Duistermaat-Heckman measure and the mixture of quantum states

In this paper, we present a general framework to solve a fundamental problem in Random Matrix Theory (RMT), i.e., the problem of describing the joint distribution of eigenvalues of the sum \bsA+\bsB of two independent random Hermitian matrices \bsA and \bsB. Some considerations about the mixture of quantum states are basically subsumed into the above mathematical problem. Instead, we focus on deriving the spectral density of the mixture of adjoint orbits of quantum states in terms of Duistermaat-Heckman measure, originated from the theory of symplectic geometry. Based on this method, we can obtain the spectral density of the mixture of independent random states. In particular, we obtain explicit formulas for the mixture of random qubits. We also find that, in the two-level quantum system, the average entropy of the equiprobable mixture of $n$ random density matrices chosen from a random state ensemble (specified in the text) increases with the number $n$. Hence, as a physical application, our results quantitatively explain that the quantum coherence of the mixture monotonously decreases statistically as the number of components $n$ in the mixture. Besides, our method may be used to investigate some statistical properties of a special subclass of unital qubit channels.Comment: 40 pages, 10 figures, LaTeX, the final version accepted for publication in J. Phys.

Modified Kedem-Katchalsky equations for osmosis through nano-pore

This work presents a modified Kedem-Katchalsky equations for osmosis through nano-pore. osmotic reflection coefficient of a solute was found to be chiefly affected by the entrance of the pore while filtration reflection coefficient can be affected by both the entrance and the internal structure of the pore. Using an analytical method, we get the quantitative relationship between osmotic reflection coefficient and the molecule size. The model is verified by comparing the theoretical results with the reported experimental data of aquaporin osmosis. Our work is expected to pave the way for a better understanding of osmosis in bio-system and to give us new ideas in designing new membranes with better performance.Comment: 19 pages, 4 figure

Penney’s game for permutations

We explore the permutation analog of Penney\u27s game for coin flips. Two players, in order, each choose a permutation of length $k\ge3$. Then a sequence of independent random values from a continuous distribution is generated until the relative order of the last $k$ numbers matches one of the chosen permutations, declaring the player who selected that permutation as the winner. We calculate the winning probabilities for all pairs of permutations of length $3$ and some pairs of length $4$, demonstrating the non-transitive property of this game, consistent with the original word version. Alternatively, we provide formulas for computing the winning probabilities more generally and conjecture a winning strategy for the second player when $k$ is arbitrary. We also consider a Markov chain variation of Penney\u27s game for permutations. After two players have selected their permutations of length $k$, the game starts at any permutation of length $k$ with probability $1/k!$. At each step, we transition from the current permutation to the next one with probability $1/k$, provided that the relative order of the last $k-1$ numbers of the current permutation coincide with the first $k-1$ numbers of the next permutation. We provide a formula for computing the expected time to observe any permutation for the first time (known as the hitting time) and discuss some conditions under which two permutations have the same hitting time. Furthermore, we compute the winning probabilities of all pairs of permutations of any length and conjecture a non-losing strategy for the second player

Penney's game for permutations

We consider the permutation analogue of Penney's game for words. Two players, in order, each choose a permutation of length $k\ge3$; then a sequence of independent random values from a continuous distribution is generated, until the relative order of the last $k$ numbers coincides with one of the chosen permutations, making that player the winner. We compute the winning probabilities for all pairs of permutations of length 3 and some pairs of length 4, showing that, as in the original version for words, the game is non-transitive. Our proofs introduce new bijections for consecutive patterns in permutations. We also give some formulas to compute the winning probabilities more generally, and conjecture a winning strategy for the second player when $k$ is arbitrary

Rethinking Medical Report Generation: Disease Revealing Enhancement with Knowledge Graph

Knowledge Graph (KG) plays a crucial role in Medical Report Generation (MRG) because it reveals the relations among diseases and thus can be utilized to guide the generation process. However, constructing a comprehensive KG is labor-intensive and its applications on the MRG process are under-explored. In this study, we establish a complete KG on chest X-ray imaging that includes 137 types of diseases and abnormalities. Based on this KG, we find that the current MRG data sets exhibit a long-tailed problem in disease distribution. To mitigate this problem, we introduce a novel augmentation strategy that enhances the representation of disease types in the tail-end of the distribution. We further design a two-stage MRG approach, where a classifier is first trained to detect whether the input images exhibit any abnormalities. The classified images are then independently fed into two transformer-based generators, namely, ``disease-specific generator" and ``disease-free generator" to generate the corresponding reports. To enhance the clinical evaluation of whether the generated reports correctly describe the diseases appearing in the input image, we propose diverse sensitivity (DS), a new metric that checks whether generated diseases match ground truth and measures the diversity of all generated diseases. Results show that the proposed two-stage generation framework and augmentation strategies improve DS by a considerable margin, indicating a notable reduction in the long-tailed problem associated with under-represented diseases