Welcome to the Quantum Realm. 

Enjoy today’s breakdown of news, research, events & jobs within quantum.

I love to hear from you! Send me a message at [email protected] for musings, for fun, or for insight if it so appeals to you.

IN TODAY’S ISSUE:

• Quantinuum is once again on the quantum leaderboard — 99.9% 2-qubit gate fidelity and 2²⁰ quantum volume

• New qiskit-torch-module for quick QNN prototyping

• A tensor-network maximum-likelihood decoding algorithm for Pauli noise model of random Clifford encoding

• Plus, a visually beautiful explanation of quantum measurement from SandboxAQ

• AND check out the poll in the “Featured Jobs” section so I can continue molding this newsletter to your needs

TOP NEWS & RESEARCH

NEWS

9s ACROSS THE BOARD FOR QUANTINUUM

The Brief Byte: Quantinuum has achieved a new benchmark marking an historic moment in the field — 99.9% 2-qubit gate fidelity.

Highlights:

1. Quantum error correction effectiveness hinges on achieving high fidelity in physical qubit operations, specifically a 99.9% 2-qubit gate fidelity. Quantinuum has become the first to achieve "three 9's" in a commercially-available quantum computer, setting a new industry standard.

2. Quantinuum announces achieving a quantum volume of 2²⁰ — four years ago Quantinuum committed to a 10x annual performance improvement of its H-Series quantum computers based on quantum volume and this achievement validates that goal.

3. These benchmarks were achieved inherently without error mitigation and offer lower overhead for error correction.

RESEARCH

NEW QISKIT-TORCH-MODULE SPEEDS UP VQA TRAINING FOR QNNS AND PROVIDES QUICK PROTOTYPING

The Brief Byte: Researchers have developed a qiskit-torch-module that significantly boosts runtime performance on quantum computer simulation software while also providing advanced tools for quantum neural networks.

Highlights:

1. Recent studies suggest that frameworks like PennyLane and TensorFlow Quantum may outperform Qiskit and qiskit-machine-learning in VQA training, but switching between them is difficult due to different syntax and programming styles.

2. The proposed qiskit-torch-module addresses the inefficiencies in qiskit-machine-learning by boosting training speeds for VQAs which cuts runtime overhead by about two orders of magnitude.

3. This new framework both enhances the integration of QNNs with PyTorch and is optimized for researchers with limited resources, allowing quick prototyping.

RESEARCH

EFFICIENT DECODING WITH 1D CLIFFORD ENCODING CIRCUITS

The Brief Byte: The development of a tensor-network maximum-likelihood decoding algorithm allows for random Clifford encoding circuits embedded in one spatial dimension with logarithmic depth to maintain a nonzero encoding rate for correcting errors under conventional Pauli noise.

Highlights:

1. This study focuses on 1D low-depth Clifford encoding circuits and demonstrates that they can achieve a rate close to the hashing bound for depolarizing noise with stochastic Pauli noise being efficiently decoded using tensor network methods in polynomial time.

2. The relationship between code distance and error correction capacity for erasure and Pauli errors indicates that code distance alone doesn't determine the overall performance of the code​.

3. The block model provides a method to assess Pauli noise thresholds for random codes, and this paper identifies scenarios where random circuit encoding offers advantages over the block model​.

MORE BRIEF BYTES

• Rigetti UK Limited and Oxford Instruments NanoScience completed a three-year project to establish one of the UK's first quantum computers

• Scott Best on the race against physics for post-quantum cryptography

• MIT team proposes new conceptual model for quantum tech — a quantum control machine

• IonQ and Oak Ridge National Laboratory join forces to see how quantum tech can secure the national power grid

• Qunnect developed an automated system that distributes high-fidelity entangled photons over a 34 km fiber network in New York City

ENTANGLED INSIGHTS

RECOMMENDED RESOURCE

SANDBOXAQ EXPLAINS QUANTUM MEASUREMENT BEAUTIFULLY

EVENTS

• Wednesday April 17 | Making Photons See Each Other featuring Professor Puneet Anantha Murthy of Quantum Center ETH Zurich

• Thursday, April 18 | C2QA Quantum Thursdays w/ Director of Quantum Systems Accelerator Bert de Jong

• Friday April 19 | Scalability of Quantum Error Mitigation Techniques from IBM Qiskit

• Tuesday, April 23 | Introduction to Quantum Application Programming from D-Wave

• Now - May 31 | Register for Google/X-Prize Quantum Challenge

FEATURED JOBS

• Deloitte Quantum Readiness Strategy Senior Consultant | PA, NC, VA, FL, TN, ID, AZ, IA, MI, CA, OH, KY, MD, WY, AL, LA, NJ, CT, MN $84.4K - $148K

• Maybell Quantum Senior Software Engineer | Denver, CO $110K - $155K

• Maybell Quantum Hardware Project Manager | Denver, CO (Hybrid)

• Maybell Quantum RF Test and Measurement Engineer | Denver, CO (Hybrid)

• Maybell Quantum RF Scientist | Denver, CO (Hybrid) $100K - $150K

• Google Senior Fabrication Hardware Engineer, Quantum AI | Goleta, CA $142K -$211K

• Booz Allen Hamilton Quantum Scientist | Annapolis Junction, MD (Hybrid) $51.6K - $105K

UNTIL TOMORROW.

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