1.9k citations · 7.5k across the 87 of their papers we have counts for
88 papers
Hardware-Aware Fermion-to-Qubit Mappings for Simulating the 2D Hubbard Model on Heavy-Hexagon Quantum Processors
Alessio Esposito, Andrea Giachero, Zoltàn Zimboràs +1
Quantum simulation of strongly correlated fermionic systems is among the most promising near- term applications of quantum computing, but its practical efficiency depends criticall…
Learning Topological Quantum Phases from Limited Subsystems
Mehran Khosrojerdi, Sougato Bose, Alessandro Cuccoli +3
Characterizing quantum topological phases requires measuring non-local string order parameters, demanding access to the full system, which is often experimentally unfeasible. In th…
Lower Bounding the Secret Key Capacity of Bosonic Gaussian Channels via Optimal Gaussian Measurements
Giuseppe Ortolano, Stefano Pirandola, Leonardo Banchi
We find the maximum rate achievable in the private communication over a bosonic quantum channel with a fully Gaussian protocol based on optimal single-mode Gaussian measurements. T…
Unsupervised Learning to Recognize Quantum Phases of Matter
Mehran Khosrojerdi, Alessandro Cuccoli, Paola Verrucchi +1
Drawing the quantum phase diagram of a many-body system in the parameter space of its Hamiltonian can be seen as a learning problem, which implies labelling the corresponding groun…
Efficient tensor-network simulations of weakly-measured quantum circuits
Darren Pereira, Leonardo Banchi
We present a tensor-network-based method for simulating a weakly-measured quantum circuit. In particular, we use a Markov chain to efficiently sample measurements and contract the…
Overshifted Parameter-Shift Rules: Optimizing Complex Quantum Systems with Few Measurements
Leonardo Banchi, Dominic Branford, Chetan Waghela
Gradient-based optimization is a key ingredient of variational quantum algorithms, with applications ranging from quantum machine learning to quantum chemistry and simulation. The…
Analysis of Quantum Image Representations for Supervised Classification
Marco Parigi, Mehran Khosrojerdi, Filippo Caruso +1
In the era of big data and artificial intelligence, the increasing volume of data and the demand to solve more and more complex computational challenges are two driving forces for…
Quantum computing and artificial intelligence: status and perspectives
Giovanni Acampora, Andris Ambainis, Natalia Ares +36
This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could supp…
Solving MNIST with a globally trained Mixture of Quantum Experts
Paolo Alessandro Xavier Tognini, Leonardo Banchi, Giacomo De Palma
We propose a new quantum neural network for image classification, which is able to classify the parity of the MNIST dataset with full resolution with a test accuracy of up to 97.5%…
Chernoff Information Bottleneck for Covert Quantum Target Sensing
Giuseppe Ortolano, Ivano Ruo-Berchera, Leonardo Banchi
The paradigm of quantum metrology and sensing aims to identify a quantum advantage in precision at a fixed energy of the probe state. However, in practice, employing high-energy cl…
Out-of-distribution generalisation for learning quantum channels with low-energy coherent states
Jason L. Pereira, Quntao Zhuang, Leonardo Banchi
When experimentally learning the action of a continuous variable quantum process by probing it with inputs, there will often be some restriction on the input states used. One exper…
Myths around quantum computation before full fault tolerance: What no-go theorems rule out and what they don't
Zoltán Zimborás, Bálint Koczor, Zoë Holmes +19
In this perspective article, we revisit and critically evaluate prevailing viewpoints on the capabilities and limitations of near-term quantum computing and its potential transitio…
Few measurement shots challenge generalization in learning to classify entanglement
Leonardo Banchi, Jason Pereira, Marco Zamboni
The ability to extract general laws from a few known examples depends on the complexity of the problem and on the amount of training data. In the quantum setting, the learner's gen…
Quantum spatial search with multiple excitations
Dylan Lewis, Leonardo Banchi, Sougato Bose
Spatial search is the problem of finding a marked vertex in a graph. A continuous-time quantum walk in the single-excitation subspace of an spin system solves the problem of sp…
Learning to Classify Quantum Phases of Matter with a Few Measurements
Mehran Khosrojerdi, Jason L. Pereira, Alessandro Cuccoli +1
We study the identification of quantum phases of matter, at zero temperature, when only part of the phase diagram is known in advance. Following a supervised learning approach, we…
Transmon qubit modeling and characterization for Dark Matter search
R. Moretti, D. Labranca, P. Campana +21
This study presents the design, simulation, and experimental characterization of a superconducting transmon qubit circuit prototype for potential applications in dark matter detect…
Quantum Adversarial Learning for Kernel Methods
Giuseppe Montalbano, Leonardo Banchi
We show that hybrid quantum classifiers based on quantum kernel methods and support vector machines are vulnerable against adversarial attacks, namely small engineered perturbation…
Characterization of a Transmon Qubit in a 3D Cavity for Quantum Machine Learning and Photon Counting
Alessandro D'Elia, Boulos Alfakes, Anas Alkhazaleh +19
In this paper we report the use of superconducting transmon qubit in a 3D cavity for quantum machine learning and photon counting applications. We first describe the realization an…
Accuracy vs Memory Advantage in the Quantum Simulation of Stochastic Processes
Leonardo Banchi
Many inference scenarios rely on extracting relevant information from known data in order to make future predictions. When the underlying stochastic process satisfies certain assum…
Full-magnetic implementation of a classical Toffoli gate
Davide Nuzzi, Leonardo Banchi, Ruggero Vaia +4
The Toffoli gate is the essential ingredient for reversible computing, an energy efficient classical computational paradigm that evades the energy dissipation resulting from Landau…
Design and simulation of a transmon qubit chip for Axion detection
Roberto Moretti, Hervè Atsè Corti, Danilo Labranca +54
Quantum Sensing is a rapidly expanding research field that finds one of its applications in Fundamental Physics, as the search for Dark Matter. Devices based on superconducting qub…
Statistical Complexity of Quantum Learning
Leonardo Banchi, Jason Luke Pereira, Sharu Theresa Jose +1
Recent years have seen significant activity on the problem of using data for the purpose of learning properties of quantum systems or of processing classical or quantum data via qu…
Continuous variable port-based teleportation
Jason L. Pereira, Leonardo Banchi, Stefano Pirandola
Port-based teleportation is generalization of the standard teleportation protocol which does not require unitary operations by the receiver. This comes at the price of requiring $N…
Time-Warping Invariant Quantum Recurrent Neural Networks via Quantum-Classical Adaptive Gating
Ivana Nikoloska, Osvaldo Simeone, Leonardo Banchi +1
Adaptive gating plays a key role in temporal data processing via classical recurrent neural networks (RNN), as it facilitates retention of past information necessary to predict the…