The research used 81 qubits and got the correct answer 13 times out of 10,000. However these kinds of problems usually have simple verification to determine the quality of the answer. So it cut down the search space from a huge number to 10,Prada Outlet,000. Dwave has been working on a 512 qubit chip for the last 10 months. The adiabatic chip does not have predetermined speed up amounts based on more qubits and depends upon what is being solved but in general the larger number of qubits will translate into better speed and larger problems that can be solved. I interviewed the CTO of Dwave Systems (Geordie Rose back in Dec, 2011). Usually the system is not yet faster than regular supercomputers (and often not faster than a desktop computer) for the 128 qubit chip but could be for some problems with the 512 qubit chip and should definitely be faster for many problems with an anticipated 2048 qubit chip. However, the Dwave system can run other kinds of algorithms and solutions which can do things that regular computers cannot. The system was used by Google to train image recognition systems to remove outliers in an automated way.
ABSTRACT - We present the first quantum-mechanical implementation of lattice protein models using a programmable quantum device. We were able to encode and to solve the global minima solution for a small tetrapeptide and hexapeptide chain under several experimental schemes involving 5 and 8 qubits for the four-amino-acid sequence (Hydrophobic-Polar model) and 5, 27,Prada Handbag Online, 28, and 81 qubits experiments for the six-amino-acid sequence under the Miyazawa-Jernigan model for general pairwise interactions. For the experiment with 8 qubits,Prada Handbag Outlet, we simulated the dynamics of the quantum device with a Redfield equation with no adjustable parameters, obtaining excellent agreement with experiment. Since the quantum annealing algorithm not only finds the ground state but also the low-lying excited states,http://www.pradahandbagoutletonline.com, it provides information about the relevant minimum energy compact structures of protein sequences and it is useful to evaluate designability and stability such as that found in natural protein sequences, where the global minimum of free energy is well separated in energy from other misfolded states. The approach employed here can be extended to treat other problems in biophysics and statistical mechanics such as molecular recognition, protein design, and sequence alignment.
512 qubits used for protein folding solutions would be a lot faster and should be able to solve far larger problems. Dwave should also be developing 2048 qubit chips in the next few years.
"The D-Wave computer found the ground-state conformation of six-amino acid lattice protein models. This is the first time a quantum device has been used to tackle optimization problems related to the natural sciences," said Professor Aln Aspuru-Guzik from the Department of Chemistry and Chemical Biology at Harvard University.
Proteins contribute to virtually every process that occurs within a cell. The shape of a protein is closely related to its function. Understanding the shape of a protein helps researchers understand how it behaves, accelerating advances in many different areas of life sciences, including drug and vaccine design.
A cornerstone of computational biophysics, lattice protein folding models provide useful insight into the energy landscapes of real proteins. Understanding these landscapes, and how real proteins fold into the shapes that help give them their function, is an extremely difficult problem for today's computers to solve.
Dr. Alejandro Perdomo-Ortiz, the lead author of the paper, stated that: "Knowing that we can use real quantum computers to solve hard problems in biology is an exciting and important result. The techniques developed in this report can also be used to tackle other biophysical problems such as molecular recognition, protein design, and sequence alignment."