165 citations · 654 across the 18 of their papers we have counts for
20 papers
Reconstructing the information processing capacity of physical systems from noisy observations
Shun Kotoku, Rodrigo Martínez-Peña, Takatomo Mihana +5
Driven dynamical systems can compute when their transient states encode complex transformations of past inputs. The information processing capacity (IPC) framework allows for a det…
A hidden bottleneck in classical and quantum linear reservoir computing
Johannes Nokkala, Federico Centrone, Francesco Arzani
We identify a hidden bottleneck in the information processing capacity of linear reservoir computers. When the measured features evolve linearly in the reservoir and the output is…
Smarter Usage of Measurement Statistics Can Greatly Improve Continuous Variable Quantum Reservoir Computing
Markku Hahto, Johannes Nokkala
Quantum reservoir computing is a machine learning scheme in which a quantum system is used to perform information processing. A prospective approach to its physical realization is…
Stability of Continuous Time Quantum Walks in Complex Networks
Adithya L J, Johannes Nokkala, Jyrki Piilo +1
We investigate the stability of continuous-time quantum walks (CTQW) across cycle, complete, star, Erdős-Rényi, small-world, and scale-free topologies under energy-based intrinsic…
State Transfer in Noisy Modular Quantum Networks
Markku Hahto, Jyrki Piilo, Johannes Nokkala
Quantum state transfer is the act of transferring quantum information from one system in a quantum network to another without physically transporting carriers of quantum informatio…
Transfer and routing of Gaussian states through quantum complex networks with and without community structure
Markku Hahto, Johannes Nokkala, Guillermo García-Pérez +2
The goal in quantum state transfer is to avoid the need to physically transport carriers of quantum information. This is achieved by using a suitably engineered Hamiltonian that in…
Retrieving past quantum features with deep hybrid classical-quantum reservoir computing
Johannes Nokkala, Gian Luca Giorgi, Roberta Zambrini
Machine learning techniques have achieved impressive results in recent years and the possibility of harnessing the power of quantum physics opens new promising avenues to speed up…
Complex Quantum Networks: a Topical Review
Johannes Nokkala, Jyrki Piilo, Ginestra Bianconi
These are exciting times for quantum physics as new quantum technologies are expected to soon transform computing at an unprecedented level. Simultaneously network science is flour…
Experimental optical simulator of reconfigurable and complex quantum environment
Paul Renault, Johannes Nokkala, Ganaël Roeland +6
No quantum system can be considered totally isolated from its environment. In most cases the interaction between the system of interest and the external degrees of freedom deeply c…
Online quantum time series processing with random oscillator networks
Johannes Nokkala
Reservoir computing is a powerful machine learning paradigm for online time series processing. It has reached state-of-the-art performance in tasks such as chaotic time series pred…
Dynamical phase transitions in quantum reservoir computing
Rodrigo Martínez-Peña, Gian Luca Giorgi, Johannes Nokkala +2
Closed quantum systems exhibit different dynamical regimes, like Many-Body Localization or thermalization, which determine the mechanisms of spread and processing of information. H…
Opportunities in Quantum Reservoir Computing and Extreme Learning Machines
Pere Mujal, Rodrigo Martínez-Peña, Johannes Nokkala +4
Quantum reservoir computing (QRC) and quantum extreme learning machines (QELM) are two emerging approaches that have demonstrated their potential both in classical and quantum mach…
Information Processing Capacity of Spin-Based Quantum Reservoir Computing Systems
R. Martínez-Peña, J. Nokkala, G. L. Giorgi +2
The dynamical behaviour of complex quantum systems can be harnessed for information processing. With this aim, quantum reservoir computing (QRC) with Ising spin networks was recent…
Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing
Johannes Nokkala, Rodrigo Martínez-Peña, Gian Luca Giorgi +3
We establish the potential of continuous-variable Gaussian states of linear dynamical systems for machine learning tasks. Specifically, we consider reservoir computing, an efficien…
Probing the spectral dimension of quantum network geometries
Johannes Nokkala, Jyrki Piilo, Ginestra Bianconi
We consider an environment for an open quantum system described by a "Quantum Network Geometry with Flavor" (QNGF) in which the nodes are coupled quantum oscillators. The geometric…
Non-Markovianity over ensemble averages in quantum complex networks
Johannes Nokkala, Sabrina Maniscalco, Jyrki Piilo
We consider bosonic quantum complex networks as structured finite environments for a quantum harmonic oscillator and investigate the interplay between the network structure and its…
Local probe for connectivity and coupling strength in quantum complex networks
Johannes Nokkala, Sabrina Maniscalco, Jyrki Piilo
We develop a local probe to estimate the connectivity of complex quantum networks. Our results show how global properties of different classes of complex networks can be estimated…
Reconfigurable optical implementation of quantum complex networks
Johannes Nokkala, Francesco Arzani, Fernando Galve +5
Network theory has played a dominant role in understanding the structure of complex systems and their dynamics. Recently, quantum complex networks, i.e. collections of quantum syst…
Energy backflow in strongly coupled non-Markovian continuous-variables systems
Giacomo Guarnieri, Johannes Nokkala, Rebecca Schmidt +2
By employing the full counting statistics formalism, we characterize the first moment of energy that is exchanged during a generally non-Markovian evolution in non-driven continuou…
Complex quantum networks as structured environments: engineering and probing
Johannes Nokkala, Fernando Galve, Roberta Zambrini +2
We consider structured environments modeled by bosonic quantum networks and investigate the probing of their spectral density, structure, and topology. We demonstrate how to engine…