Quantum Computation
A fully connected quantum annealing architecture;
Sci. Adv. 1, 9, e1500838 (2015)
Quantum computers show the potential of outperforming classical computers in a variety of applications. We are interested in developing algorithms for solving relevant practical problems, ranging from the simulation of quantum many-body systems to the solution of NP-complete optimization problems. Besides gate-based quantum computers, we also investigate adiabatic quantum optimization and quantum annealing. Further interests include the development of improved implementations, e.g., in trapped-ion architectures, as well as understanding the role of various quantum resources on the road to achieving a tangible quantum advantage.
Philipp Hauke
Professor
Ganesh Hanchanahal
PhD Student
Alberto Bottarelli
PhD Student
Sebastian Nagies
PhD Student
Matteo M. Wauters
Postdoc
Chiara Capecci
Postdoc
Publications
Practical Noise Mitigation for Quantum Annealing via Dynamical Decoupling -- Towards Industry-Relevant Optimization using Trapped Ions
Quantum annealing is a framework for solving combinatorial optimization problems. While it offers a promising path towards a practical …
Enhancing Expressivity of Quantum Neural Networks Based on the SWAP test
Parameterized quantum circuits represent promising architectures for machine learning applications, yet many lack clear connections to …
Role of Nonstabilizerness in Quantum Optimization
Quantum optimization has emerged as a promising approach for tackling complicated classical optimization problems using quantum …
Impact of Clifford operations on non-stabilizing power and quantum chaos
Non-stabilizerness, alongside entanglement, is a crucial ingredient for fault-tolerant quantum computation and achieving a genuine …
Disorder-averaged Qudit Dynamics
Understanding how physical systems are influenced by disorder is a fundamental challenge in quantum science. Addressing its effects …
Boosting quantum annealing performance through direct polynomial unconstrained binary optimization
Quantum annealing aims at solving optimization problems of practical relevance using quantum computing hardware. Problems of interest …
Genuine multipartite entanglement in quantum optimization
The ability to generate bipartite entanglement in quantum computing technologies is widely regarded as pivotal. However, the role of …
The role of higher-order terms in trapped-ion quantum computing with magnetic gradient induced coupling
Trapped-ion hardware based on the Magnetic Gradient Induced Coupling (MAGIC) scheme is emerging as a promising platform for quantum …
A Monte Carlo Tree Search approach to QAOA: finding a needle in the haystack
The search for quantum algorithms to tackle classical combinatorial optimization problems has long been one of the most attractive yet …
Qudit-native measurement protocol for dynamical correlations using Hadamard tests
Dynamical correlations reveal important out-of-equilibrium properties of the underlying quantum many-body system, yet they are …
Quantum Computation of Thermal Averages for a Non-Abelian D4 Lattice Gauge Theory via Quantum Metropolis Sampling
In this paper, we show the application of the Quantum Metropolis Sampling (QMS) algorithm to a toy gauge theory with discrete …
Squeezing and quantum approximate optimization
Variational quantum algorithms offer fascinating prospects for the solution of combinatorial optimization problems using digital …
Quantum approximate optimization algorithm for qudit systems
A frequent starting point of quantum computation platforms is the two-state quantum system, i.e., the qubit. However, in the context of …
Probing confinement in a $\mathbb{Z}_2$ lattice gauge theory on a quantum computer
Digital quantum simulators provide a table-top platform for addressing salient questions in particle and condensed-matter physics. A …
Sampling Rare Conformational Transitions with a Quantum Computer
Spontaneous structural rearrangements play a central role in the organization and function of complex biomolecular systems. In …
Polymer Physics by Quantum Computing
Sampling equilibrium ensembles of dense polymer mixtures is a paradigmatically hard problem in computational physics, even in …
Dominant Reaction Pathways by Quantum Computing
Characterizing thermally activated transitions in high-dimensional rugged energy surfaces is a very challenging task for classical …
Perspectives of quantum annealing: Methods and implementations
Quantum annealing is a computing paradigm that has the ambitious goal of efficiently solving large-scale combinatorial optimization …
Quantum localization bounds Trotter errors in digital quantum simulation
A fundamental challenge in digital quantum simulation (DQS) is the control of an inherent error, which appears when discretizing the …
Real-time dynamics of lattice gauge theories with a few-qubit quantum computer
Gauge theories are fundamental to our understanding of interactions between the elementary constituents of matter as mediated …
A quantum annealing architecture with all-to-all connectivity from local interactions
Quantum annealers are physical devices that aim at solving NP-complete optimization problems by exploiting quantum mechanics. The basic …
Talks
Implementing a $\mathbb{Z}_2$ Lattice Gauge Theory in a Digital Quantum Simulator
Digital quantum simulators provide a table-top platform for addressing salient questions in particle, nuclear, and condensed-matter …
Mirradio - Le chicche di Mirradio: Puntata 1 | Quantum Computing
Di quantum computing si sente parlare da un po’ di tempo, ma non sempre viene presentato con chiarezza.
Per raccontarlo come si deve, …