Publications (32)
Single-shot Adaptive Measurement for Quantum-enhanced Metrology
Pantita Palittapongarnpim, Peter Wittek, Barry C. Sanders
Quantum-enhanced metrology aims to estimate an unknown parameter such that the precision scales better than the shot-noise bound. Single-shot adaptive quantum-enhanced metrology (A…
Optimal randomness certification from one entangled bit
Antonio AcÃn, Stefano Pironio, Tamás Vértesi +1
By performing local projective measurements on a two-qubit entangled state one can certify in a device-independent way up to one bit of randomness. We show here that general measur…
Identifying Quantum Phase Transitions with Adversarial Neural Networks
Patrick Huembeli, Alexandre Dauphin, Peter Wittek
The identification of phases of matter is a challenging task, especially in quantum mechanics, where the complexity of the ground state appears to grow exponentially with the size…
Anchored Network Users: Stochastic Evolutionary Dynamics of Cognitive Radio Network Selection
Ik Soo Lim, Peter Wittek
To solve the spectrum scarcity problem, the cognitive radio technology involves licensed users and unlicensed users. A fundamental issue for the network users is whether it is bett…
Quantum Machine Learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti +3
Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce co…
Risk and Ambiguity in Information Seeking: Eye Gaze Patterns Reveal Contextual Behaviour in Dealing with Uncertainty
Peter Wittek, Ying-Hsang Liu, Sándor Darányi +2
Information foraging connects optimal foraging theory in ecology with how humans search for information. The theory suggests that, following an information scent, the information s…
On the Origin of Risk Sensitivity: the Energy Budget Rule Revisited
Ik Soo Lim, Peter Wittek, John Parkinson
The risk-sensitive foraging theory formulated in terms of the (daily) energy budget rule has been influential in behavioural ecology as well as other disciplines. Predicting risk-a…
An Artificial Spiking Quantum Neuron
Lasse Bjørn Kristensen, Matthias Degroote, Peter Wittek +2
Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such as time series prediction and signal processin…
Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines
Aidan Kehoe, Peter Wittek, Yanbo Xue +1
We provide a robust defence to adversarial attacks on discriminative algorithms. Neural networks are naturally vulnerable to small, tailored perturbations in the input data that le…
Verifying the output of quantum optimizers with ground-state energy lower bounds
Flavio Baccari, Christian Gogolin, Peter Wittek +1
Solving optimisation problems encoded in the ground state of classical-spin systems is a focus area for quantum computing devices, providing upper bounds to the unknown solution. T…
Satisfied-defect, unsatisfied-cooperate: An evolutionary dynamics of cooperation led by aspiration
Ik Soo Lim, Peter Wittek
Evolutionary game theory has been widely used to study the evolution of cooperation in social dilemmas where imitation-led strategy updates are typically assumed. However, results…
Quantum Enhanced Inference in Markov Logic Networks
Peter Wittek, Christian Gogolin
Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and firs…
Ruling Out Static Latent Homophily in Citation Networks
Peter Wittek, Sándor Darányi, Gustaf Nelhans
Citation and coauthor networks offer an insight into the dynamics of scientific progress. We can also view them as representations of a causal structure, a logical process captured…
Algorithm 950: Ncpol2sdpa---Sparse Semidefinite Programming Relaxations for Polynomial Optimization Problems of Noncommuting Variables
Peter Wittek
A hierarchy of semidefinite programming (SDP) relaxations approximates the global optimum of polynomial optimization problems of noncommuting variables. Generating the relaxation,…
Evaluating probabilistic programming languages for simulating quantum correlations
Abdul Obeid, Peter D. Bruza, Peter Wittek
This article explores how probabilistic programming can be used to simulate quantum correlations in an EPR experimental setting. Probabilistic programs are based on standard probab…
Open source software in quantum computing
Mark Fingerhuth, Tomáš Babej, Peter Wittek
Open source software is becoming crucial in the design and testing of quantum algorithms. Many of the tools are backed by major commercial vendors with the goal to make it easier t…
Automated discovery of characteristic features of phase transitions in many-body localization
Patrick Huembeli, Alexandre Dauphin, Peter Wittek +1
We identify a new "order parameter" for the disorder driven many-body localization (MBL) transition by leveraging artificial intelligence. This allows us to pin down the transition…
Vortex dynamics in coherently coupled Bose-Einstein condensates
Luca Calderaro, Alexander L. Fetter, Pietro Massignan +1
In classical hydrodynamics with uniform density, vortices move with the local fluid velocity. This description is rewritten in terms of forces arising from the interaction with oth…
Learning in Quantum Control: High-Dimensional Global Optimization for Noisy Quantum Dynamics
Pantita Palittapongarnpim, Peter Wittek, Ehsan Zahedinejad +2
Quantum control is valuable for various quantum technologies such as high-fidelity gates for universal quantum computing, adaptive quantum-enhanced metrology, and ultra-cold atom m…
Entangled systems are unbounded sources of nonlocal correlations and of certified random numbers
Florian J. Curchod, Markus Johansson, Remigiusz Augusiak +3
The outcomes of local measurements made on entangled systems can be certified to be random provided that the generated statistics violate a Bell inequality. This way of producing r…
Inductive supervised quantum learning
Alex Monrà s, Gael SentÃs, Peter Wittek
In supervised learning, an inductive learning algorithm extracts general rules from observed training instances, then the rules are applied to test instances. We show that this spl…
A Second-Order Distributed Trotter-Suzuki Solver with a Hybrid Kernel
Peter Wittek, Fernando M. Cucchietti
The Trotter-Suzuki approximation leads to an efficient algorithm for solving the time-dependent Schrödinger equation. Using existing highly optimized CPU and GPU kernels, we devel…
Monitoring Term Drift Based on Semantic Consistency in an Evolving Vector Field
Peter Wittek, Sándor Darányi, Efstratios Kontopoulos +2
Based on the Aristotelian concept of potentiality vs. actuality allowing for the study of energy and dynamics in language, we propose a field approach to lexical analysis. Falling…
Vulnerability of quantum classification to adversarial perturbations
Nana Liu, Peter Wittek
High-dimensional quantum systems are vital for quantum technologies and are essential in demonstrating practical quantum advantage in quantum computing, simulation and sensing. Sin…
Efficient device-independent entanglement detection for multipartite systems
Flavio Baccari, Daniel Cavalcanti, Peter Wittek +1
Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement i…
Unfolding as Quantum Annealing
Kyle Cormier, Riccardo Di Sipio, Peter Wittek
High-energy physics is replete with hard computational problems and it is one of the areas where quantum computing could be used to speed up calculations. We present an implementat…
Bell inequalities tailored to maximally entangled states
Alexia Salavrakos, Remigiusz Augusiak, Jordi Tura +3
Bell inequalities have traditionally been used to demonstrate that quantum theory is nonlocal, in the sense that there exist correlations generated from composite quantum states th…
Bayesian Deep Learning on a Quantum Computer
Zhikuan Zhao, Alejandro Pozas-Kerstjens, Patrick Rebentrost +1
Bayesian methods in machine learning, such as Gaussian processes, have great advantages com-pared to other techniques. In particular, they provide estimates of the uncertainty asso…
Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure
Ding Liu, Shi-Ju Ran, Peter Wittek +4
The resemblance between the methods used in quantum-many body physics and in machine learning has drawn considerable attention. In particular, tensor networks (TNs) and deep learni…
A Physical Metaphor to Study Semantic Drift
Sándor Darányi, Peter Wittek, Konstantinos Konstantinidis +2
In accessibility tests for digital preservation, over time we experience drifts of localized and labelled content in statistical models of evolving semantics represented as a vecto…
Somoclu: An Efficient Parallel Library for Self-Organizing Maps
Peter Wittek, Shi Chao Gao, Ik Soo Lim +1
Somoclu is a massively parallel tool for training self-organizing maps on large data sets written in C++. It builds on OpenMP for multicore execution, and on MPI for distributing t…
Simulating positive-operator-valued measures with projective measurements
MichaÅ Oszmaniec, Leonardo Guerini, Peter Wittek +1
Standard projective measurements represent a subset of all possible measurements in quantum physics, defined by positive-operator-valued measures. We study what quantum measurement…