Bounded-Error Quantum Simulation via Hamiltonian and Liouvillian Learning
We provide an overview of ongoing research in quantum simulation at IQOQI Innsbruck. This includes the development of bounded-error quantum simulation techniques based on Hamiltonian and Liouvillian learning, along with initial experimental implementations using trapped-ion systems. Furthermore, we investigate inverse quantum simulation as a novel approach to quantum material design with quantum simulators.
Peter Zoller - Institute for Theoretical Physics, University of Innsbruck, and IQOQI, Academy of Sciences, Innsbruck, Austria
New Platforms for Quantum Sensing and Quantum Computing
The nitrogen vacancy (NV) center in diamond exhibits spin-dependent fluorescence and long spin
coherence times under ambient conditions, enabling applications in quantum information processing and
sensing. NV centers near the surface can have strong interactions with external materials and spins, enabling
new forms of nanoscale spectroscopy. However, NV spin coherence degrades within 100 nanometers of the
surface, suggesting that diamond surfaces are plagued with ubiquitous defects. I will describe our recent
Programmable real and synthetic dimensions: from correlated fermions to paraparticles
I will describe our theory research towards harnessing ultracold matter by programming the systems' behavior in both real space and "synthetic" space.
Fermions in an Optical Box
For the past two decades harmonically trapped ultracold atomic gases have been used with
great success to study fundamental many-body physics in flexible experimental settings.
However, the resulting gas density inhomogeneity in those traps has made it challenging to
study paradigmatic uniform-system physics (such as critical behavior near phase transitions) or
complex quantum dynamics. The realization of homogeneous quantum gases trapped in optical
boxes has been a milestone in quantum simulation [1]. These textbook systems have proved to
Nonlinear integrated photonics for deployable clocks and quantum sensors
The deployment of photonic quantum technologies outside of laboratories and into application
environments involves new components and system architectures, many of which are based on
photonic integrated circuits (PICs). In this talk, I will present our lab’s research on PIC components that
harness nonlinear optical processes in the context of optical atomic clocks and quantum sensors. For
such applications, nonlinear frequency conversion can generate the coherent visible and short near-
Building a Better Superconducting Qubit
Superconducting qubits are one of the leading platforms for quantum information processing but have not yet reached the performance necessary for useful quantum computation. In this talk, I will discuss current limitations on measurement and gate fidelity in superconducting qubits using the fluxonium as a case study. I will discuss our work understanding the origins of these limitations and the usage of applied microwave drives to improve measurement and gate fidelity.
Quantum Computation and Quantum Field Theory
We will discuss the path towards using quantum computers for quantum field theory calculations. In particular, two problems will be addressed: how to truncate the Hilbert space of bosonic fields and how to take the continuum limit without incurring in exponentially large costs. We will discuss the particular case of the non-linear sigma model, where those questions are fully understood, followed by gauge theories, where those questions remain fairly open.
Assembling and Probing Highly Entangled Quantum Matter with Superconducting Circuits
Superconducting circuits are a powerful platform for quantum computation and sensing. In this talk I will show how we can use techniques from those domains to create and interrogate strongly interacting matter from microwave photons. In particular we discuss how disorder can be leveraged to assemble compressible quantum fluids. Using correlation measurements we can can observe photon fermionization.