from qb_sdk import QUBEC
qubec_job = QUBEC.execute(
molecule, provider = "ibmq",
chip = "ibmq_casablanca", nshots = 10_000
)
result = qubec_job.result()
Vincent Elfving, CTO
QUBEC is the first quantum computational platform which is specifically designed for chemistry and materials science. QUBEC contains chemistry algorithms and process automation and is integrated with Schrödinger's Maestro chemical modelling interface.
QUBEC also includes our automated quantum resource estimator Q-time which helps you assess when to expect quantum advantage for your industry-relevant chemistry or materials problems.
And in this beta release QUBEC’s quantum-workflow manager takes care of chemistry data pipelining to-and-from quantum computational co-processors from IBM, IonQ and Rigetti, available through the IBM Quantum Experience and Amazon Braket platforms.
In September 2019 Qu&Co started a collaboration with Schrödinger Inc. to advance the use of quantum algorithms on complex chemical systems using quantum computing hardware. Within Qu&Co’s beta testing environment, QUBEC users can now set-up quantum computational simulations directly in Schrödinger’s Maestro user interface, which includes an intuitive 3D molecular designer, from where they can run chemistry simulations on current day quantum processors. For batch processing, a separate programmatic API allows convenient scalable access to QUBEC.
“Quantum computational software is likely to become a powerful addition to existing conventional tools, such as the ones we have developed at Schrödinger,” said Pat Lorton, CTO of Schrödinger. “The integration of quantum and conventional computations may be the key to solving many difficult problems. We are pleased to be working with Qu&Co, a leading quantum software provider, to pursue our shared goals of continued innovation in chemistry and materials science.”
Quantum mechanical simulations have become a powerful tool to accelerate chemistry and materials design, butexecuting the same computations on quantum computers so far remains at an early stage of development.
From QUBEC, proof of concept chemistry simulations with limited size basis sets can already be implemented on currentday small scale and noisy quantum processors by employing hybrid quantum-classical algorithms. QUBEC's libraries contain state-of-the-art proprietary and open-source chemistry algorithms that can optimize for chemical properties variationally, such as electronic ground- and excited states. For somewhat larger chemical systems, QUBEC offers classical simulations of quantum hardware with or without noise emulation.
Many of our clients want to know when they will be able to solve their industry sized problems on some future quantum processor. To help provide such insights, Qu&Co has developed an automated quantum resource estimator, Q-Time, that calculates the required quantum hardware specifications and estimated wall clock runtime requirements for future fault-tolerant simulations to a desired level of precision.
Q-Time has been integrated within QUBEC and also includes a small but growing library of algorithms which are in time expected to offer a quantum advantage over classical simulations in chemistry. Multiple Hamiltonian simulation approaches are included, as well as different error-correcting codes and typical operating parameters for multiple types of quantum hardware.
Our aim is that a corporate researcher can obtain good results from our solutions with only a minimal amount of training in quantum computing. We know from experience that developing quantum computing solutions and running quantum enhanced workloads is a highly specialized job and to really make it work you need deep expertise in this field. However, it is unlikely that many corporates will be able to build up such deep expertise in-house.
Therefore, at Qu&Co we have decided that we need to make the expertise of our quantum-developers accessible to our clients in a scalable and cost-efficient way. And this starts by including a high-level of automation in our platform. It should not only handle pre- and post-processing of data, but they should also include tools which automatically optimize the parameterization of the quantum algorithms and the handling of the quantum processors. For expert uses, all of these settings can be fine-tuned from within the GUI and programmatic API.
Although current day quantum processors are not yet capable of outperforming conventional computers for chemical simulations, Qu&Co is now offering a glimpse of what the future of quantum chemistry simulations will look like.
With QUBEC you can run small scale chemistry simulations on current day quantum processors. In the current beta release users have access to processors from IBM, IonQ (a.o. their 11 qubit processor) and Rigetti (a.o. the Aspen9 31 qubit processor), available through the IBM Quantum Experience and Amazon Braket platforms. Additional hardware platforms will be added in the near future. For simulations which require larger quantum processors, QUBEC offers classical simulation of quantum hardware with or without noise emulation or Q-Time: our quantum resource estimator.
from qb_sdk import QUBEC
qubec_job = QUBEC.execute(
molecule, provider = "ibmq",
chip = "ibmq_casablanca", nshots = 10_000
)
result = qubec_job.result()