Attila Andai

Uncertainty principle with quantum Fisher information

In this paper we prove a lower bound for the determinant of the covariance matrix of quantum mechanical observables, which was conjectured by Gibilisco et al. and has the interpretation of uncertainty. The lower bound is given in terms of the commutator of the state and the observables and quantum Fisher information (generated by an operator monotone function).

Monotone Riemannian metrics on density matrices with non-monotone scalar curvature ∗

The theory of monotone Riemannian metrics on the state space of a quantum system was established by Denes Petz in 1996. In a recent paper he argued that the scalar curvature of a statistically relevant—monotone—metric can be interpreted as an average statistical uncertainty. The present paper contributes to this subject. It is reasonable to expect that states which are more mixed are less distinguishable than those which are less mixed. The manifestation of this behavior could be that for such a metric the scalar curvature has a maximum at the maximally mixed state. We show that not every monotone metric fulfils this expectation, some of them behave in a very different way. A mathematical condition is given for monotone Riemannian metrics to have a local minimum at the maximally mixed state and examples are given for such metrics.

Volume of the quantum mechanical state space

The volume of the quantum mechanical state space over n-dimensional real, complex and quaternionic Hilbert spaces with respect to the canonical Euclidean measure is computed, and explicit formulae are presented for the expected value of the determinant also in the general setting. The case when the state space is endowed with a monotone metric or a pull-back metric is also considered; we give formulae for the volume of the state space with respect to the given Riemannian metric. We present the volume of the space of qubits with respect to various monotone metrics. It turns out that the volume of the space of qubits can also be infinite. We characterize those monotone metrics which generate infinite volume.

Invariance of separability probability over reduced states in 4 × 4 bipartite systems

The geometric separability probability of composite quantum systems is extensively studied in the last decades. One of most simple but strikingly difficult problem is to compute the separability probability of qubit-qubit and rebit-rebit quantum states with respect to the Hilbert-Schmidt measure. A lot of numerical simulations confirm the P(rebit-rebit)=29/64 and P(qubit-qubit)=8/33 conjectured probabilities. Milz and Strunz studied the separability probability with respect to given subsystems. They conjectured that the separability probability of qubit-qubit (and qubit-qutrit) depends on sum of single qubit subsystems (D), moreover it depends just on the Bloch radii (r) of D and it is constant in r. Using the Peres-Horodecki criterion for separability we give mathematical proof for the P(rebit-rebit)=29/64 probability and we present an integral formula for the complex case which hopefully will help to prove the P(qubit-qubit)=8/33 probability too. We prove Milz and Strunzs conjecture for rebit-rebit and qubit-qubit states. The case, when the state space is endowed with the volume form generated by the operator monotone function f(x)=sqrt(x) is studied too in detail. We show, that even in this setting the Milz and Strunzs conjecture holds and we give an integral formula for separability probability according to this measure.

Refinement of Robertson-type uncertainty principles with geometric interpretation ∗

A generalisation of the classical covariance for quantum mechanical observables has previously been presented by Gibilisco, Hiai and Petz. Gibilisco and Isola has proved that the usual quantum covariance gives the sharpest inequalities for the determinants of covariance matrices. We introduce a new generalisation of the classical covariance which gives better inequalities than the classical one furthermore it has a direct geometric interpretation.