.stat-mech↗

arXiv2022

Airborne Radiometric Surveys and Machine Learning Algorithms for Revealing Soil Texture

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 $km^2$ agricultural plain investigated through a ded-icated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gam-ma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

physics.geo-ph↗

arXiv2022

How Covid mobility restrictions modified the population of investors in Italian stock markets

This paper investigates how Covid mobility restrictions impacted the population of investors of the Italian stock market. The analysis tracks the trading activity of individual investors in Italian stocks in the period January 2019-September 2021, investigating how their composition and the trading activity changed around the Covid-19 lockdown period (March 9 - May 19, 2020) and more generally in the period of the pandemic. The results pinpoint that the lockdown restriction was accompanied by a surge in interest toward stock market, as testified by the trading volume by households. Given the generically falling prices during the lockdown, the households, which are typically contrarian, were net buyers, even if less than expected from their trading activity in 2019. This can be explained by the arrival, during the lockdown, of a group of about 185k new investors (i.e. which had never traded since January 2019) which were on average ten year younger and with a larger fraction of males than the pre-lockdown investors. By looking at the gross P&L, there is clear evidence that these new investors were more skilled in trading. There are thus indications that the lockdown, and more generally the Covid pandemic, created a sort of regime change in the population of financial investors.

q-fin.TR↗

arXiv2022

Setchain: Improving Blockchain Scalability with Byzantine Distributed Sets and Barriers

Blockchain technologies are facing a scalability challenge, which must be overcome to guarantee a wider adoption of the technology. This scalability issue is mostly caused by the use of consensus algorithms to guarantee the total order of the chain of blocks (and of the operations within each block). However, total order is often overkilling, since important advanced applications of smart-contracts do not require a total order of all the operations. Hence, if a more relaxed partial order (instead of a total order) is allowed under certain safety conditions, a much higher scalability can be achieved. In this paper, we propose a distributed concurrent data type, called Setchain, that allows implementing this partial order and increases significantly blockchain scalability. A Setchain implements a grow-only set object whose elements are not totally ordered, unlike conventional blockchain operations. When convenient, the Setchain allows forcing a synchronization barrier that assigns permanently an epoch number to a subset of the latest elements added. With the Setchain, operations in the same epoch are not ordered, while operations in different epochs are. We present different Byzantine-tolerant implementations of Setchain, prove their correctness and report on an empirical evaluation of a direct implementation. Our results show that Setchain is orders of magnitude faster than consensus-based ledgers to implement grow-only sets with epoch synchronization. Since the Setchain barriers can be synchronized with block consolidation, Setchain objects can be used as a sidechain to implement many smart contract solutions with much faster operations than on basic blockchains.

cs.DC↗

arXiv2022

Validated Objects: Specification, Implementation, and Applications

Guaranteeing the validity of concurrent operations on distributed objects is a key property for ensuring reliability and consistency in distributed systems. Usually, the methods for validating these operations, if present, are wired in the object implementation. In this work, we formalize the notion of a {\em validated object}, decoupling the object operations and properties from the validation procedure. We consider two types of objects, satisfying different levels of consistency: the validated {\em totally-ordered} object, offering a total ordering of its operations, and its weaker variant, the validated {\em regular} object. We provide conditions under which it is possible to implement these objects. In particular, we show that crash-tolerant implementations of validated regular objects are always possible in an asynchronous system with a majority of correct processes. However, for validated totally-ordered objects, consensus is always required if a property of the object we introduce in this work, {\em persistent validity,} does not hold. Persistent validity combined with another new property, {\em persistent execution}, allows consensus-free crash-tolerant implementations of validated totally-ordered objects. We demonstrate the utility of validated objects by considering several applications conforming to our formalism.

cs.DC↗