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- Bernard Krauth Wilson 2009 (6284 bytes)
64: data = []
72: data.append(dist(L[i],L[j]))
101: pylab.hist(data,bins=40,normed=True,alpha=0.5,cumulative=True) - Holzmann Krauth 2008 (1166 bytes)
4: ...hing in the thermodynamic limit. We interpret our data in the framework of the local-density approximati... - Krauth 2010 (5787 bytes)
64: def tower_sample(data,Upsilon): #naive tower sampling, cf. SMAC Sect. 1...
65: for k in range(len(data)):
66: if Upsilon<data[k]: break - Navon Piatecki Guenter et al 2011 (1155 bytes)
4: ...amples. For increasing repulsive interactions our data shows a clear departure from mean-field theory an... - Bernard Krauth 2012 (24591 bytes)
125: data = []
138: data.append(dist(L[i],L[j]))
206: f=open("event_stepped_13.data","w")
207: cPickle.dump(data,f)
209: pylab.hist(data,bins=40,normed=True) - Comparin Krauth 2016a (1510 bytes)
6: ...re this crucial observable to recent experimental data. The weak dependence of physical observables on t... - Levy problem HW01 ICFP 2018.py (676 bytes)
8: Ndata = 1000
9: data = []
12: for l in range(Ndata):
14: data.append(x / Ndata - 1.0/(gamma + 1.0))
15: pylab.hist(data,bins=100, range=(-1.0, 2.0), normed=True) - Bayes tank problem HW02 ICFP 2019.py (910 bytes)
9: data = range(1, N + 1)
10: random.shuffle(data)
11: data[0: 4] = sorted(data[0:4])
12: # if data[3] == 14:
13: if data[0: 4] == [1, 2, 4, 14]: - Vortex pair.py (2992 bytes)
9: def plot_spin(data, L):
10: data = data.reshape(L*L)
14: U = numpy.cos(data)
15: V = numpy.sin(data)
16: data = data.reshape(L, L) - Hard disks: A Window into the World of Stat Physics (3699 bytes)
33: ## Algorithms and data structures - Li Todo Maggs Krauth 2020 (1530 bytes)
5: ...ntation that uses compare-and-swap primitives for data access achieves considerable speed-up with respec... - PastResearchNotices (28752 bytes)
20: ...ntation that uses compare-and-swap primitives for data access achieves considerable speed-up with respec...
81: ...nt-chain Monte Carlo]]), we confirmed our earlier data (see figure to the left). We are all happy about ...
83: ...e! The inset gives the difference between the old data (from last year) and the new ones. Let me note th... - Levy problem HW01 ICFP 2017.py (627 bytes)
8: Ndata = 1000
9: data = []
12: for l in range(Ndata):
14: data.append(x / Ndata - 1.0/(gamma + 1.0))
15: pylab.hist(data,bins=100, range=(-1.0, 2.0), normed=True) - PhD2019 Proposal (5501 bytes)
1: ...ter statistical physics, quantum computation, and data science'''
48: ...ng. The use of the Beyond-Metropolis approach for data science will thus also be investigated. - Li Nishikawa et al 2022 (1587 bytes)
4: ...ling algorithms. A synopsis of hard-disk pressure data as well as different versions of the sampling alg... - CardShuffle.py (535 bytes)
3: data = []
4: HistoData = {}
13: if LL in HistoData: HistoData[LL] += 1
14: else: HistoData[LL] = 1
15: data.append(iter2) - Direct N bosons.py (2580 bytes)
25: def tower_sample(data, Upsilon): #fully naive tower sampling
26: for k in range(len(data)):
27: if Upsilon < data[k]: break - Walker.py (2274 bytes)
40: data = [0] * N
49: data[sample] += 1.0 / NSample
51: print(pi[i], data[i]) - Top to random simul.py (579 bytes)
8: data = {}
15: data[L] = data.get(L, 0) + 1
16: for k in data:
17: print(k, data[k]) - Diffusion.py (2640 bytes)
14: data = []
20: data.append(pos)
22: plt.hist(data, bins=N, range=(-0.5, N-0.5), density=True)
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