Qubit Roundup – Quantum Zoo Grows, Rigetti’s QPU Play, Google’s New Algorithm, QuEra’s EC Advance, and More

By John Russell

December 11, 2023

While the IBM Quantum Summit and the QC Ware’s Q2B Silicon Valley conference dominated last week’s news flow, there was no shortage of other quantum news emerging. Here’s brief recap of highlights.

Let’s start with work published in Science last Thursday in which two groups of researchers, one from Harvard University and another from Princeton, were able to use whole molecules as qubits. The two groups used optical tweezers to control molecules of calcium fluoride and bring about entanglement. Nature has a nice summary of the research by Davide Castelvecchi.

“Both studies used arrays of optical tweezers with one molecule trapped in each tweezer unit. Through laser techniques, they cooled the molecules to temperatures of tens of microkelvin, just millionths of a degree above absolute zero. In this state, the molecules were close to being completely still. Their rotation could be stopped, or they could be made to rotate with just one quantum of angular momentum, called ħ — the smallest rotational frequency they can possibly have. Both teams used non-rotating molecules to represent the ‘0’ state of their qubits, and rotating ones to represent the ‘1’,” wrote Castelvecchi.

So, the quantum qubit zoo, perhaps, gets another member.

There had been work years ago attempting to use full molecules as “qubits”. The recent work is big step forward. There are, of course, a growing number of qubit modalities vying for sway; the main ones include superconducting, trapped ion, neutral atoms, photonics, silicon spin, diamond-vacancy, and topological. (Figure from a pre-print paper of the Harvard work)

“For most applications, molecular quantum computers will be slower than those using other types of qubit, researchers say,” wrote Castelvecchi. “But molecules could be a natural environment in which to manipulate quantum information using ‘qutrits’, which have three possible states: −1, 0 and +1. Qutrits could offer a way to carry out quantum simulations of complex materials or the fundamental forces of physics.”

Here are links to the two papers:

It seems likely there are more qubit modalities to come.

Last August, Peter Chapman, CEO of trapped ion specialist IonQ, told HPCwire, “This is a little controversial, but I think that there’s other qubit modalities, longer term that might be better. It’s just that in the next five to 10 years, they’re not going to be where we [trapped ion qubits] are today. So, I’m happy to have the market to myself, sure, you know, for several years. But if you said to me 15 or 20 years from now, what qubit modality do you think I think you might be using? I don’t know, neutral atoms might be an interesting platform in that timeframe or something else.”

Rigetti’s New QPU Offering Hints at (Small) Merchant QPU Market

Also on Thursday, Rigetti Computing introduced 9-qubit Novera QPU for direct sale to researchers.  Rigetti reported, “The Novera QPU is available to order at rigetti.com/novera starting at $900,000 and ships within 4-6 weeks after the order is confirmed and shipping and logistics are finalized.”

This is an interesting gambit that might constitute a cautious toe-dip into a merchant QPU market. Here’s Rigetti’s brief summary of how the new QPU could be used:

“The Novera QPU implements universal, gate-based quantum computing and can be used by quantum software and algorithm experts to prototype and test: (1) hybrid quantum algorithms, (2) characterization, calibration, and error mitigation, and (3) quantum error correction (QEC) experiments.

“Additionally, organizations looking to develop components of their quantum computing stack can leverage the Novera QPU to accelerate areas such as: (1) control electronics and software, (2) QEC decoders, (3) control optimization algorithms, (3) native gate architectures, and (4) measurement and calibration, and accompanying software.”

That sounds closer to a research tool rather than a commercial component for a build-your-own QC effort. Rigetti reported the Novera QPU is manufactured in “Rigetti’s Fab-1, the industry’s first dedicated and integrated quantum device manufacturing facility.”

Here’s Rigetti’s description of the Novera QPU components:

  • A puck that contains both the 9-qubit and 5-qubit chips, interposers and a PCB to route signals to SMPM connectors at the puck periphery.
  • A tower that hangs from the MXC and connects coaxial cables between the puck and the SMA patch panel. The tower delivers cooling power from the MXC to the chips.
  • Shields that surround the tower to isolate the puck from infrared radiation and stray magnetic fields.
  • Payload brackets and a signal chain installed around the tower with mounted signal conditioning devices, including ferrite isolators, diplexers, filters, and optional quantum-limited amplifiers.

You’ll need your own dilution refrigerator. Novera is built using the same architecture as Rigetti’s fourth-generation Ankaa-class architecture featuring tunable couplers and a square lattice for denser connectivity and fast 2-qubit operations. Notably, a number of the QPUs have been commissioned by national labs.

Google Quantum Algorithm for Classical Mechanics Achieves Exponential Speedup

There is a fever pitch race to develop quantum algorithms – a la Peter Shor’s algorithm –that are able to show provable speedups over classical algorithms. Google reported one such advance in a blog last week, and has a paper (Exponential Quantum Speedup in Simulating Coupled Classical Oscillators) on the work.

Here’s the abstract:

“We present a quantum algorithm for simulating the classical dynamics of 2n coupled oscillators (e.g., 2n masses coupled by springs). Our approach leverages a mapping between the Schrödinger equation and Newton’s equation for harmonic potentials such that the amplitudes of the evolved quantum state encode the momenta and displacements of the classical oscillators. When individual masses and spring constants can be efficiently queried, and when the initial state can be efficiently prepared, the complexity of our quantum algorithm is polynomial in n, almost linear in the evolution time, and sublinear in the sparsity.

“As an example application, we apply our quantum algorithm to efficiently estimate the kinetic energy of an oscillator at any time. We show that any classical algorithm solving this same problem is inefficient and must make 2Ω(n) queries to the oracle, and when the oracles are instantiated by efficient quantum circuits, the problem is bounded-error quantum polynomial time complete. Thus, our approach solves a potentially practical application with an exponential speedup over classical computers. Finally, we show that under similar conditions our approach can efficiently simulate more general classical harmonic systems with 2n modes.”

Looking ahead the blog authors write, “We showed that the dynamics of any classical system of harmonic oscillators can indeed be equivalently understood as the dynamics of a corresponding quantum system of exponentially smaller size. In this way we can simulate Grover and Sengupta’s system of pendulums on a quantum computer of log(N) qubits, and find a different quantum algorithm that can find the correct element in time ~√(N). The analogy we discovered between classical and quantum systems can be used to construct other quantum algorithms offering exponential speedups, where the reason for the speedups is now more evident from the way that classical waves propagate.”

Harvard Executes EC Algorithm using 48 Logical Qubits

Effective error correction/mitigation has become, perhaps, the central challenge in quantum computing. Neutral atom-based QC specialist, QuEra, reported last week that work led by Harvard University in collaboration with QuEra, MIT, and NIST/UMD, successfully executed large-scale algorithms on an error-corrected quantum computer with 48 logical qubits and hundreds of entangling logical operations.

The researchers cite these highlights:

  • Creation and entanglement of the largest logical qubits to date, demonstrating a code distance of 7, enabling the detection and correction of arbitrary errors occurring during the entangling logical gate operations. Larger code distances imply higher resistance to quantum errors. The research showed for the first time that increasing the code distance indeed reduces the error rate in logical operations.
  • Realization of 48 small logical qubits that were used to execute complex algorithms, surpassing the performance of the same algorithms when executed with physical qubits.
  • Construction of 40 medium-sized error-correcting codes by controlling 280 physical qubits.

The work was reported in Nature last week (Logical quantum processor based on reconfigurable atom arrays). Here’s the abstract:

“[W]e report the realization of a programmable quantum processor based on encoded logical qubits operating with up to 280 physical qubits. Utilizing logical-level control and a zoned architecture in reconfigurable neutral atom arrays, our system combines high two-qubit gate fidelities, arbitrary connectivity, as well as fully programmable single-qubit rotations and mid-circuit readout. Operating this logical processor with various types of encodings, we demonstrate improvement of a two-qubit logic gate by scaling surface code distance from d = 3 to d = 7, preparation of color code qubits with break-even fidelities5, fault-tolerant creation of logical GHZ states and feedforward entanglement teleportation, as well as operation of 40 color code qubits.

“Finally, using three-dimensional code blocks, we realize computationally complex sampling circuits with up to 48 logical qubits entangled with hypercube connectivity with 228 logical two-qubit gates and 48 logical CCZ gates. We find that this logical encoding substantially improves algorithmic performance with error detection, outperforming physical qubit fidelities at both cross-entropy benchmarking and quantum simulations of fast scrambling.”

The researchers say these results herald the “advent of early error-corrected quantum computation and chart a path toward large-scale logical processors.” That’s a big goal.

Stay tuned.

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