Quantum Computation as Geometry

Quantum computers hold great promise, but it remains a challenge to find efficient quantum circuits that solve interesting computational problems. We show that finding optimal quantum circuits is essentially equivalent to finding the shortest path between two points in a certain curved geometry. By recasting the problem of finding quantum circuits as a geometric problem, we open up the possibility of using the mathematical techniques of Riemannian geometry to suggest new quantum algorithms, or to prove limitations on the power of quantum computers.Comment: 13 Pages, 1 Figur

Simplicial Ricci Flow

We construct a discrete form of Hamilton's Ricci flow (RF) equations for a d-dimensional piecewise flat simplicial geometry, S. These new algebraic equations are derived using the discrete formulation of Einstein's theory of general relativity known as Regge calculus. A Regge-Ricci flow (RRF) equation is naturally associated to each edge, L, of a simplicial lattice. In defining this equation, we find it convenient to utilize both the simplicial lattice, S, and its circumcentric dual lattice, S*. In particular, the RRF equation associated to L is naturally defined on a d-dimensional hybrid block connecting $\ell$ with its (d-1)-dimensional circumcentric dual cell, L*. We show that this equation is expressed as the proportionality between (1) the simplicial Ricci tensor, Rc_L, associated with the edge L in S, and (2) a certain volume weighted average of the fractional rate of change of the edges, lambda in L*, of the circumcentric dual lattice, S*, that are in the dual of L. The inherent orthogonality between elements of S and their duals in S* provide a simple geometric representation of Hamilton's RF equations. In this paper we utilize the well established theories of Regge calculus, or equivalently discrete exterior calculus, to construct these equations. We solve these equations for a few illustrative examples.Comment: 34 pages, 10 figures, minor revisions, DOI included: Commun. Math. Phy

An analytic relation for the thickness of accretion flows

We take the vertical distribution of the radial and azimuthal velocity into account in spherical coordinates, and find that the analytic relation c_{s0}/(v_K \Theta) = [(\gamma -1)/(2\gamma)]^{1/2} is valid for both geometrically thin and thick accretion flows, where c_{s0} is the sound speed on the equatorial plane, v_K is the Keplerian velocity, \Theta is the half-opening angle of the flow, and \gamma is the adiabatic index.Comment: 4 pages, 2 figures, accepted by Science in China Series

Earth matter density uncertainty in atmospheric neutrino oscillations

That muon neutrinos $\nu_{\mu}$ oscillating into the mixture of tau neutrinos $\nu_{\tau}$ and sterile neutrinos $\nu_{s}$ has been studied to explain the atmospheric $\nu_{\mu}$ disappearance. In this scenario, the effect of Earth matter is a key to determine the fraction of $\nu_{s}$. Considering that the Earth matter density has uncertainty and this uncertainty has significant effects in some neutrino oscillation cases, such as the CP violation in very long baseline neutrino oscillations and the day-night asymmetry for solar neutrinos, we study the effects caused by this uncertainty in the above atmospheric $\nu_{\mu}$ oscillation scenario. We find that this uncertainty seems to have no significant effects and that the previous fitting results need not to be modified fortunately.Comment: 7 pages, 1 figure, to appear in Phys. Rev.

The Stream-Stream Collision after the Tidal Disruption of a Star Around a Massive Black Hole

A star can be tidally disrupted around a massive black hole. It has been known that the debris forms a precessing stream, which may collide with itself. The stream collision is a key process determining the subsequent evolution of the stellar debris: if the orbital energy is efficiently dissipated, the debris will eventually form a circular disk (or torus). In this paper, we have numerically studied such stream collision resulting from the encounter between a 10^6 Msun black hole and a 1 Msun normal star with a pericenter radius of 100 Rsun. A simple treatment for radiative cooling has been adopted for both optically thick and thin regions. We have found that approximately 10 to 15% of the initial kinetic energy of the streams is converted into thermal energy during the collision. The angular momentum of the incoming stream is increased by a factor of 2 to 3, and such increase, together with the decrease in kinetic energy, significantly helps the circularization process. Initial luminosity burst due to the collision may reach as high as 10^41 erg/sec in 10^4 sec, after which the luminosity increases again (but slowly this time) to a steady value of a few 10^40 erg/sec in a few times of 10^5 sec. The radiation from the system is expected to be close to Planckian with effective temperature of \~10^5K.Comment: 19 pages including 12 figures; Accepted for publication in Ap

Active Semi-Supervised Learning Using Sampling Theory for Graph Signals

We consider the problem of offline, pool-based active semi-supervised learning on graphs. This problem is important when the labeled data is scarce and expensive whereas unlabeled data is easily available. The data points are represented by the vertices of an undirected graph with the similarity between them captured by the edge weights. Given a target number of nodes to label, the goal is to choose those nodes that are most informative and then predict the unknown labels. We propose a novel framework for this problem based on our recent results on sampling theory for graph signals. A graph signal is a real-valued function defined on each node of the graph. A notion of frequency for such signals can be defined using the spectrum of the graph Laplacian matrix. The sampling theory for graph signals aims to extend the traditional Nyquist-Shannon sampling theory by allowing us to identify the class of graph signals that can be reconstructed from their values on a subset of vertices. This approach allows us to define a criterion for active learning based on sampling set selection which aims at maximizing the frequency of the signals that can be reconstructed from their samples on the set. Experiments show the effectiveness of our method.Comment: 10 pages, 6 figures, To appear in KDD'1