The Power of Complexity and Entanglement, from Thousands of Miles Away

by Siobhan Roberts (Journalist in Residence, Simons Institute)

In January 2014, during an open problems session in the auditorium at the Simons Institute, the computer scientist Thomas Vidick posed a question that he expected would go nowhere.

The research program on Quantum Hamiltonian Complexity had just commenced — probing techniques from both quantum complexity theory and condensed matter physics and asking questions such as: Is the scientific method sufficiently powerful to understand general quantum systems? Is materials science about to hit a computational barrier? 

Vidick’s questions waded further into the weeds. 

“A central conjecture, the so-called quantum PCP conjecture, crystallizes many of these issues, and the conjecture was hotly debated throughout the semester,” recounted Vidick, a professor of computing and mathematical sciences at Caltech, in his research vignette published later that year.

Two of the program’s organizers, Umesh Vazirani of UC Berkeley and Dorit Aharonov at the Hebrew University of Jerusalem, encouraged him to formulate a new variant of the conjecture, which (for those readers at least somewhat in the know) he described as follows:

“This formulation of the PCP theorem gives rise to a quantum analogue whose relation to the quantum PCP conjecture is a priori unclear. The new variant asks the following: Do all languages in QMA admit an efficient verification procedure of the above form, in which the verifier and communication may be quantum? Here it is important to also allow the provers to be initialized in an arbitrary entangled state, as this may be necessary to encode the QMA witness whose existence the provers are supposed to convey to the verifier.”

Vidick admitted the problem was tantalizing, yet he believed it would lead to a dead end.

Six years later, however, quite the contrary has proved to be the case: that dead-end question ultimately led to a breakthrough result.

The day before the 2020 spring term began at the Simons Institute — with a timely pairing of two interconnected programs, Lattices: Algorithms, Complexity, and Cryptography and The Quantum Wave in Computing — Vidick and his collaborators1 posted a 165-page paper to arXiv titled “MIP*=RE.”

It had been a long time coming. And during the home stretch, another team of researchers seemed to have proved the opposite result — via a very different language and approach — but a gap emerged with a lemma that could not be fixed.

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Theory at the Institute and Beyond

by Prasad Raghavendra

Amid the biggest pandemic in a century, one that has disrupted lives and livelihoods the world over, it is gratifying to see how people in different walks of life have found ways to cope and carry on. Within the realm of theory research, the pursuit to better understand the foundations of computation and their implications doesn’t seem to have slowed down even a bit.

Make no mistake, the pandemic has disrupted our traditional modes of operation. A typical theorist might spend several hours each day brainstorming in a group, often over a beverage. For most theorists, this is the single most productive and enjoyable activity each day. As these meetings move online, they remain a shadow of what they used to be. Normally, surprising results often arise out of chance encounters between researchers from very different areas. As conferences and workshops shift online, however, these chance encounters become very rare. Finally, on most days, we are struggling along an unforgiving trail in an attempt to scale a seemingly insurmountable peak. Doubts — such as, Are we on the right trail? Even if we are on the right trail, are we strong enough to get through it? — often linger and can easily set one up for failure. Sharing these “theoretical” struggles with other researchers over lunch or in the corridors can be critical to keep us going. Sadly, these opportunities are rare these days.

Yet theory research does not seem to have missed a beat. The ACM STOC conference was held online for the first time. Despite the limitations of the medium, there are many silver linings to an online conference. Participation at the conference nearly doubled from last year, with 606 participants from 33 countries, many of which had not been represented at typical STOC conferences before. The videos of the conference talks are all available online, a fantastic resource for researchers going forward. Finally, as Ronen Eldan’s talk at the conference beautifully demonstrated, video is a really effective medium to communicate a research work in broad strokes in a very short time. In fact, this year’s online conference seemed to have so many advantages that the PC chair, Julia Chuzhoy, suggested holding the STOC conference twice each year, once online and once offline. 

As weekly seminars at most universities move online, they have begun to attract participants from across the world. CS Theory Online Talks maintains a list of theory talks that are available online (also see here and here). The PIMS-CRM summer school on probability has morphed into a great set of online courses that I have really enjoyed. The Oxford-Warwick Complexity Meetings are an online lecture series dedicated to complexity theory, while we at the Simons Institute are also hosting a lecture series, on Boolean function analysis (more on this later). This flurry of online activity catalyzed by the pandemic is promising to make theory research broadly accessible to graduate students and undergraduates across the globe.

Meanwhile, fantastic new results keep pouring in. The biggest breakthrough this summer is the work of Karlin, Klein, and Oveis Gharan on the metric traveling salesman problem (metric TSP). They have posted a 1.5 – ε approximation algorithm for metric TSP for some constant ε > 10 -36. Metric TSP is a fundamental combinatorial optimization problem wherein the inputs consist of a network of cities and the distances between them. The goal is to find the shortest-length route that visits each city exactly once and returns to the starting point. This problem is called metric TSP if the distances between cities are assumed to satisfy the triangle inequality, namely the distance from City A to City C is at most the sum of the distances from City A to City B and from City B to City C. 

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