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Posted by Kate Weber and Shannon Leon, Google Research, Quantum AI Team

Today the 2024 March Meeting of the American Physical Society (APS) kicks off in Minneapolis, MN. A premier conference on topics ranging across physics and related fields, APS 2024 brings together researchers, students, and industry professionals to share their discoveries and build partnerships with the goal of realizing fundamental advances in physics-related sciences and technology.

This year, Google has a strong presence at APS with a booth hosted by the Google Quantum AI team, 50+ talks throughout the conference, and participation in conference organizing activities, special sessions and events. Attending APS 2024 in person? Come visit Googles Quantum AI booth to learn more about the exciting work were doing to solve some of the fields most interesting challenges.

You can learn more about the latest cutting edge work we are presenting at the conference along with our schedule of booth events below (Googlers listed in bold).

Session Chairs include: Aaron Szasz

This schedule is subject to change. Please visit the Google Quantum AI booth for more information.

Crumble: A prototype interactive tool for visualizing QEC circuits Presenter: Matt McEwen Tue, Mar 5 | 11:00 AM CST

Qualtran: An open-source library for effective resource estimation of fault tolerant algorithms Presenter: Tanuj Khattar Tue, Mar 5 | 2:30 PM CST

Qualtran: An open-source library for effective resource estimation of fault tolerant algorithms Presenter: Tanuj Khattar Thu, Mar 7 | 11:00 AM CST

$5M XPRIZE / Google Quantum AI competition to accelerate quantum applications Q&A Presenter: Ryan Babbush Thu, Mar 7 | 11:00 AM CST

Certifying highly-entangled states from few single-qubit measurements Presenter: Hsin-Yuan Huang Author: Hsin-Yuan Huang Session A45: New Frontiers in Machine Learning Quantum Physics

Toward high-fidelity analog quantum simulation with superconducting qubits Presenter: Trond Andersen Authors: Trond I Andersen, Xiao Mi, Amir H Karamlou, Nikita Astrakhantsev, Andrey Klots, Julia Berndtsson, Andre Petukhov, Dmitry Abanin, Lev B Ioffe, Yu Chen, Vadim Smelyanskiy, Pedram Roushan Session A51: Applications on Noisy Quantum Hardware I

Measuring circuit errors in context for surface code circuits Presenter: Dripto M Debroy Authors: Dripto M Debroy, Jonathan A Gross, lie Genois, Zhang Jiang Session B50: Characterizing Noise with QCVV Techniques

Quantum computation of stopping power for inertial fusion target design I: Physics overview and the limits of classical algorithms Presenter: Andrew D. Baczewski Authors: Nicholas C. Rubin, Dominic W. Berry, Alina Kononov, Fionn D. Malone, Tanuj Khattar, Alec White, Joonho Lee, Hartmut Neven, Ryan Babbush, Andrew D. Baczewski Session B51: Heterogeneous Design for Quantum Applications Link to Paper

Quantum computation of stopping power for inertial fusion target design II: Physics overview and the limits of classical algorithms Presenter: Nicholas C. Rubin Authors: Nicholas C. Rubin, Dominic W. Berry, Alina Kononov, Fionn D. Malone, Tanuj Khattar, Alec White, Joonho Lee, Hartmut Neven, Ryan Babbush, Andrew D. Baczewski Session B51: Heterogeneous Design for Quantum Applications Link to Paper

Calibrating Superconducting Qubits: From NISQ to Fault Tolerance Presenter: Sabrina S Hong Author: Sabrina S Hong Session B56: From NISQ to Fault Tolerance

Measurement and feedforward induced entanglement negativity transition Presenter: Ramis Movassagh Authors: Alireza Seif, Yu-Xin Wang, Ramis Movassagh, Aashish A. Clerk Session B31: Measurement Induced Criticality in Many-Body Systems Link to Paper

Effective quantum volume, fidelity and computational cost of noisy quantum processing experiments Presenter: Salvatore Mandra Authors: Kostyantyn Kechedzhi, Sergei V Isakov, Salvatore Mandra, Benjamin Villalonga, X. Mi, Sergio Boixo, Vadim Smelyanskiy Session B52: Quantum Algorithms and Complexity Link to Paper

Accurate thermodynamic tables for solids using Machine Learning Interaction Potentials and Covariance of Atomic Positions Presenter: Mgcini K Phuthi Authors: Mgcini K Phuthi, Yang Huang, Michael Widom, Ekin D Cubuk, Venkat Viswanathan Session D60: Machine Learning of Molecules and Materials: Chemical Space and Dynamics

IN-Situ Pulse Envelope Characterization Technique (INSPECT) Presenter: Zhang Jiang Authors: Zhang Jiang, Jonathan A Gross, lie Genois Session F50: Advanced Randomized Benchmarking and Gate Calibration

Characterizing two-qubit gates with dynamical decoupling Presenter: Jonathan A Gross Authors: Jonathan A Gross, Zhang Jiang, lie Genois, Dripto M Debroy, Ze-Pei Cian*, Wojciech Mruczkiewicz Session F50: Advanced Randomized Benchmarking and Gate Calibration

Statistical physics of regression with quadratic models Presenter: Blake Bordelon Authors: Blake Bordelon, Cengiz Pehlevan, Yasaman Bahri Session EE01: V: Statistical and Nonlinear Physics II

Improved state preparation for first-quantized simulation of electronic structure Presenter: William J Huggins Authors: William J Huggins, Oskar Leimkuhler, Torin F Stetina, Birgitta Whaley Session G51: Hamiltonian Simulation

Controlling large superconducting quantum processors Presenter: Paul V. Klimov Authors: Paul V. Klimov, Andreas Bengtsson, Chris Quintana, Alexandre Bourassa, Sabrina Hong, Andrew Dunsworth, Kevin J. Satzinger, William P. Livingston, Volodymyr Sivak, Murphy Y. Niu, Trond I. Andersen, Yaxing Zhang, Desmond Chik, Zijun Chen, Charles Neill, Catherine Erickson, Alejandro Grajales Dau, Anthony Megrant, Pedram Roushan, Alexander N. Korotkov, Julian Kelly, Vadim Smelyanskiy, Yu Chen, Hartmut Neven Session G30: Commercial Applications of Quantum Computing Link to Paper

Gaussian boson sampling: Determining quantum advantage Presenter: Peter D Drummond Authors: Peter D Drummond, Alex Dellios, Ned Goodman, Margaret D Reid, Ben Villalonga Session G50: Quantum Characterization, Verification, and Validation II

Attention to complexity III: learning the complexity of random quantum circuit states Presenter: Hyejin Kim Authors: Hyejin Kim, Yiqing Zhou, Yichen Xu, Chao Wan, Jin Zhou, Yuri D Lensky, Jesse Hoke, Pedram Roushan, Kilian Q Weinberger, Eun-Ah Kim Session G50: Quantum Characterization, Verification, and Validation II

Balanced coupling in superconducting circuits Presenter: Daniel T Sank Authors: Daniel T Sank, Sergei V Isakov, Mostafa Khezri, Juan Atalaya Session K48: Strongly Driven Superconducting Systems

Resource estimation of Fault Tolerant algorithms using Q Presenter: Tanuj Khattar Author: Tanuj Khattar, Matthew Harrigan, Fionn D. Malone, Nour Yosri, Nicholas C. Rubin Session K49: Algorithms and Implementations on Near-Term Quantum Computers

Discovering novel quantum dynamics with superconducting qubits Presenter: Pedram Roushan Author: Pedram Roushan Session M24: Analog Quantum Simulations Across Platforms

Deciphering Tumor Heterogeneity in Triple-Negative Breast Cancer: The Crucial Role of Dynamic Cell-Cell and Cell-Matrix Interactions Presenter: Susan Leggett Authors: Susan Leggett, Ian Wong, Celeste Nelson, Molly Brennan, Mohak Patel, Christian Franck, Sophia Martinez, Joe Tien, Lena Gamboa, Thomas Valentin, Amanda Khoo, Evelyn K Williams Session M27: Mechanics of Cells and Tissues II

Toward implementation of protected charge-parity qubits Presenter: Abigail Shearrow Authors: Abigail Shearrow, Matthew Snyder, Bradley G Cole, Kenneth R Dodge, Yebin Liu, Andrey Klots, Lev B Ioffe, Britton L Plourde, Robert McDermott Session N48: Unconventional Superconducting Qubits

Electronic capacitance in tunnel junctions for protected charge-parity qubits Presenter: Bradley G Cole Authors: Bradley G Cole, Kenneth R Dodge, Yebin Liu, Abigail Shearrow, Matthew Snyder, Andrey Klots, Lev B Ioffe, Robert McDermott, B.L.T. Plourde Session N48: Unconventional Superconducting Qubits

Overcoming leakage in quantum error correction Presenter: Kevin C. Miao Authors: Kevin C. Miao, Matt McEwen, Juan Atalaya, Dvir Kafri, Leonid P. Pryadko, Andreas Bengtsson, Alex Opremcak, Kevin J. Satzinger, Zijun Chen, Paul V. Klimov, Chris Quintana, Rajeev Acharya, Kyle Anderson, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Joseph C. Bardin, Alexandre Bourassa, Jenna Bovaird, Leon Brill, Bob B. Buckley, David A. Buell, Tim Burger, Brian Burkett, Nicholas Bushnell, Juan Campero, Ben Chiaro, Roberto Collins, Paul Conner, Alexander L. Crook, Ben Curtin, Dripto M. Debroy, Sean Demura, Andrew Dunsworth, Catherine Erickson, Reza Fatemi, Vinicius S. Ferreira, Leslie Flores Burgos, Ebrahim Forati, Austin G. Fowler, Brooks Foxen, Gonzalo Garcia, William Giang, Craig Gidney, Marissa Giustina, Raja Gosula, Alejandro Grajales Dau, Jonathan A. Gross, Michael C. Hamilton, Sean D. Harrington, Paula Heu, Jeremy Hilton, Markus R. Hoffmann, Sabrina Hong, Trent Huang, Ashley Huff, Justin Iveland, Evan Jeffrey, Zhang Jiang, Cody Jones, Julian Kelly, Seon Kim, Fedor Kostritsa, John Mark Kreikebaum, David Landhuis, Pavel Laptev, Lily Laws, Kenny Lee, Brian J. Lester, Alexander T. Lill, Wayne Liu, Aditya Locharla, Erik Lucero, Steven Martin, Anthony Megrant, Xiao Mi, Shirin Montazeri, Alexis Morvan, Ofer Naaman, Matthew Neeley, Charles Neill, Ani Nersisyan, Michael Newman, Jiun How Ng, Anthony Nguyen, Murray Nguyen, Rebecca Potter, Charles Rocque, Pedram Roushan, Kannan Sankaragomathi, Christopher Schuster, Michael J. Shearn, Aaron Shorter, Noah Shutty, Vladimir Shvarts, Jindra Skruzny, W. Clarke Smith, George Sterling, Marco Szalay, Douglas Thor, Alfredo Torres, Theodore White, Bryan W. K. Woo, Z. Jamie Yao, Ping Yeh, Juhwan Yoo, Grayson Young, Adam Zalcman, Ningfeng Zhu, Nicholas Zobrist, Hartmut Neven, Vadim Smelyanskiy, Andre Petukhov, Alexander N. Korotkov, Daniel Sank, Yu Chen Session N51: Quantum Error Correction Code Performance and Implementation I Link to Paper

Modeling the performance of the surface code with non-uniform error distribution: Part 1 Presenter: Yuri D Lensky Authors: Yuri D Lensky, Volodymyr Sivak, Kostyantyn Kechedzhi, Igor Aleiner Session N51: Quantum Error Correction Code Performance and Implementation I

Modeling the performance of the surface code with non-uniform error distribution: Part 2 Presenter: Volodymyr Sivak Authors: Volodymyr Sivak, Michael Newman, Cody Jones, Henry Schurkus, Dvir Kafri, Yuri D Lensky, Paul Klimov, Kostyantyn Kechedzhi, Vadim Smelyanskiy Session N51: Quantum Error Correction Code Performance and Implementation I

Highly optimized tensor network contractions for the simulation of classically challenging quantum computations Presenter: Benjamin Villalonga Author: Benjamin Villalonga Session Q51: Co-evolution of Quantum Classical Algorithms

Teaching modern quantum computing concepts using hands-on open-source software at all levels Presenter: Abraham Asfaw Author: Abraham Asfaw Session Q61: Teaching Quantum Information at All Levels II

New circuits and an open source decoder for the color code Presenter: Craig Gidney Authors: Craig Gidney, Cody Jones Session S51: Quantum Error Correction Code Performance and Implementation II Link to Paper

Performing Hartree-Fock many-body physics calculations with large language models Presenter: Eun-Ah Kim Authors: Eun-Ah Kim, Haining Pan, Nayantara Mudur, William Taranto, Subhashini Venugopalan, Yasaman Bahri, Michael P Brenner Session S18: Data Science, AI and Machine Learning in Physics I

New methods for reducing resource overhead in the surface code Presenter: Michael Newman Authors: Craig M Gidney, Michael Newman, Peter Brooks, Cody Jones Session S51: Quantum Error Correction Code Performance and Implementation II Link to Paper

Challenges and opportunities for applying quantum computers to drug design Presenter: Raffaele Santagati Authors: Raffaele Santagati, Alan Aspuru-Guzik, Ryan Babbush, Matthias Degroote, Leticia Gonzalez, Elica Kyoseva, Nikolaj Moll, Markus Oppel, Robert M. Parrish, Nicholas C. Rubin, Michael Streif, Christofer S. Tautermann, Horst Weiss, Nathan Wiebe, Clemens Utschig-Utschig Session S49: Advances in Quantum Algorithms for Near-Term Applications Link to Paper

Dispatches from Google's hunt for super-quadratic quantum advantage in new applications Presenter: Ryan Babbush Author: Ryan Babbush Session T45: Recent Advances in Quantum Algorithms

Qubit as a reflectometer Presenter: Yaxing Zhang Authors: Yaxing Zhang, Benjamin Chiaro Session T48: Superconducting Fabrication, Packaging, & Validation

Random-matrix theory of measurement-induced phase transitions in nonlocal Floquet quantum circuits Presenter: Aleksei Khindanov Authors: Aleksei Khindanov, Lara Faoro, Lev Ioffe, Igor Aleiner Session W14: Measurement-Induced Phase Transitions

Continuum limit of finite density many-body ground states with MERA Presenter: Subhayan Sahu Authors: Subhayan Sahu, Guifr Vidal Session W58: Extreme-Scale Computational Science Discovery in Fluid Dynamics and Related Disciplines II

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain Presenter: Eliott Rosenberg Authors: Eliott Rosenberg, Trond Andersen, Rhine Samajdar, Andre Petukhov, Jesse Hoke*, Dmitry Abanin, Andreas Bengtsson, Ilya Drozdov, Catherine Erickson, Paul Klimov, Xiao Mi, Alexis Morvan, Matthew Neeley, Charles Neill, Rajeev Acharya, Richard Allen, Kyle Anderson, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Juan Atalaya, Joseph Bardin, A. Bilmes, Gina Bortoli, Alexandre Bourassa, Jenna Bovaird, Leon Brill, Michael Broughton, Bob B. Buckley, David Buell, Tim Burger, Brian Burkett, Nicholas Bushnell, Juan Campero, Hung-Shen Chang, Zijun Chen, Benjamin Chiaro, Desmond Chik, Josh Cogan, Roberto Collins, Paul Conner, William Courtney, Alexander Crook, Ben Curtin, Dripto Debroy, Alexander Del Toro Barba, Sean Demura, Agustin Di Paolo, Andrew Dunsworth, Clint Earle, E. Farhi, Reza Fatemi, Vinicius Ferreira, Leslie Flores, Ebrahim Forati, Austin Fowler, Brooks Foxen, Gonzalo Garcia, lie Genois, William Giang, Craig Gidney, Dar Gilboa, Marissa Giustina, Raja Gosula, Alejandro Grajales Dau, Jonathan Gross, Steve Habegger, Michael Hamilton, Monica Hansen, Matthew Harrigan, Sean Harrington, Paula Heu, Gordon Hill, Markus Hoffmann, Sabrina Hong, Trent Huang, Ashley Huff, William Huggins, Lev Ioffe, Sergei Isakov, Justin Iveland, Evan Jeffrey, Zhang Jiang, Cody Jones, Pavol Juhas, D. Kafri, Tanuj Khattar, Mostafa Khezri, Mria Kieferov, Seon Kim, Alexei Kitaev, Andrey Klots, Alexander Korotkov, Fedor Kostritsa, John Mark Kreikebaum, David Landhuis, Pavel Laptev, Kim Ming Lau, Lily Laws, Joonho Lee, Kenneth Lee, Yuri Lensky, Brian Lester, Alexander Lill, Wayne Liu, William P. Livingston, A. Locharla, Salvatore Mandr, Orion Martin, Steven Martin, Jarrod McClean, Matthew McEwen, Seneca Meeks, Kevin Miao, Amanda Mieszala, Shirin Montazeri, Ramis Movassagh, Wojciech Mruczkiewicz, Ani Nersisyan, Michael Newman, Jiun How Ng, Anthony Nguyen, Murray Nguyen, M. Niu, Thomas O'Brien, Seun Omonije, Alex Opremcak, Rebecca Potter, Leonid Pryadko, Chris Quintana, David Rhodes, Charles Rocque, N. Rubin, Negar Saei, Daniel Sank, Kannan Sankaragomathi, Kevin Satzinger, Henry Schurkus, Christopher Schuster, Michael Shearn, Aaron Shorter, Noah Shutty, Vladimir Shvarts, Volodymyr Sivak, Jindra Skruzny, Clarke Smith, Rolando Somma, George Sterling, Doug Strain, Marco Szalay, Douglas Thor, Alfredo Torres, Guifre Vidal, Benjamin Villalonga, Catherine Vollgraff Heidweiller, Theodore White, Bryan Woo, Cheng Xing, Jamie Yao, Ping Yeh, Juhwan Yoo, Grayson Young, Adam Zalcman, Yaxing Zhang, Ningfeng Zhu, Nicholas Zobrist, Hartmut Neven, Ryan Babbush, Dave Bacon, Sergio Boixo, Jeremy Hilton, Erik Lucero, Anthony Megrant, Julian Kelly, Yu Chen, Vadim Smelyanskiy, Vedika Khemani, Sarang Gopalakrishnan, Toma Prosen, Pedram Roushan Session W50: Quantum Simulation of Many-Body Physics Link to Paper

The fast multipole method on a quantum computer Presenter: Kianna Wan Authors: Kianna Wan, Dominic W Berry, Ryan Babbush Session W50: Quantum Simulation of Many-Body Physics

The quantum computing industry and protecting national security: what tools will work? Presenter: Kate Weber Author: Kate Weber Session Y43: Industry, Innovation, and National Security: Finding the Right Balance

Novel charging effects in the fluxonium qubit Presenter: Agustin Di Paolo Authors: Agustin Di Paolo, Kyle Serniak, Andrew J Kerman, William D Oliver Session Y46: Fluxonium-Based Superconducting Quibits

Microwave Engineering of Parametric Interactions in Superconducting Circuits Presenter: Ofer Naaman Author: Ofer Naaman Session Z46: Broadband Parametric Amplifiers and Circulators

Linear spin wave theory of large magnetic unit cells using the Kernel Polynomial Method Presenter: Harry Lane Authors: Harry Lane, Hao Zhang, David A Dahlbom, Sam Quinn, Rolando D Somma, Martin P Mourigal, Cristian D Batista, Kipton Barros Session Z62: Cooperative Phenomena, Theory

*Work done while at Google

Read this article:
Google at APS 2024 Google Research Blog - Google Research

Scientists have created an error-free quantum bit, or qubit, from a single pulse of light, raising hopes for a light-based room-temperature quantum computer in the future.

While bits in classical computers store information as either 1 or 0, qubits in quantum computers can encode information as a superposition of 1 and 0, meaning one qubit can adopt both states simultaneously.

When quantum computers have millions of qubits in the future, they will process calculations in a fraction of the time that today's most powerful supercomputers can. But the most powerful quantum computers so far have only been built with roughly 1,000 qubits.

Most qubits are made from a superconducting metal, but these need to be cooled to near absolute zero to achieve stability for the laws of quantum mechanics to dominate. Qubits are also highly prone to failure, and if a qubit fails during a computation, the data it stores is lost, and a calculation is delayed.

One way to solve this problem is to stitch multiple qubits together using quantum entanglement, an effect Albert Einstein famously referred to as "spooky action at a distance. By connecting them intrinsically through space and time so they share a single quantum state, scientists can form one "logical qubit," storing the same information in all of the constituent physical qubits. If one or more physical qubits fails, the calculation can continue because the information is stored elsewhere.

Related: How could this new type of room-temperature qubit usher in the next phase of quantum computing?

But you need many physical qubits to create one logical qubit. Quantum computing company QuEra and researchers at Harvard, for example, recently demonstrated a breakthrough in quantum error correction using logical qubits, publishing their findings Dec. 6, 2023, in the journal Nature. This will lead to the launch of a quantum computer with 10 logical qubits later this year but it will be made using 256 physical qubits.

For that reason, researchers are looking at alternative ways to create qubits and have previously demonstrated that you can create a physical qubit from a single photon (particle of light). This can also operate at room temperature because it doesn't rely on the conventional way to make qubits, using superconducting metals that need to be cooled. But single physical photonic qubits are still prone to failure.

In a study published in August 2023 in the journal Nature, scientists showed that you can successfully entangle multiple photonic qubits. Building on this research, the same team has now demonstrated that you can create a de facto logical qubit which has an inherent capacity for error correction using a single laser pulse that contains multiple photons entangled by nature. They published their findings Jan. 18 in the journal Science.

"Our laser pulse was converted to a quantum optical state that gives us an inherent capacity to correct errors," Peter van Loock, a professor of theoretical quantum optics at Johannes Gutenberg University of Mainz in Germany and co-author of the Dec. 6 study, said in a statement. "Although the system consists only of a laser pulse and is thus very small, it can in principle eradicate errors immediately."

Based on their results, there's no need to create individual photons as qubits from different light pulses and entangle them afterward. You would need just one light pulse to create a "robust logical qubit," van Loock added.

Although the results are promising, the logical qubit they created experimentally wasn't good enough to achieve the error-correction levels needed to perform as a logical qubit in a real quantum computer. Rather, the scientists said this work shows you can transform a non-correctable qubit into a correctable qubit using photonic methods.

See more here:
Qubits are notoriously prone to failure but building them from a single laser pulse may change this - Livescience.com

Researchers at Penn State have introduced a groundbreaking material fusion that enables a new form of superconductivity, crucial for advancing quantum computing and exploring the theoretical chiral Majorana particles. Their study demonstrates how combining magnetic materials can lead to emergent superconductivity, marking a significant leap in creating chiral topological superconductors and potentially unlocking new avenues in quantum computing research.

A new fusion of materials, each with special electrical properties, has all the components required for a unique type of superconductivity that could provide the basis for more robust quantum computing. The new combination of materials, created by a team led by researchers at Penn State, could also provide a platform to explore physical behaviors similar to those of mysterious, theoretical particles known as chiral Majoranas, which could be another promising component for quantum computing.

The new study was recently published in the journal Science. The work describes how the researchers combined the two magnetic materials in what they called a critical step toward realizing the emergent interfacial superconductivity, which they are currently working toward.

Superconductors materials with no electrical resistance are widely used in digital circuits, the powerful magnets in magnetic resonance imaging (MRI) and particle accelerators, and other technology where maximizing the flow of electricity is crucial. When superconductors are combined with materials called magnetic topological insulators thin films only a few atoms thick that have been made magnetic and restrict the movement of electrons to their edges the novel electrical properties of each component work together to produce chiral topological superconductors. The topology, or specialized geometries and symmetries of matter, generates unique electrical phenomena in the superconductor, which could facilitate the construction of topological quantum computers.

Quantum computers have the potential to perform complex calculations in a fraction of the time it takes traditional computers because, unlike traditional computers which store data as a one or a zero, the quantum bits of quantum computers store data simultaneously in a range of possible states. Topological quantum computers further improve upon quantum computing by taking advantage of how electrical properties are organized to make the computers robust to decoherence, or the loss of information that happens when a quantum system is not perfectly isolated.

Creating chiral topological superconductors is an important step toward topological quantum computation that could be scaled up for broad use, said Cui-Zu Chang, Henry W. Knerr Early Career Professor and associate professor of physics at Penn State and co-corresponding author of the paper. Chiral topological superconductivity requires three ingredients: superconductivity, ferromagnetism, and a property called topological order. In this study, we produced a system with all three of these properties.

The researchers used a technique called molecular beam epitaxy to stack together a topological insulator that has been made magnetic and an iron chalcogenide (FeTe), a promising transition metal for harnessing superconductivity. The topological insulator is a ferromagnet a type of magnet whose electrons spin the same way while FeTe is an antiferromagnet, whose electrons spin in alternating directions. The researchers used a variety of imaging techniques and other methods to characterize the structure and electrical properties of the resulting combined material and confirmed the presence of all three critical components of chiral topological superconductivity at the interface between the materials.

Prior work in the field has focused on combining superconductors and nonmagnetic topological insulators. According to the researchers, adding in the ferromagnet has been particularly challenging.

Normally, superconductivity and ferromagnetism compete with each other, so it is rare to find robust superconductivity in a ferromagnetic material system, said Chao-Xing Liu, professor of physics at Penn State and co-corresponding author of the paper. But the superconductivity in this system is actually very robust against the ferromagnetism. You would need a very strong magnetic field to remove the superconductivity.

The research team is still exploring why superconductivity and ferromagnetism coexist in this system.

Its actually quite interesting because we have two magnetic materials that are non-superconducting, but we put them together and the interface between these two compounds produces very robust superconductivity, Chang said. Iron chalcogenide is antiferromagnetic, and we anticipate its antiferromagnetic property is weakened around the interface to give rise to the emergent superconductivity, but we need more experiments and theoretical work to verify if this is true and to clarify the superconducting mechanism.

The researchers said they believe this system will be useful in the search for material systems that exhibit similar behaviors as Majorana particles theoretical subatomic particles first hypothesized in 1937. Majorana particles act as their own antiparticle, a unique property that could potentially allow them to be used as quantum bits in quantum computers.

Providing experimental evidence for the existence of chiral Majorana will be a critical step in the creation of a topological quantum computer, Chang said. Our field has had a rocky past in trying to find these elusive particles, but we think this is a promising platform for exploring Majorana physics.

Reference: Interface-induced superconductivity in magnetic topological insulators by Hemian Yi, Yi-Fan Zhao, Ying-Ting Chan, Jiaqi Cai, Ruobing Mei, Xianxin Wu, Zi-Jie Yan, Ling-Jie Zhou, Ruoxi Zhang, Zihao Wang, Stephen Paolini, Run Xiao, Ke Wang, Anthony R. Richardella, John Singleton, Laurel E. Winter, Thomas Prokscha, Zaher Salman, Andreas Suter, Purnima P. Balakrishnan, Alexander J. Grutter, Moses H. W. Chan, Nitin Samarth, Xiaodong Xu, Weida Wu, Chao-Xing Liu and Cui-Zu Chang, 8 February 2024, Science. DOI: 10.1126/science.adk1270

In addition to Chang and Liu, the research team at Penn State at the time of the research included postdoctoral researcher Hemian Yi; graduate students Yi-Fan Zhao, Ruobing Mei, Zi-Jie Yan, Ling-Jie Zhou, Ruoxi Zhang, Zihao Wang, Stephen Paolini and Run Xiao; assistant research professors in the Materials Research Institute Ke Wang and Anthony Richardella; Evan Pugh University Professor Emeritus of Physics Moses Chan; and Verne M. Willaman Professor of Physics and Professor of Materials Science and Engineering Nitin Samarth. The research team also includes Ying-Ting Chan and Weida Wu at Rutgers University; Jiaqi Cai and Xiaodong Xu at the University of Washington; Xianxin Wu at the Chinese Academy of Sciences; John Singleton and Laurel Winter at the National High Magnetic Field Laboratory; Purnima Balakrishnan and Alexander Grutter at the National Institute of Standards and Technology; and Thomas Prokscha, Zaher Salman, and Andreas Suter at the Paul Scherrer Institute of Switzerland.

This research is supported by the U.S. Department of Energy. Additional support was provided by the U.S. National Science Foundation (NSF), the NSF-funded Materials Research Science and Engineering Center for Nanoscale Science at Penn State, the Army Research Office, the Air Force Office of Scientific Research, the state of Florida and the Gordon and Betty Moore Foundations EPiQS Initiative.

Here is the original post:
Quantum Computing Breakthrough: New Fusion of Materials Has All the Components Required for a Unique Type of ... - SciTechDaily

Apples security team claims to have achieved a breakthrough that advances the state of the art of end-to-end messaging. With the upcoming release of iOS 17.4, iPadOS 17.4, macOS 14.4, and watchOS 10.4, the company is bringing a new cryptographic protocol called PQ3 to iMessage that it purports to offer even more robust encryption and defenses against sophisticated quantum computing attacks.

Such attacks arent yet a broad threat today, but Apple is preparing for a future where bad actors try to unwind current encryption standards and iMessages security layers with the help of massively powerful computers. Such scenarios could start playing out by the end of the decade, but experts agree that the tech industry need to start defending against them well in advance.

PQ3 is the first messaging protocol to reach what we call Level 3 security providing protocol protections that surpass those in all other widely deployed messaging apps, the security team wrote. Yes, Apple came up with its own ranking system for messaging service security, and iMessage now stands alone at the top thanks to these latest PQ3 advancements.

In the companys view, theyre enough to put Apples service above Signal, which itself recently rolled out more sophisticated security defenses. (For reference, the current version of iMessage ranks as level 1 alongside WhatsApp, Viber, Line, and the older version of Signal.) More than simply replacing an existing algorithm with a new one, we rebuilt the iMessage cryptographic protocol from the ground up to advance the state of the art in end-to-end encryption, Apple wrote.

Apple says that hackers can stow away any encrypted data they obtain today in hopes of being able to break through in several years once quantum computers become a realistic attack vector:

Although quantum computers with this capability dont exist yet, extremely well-resourced attackers can already prepare for their possible arrival by taking advantage of the steep decrease in modern data storage costs. The premise is simple: such attackers can collect large amounts of todays encrypted data and file it all away for future reference. Even though they cant decrypt any of this data today, they can retain it until they acquire a quantum computer that can decrypt it in the future, an attack scenario known asHarvest Now, Decrypt Later.

You can read all the nitty-gritty details on PQ3 in Apples blog post, which is a great example of the companys focus on protecting user data. And as weve learned in recent months, Apple wont hesitate to shut out third parties even those with well-meaning intentions that attempt to encroach on its iPhone-selling messaging platform in any way.

See the article here:
Apple is already defending iMessage against tomorrow's quantum computing attacks - The Verge

Quantum computing has long been celebrated for its potential to surpass traditional computing in terms of speed and memory efficiency. This innovative technology promises to revolutionize our ability to predict physical phenomena that were once deemed impossible to forecast.

The essence of quantum computing lies in its use of quantum bits, or qubits, which, unlike the binary digits of classical computers, can represent values anywhere between 0 and 1.

This fundamental difference allows quantum computers to process and store information in a way that could vastly outpace their classical counterparts under certain conditions.

However, the journey of quantum computing is not without its challenges. Quantum systems are inherently delicate, often struggling with information loss, a hurdle classical systems do not face.

Additionally, converting quantum information into a classical format, a necessary step for practical applications, presents its own set of difficulties.

Contrary to initial expectations, classical computers have been shown to emulate quantum computing processes more efficiently than previously believed, thanks to innovative algorithmic strategies.

Recent research has demonstrated that with a clever approach, classical computing can not only match but exceed the performance of cutting-edge quantum machines.

The key to this breakthrough lies in an algorithm that selectively maintains quantum information, retaining just enough to accurately predict outcomes.

This work underscores the myriad of possibilities for enhancing computation, integrating both classical and quantum methodologies, explains Dries Sels, an Assistant Professor in the Department of Physics at New York University and co-author of the study.

Sels emphasizes the difficulty of securing a quantum advantage given the susceptibility of quantum computers to errors.

Moreover, our work highlights how difficult it is to achieve quantum advantage with an error-prone quantum computer, Sels emphasized.

The research team, including collaborators from the Simons Foundation, explored optimizing classical computing by focusing on tensor networks.

These networks, which effectively represent qubit interactions, have traditionally been challenging to manage.

Recent advancements, however, have facilitated the optimization of these networks using techniques adapted from statistical inference, thereby enhancing computational efficiency.

The analogy of compressing an image into a JPEG format, as noted by Joseph Tindall of the Flatiron Institute and project lead, offers a clear comparison.

Just as image compression reduces file size with minimal quality loss, selecting various structures for the tensor network enables different forms of computational compression, optimizing the way information is stored and processed.

Tindalls team is optimistic about the future, developing versatile tools for handling diverse tensor networks.

Choosing different structures for the tensor network corresponds to choosing different forms of compression, like different formats for your image, says Tindall.

We are successfully developing tools for working with a wide range of different tensor networks. This work reflects that, and we are confident that we will soon be raising the bar for quantum computing even further.

In summary, this brilliant work highlights the complexity of achieving quantum superiority and showcases the untapped potential of classical computing.

By reimagining classical algorithms, scientists are challenging the boundaries of computing and opening new pathways for technological advancement, blending the strengths of both classical and quantum approaches in the quest for computational excellence.

As discussed above, quantum computing represents a revolutionary leap in computational capabilities, harnessing the peculiar principles of quantum mechanics to process information in fundamentally new ways.

Unlike traditional computers, which use bits as the smallest unit of data, quantum computers use quantum bits or qubits. These qubits can exist in multiple states simultaneously, thanks to the quantum phenomena of superposition and entanglement.

At the heart of quantum computing lies the qubit. Unlike a classical bit, which can be either 0 or 1, a qubit can be in a state of 0, 1, or both 0 and 1 simultaneously.

This capability allows quantum computers to perform many calculations at once, providing the potential to solve certain types of problems much more efficiently than classical computers.

The power of quantum computing scales exponentially with the number of qubits, making the technology incredibly potent even with a relatively small number of qubits.

Quantum supremacy is a milestone in the field, referring to the point at which a quantum computer can perform a calculation that is practically impossible for a classical computer to execute within a reasonable timeframe.

Achieving quantum supremacy demonstrates the potential of quantum computers to tackle problems beyond the reach of classical computing, such as simulating quantum physical processes, optimizing large systems, and more.

The implications of quantum computing are vast and varied, touching upon numerous fields. In cryptography, quantum computers pose a threat to traditional encryption methods but also offer new quantum-resistant algorithms.

In drug discovery and material science, they can simulate molecular structures with high precision, accelerating the development of new medications and materials.

Furthermore, quantum computing holds the promise of optimizing complex systems, from logistics and supply chains to climate models, potentially leading to breakthroughs in how we address global challenges.

Despite the exciting potential, quantum computing faces significant technical hurdles, including error rates and qubit stability.

Researchers are actively exploring various approaches to quantum computing, such as superconducting qubits, trapped ions, and topological qubits, each with its own set of challenges and advantages.

As the field progresses, the collaboration between academia, industry, and governments continues to grow, driving innovation and overcoming obstacles.

The journey toward practical and widely accessible quantum computing is complex and uncertain, but the potential rewards make it one of the most thrilling areas of modern science and technology.

Quantum computing stands at the frontier of a new era in computing, promising to redefine what is computationally possible.

As researchers work to scale up quantum systems and solve the challenges ahead, the future of quantum computing shines with the possibility of solving some of humanitys most enduring problems.

The full study was published by PRX Quantum.

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Quantum computer outperformed by new traditional computing type - Earth.com