I attended the Q2B (Quantum for Business) Conference at the Computer History Museum in Mountain View, California organized QCWare last week. This was the second year for this conference and like many other things quantum, we saw an increased level of participation and excitement.  This year there were about 375 attendees from 17 countries representing a broad cross-section of quantum players in industry, government, universities, and laboratories. This represents a 50% increase from the 250 people who attended last year.

I’ll try to document some of the things I learned in thisarticle, but I will caution that it may not be fully complete.  This year’s conference had parallel sessions and I am sure I missed some of interesting discussions in the sessions that were going on in other rooms.  Here is a brief summary of some of the things I heard.

Hardware and Software Platforms

IBM described some of the new capabilities in their Qiskit software.  In particular, they have released open-sourced software called OpenPulse that would allow auser to control the qubits gates at the lowest level by controlling the microwave pulses.  They also described a new Terra transpiler that will compile and optimize quantum gate configurations. And finally, they also described a new simulator called Aer that has high performance and good capabilities to incorporate noise models in a quantum simulation.

Google described their Cirq software platform.  A key goal for this platform was to specifically design it for NISQ level quantum computers.  As such, a major design philosophy was to expose the details of the hardware to the programmers rather than trying to hide it.

Microsoft discussed their Quantum Development Kit (QDK) and announced a software partners program.  They mentioned that their QDK has been downloaded over 85,000 times.  Microsoft did not mention anything new abouttheir topological qubit development status. However, they did indicate excitement over quantum inspired algorithms and felt their quantum activities had a side benefit because it helped accelerate advances in this area.

Rigetti discussed some performance improvements with their new architecture.  They indicated they were seeing roughly a 35X improvement in runtime versus their previous generation on some hybrid classical/quantum algorithms due to improvements in colocation of the classical and quantum computers, parameter compilation, and active qubit reset.

D-Wave announced a new software feature called D-Wave Hybrid.  This feature allows users tomore easily develop classical/quantum hybrid algorithms with their quantum annealer.  They also described some ofthe 100 different applications that end users have developed on their machines.  In particular, they mentioned 3 or 4 of those applications may be getting near to production use.

IonQ described some testing results of their ion trap quantum computer prototype.  They have built hardware and have tested versions with 11 fully connected qubits.  They have tested this version with two-qubit gates and have achieved two-qubit gate fidelities between 96% and 99.3% which is significantly better than has been reported for the superconducting implementations.  They also have seen a 79 qubit implementation and were able to show single qubit gates on these. IonQ announced that they will be initiating quantum cloud services to select beta users in 2019 which will be more upgraded versions of these chips.


The U.S. Air Force Research Laboratory described some of the applications they think quantum technology may be applicable.  The nearest term application would be quantum timing.  The accuracy of GPS positioning is impacted by clock drift and using quantum technology to achieve moreaccurate clocks would improve the accuracy. Another application would be in quantum sensing.  Quantum technology could potentially providemore accurate sensors for acceleration, rotation, gravitation, and magnetic fields. Improvements in quantum sensors could potentially allow development of inertial navigation systems that would be accurate for hours, even when the GPS system is unavailable.

Other end users describing their interest in quantum applications included BMW, Airbus, and the Beyond Core group at BBVA (Banco Bilbao Vizcaya Argentaria).  They discussed potential applications in finance, materials design, and flight physics as among the areas where quantum computing could be helpful.

Airbus announced an Airbus Quantum Computing Challenge to help find quantum solutions for five specific problems they see in the aerospace industry.  These challenges include aircraft climb optimization, computational fluid dynamics, quantum neural networks for solving partial differential equations, wingbox design optimization, and aircraft loading optimization.  The challenge is open to all quantum computing experts and enthusiasts (post-graduate students, PhDs, academics, researchers, start-ups, or professionals in the field), either as an individual or as a team. Participants will be provided further technical details to the problem statements following the launch in early 2019.  (Our note to Airbus: We recommend you consider providing some more concrete monetary incentives to encourage individuals to participate in your challenge. There will be a lot of competition for the attention of quantum researchers to work on many different quantum problems and you should make it worth their while to spend time working on your problems.)

Academic Research

Professor John Preskill from Caltech provided a good overview of quantum applications including quantum computation, quantum simulation, quantum networks, and quantum sensing.

Professor Scott Aaronson from the University of Texas at Austin presented some of his work to use a NISQ level quantum computer to produce a certifiable random number.  An interesting aspect of this problem is that it could potentially produce the first real world result of a problem where a quantum computer provides a quantum advantage.

Professor Eddie Farhi from MIT/Google discussed a very recently published paper that describes an improvement to QAOA (Quantum Approximate Optimization Algorithm).  The improvements could potentially reduce or eliminate the use of the outer loop optimization in the algorithm and allow one to find good solutions with fewer calls to the quantum computer. This could potentially be important because QAOA may be one of the very first algorithms that can help show a distinct quantum advantage over a classical computer and anything that can make it better could accelerate when this milestone is achieved.


Like all such conferences there were a lot of hallway conversations and a great opportunity to network.  There were also some interesting vendor exhibits.  QCWare will be posting the presentations and videos of the sessions on the Q2B web site shortly and we invite readers to review them when they are available to see more details.