arXiv subjects

Mirko Rossini

Publications and source records attributed to Mirko Rossini.

7 recordsLinked to original sources

arXiv2025

Tailored Error Mitigation for Single-Qubit Magnetometry

Quantum sensing is an emerging field with the potential to outperform classical methods in both precision and spatial resolution. However, the sensitivity of the underlying quantum platform also makes the sensors highly susceptible to their environmental noise. To address this issue, techniques from the field of quantum error mitigation use information about the noise to improve measurement results. We present a novel mitigation technique for quantum sensors to efficiently reverse the effects of any noise that can be described by a completely positive trace preserving map. The method leverages the knowledge acquired by a pre-characterization step of the device to automatically adapt to the complexity of the dissipative evolution and to indicate optimal sensing times $\tau$ to achieve the most accurate results. We demonstrate that our method reaches the best achievable sensitivity in noisy single-NV-center magnetometry. This work marks a further step toward more resilient quantum sensors with the smallest scale of resolution.

quant-ph↗

arXiv2025

QuantumDNA: A Python Package for Analyzing Quantum Charge Dynamics in DNA and Exploring Its Biological Relevance

The study of DNA charge dynamics is a highly interdisciplinary field that bridges physics, chemistry, biology, and medicine, and plays a critical role in processes such as DNA damage detection, protein-DNA interactions, and DNA-based nanotechnology. However, despite significant advances in each of these areas, knowledge often remains inaccessible to other scientific communities, limiting the broader impact of advances across disciplines. To bridge this gap, we present QuantumDNA, an open-source Python package for simulating DNA charge transfer (CT) and excited states using quantum-physical methods. QuantumDNA combines an efficient Linear Combination of Atomic Orbitals (LCAO) approach with tight-binding (TB) models, incorporating open quantum systems techniques to account for environmental effects. This approach allows rapid yet accurate analysis of large DNA ensembles, enabling statistical studies of genetic and epigenetic phenomena. To ensure accessibility, the package features a graphical user interface (GUI), making it suitable for researchers across disciplines.

q-bio.BM↗

arXiv2024

A Novel Quantum Algorithm for Efficient Attractor Search in Gene Regulatory Networks

The description of gene interactions that constantly occur in the cellular environment is an extremely challenging task due to an immense number of degrees of freedom and incomplete knowledge about microscopic details. Hence, a coarse-grained and rather powerful modeling of such dynamics is provided by Boolean Networks (BNs). BNs are dynamical systems composed of Boolean agents and a record of their possible interactions over time. Stable states in these systems are called attractors which are closely related to the cellular expression of biological phenotypes. Identifying the full set of attractors is, therefore, of substantial biological interest. However, for conventional high-performance computing, this problem is plagued by an exponential growth of the dynamic state space. Here, we demonstrate a novel quantum search algorithm inspired by Grover's algorithm to be implemented on quantum computing platforms. The algorithm performs an iterative suppression of states belonging to basins of previously discovered attractors from a uniform superposition, thus increasing the amplitudes of states in basins of yet unknown attractors. This approach guarantees that a new attractor state is measured with each iteration of the algorithm, an optimization not currently achieved by any other algorithm in the literature. Tests of its resistance to noise have also shown promising performance on devices from the current Noise Intermediate Scale Quantum Computing (NISQ) era.

quant-ph↗

arXiv2024

Effect of environmental noise on charge diffusion in DNA: Towards modeling its potential epigenetic impact in live processes

Charge diffusion through desoxyribonucleic acid (DNA) is a physico-chemical phenomenon that on the one hand is being explored for technological purposes, on the other hand is applied by nature for various informational processes in life. With regard to the latter, increasing experimental and theoretical evidence indicates that charge diffusion through DNA is involved in basic steps of DNA replication and repair, as well as regulation of gene expression via epigenetic mechanisms such as DNA methylation or DNA binding of proteins. From the physics point of view, DNA supports a metallic-like behavior with long-range charge mobility. Nevertheless, particularly considering a living environment, charge mobility in DNA needs to take into account omnipresent noise and disorder. Here, we analyze quantum diffusion of single charges along DNA-inspired two-dimensional tight-binding lattices in presence of different sources of intrinsic and environmental fluctuations. It is shown that double-strand lattices, parametrized according to atomistic calculations of DNA sequences, offer a complex network of pathways between sites and may give rise to long-distance coherence phenomena. These effects strongly depend on carrier type (electrons, holes), the energetic profile of the lattice (composition) as well as the type of noise and disorder. Of particular interest are spatially correlated low-frequency fluctuations which may support coherent charge transfer over distances of a few sites. Our results may trigger further experimental activities aiming at investigating charge mobility in DNA both in the native in-vivo context as well as on artificial platforms.

physics.bio-ph↗

arXiv2023

AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions

Transcendental functions, such as the exponential, are central to scientific computing, yet they cannot be natively calculated by digital hardware. Instead, computers must approximate these functions by combining basic operations, such as $\{+, -, \times, \div\}$, using methods like Taylor series. These methods were developed over centuries by mathematicians, who focused on approaches that could attain arbitrary accuracy. However, computers can handle most applications by using only finite-precision types, like float32, where any accuracy beyond the type's precision is effectively discarded. We explore, therefore, whether forgoing arbitrary accuracy can lead to the discovery of more efficient approximations. The evolutionary method of symbolic regression is particularly suitable, as it can search for arbitrary operation combinations and can optimize non-differentiable objectives, such as the number of operations used. Our results show that evolution can discover computer programs that outperform established methods in this setting, despite having no prior mathematical knowledge beyond the calculation of the basic operations. Starting from empty code, symbolic regression constructs programs representing novel mathematical expressions. In particular, we discovered a 10-operation program that approximates the exponential function to 14 significant figures, exceeding the accuracy of previously known approximations of this size by more than 6 orders of magnitude.

cs.NE↗

arXiv2023

Single Qubit Error Mitigation by Simulating Non-Markovian Dynamics

Quantum simulation is a powerful tool to study the properties of quantum systems. The dynamics of open quantum systems are often described by Completely Positive (CP) maps, for which several quantum simulation schemes exist. We present a simulation scheme for open qubit dynamics described by a larger class of maps: the general dynamical maps which are linear, hermitian preserving and trace preserving but not necessarily positivity preserving. The latter suggests an underlying system-reservoir model where both are entangled and thus non-Markovian qubit dynamics. Such maps also come about as the inverse of CP maps. We illustrate our simulation scheme on an IBM quantum processor by showing that we can recover the initial state of a Lindblad evolution. This paves the way for a novel form of quantum error mitigation. Our scheme only requires one ancilla qubit as an overhead and a small number of one and two qubit gates.

quant-ph↗

arXiv2018

Sliding states of a soft-colloid cluster crystal: Cluster versus single-particle hopping

We study a two-dimensional model for interacting colloidal particles which displays spontaneous clustering. Within this model we investigate the competition between the pinning to a periodic corrugation potential, and a sideways constant pulling force which would promote a sliding state. For a few sample particle densities and amplitudes of the periodic corrugation potential we investigate the depinning from the statically pinned to the dynamically sliding regime. This sliding state exhibits the competition between a dynamics where entire clusters are pulled from a minimum to the next and a dynamics where single colloids or smaller groups leave a cluster and move across the corrugation energy barrier to join the next cluster downstream in the force direction. Both kinds of sliding states can occur either coherently across the entire sample, or asynchronously: the two regimes result in different average mobilities. Finite temperature tends to destroy separate sliding regimes, generating a smoother dependence of the mobility on the driving force.

cond-mat.soft↗