arXiv subjects

Carlo Piermarocchi

Publications and source records attributed to Carlo Piermarocchi.

At least 19 recordsLinked to original sources

arXiv2025

Critical Dynamics and Cyclic Memory Retrieval in Non-reciprocal Hopfield Networks

We study Hopfield networks with non-reciprocal coupling inducing switches between memory patterns. Dynamical phase transitions occur between phases of no memory retrieval, retrieval of multiple point-attractors, and limit-cycle attractors. The limit cycle phase is bounded by two critical regions: a Hopf bifurcation line and a fold bifurcation line, each with unique dynamical critical exponents and sensitivity to perturbations. A Master Equation approach numerically verifies the critical behavior predicted analytically. We discuss how these networks could model biological processes near a critical threshold of cyclic instability evolving through multi-step transitions.

cond-mat.dis-nn↗

arXiv2023

Transient dynamics of subradiance and superradiance in open optical ensembles

We introduce a computational Maxwell-Bloch framework for investigating out-of-equilibrium optical emitters in open systems. To do so, we compute the pulse-induced dynamics of each emitter from fundamental light-matter interactions and self-consistently calculate their radiative coupling, including phase inhomogeneity from propagation effects. This semiclassical framework is applied to open quantum dots systems with different densities and dipolar coupling. We observe signatures of superradiant behavior, such as directionality and faster decay, as well as subradiant emission. We compare and discuss the computed light emission obtained with our method and a Master equation approach. Our framework enables quantitative investigations of large optical ensembles in the time domain and could be used to design new systems with enhanced superradiant and subradiant properties.

physics.optics↗

arXiv2017

Collective Rabi dynamics of electromagnetically-coupled quantum dot ensembles

Rabi oscillations typify the inherent nonlinearity of optical excitations in quantum dots. Using an integral kernel formulation to solve the 3D Maxwell-Bloch equations in ensembles of up to $10^4$ quantum dots, we observe features in Rabi oscillations due to the interplay of nonlinearity, non-equilibrium excitation, and electromagnetic coupling between the dots. This approach allows us to observe the dynamics of each dot in the ensemble without resorting to spatial averages. Our simulations predict synchronized multiplets of dots that exchange energy, dots that dynamically couple to screen the effect of incident external radiation, localization of the polarization due to randomness and interactions, as well as wavelength-scale regions of enhanced and suppressed polarization.

physics.atm-clus↗

arXiv2017

Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems

Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series data sets in the near future, we use the Hopfield model, a recurrent neural network based on spin glasses, to model the dynamics of cell cycle in HeLa (human cervical cancer) and S. cerevisiae cells. We study some of the rich dynamical properties of these cyclic Hopfield systems, including the ability of populations of simulated cells to recreate experimental expression data and the effects of noise on the dynamics. Next, we use a genetic algorithm to identify sets of genes which, when selectively inhibited by local external fields representing gene silencing compounds such as kinase inhibitors, disrupt the encoded cell cycle. We find, for example, that inhibiting the set of four kinases BRD4, MAPK1, NEK7, and YES1 in HeLa cells causes simulated cells to accumulate in the M phase. Finally, we suggest possible improvements and extensions to our model.

q-bio.MN↗

arXiv2015

Evolutionary and topological properties of gene modules and driver mutations in a leukemia gene regulatory network

The diverse, specialized genes in today's lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins' binding partners. We show that the topology of a leukemia gene regulatory network is strongly coupled with evolutionary properties. Slowly-evolving ("cold"), old genes tend to interact with each other, as do rapidly-evolving ("hot"), young genes, causing genes to evolve in clusters. We argue that gene duplication placed old, cold genes at the center of the network, and young, hot genes on the periphery, and demonstrate this with single-node centrality measures and two new measures of efficiency. Integrating centrality measures with evolutionary information, we define a medically-relevant "cancer network core," strongly enriched for common cancer mutations ($p=2\times 10^{-14}$). This could aid in identifying driver mutations and therapeutic targets.

q-bio.MN↗

arXiv2015

Computational dynamics of acoustically-driven microsphere systems

We propose a computational framework for the self-consistent dynamics of a microsphere system driven by a pulsed acoustic field in an ideal fluid. Our framework combines a molecular dynamics integrator describing the dynamics of the microsphere system with a time-dependent integral equation solver for the acoustic field that makes use of fields represented as surface expansions in spherical harmonic basis functions. The presented approach allows us to describe the inter-particle interaction induced by the field as well as the dynamics of trapping in counter-propagating acoustic pulses. The integral equation formulation leads to equations of motion for the microspheres describing the effect of non-dissipative drag forces. We show (1) that the field-induced interactions between the microspheres give rise to effective dipolar interactions, with effective dipoles defined by their velocities, and (2) that the dominant effect of an ultrasound pulse through a cloud of microspheres gives rise mainly to a translation of the system, though we also observe both expansion and contraction of the cloud determined by the initial system geometry.

physics.comp-ph↗

arXiv2014

Multi-species network inference improves gene regulatory network reconstruction for early embryonic development in Drosophila

Gene regulatory network inference uses genome-wide transcriptome measurements in response to genetic, environmental or dynamic perturbations to predict causal regulatory influences between genes. We hypothesized that evolution also acts as a suitable network perturbation and that integration of data from multiple closely related species can lead to improved reconstruction of gene regulatory networks. To test this hypothesis, we predicted networks from temporal gene expression data for 3,610 genes measured during early embryonic development in six Drosophila species and compared predicted networks to gold standard networks of ChIP-chip and ChIP-seq interactions for developmental transcription factors in five species. We found that (i) the performance of single-species networks was independent of the species where the gold standard was measured; (ii) differences between predicted networks reflected the known phylogeny and differences in biology between the species; (iii) an integrative consensus network which minimized the total number of edge gains and losses with respect to all single-species networks performed better than any individual network. Our results show that in an evolutionarily conserved system, integration of data from comparable experiments in multiple species improves the inference of gene regulatory networks. They provide a basis for future studies on the numerous multi-species gene expression datasets for other biological processes available in the literature.

q-bio.GN↗

arXiv2014

Control of asymmetric Hopfield networks and application to cancer attractors

The asymmetric Hopfield model is used to simulate signaling dynamics in gene/transcription factor networks. The model allows for a direct mapping of a gene expression pattern into attractor states. We analyze different control strategies aiming at disrupting attractor patterns using selective local fields representing therapeutic interventions. The control strategies are based on the identification of signaling $bottlenecks$, which are single nodes or strongly connected clusters of nodes that have a large impact on the signaling. We provide a theorem with bounds on the minimum number of nodes that guarantee controllability of bottlenecks consisting of strongly connected components. The control strategies are applied to the identification of sets of proteins that, when inhibited, selectively disrupt the signaling of cancer cells while preserving the signaling of normal cells. We use an experimentally validated non-specific network and a specific B cell interactome reconstructed from gene expression data to model cancer signaling in lung and B cells, respectively. This model could help in the rational design of novel robust therapeutic interventions based on our increasing knowledge of complex gene signaling networks.

q-bio.MN↗

arXiv2013

Dynamics of exciton-polaritons in a Josephson double dimer

We study the dynamics of exciton-polaritons in a double-well configuration. The system consists of two weakly coupled Bose-Josephson junctions, each corresponding to a different circular polarization of the polaritons, forming a {\it Josephson double dimer}. We show that the Josephson oscillation between the wells is strongly coupled to the polarization rotation and that consequently Josephson excitation is periodically exchanged between the two polarizations. Linearized analysis agrees well with numerical simulations using typical experimental parameters.

cond-mat.quant-gas↗

arXiv2013

Prediction of kinase inhibitor response using activity profiling, in-vitro screening, and elastic net regression

Many kinase inhibitors have been approved as cancer therapies. Recently, libraries of kinase inhibitors have been extensively profiled, thus providing a map of the strength of action of each compound on a large number of its targets. These profiled libraries define drug-kinase networks that can predict the effectiveness of new untested drugs and elucidate the role played by specific kinases in different cellular systems. Predictions of drug effectiveness based on a comprehensive network model of cellular signalling are difficult, due to our partial knowledge of the complex biological processes downstream of the targeted kinases. We have developed the Kinase Inhibitors Elastic Net (KIEN) method, which integrates information contained in drug-kinase networks with in vitro screening. The method uses the in vitro cell response of single drugs and drug pair combinations as a training set to build linear and nonlinear regression models. Besides predicting the effectiveness of untested drugs, the method identifies sets of kinases that are statistically associated to drug sensitivity in a given cell line. We compare different versions of the method, which is based on a regression technique known as elastic net. Data from two-drug combinations leads to predictive models, and predictivity can be improved by applying logarithmic transformation to the data. The method is applied to the A549 lung cancer cell line. A pathway enrichment analysis of the set of kinases identified by the method shows that axon guidance, activation of Rac, and semaphorin interactions pathways are associated to a selective response to therapeutic intervention in this cell line.

q-bio.QM↗

arXiv2010

Biological control networks suggest the use of biomimetic sets for combinatorial therapies

Cells are regulated by networks of controllers having many targets, and targets affected by many controllers, but these "many-to-many" combinatorial control systems are poorly understood. Here we analyze distinct cellular networks (transcription factors, microRNAs, and protein kinases) and a drug-target network. Certain network properties seem universal across systems and species, suggesting the existence of common control strategies in biology. The number of controllers is ~8% of targets and the density of links is 2.5% \pm 1.2%. Links per node are predominantly exponentially distributed, implying conservation of the average, which we explain using a mathematical model of robustness in control networks. These findings suggest that optimal pharmacological strategies may benefit from a similar, many-to-many combinatorial structure, and molecular tools are available to test this approach.

q-bio.MN↗

arXiv2010

Trionic Optical Potential for Electrons in Semiconductors

Laser-induced optical potentials for atoms have led to remarkable advances in precision measurement, quantum information, and towards addressing fundamental questions in condensed matter physics. Here, we describe analogous optical potentials for electrons in quantum wells and wires that can be generated by optically driving the transition between a single electron and a three-body electron-exciton bound state, known as a trion. The existence of a bound trion state adds a term to the ac Stark shift of the material proportional to the light intensity at the position of the electron. According to our theoretical calculations, this shift can be large relative to the thermal equilibrium temperature of the electron, resulting in a relatively strong optical potential that could be used to trap, guide, and manipulate individual electrons within a semiconductor quantum well or wire. These potentials can be thought of as artificial nano-structures on the scale of 100 nm that can be spin-dependent and reconfigurable in real-time. Our results suggest the possibility of integrating ultrafast optics and gate voltages in new resolved-carrier semiconductor opto-electronic devices, with potential applications in fields such as nano-electronics, spintronics, and quantum information processing

cond-mat.mtrl-sci↗

arXiv2009

Systems approaches and algorithms for discovery of combinatorial therapies

Effective therapy of complex diseases requires control of highly non-linear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of signaling in cellular networks. Identification of control parameters presents an extreme challenge due to the combinatorial explosion of control possibilities in combination therapy and to the incomplete knowledge of the systems biology of cells. In this review paper we describe the main current and proposed approaches to the design of combinatorial therapies, including the empirical methods used now by clinicians and alternative approaches suggested recently by several authors. New approaches for designing combinations arising from systems biology are described. We discuss in special detail the design of algorithms that identify optimal control parameters in cellular networks based on a quantitative characterization of control landscapes, maximizing utilization of incomplete knowledge of the state and structure of intracellular networks. The use of new technology for high-throughput measurements is key to these new approaches to combination therapy and essential for the characterization of control landscapes and implementation of the algorithms. Combinatorial optimization in medical therapy is also compared with the combinatorial optimization of engineering and materials science and similarities and differences are delineated.

q-bio.QM↗

arXiv2008

Multi-spin errors in the optical control of a spin quantum memory

We study a quantum memory composed of an array of charged quantum dots embedded in a planar cavity. Optically excited polaritons, i.e. exciton-cavity mixed states, interact with the electron spins in the dots. Linearly polarized excitation induces two-spin and multi-spin interactions. We discuss how the multi-spin interaction terms, which represent a source of errors for two-qubit quantum gates, can be suppressed using local control of the exciton energy. We show that using detuning conditional phase shift gates with high fidelity can be obtained. The cavity provides long-range spin coupling and the resulting gate operation time is shorter than the spin decoherence time.

cond-mat.mes-hall↗

arXiv2008

Microcavity polaritons in disordered exciton lattices

We investigate the interaction of excitons in a two dimensional lattice and photons in a planar cavity in the presence of disorder. The strong exciton-photon coupling is described in terms of polariton quasi-particles, which are scattered by a disorder potential. We consider three kinds of disorder: (a) inhomogeneous exciton energy, (b) inhomogeneous exciton-photon coupling and (c) deviations from an ideal lattice. These three types of disorder are characteristic of different physical systems, and their separate analysis gives insight on the competition between randomness and light-matter coupling. We consider conventional planar polariton structures (with excitons resonant to photon modes emitting normal to the cavity) and Bragg polariton structures, in which excitons in a lattice are resonant with photon modes at a finite angle satisfying the Bragg condition. We calculate the absorption spectra in the normal direction and at the Bragg angle by a direct diagonalization of the exciton-photon Hamiltonian. We found that in some cases weak disorder increases the light-matter coupling and leads to a larger polariton splitting. Moreover, we found that the coupling of excitons and photons is less sensitive to disorder of type (b) and (c). This suggests that polaritonic structures realized with impurities in a semiconductor or with atoms in optical lattices are good candidate for the observation of some of the Bragg polariton features.

cond-mat.mes-hall↗

arXiv2007

Selective control of the apoptosis signaling network in heterogeneous cell populations

Selective control in a population is the ability to control a member of the population while leaving the other members relatively unaffected. The concept of selective control is developed using cell death or apoptosis in heterogeneous cell populations as an example. Apoptosis signaling in heterogeneous cells is described by an ensemble of gene networks with identical topology but different link strengths. Selective control depends on the statistics of signaling in the ensemble of networks and we analyse the effects of superposition, non-linearity and feedback on these statistics. Parallel pathways promote normal statistics while series pathways promote skew distributions which in the most extreme cases become log-normal. We also show that feedback and non-linearity can produce bimodal signaling statistics, as can discreteness and non-linearity. Two methods for optimizing selective control are presented. The first is an exhaustive search method and the second is a linear programming based approach. Though control of a single gene in the signaling network yields little selectivity, control of a few genes typically yields higher levels of selectivity. The statistics of gene combinations susceptible to selective control is studied and is used to identify general control strategies. We found that selectivity is promoted by acting on the least sensitive nodes in the case of weak populations, while selective control of robust populations is optimized through perturbations of more sensitive nodes. High throughput experiments with heterogeneous cell lines could be designed in an analogous manner, with the further possibility of incorporating the selectivity optimization process into a closed-loop control system.

q-bio.QM↗

arXiv2006

Radiation-induced current in quantum wires with side-coupled nano-rings

Photocurrent generation is studied in a system composed of a quantum wire with side-coupled quantum rings. The current generation results from the interplay of the particular geometry of the system and the use of circularly polarized radiation. We study the energy-momentum conservation for optical transitions involving electrons moving forwards and backwards in the wire. Due to the lack of time-reversal symmetry in the radiation, the optical transitions depend on the direction of motion of the electrons, leading to a current at zero bias voltage. The photocurrent increases with the number of rings within a wide range of physical parameters. A weak non-linear dependence of the current in the number of rings, related to quantum interference effects, is also predicted. This geometry suggests a scalable method for the generation of sizeable photocurrents based on nanoscale components.

cond-mat.mes-hall↗

arXiv2005

Persistent and radiation-induced currents in distorted quantum rings

Persistent and radiation-induced currents in distorted narrow quantum rings are theoretically investigated. We show that ring distorsions can be described using a geometrical potential term. We analyse the effect of this term on the current induced by a magnetic flux (persistent current) and by a polarized coherent electromagnetic field (radiation-induced current). The strongest effects in persistent currents are observed for distorted rings with a small number of electrons. The distortion smoothes the current oscillations as a function of the magnetic flux and changes the temperature dependence of the current amplitude. For radiation-induced currents, the distortion induces an ac component in the current and affects its dependence on the radiation frequency and intensity.

cond-mat.mes-hall↗