Quantum information science asks what information
processing tasks are
possible if single quantum systems are used as elementary carries of
information. The ability to coherently manipulate the state of a
quantum system allows for tasks that are thought to be unachievable in
the classical context - such as secure transmission of information - or
for the efficient solution of computational problems for which no
classical efficient algorithm is known.
We ask - with methods of
mathematical physics - questions of how to
grasp entanglement, giving
rise to quantum correlations that are
stronger than classically attainable, of quantum channel capacities,
and of new quantum computational
models, based on quantum many-body
ideas and tensor networks.
Recently newly acquired interest is
concerned
with pseudo-random states and
operations in quantum expanders
and
unitary designs,
as well as questions of concentration
of measure and
classical percolation
ideas.
A main theme recently is first and
foremost the idea of quantum systems
identification: Often, one can
much more efficiently and cheaply estimate intricate properties of
quantum systems, without the need of full quantum state or process
tomography. Using the idea of compressed
sensing, even full quantum
state tomography can be made for low rank states with about the square
root of the previously known effort. Quantum information ideas are
often a guiding
principle in work that is not directly related to information
processing as such.
For a comprehensive list of tutorials and review articles, see this link. For popular articles
about our
work, see this link.
"Gaussian
quantum channels",
In: "Continuous-variable quantum information science", Eds. E. Polzik,
N. Cerf, G. Leuchs (Imperial College Press, London, 2007).
Quantum information science asks what information
processing tasks are
possible if single quantum systems are used as elementary carries of
information. The ability to coherently manipulate the state of a
quantum system allows for tasks that are thought to be unachievable in
the classical context - such as secure transmission of information - or
for the efficient solution of computational problems for which no
classical efficient algorithm is known.