Locality and Statistical Error Reduction on Correlation Functions

We propose a multilevel Monte-Carlo scheme, applicable to local actions, which is expected to reduce statistical errors on correlation functions. We give general arguments to show how the efficiency and parameters of the algorithm are determined by the low-energy spectrum. As an application, we measure the euclidean-time correlation of pairs of Wilson loops in SU(3) pure gauge theory with constant relative errors. In this case the ratio of the new method's efficiency to the standard one increases as exp{m_0t/2}, where m_0 is the mass gap and t the time separation.Comment: One paragraph changed in the introduction; some misprints corrected; 12 pages, 6 figure

Increased Metabolic Rate in X-linked Hypophosphatemic Mice

Hyp mice are a model for human X-linked hypophosphatemia, the most common form of vitamin D-resistant rickets. It has previously been observed that Hyp mice have a greater food consumption per gram body weight than do normal mice. This led to the search for some alteration in metabolism in Hyp mice. We found that oxygen consumption was significantly higher in Hyp mice than in normal C57BL/6J mice and this was accompanied by an increased percentage of cardiac output being delivered to organs of heat production (liver and skeletal muscle), to the skin, and to bone and a decreased percentage to the gastrointestinal tract of Hyp mice. The increased oxygen consumption in Hyp mice was not associated with increased plasma free T4 levels and was not affected by alterations in plasma phosphate produced by a low phosphate diet. The cause of the increased oxygen consumption is not known, and the role that this change and reported changes in distribution of cardiac output may play in the development of X-linked hypophosphatemia is also unknown. Study of the cardiovascular and thermoregulatory systems in Hyp mice should help increase understanding of the underlying mechanisms of this disease

Density, short-range order and the quark-gluon plasma

We study the thermal part of the energy density spatial correlator in the quark-gluon plasma. We describe its qualitative form at high temperatures. We then calculate it out to distances approx. 1.5/T in SU(3) gauge theory lattice simulations for the range of temperatures 0.9<= T/T_c<= 2.2. The vacuum-subtracted correlator exhibits non-monotonic behavior, and is almost conformal by 2T_c. Its broad maximum at r approx. 0.6/T suggests a dense medium with only weak short-range order, similar to a non-relativistic fluid near the liquid-gas phase transition, where eta/s is minimal.Comment: 4 pages, 4 figure

Transformation

Prior to leaving for Claremont Colleges’ Envriolab Asia trip to Malaysia and Singapore, I was conflicted by the question: Do we have the moral authority to interfere with resource extraction and oil-palm development in SE Asia? At that time, the trip seemed imperialistic. Why should people from Malaysia, Indonesia or any developing SE Asia country listen to a group of liberal arts college faculty from a city where widespread habitat modifications have led to significant loss of native habitats, declines in biodiversity, and changes in how these ecosystems function? Many observations transformed my opinion and have inspired me to advocate for transformative environmental and social change both in SE Asia and at home

A linear memory algorithm for Baum-Welch training

Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. Methods and results: We introduce a linear space algorithm for Baum-Welch training. For a hidden Markov model with M states, T free transition and E free emission parameters, and an input sequence of length L, our new algorithm requires O(M) memory and O(L M T_max (T + E)) time for one Baum-Welch iteration, where T_max is the maximum number of states that any state is connected to. The most memory efficient algorithm until now was the checkpointing algorithm with O(log(L) M) memory and O(log(L) L M T_max) time requirement. Our novel algorithm thus renders the memory requirement completely independent of the length of the training sequences. More generally, for an n-hidden Markov model and n input sequences of length L, the memory requirement of O(log(L) L^(n-1) M) is reduced to O(L^(n-1) M) memory while the running time is changed from O(log(L) L^n M T_max + L^n (T + E)) to O(L^n M T_max (T + E)). Conclusions: For the large class of hidden Markov models used for example in gene prediction, whose number of states does not scale with the length of the input sequence, our novel algorithm can thus be both faster and more memory-efficient than any of the existing algorithms.Comment: 14 pages, 1 figure version 2: fixed some errors, final version of pape

On qpqp-Deformations in Statistical Mechanics of Bosons in D Dimensions

The Bose distribution for a gas of nonrelativistic free bosons is derived in the framework of $qp$-deformed second quantization. Some thermodynamical functions for such a system in D dimensions are derived. Bose-Einstein condensation is discussed in terms of the parameters q and p as well as a parameter $\nu_0'$ which characterizes the representation space of the oscillator algebra.Comment: 15 pages, Latex File, to be published in Symmetry and Structural Properties of Condensed Matter, Eds. T. Lulek, B. Lulek and W. Florek (World Scientific, Singapore, 1997