Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram

We describe an efficient Monte Carlo algorithm using a random walk in energy space to obtain a very accurate estimate of the density of states for classical statistical models. The density of states is modified at each step when the energy level is visited to produce a flat histogram. By carefully controlling the modification factor, we allow the density of states to converge to the true value very quickly, even for large systems. This algorithm is especially useful for complex systems with a rough landscape since all possible energy levels are visited with the same probability. In this paper, we apply our algorithm to both 1st and 2nd order phase transitions to demonstrate its efficiency and accuracy. We obtained direct simulational estimates for the density of states for two-dimensional ten-state Potts models on lattices up to $200 \times 200$ and Ising models on lattices up to $256 \times 256$. Applying this approach to a 3D $\pm J$ spin glass model we estimate the internal energy and entropy at zero temperature; and, using a two-dimensional random walk in energy and order-parameter space, we obtain the (rough) canonical distribution and energy landscape in order-parameter space. Preliminary data suggest that the glass transition temperature is about 1.2 and that better estimates can be obtained with more extensive application of the method.Comment: 22 pages (figures included

Fungal infections in marrow transplant recipients under antifungal prophylaxis with fluconazole

Fungal infection is one of the most important causes of morbidity and mortality in bone marrow transplant (BMT) recipients. The growing incidence of these infections is related to several factors including prolonged granulocytopenia, use of broad-spectrum antibiotics, conditioning regimens, and use of immunosuppression to avoid graft-versus-host disease (GvHD). In the present series, we report five cases of invasive mold infections documented among 64 BMT recipients undergoing fluconazole antifungal prophylaxis: 1) A strain of Scedosporium prolificans was isolated from a skin lesion that developed on day +72 after BMT in a chronic myeloid leukemic patient. 2) Invasive pulmonary aspergillosis (Aspergillus fumigatus) was diagnosed on day +29 in a patient with a long period of hospitalization before being transplanted for severe aplastic anemia. 3) A tumoral lung lesion due to Rhizopus arrhizus (zygomycosis) was observed in a transplanted patient who presented severe chronic GvHD. 4) A tumoral lesion due to Aspergillus spp involving the 7th, 8th and 9th right ribs and local soft tissue was diagnosed in a BMT patient on day +110. 5) A patient with a history of Ph1-positive acute lymphocytic leukemia exhibited a cerebral lesion on day +477 after receiving a BMT during an episode of severe chronic GvHD. At that time, blood and spinal fluid cultures yielded Fusarium sp. Opportunistic infections due to fungi other than Candida spp are becoming a major problem among BMT patients receiving systemic antifungal prophylaxis with fluconazole.Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Disciplina de Hematologia e HemoterapiaCasa de Saúde Santa Marcelina Serviço de HematologiaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de PatologiaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Divisão de Moléstias InfecciosasUNIFESP, EPM, Disciplina de Hematologia e HemoterapiaUNIFESP, EPM, Depto. de PatologiaUNIFESP, EPM, Divisão de Moléstias InfecciosasSciEL