Dirac-1
Overview
Dirac-1 is a "qubit" entropy quantum computer. It minimizes quadratic Hamiltonian operators over a n-binary domain, where n is the variable size. It uses the same principles as all other EQC devices to perform computations.
Our Binary Programming model
Our binary programming model, available on the Dirac-1 quantum computer, is
where the z’s are binary variables which can have the values 0 or 1 and {h, J} are constants. Analogous to the QUBO and Ising model, the programmer’s job is to set the h values (linear terms) and J values (quadratic terms) in order to solve the problem, which has been expressed in binary decision variables.
Data format
To upload a Hamiltonian operator, we encode it in a sparse matrix format as shown below. We use Numpy array notation. The order-2 Hamiltonian supported by Dirac-2 has two parts. The first part is a single-dimension array for the linear terms. The second part is a two-dimension array for the quadratic terms. They will be called `h` and `J`, respectively.
1
h = np.array([-1, -1, -1])
1
J = np.array([[0, -1.5, 0.5], [-1.5, 0, 0], [0.5, 0, 0]])
We put these together into one matrix sized
NxN+1
. 1
H = np.hstack([h, J])
then the JSON will take the following list of dictionary sparse matrix format:
{(i,j): value}
123456789101112131415161718192021222324252627282930313233343536373839404142
hamiltonian_data = {
"data": [
{
"i": 0,
"j": 0,
"val": -1
},
{
"i": 1,
"j": 0,
"val": -1
},
{
"i": 2,
"j": 0,
"val": -1,
},
{
"i": 0,
"j": 2,
"val": -1.5
},
{
"i": 0,
"j": 3,
"val": 0.5
},
{
"i": 1,
"j": 1,
"val": -1.5
},
{
"i": 2,
"j": 1,
"val": 0.5
}
],
"file_name": "simple_hamiltonian.json", # can be any short string
"num_variables": 3, # number of rows
"file_type": "hamiltonian" # defines the data type as hamiltonian
}
Uploading
To upload the matrix encoded above in
hamiltonian_data
, we use the the qci_client
imported previously. The following line 1
response_json = qci.upload_file(qubo_data)
The response contains a
file_id
for the uploaded file. This id is provided when a job is run, along a few other parameters (see #Running). Note: the same file_id
can be used multiple times to run a problem repeatedly. This enables an "upload once, run many times" scheme, which is especially useful for job types in which parameter searches may be involved.