Zapata Computing is the leader in applying quantum algorithms to the best quantum hardware in order to create improved solutions for the most important problems of the largest companies in the world. Nextbigfuture interviewed Zapata Computing CEO Chris Savoie on how they are helping large companies to find how to use Quantum Computers to make Quantum Solutions that will capture real performance gains.
* Zapata has a workflow system (called Orquestra) that accelerates the development of real solutions using quantum computers.
* Zapata has a strategic partnership with Honeywell and Honeywell might become the leader with quantum when they release a trapped ion computer with a quantum volume of 64. Honeywell claims they could reach quantum volume of 6.4 million by 2026.
* Zapata is making progress with benchmarks that can approximate when particular quantum hardware might provide real gains on a real world problem.
Zapata Computing is providing companies with Early Access Program for Orquestra Training. Companies can work with Zapata’s World Class team for “Proof of Technology” projects and receive ongoing support. The invitation-only Orquestra Workshops for hands-on training had 23 users trained in the third week in Apri and the last week in April had over 50 users.
Zapata Computing has worked with many enterprise clients to determine how to apply quantum computing enhancement of their real problems using real company datasets.
They have applied the real-world, real-data experience to create a workflow system to accelerate the processes for creating commercial quantum computing solutions.
Zapata Computing Is Getting Better Answers About When Would A Quantum Computing Be Useful for a Real Problem
Zapata has created a test drive for quantum chemistry. The test will let companies know if they should expect performance gains using a particular quantum computer for their particular quantum chemistry problem. The test is general enough to be applied to any quantum computer, but our team has worked out the explicit details for the test on Google’s Sycamore chip.
Zapata has created other industry and problem-specific benchmarks that help answer the question of how useful might particular quantum hardware be for specific classes of problems.
They calculated that the fermionic length of the Google Sycamore chip with a maximum of 33 layers is L∗ = 6.
Once a one-dimensional FHM chain can be converged on a quantum processor, we propose using adiabatic-assisted VQE to prepare the ground state of more complicated systems like the two-dimensional FHM. It would then be possible to try optimizing a 3×3×3 instance of the FHM by taking advantage of the full size of the Sycamore chip. This would be a step on the path to concrete applications of quantum computing technologies.
It should be possible to design hardware efficient fermionic ansatzes for other quantum computing architectures such as ion traps. In principle, this ansatz could be realized using native gates, such as the MølmerSørensen gate, and a trap architecture that allows for the
execution of a number of simultaneous two-qubit gates that scales with the number of qubits.
Honeywell Strategic Partnership
In 2017, Zapata Computing spun out of Harvard to develop quantum software and algorithms for business and they have received over $26 million in funding. The $26 million does not include an undisclosed funding by Honeywell Ventures.
Honeywell plans to release an extremely powerful quantum computer with unique and highly scalable architecture. It will be a major technical breakthrough in accelerating quantum capability that will change the dynamics in the quantum computing industry. There have been reports a trapped ion system from Honeywell will have a quantum volume of 64. The best system from IBM has a quantum volume of 32. Honeywell’s goal to increase the quantum volume by an order of magnitude each year, for the next five years.
Zapata Computer Orquestra Accelerates Making Real-World Solutions Using Quantum Computers
Zapata Computing’s platform for quantum-enabled workflows, Orquestra
Zapata Computing Has Elite World Class Quantum Scientists
Professor Alan Aspuru-Guzik is a world leader in quantum computing algorithms. He authored the first quantum algorithm for chemistry and the first algorithm for near-term quantum computing. The algorithm is the foundation of the Noisy Intermediate-Scale Quantum (NISQ) era of quantum computers. Alan has trained the top researchers in the field of NISQ computing and many of top NISQ scientists are with Zapata.
Zapata’s scientists helped create the field of near-term quantum algorithms including the invention of VQE, the progenitor of variational quantum algorithms. They use this expertise to solve customer problems.
In 2019, Zapata worked with IBM to develop a new way to factor large numbers, using it on the largest number that has been factored with a quantum computer so far. The team found that 1,099,551,473,989 is equal to 1,048,589 multiplied by 1,048,601.
Zapata’s focus right now is on applications where quantum computing can offer some advantages over traditional supercomputing, particularly in three key areas: simulation of chemical reactions, machine learning and optimization problems, which are of particular interest in areas like logistics and planning.
Zapata’s product is Orquestra
Zapata is developing powerful, hardware-agnostic solutions for a wide range of industries including chemistry, finance, logistics, pharmaceuticals, engineering, and materials.
Abstract -An application benchmark for fermionic quantum simulations
It is expected that the simulation of correlated fermions in chemistry and material science will be one of the first practical applications of quantum processors. Given the rapid evolution of quantum hardware, it is increasingly important to develop robust benchmarking techniques to gauge the capacity of quantum hardware specifically for the purpose of fermionic simulation. Here we propose using the one-dimensional Fermi-Hubbard model as an application benchmark for variational quantum simulations on near-term quantum devices. Since the one-dimensional Hubbard model is both strongly correlated and exactly solvable with the Bethe ansatz, it provides a reference ground state energy that a given device with limited coherence will be able to approximate up to a maximal size. The length of the largest chain that can be simulated provides an effective fermionic length. We use variational quantum eigensolver to approximate the ground state energy values of FermiHubbard instances and show how the fermionic length benchmark can be used in practice to assess the performance of bounded-depth devices in a scalable fashion.