Modified Dark Matter: Relating Dark Energy, Dark Matter and Baryonic Matter

Modified dark matter (MDM) is a phenomenological model of dark matter, inspired by gravitational thermodynamics. For an accelerating Universe with positive cosmological constant ($\Lambda$), such phenomenological considerations lead to the emergence of a critical acceleration parameter related to $\Lambda$. Such a critical acceleration is an effective phenomenological manifestation of MDM, and it is found in correlations between dark matter and baryonic matter in galaxy rotation curves. The resulting MDM mass profiles, which are sensitive to $\Lambda$, are consistent with observational data at both the galactic and cluster scales. In particular, the same critical acceleration appears both in the galactic and cluster data fits based on MDM. Furthermore, using some robust qualitative arguments, MDM appears to work well on cosmological scales, even though quantitative studies are still lacking. Finally, we comment on certain non-local aspects of the quanta of modified dark matter, which may lead to novel non-particle phenomenology and which may explain why, so far, dark matter detection experiments have failed to detect dark matter particles

Coloring vertices of a graph or finding a Meyniel obstruction

A Meyniel obstruction is an odd cycle with at least five vertices and at most one chord. A graph is Meyniel if and only if it has no Meyniel obstruction as an induced subgraph. Here we give a O(n^2) algorithm that, for any graph, finds either a clique and coloring of the same size or a Meyniel obstruction. We also give a O(n^3) algorithm that, for any graph, finds either aneasily recognizable strong stable set or a Meyniel obstruction

Electrostatic Modulation of the Electronic Properties of Dirac Semimetal Na3Bi

Large-area thin films of topological Dirac semimetal Na$_3$Bi are grown on amorphous SiO$_2$:Si substrates to realise a field-effect transistor with the doped Si acting as back gate. As-grown films show charge carrier mobilities exceeding 7,000 cm$^2$/Vs and carrier densities below 3 $\times$10$^{18}$ cm$^{-3}$, comparable to the best thin-film Na$_3$Bi. An ambipolar field effect and minimum conductivity are observed, characteristic of Dirac electronic systems. The results are quantitatively understood within a model of disorder-induced charge inhomogeneity in topological Dirac semimetals. Due to the inverted band structure, the hole mobility is significantly larger than the electron mobility in Na$_3$Bi, and when present, these holes dominate the transport properties.Comment: 5 pages, 4 figures; minor corrections and revisions for readabilit

Testing Modified Dark Matter with Galaxy Clusters: Does Dark Matter know about the Cosmological Constant?

We discuss the possibility that the cold dark matter mass profiles contain information on the cosmological constant, and that such information constrains the nature of cold dark matter (CDM). We call this approach Modified Dark Matter (MDM). In particular, we examine the ability of MDM to explain the observed mass profiles of 13 galaxy clusters. Using general arguments from gravitational thermodynamics, we provide a theoretical justification for our MDM mass profile and successfully compare it to the NFW mass profiles both on cluster and galactic scales. Our results suggest that indeed the CDM mass profiles contain information about the cosmological constant in a non-trivial way

Distributed Approximation of Maximum Independent Set and Maximum Matching

We present a simple distributed $\Delta$-approximation algorithm for maximum weight independent set (MaxIS) in the $\mathsf{CONGEST}$ model which completes in $O(\texttt{MIS}(G)\cdot \log W)$ rounds, where $\Delta$ is the maximum degree, $\texttt{MIS}(G)$ is the number of rounds needed to compute a maximal independent set (MIS) on $G$, and $W$ is the maximum weight of a node. %Whether our algorithm is randomized or deterministic depends on the \texttt{MIS} algorithm used as a black-box. Plugging in the best known algorithm for MIS gives a randomized solution in $O(\log n \log W)$ rounds, where $n$ is the number of nodes. We also present a deterministic $O(\Delta +\log^* n)$-round algorithm based on coloring. We then show how to use our MaxIS approximation algorithms to compute a $2$-approximation for maximum weight matching without incurring any additional round penalty in the $\mathsf{CONGEST}$ model. We use a known reduction for simulating algorithms on the line graph while incurring congestion, but we show our algorithm is part of a broad family of \emph{local aggregation algorithms} for which we describe a mechanism that allows the simulation to run in the $\mathsf{CONGEST}$ model without an additional overhead. Next, we show that for maximum weight matching, relaxing the approximation factor to ($2+\varepsilon$) allows us to devise a distributed algorithm requiring $O(\frac{\log \Delta}{\log\log\Delta})$ rounds for any constant $\varepsilon>0$. For the unweighted case, we can even obtain a $(1+\varepsilon)$-approximation in this number of rounds. These algorithms are the first to achieve the provably optimal round complexity with respect to dependency on $\Delta$

Testing MONDian Dark Matter with Galactic Rotation Curves

MONDian dark matter (MDM) is a new form of dark matter quantum that naturally accounts for Milgrom's scaling, usually associated with modified Newtonian dynamics (MOND), and theoretically behaves like cold dark matter (CDM) at cluster and cosmic scales. In this paper, we provide the first observational test of MDM by fitting rotation curves to a sample of 30 local spiral galaxies (z approximately 0.003). For comparison, we also fit the galactic rotation curves using MOND, and CDM. We find that all three models fit the data well. The rotation curves predicted by MDM and MOND are virtually indistinguishable over the range of observed radii (~1 to 30 kpc). The best-fit MDM and CDM density profiles are compared. We also compare with MDM the dark matter density profiles arising from MOND if Milgrom's formula is interpreted as Newtonian gravity with an extra source term instead of as a modification of inertia. We find that discrepancies between MDM and MOND will occur near the center of a typical spiral galaxy. In these regions, instead of continuing to rise sharply, the MDM mass density turns over and drops as we approach the center of the galaxy. Our results show that MDM, which restricts the nature of the dark matter quantum by accounting for Milgrom's scaling, accurately reproduces observed rotation curves.Comment: Preprint number IPMU13-0147. Accepted for publication in Ap

Machine Learning-Based Side-Channel Analysis on the Advanced Encryption Standard

Hardware security is essential in keeping sensitive information private. Because of this, it’s imperative that we evaluate the ability of cryptosystems to withstand cutting edge attacks. Doing so encourages the development of countermeasures and new methods of data protection as needed. In this thesis, we present our findings of an evaluation of the Advanced Encryption Standard, particularly unmasked and masked AES-128, implemented in software on an STM32F415 microcontroller unit (MCU), against machine learning-based side-channel analysis (MLSCA). 12 machine learning classifiers were used in combination with a side-channel leakage model in the context of four scenarios: profiling one device and key and attacking the same device with the same key, profiling one device and key and attacking a different device with the same key, profiling one device and key and attacking the same device with a different key, and profiling one device and key and attacking a different device with a different key. We found that unmasked AES-128 can be very vulnerable to this form of attack and that masking can be applied as a countermeasure to successfully prevent attacks in 2 out of the 4 tested scenarios. In addition to providing our experimental results on the following pages, we also plan to release a public GitHub repository with all of our collected side-channel data along with sample analysis code shortly after the time of writing this. We hope that doing so will allow for complete reproducibility of our results and encourage future research without the need for purchasing hardware equipment