You pay a much higher price than the article processing fee if you publish in Scientific Reports: your inbox and your reputation are at stake.

## The real price of publishing in Scientific Reports

## From stochastic matrices to process matrices

The intuition behind the process matrix formalism in quantum physics from the perspective of probability theory

## Advances in quantum machine learning in 2016 and in early 2017

Desperately trying to keep up with the latest developments in quantum machine learning, let that be a new quantum-enhanced learning protocol, or some exciting connection between quantum many-body physics and statistical learning theory

## 7 Easy Ways to Alienate Authors from Your Journal

Your high-impact and very important journal will stay on top if and only if you publish papers written exclusively by well-funded groups of famous scientists. Save yourself the trouble of having to deal with small fish by following these 7 easy steps.

## Hot authors and topics in quant-ph in 2016 and how to generate a sexy abstract

SciRate gives instant gratification for our precious preprints on arXiv. We analyse the metadata of the papers that appeared in quant-ph in 2016 to find out the hottest authors and topics, and we train a recurrent neural network to generate fake abstracts.

## Comparing three numerical solvers of the Gross-Pitaevskii equation

A quick comparison of Trotter-Suzuki-MPI, GPELab, and GPUE for simulating the evolution of Bose-Einstein Condensates

## Quantum machine learning in 2015

Quantum machine learning as a research field is exploding: here we give a brief overview of the relevant papers that appeared on arXiv in 2015.

## Relaxations of parametric and bilevel polynomial optimization problems

Semidefinite programming relaxations of polynomial optimization problems of commuting variables with moment constraints, parametric and bilevel variants.

## Fast self-organizing maps in Python with Somoclu

Somoclu, a massively parallel implementation of self-organizing maps, has updated its visual capabilities for its Python interface.

## Semidefinite programming in Python

A brief overview of SDP solvers and tools in Python

## The horror of Juniper VPN

We waste tax payers money on an outrageously bad piece of VPN software that also opens backdoors for government and industrial espionage.

## Optimal randomness generation from entangled quantum states

Optimal randomness generation from entangled quantum states: computational appendix to arXiv:1505.03837.

## Machine learning and quantum physics in the first third of 2015

Looking at the crop of quantum machine learning manuscripts on arXiv from the beginning of 2015 until the middle of May.

## Detecting a rank loop in the NPA hierarchy

It is possible to detect a rank loop in the hierarchy of SDP relaxations of polynomial optimization problems, but an arbitrary-precision SDP solver is recommended.

## Reflective random indexing on short documents with fixed vocabulary

Reflective random indexing can lead to strange results: if the vocabulary is small compared to the number of documents, term vectors will show little variety.

## End-of-year updates on quantum machine learning

Another handful of papers on quantum machine learning that appeared in the last two months of 2014, and perhaps slightly earlier.

## Migrating an academic website from Wordpress to Pelican

In pursuit of open science, academics should blog. As good nerds, they should opt for static website generators. Pelican is a great option, but caveats apply.

## Random number generation with C++11 and VSL

Benchmarking the speed of random number generation in C++11 with GCC and with VSL and ICC.

## Using Cython with Pypy and Numpy

Load Cython modules from Pypy while also using Numpy.

## Some recent advances in quantum machine learning

A quick overview of a handful of papers on quantum machine learning that appeared recently.

## Causal structures, Bayesian nets, and quantum systems

New characterizations of Bell inequalities in terms of causal structures are emerging: they can give rise to quantum versions of Bayesian networks.

## Alarming state of browsing academic material anonymously

Cookies, browser-fingerprinting, tracking, and blocking of Tor exit nodes are becoming standard strategies while reading abstracts and exporting citations.

## SDPA with different compilers and linear algebra libraries

GCC, ICC, PGI compilers with BLAS/LAPACK, MKL, and ACML are compared in solving an SDP with SDPA.

## More on the quantum learning of unitaries, process tomography, and classical regression

Classical regression, induction, transduction and the quantum learning of unitaries, plus making the difference explicit to process tomography.

## The Jordan-Wigner transformation in Python

Using SymPy, it is easy to calculate the Jordan-Wigner transformation in Python.

## Reproducible research, literate programming, IPython, and GitHub

IPython's notebook interface combined with git and GitHub makes a perfect tool to promote reproducible academic publications.

## Ground state of spinless fermions with DMRG

Calculating the ground state of spinless fermions on an open two-dimensional lattice with density matrix renormalization group using ALPS.

## Running Arch Linux from an SD Card on an iMac

Why would you use the spyware operating system installed on an iMac when you can run Arch Linux from an SD card?

## Full-page ad by NSA in the Communications of the ACM

ACM's relationship with NSA is far tighter than one could wish.

## Training emergent self-organizing maps on sparse data with Somoclu

Self-organizing maps are computationally expensive to train -- emergent maps are even more so. This post looks at the constraints with sparse data.

## Comparing LaTeX conversion tools

Converting LaTeX to word processor formats is the holy grail of document conversion. Perhaps we are getting closer to a viable solution.

## Quantum process tomography and machine learning

The optimal estimation of a group of unitary transforms allows for learning an unknown function: this is similar to regression in classical machine learning.

## Computer algebra system on a cell phone

Smartphones are powerful enough to run a Linux with a graphical interface: computer algebra systems are the next frontier in mobile computing.

## Make your manuscripts available online

You are legally allowed to put a PDF of your paper online. Pre-publication manuscripts can be published in an institutional repository or on arXiv.

## Analysing three months of academic spam

Unsolicited calls for papers flood our inboxes: here we analyse three months of academic spam to identify the sources.

## Understanding quantum support vector machines

Training least squares support vector machines on quantum hardware results in exponential speedup; we take a machine learning perspective at the new algorithm.

## ACM wants you to be spied on

ACM member's forwarding email address must undergo filtering by Google. Your email correspondence cannot escape the attention of NSA.

## Spyder: Getting closer to a viable Mathematica alternative

A combination of Spyder, IPython, SymPy, NumPy, and Matplotlib gets pretty close to replace Mathematica in most of my use cases.

## Merging a distributional and a semantic vector space in complex Hilbert space

Describing how to build a complex-valued random index using a term and a concept vector space.

## CuBlas matrix multiplication with C-style arrays

Getting around Fortran-style array indexing in CuBlas from C code without transponation. Bonus Thrust vector casting added.

## Second-order semidefinite relaxation of a commutative polynomial optimization problem

Second-order semidefinite relaxation of a constrained commutative polynomial optimization problem using PICOS in Python, exporting to SDPA.

## Generating noncommutative monomials with SymPy

A Python solution to generate monomials of noncommutative variables.

## Summing the entries of a matrix using a stencil with Thrust

Thrust-based summing of the elements of a submatrix at a given offset according to a stencil.

## Argmin on the rows of a matrix with Thrust

A detailed description of how to use Thrust reduce by key to calculate the argmins of the rows of a matrix